ドキュメント変更履歴 2026-08-21

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql-regional-availability+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/aisql-regional-availability@@ -24,5 +24,5 @@ If you're not sure where to start, try the most capable models first to establish a baseline to evaluate other models. `claude-opus-5` and `gemini-3.1-pro` are the most capable models offered by Snowflake Cortex,-and will give you a good idea what a state-of-the-art model can do.+and will give you a good idea of what a state-of-the-art model can do.  - `claude-opus-5` is Anthropic's flagship Claude Opus model, with improved performance on coding, long-horizon agentic work, and professional tasks like document drafting and data analysis. With a 1,000,000-token context window and up to 128,000 output tokens, it can analyze large document collections and produce detailed responses in a single call.@@ -44,5 +44,5 @@ - `llama3.1-8b` is ideal for tasks that require low to moderate reasoning. It's a light-weight, ultra-fast model with a context window   of 128K. `llama3-8b` provides a smaller context window and relatively lower accuracy.-- `mistral-7b` is ideal for your simplest summarization, structuration, and question answering tasks that need to be+- `mistral-7b` is ideal for your simplest summarization, structuring, and question-answering tasks that need to be   done quickly. It offers low latency and high throughput processing for multiple pages of text with its 32K context   window.@@ -53,5 +53,5 @@ | Model                                                                                              | Context Window (Tokens) | MMLU (Reasoning) | HumanEval (Coding) | GSM8K (Arithmetic Reasoning) | Spider 1.0 (SQL) | | -------------------------------------------------------------------------------------------------- | ----------------------- | ---------------- | ------------------ | ---------------------------- | ---------------- |-| [GPT 4.o](https://openai.com/index/hello-gpt-4o/)                                                  | 128,000                 | 88.7             | 90.2               | 96.4                         | -                |+| [GPT-4o](https://openai.com/index/hello-gpt-4o/)                                                   | 128,000                 | 88.7             | 90.2               | 96.4                         | -                | | [llama3.1-70b](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md) | 128,000                 | 86               | 80.5               | 95.1                         | -                | | [mistral-large2](https://mistral.ai/news/mistral-large-2407/)                                      | 128,000                 | 84               | 92                 | 93                           | -                |@@ -148,13 +148,16 @@   <colgroup>     <col style={{width: "28.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />-    <col style={{width: "8.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />+    <col style={{width: "6.0%"}} />   </colgroup>   <thead>@@ -164,8 +167,11 @@       <th>AWS US (Cross-Region)</th>       <th>AWS US Commercial Gov (Cross-Region)</th>+      <th>AWS US FedRAMP High Plus (Cross-Region)</th>+      <th>AWS US DoD (Cross-Region)</th>       <th>AWS EU (Cross-Region)</th>       <th>AWS APJ (Cross-Region)</th>       <th>AWS AU (Cross-Region)</th>       <th>Azure US (Cross-Region)</th>+      <th>Azure US FedRAMP High Plus (Cross-Region)</th>       <th>Azure EU (Cross-Region)</th>       <th>Google Cloud US (Cross-Region)</th>@@ -184,4 +190,7 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -190,5 +199,8 @@       <td>%cm%</td>       <td></td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -202,5 +214,8 @@       <td>\*</td>       <td></td>+      <td></td>+      <td></td>       <td>\*</td>+      <td></td>       <td></td>       <td></td>@@ -214,4 +229,6 @@       <td>\*</td>       <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td></td>@@ -220,4 +237,5 @@       <td></td>       <td></td>+      <td></td>     </tr>     <tr>@@ -226,5 +244,8 @@       <td>%cm%</td>       <td></td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -237,8 +258,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td></td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -250,7 +274,10 @@       <td>%cm%</td>       <td></td>-      <td>%cm%</td>-      <td></td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -265,5 +292,8 @@       <td>%cm%</td>       <td>%cm%</td>-      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>+      <td>%cm%</td>       <td></td>       <td></td>@@ -274,5 +304,8 @@       <td>%cm%</td>       <td></td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -286,7 +319,10 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -298,6 +334,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -316,4 +355,7 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -328,4 +370,7 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -334,8 +379,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>       <td></td>@@ -346,8 +394,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>       <td></td>@@ -358,8 +409,11 @@       <td>%cm%</td>       <td></td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>       <td></td>@@ -373,5 +427,8 @@       <td></td>       <td></td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -385,5 +442,8 @@       <td></td> ... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/user-guide/cost-anomalies-ui+++ bhttps://docs.snowflake.com/en/user-guide/cost-anomalies-ui@@ -3,43 +3,15 @@ - [](/user-guide/cost-anomalies) -This topic describes how to use %sf-web-interface% to identify and investigate cost anomalies, which occur when daily consumption in an-account or organization is above or below the expected range of consumption for the day. It also describes how to use %sf-web-interface% to-configure notifications so specific users are emailed when cost anomalies occur.--For an overview of cost anomalies, see [](/user-guide/cost-anomalies).--<a id="label-cost-anomaly-notifications"></a>--## Configure notifications with %sf-web-interface%--When Snowflake identifies a cost anomaly, it sends a notification to a list of email addresses. When deciding who will receive notifications for cost anomalies, be aware that email notifications might contain details about how much was spent by an account.--Each account can have a notification list for account-level anomalies within the account. You can also define a separate notification list for the organization to-control who is notified when there is an organization-level anomaly.--Each email address must have been [verified by the user](#label-snowsight-verify-email-address).--You can use a group email address, such as a distribution list, for notifications, but this email address must be verified. Before adding a group email address to the notification list, you might need to create a new Snowflake user with the group email address so you can verify it.--Email notifications are processed through Snowflake’s Amazon Web Services (AWS) deployments, using AWS Simple Email Service-(SES). The content of an email message sent using AWS may be retained by Snowflake for up to thirty days to manage the delivery-of the message. After this period, the message content is deleted.--To add email addresses where notifications are sent when there is a cost anomaly, complete the following steps:+This topic describes how to use %sf-web-interface% to identify and investigate [cost anomalies](/user-guide/cost-anomalies), create anomaly+monitors that watch a custom scope, and configure notifications.++All of the tasks in this topic start on the **Anomalies** tab. To open it:  1. Sign in to %sf-web-interface-link% as a user with the [required privileges](/user-guide/cost-anomalies-access-control). 2. In the navigation menu, select **Admin** %raa% **Cost management**, and then select **Anomalies**.-3. Select **Notifications**.-4. To specify who gets notified for an [account-level anomaly](#label-cost-anomaly-level), do the following:-   1. In the **Notify for account anomalies** field, enter the email address of a Snowflake user you want contacted for anomalies.-   2. Press Enter.-   3. Repeat for additional users.--5. To specify who gets notified for an [organization-level anomaly](#label-cost-anomaly-level), do the following:-   1. In the **Notify for organization anomalies** field, enter the email addresses of a Snowflake user you want contacted for anomalies.-   2. Press Enter.-   3. Repeat for additional users.--6. Select **Save changes**.++The Anomalies tab opens, showing a consumption chart with the expected range and any detected anomalies, and a table of those anomalies:++![The Anomalies tab in Cost management, with the timeframe and account filters, a consumption chart showing the expected range and two anomalies, and a table listing each anomaly with its date, consumption, expected range, and amount over or under expected](/static/images/cost-anomaly-anomalies-tab.png)  <a id="label-cost-anomaly-identify-ui"></a>@@ -49,64 +21,74 @@ **Step 1: Identify cost anomalies** -1. Sign in to %sf-web-interface-link% as a user with the [required privileges](/user-guide/cost-anomalies-access-control).-2. In the navigation menu, select **Admin** %raa% **Cost management**, and then select **Anomalies**.-3. Use the filters to select a timeframe and account. If you want to identify-   [organization-level anomalies](#label-cost-anomaly-level), select **All accounts**.-4. Do one of the following:-   1. Use the chart to visually track actual consumption and the expected range of consumption over time. Cost anomalies where actual-      consumption went above or below the expected range are visually represented in the chart.-   2. Use the table to view a list of all cost anomalies within the timeframe. Sort as desired.+1. Open the Anomalies tab.+2. Use the filters to select a timeframe, and then choose what you want to review:+   - **A single account:** From the **Account** filter, select the account. The chart and table show+     [account-level anomalies](#label-cost-anomaly-level) for that account.+   - **The whole organization:** From the **Account** filter, select **All accounts**. The chart and table show+     [organization-level anomalies](#label-cost-anomaly-level).+   - **An anomaly monitor:** From the **Account** filter, select the account you're currently signed in to, and then select a monitor from+     the **Monitors** filter. Monitor filters appear only for the current account. For more information, see+     [](#label-cost-anomaly-monitors-ui).++3. Use the chart to track actual consumption against the expected range over time, or use the table to list and sort every anomaly in the+   timeframe.  **Step 2: Investigate a cost anomaly** -After identifying a cost anomaly, you can investigate it using the side panel or by using Cortex Code to ask natural-language questions.+You can investigate an anomaly using the side panel, which supports account-level and organization-level anomalies, or Cortex Code, which+also supports [anomaly monitors](#label-cost-anomaly-monitors).  ### Investigate using the side panel -1. Select a cost anomaly by clicking the indicator in the chart or selecting a row in the table. A side panel opens.-2. If you are investigating an account-level anomaly (you selected a specific account in the filter), you can use the side panel to drill down into the following:-   - Use the **Top consumption drivers** section to investigate hourly consumption within the account. You can view consumption for all service types or you can focus on the services that consumed the most credits during the day.-   - Use the **Top warehouses** section to identify the warehouses within the account that had the greatest absolute change in consumption.-   - If you are investigating anomalies in the account that you are currently signed in to, use the **Top queries** section to identify the most expensive queries in the warehouse that had the greatest change in consumption. This might not show the most expensive query in the account because it focuses on queries in a specific warehouse (the one with the greatest change in consumption).-   - Drill down into the most expensive queries by selecting the **Open in Worksheet** icon that is located near the Query ID. A worksheet opens that shows the query that was executed.--3. If you are investigating an organization-level anomaly (you selected **All Accounts** in the filter), you can use the side panel to drill down into the following:--   - Use the **Top accounts** section to identify the accounts that had the greatest absolute change in consumption.-   - Use the **Top warehouses** section to drill down into the account with the greatest change in consumption. You can identify the warehouses within the account that had the greatest change in consumption.--   This might not show the warehouse with the greatest change within the entire organization because it focuses on warehouses in a specific account (the one with the greatest change in consumption). To programmatically retrieve the top warehouses in a different account or within the organization, see [Warehouse-level consumption](#label-cost-anomaly-investigate-warehouse-class).--If the... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-rest-api+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-rest-api@@ -318,12 +318,16 @@   <colgroup>     <col style={{width: "30.4%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />-    <col style={{width: "8.7%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />+    <col style={{width: "5.8%"}} />   </colgroup>   <thead>@@ -333,8 +337,12 @@       <th>AWS Global (Cross-Region)</th>       <th>AWS US (Cross-Region)</th>+      <th>AWS US Commercial Gov (Cross-Region)</th>+      <th>AWS US FedRAMP High Plus (Cross-Region)</th>+      <th>AWS US DoD (Cross-Region)</th>       <th>AWS EU (Cross-Region)</th>       <th>AWS APJ (Cross-Region)</th>       <th>Azure Global (Cross-Region)</th>       <th>Azure US (Cross-Region)</th>+      <th>Azure US FedRAMP High Plus (Cross-Region)</th>       <th>Azure EU (Cross-Region)</th>     </tr>@@ -346,5 +354,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -357,5 +369,9 @@       <td>\*</td>       <td>\*</td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>+      <td></td>       <td></td>       <td></td>@@ -368,5 +384,9 @@       <td>\*</td>       <td>\*</td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>+      <td></td>       <td></td>       <td></td>@@ -379,4 +399,7 @@       <td>\*</td>       <td>\*</td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td></td>@@ -384,4 +407,5 @@       <td></td>       <td></td>+      <td></td>     </tr>     <tr>@@ -391,5 +415,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -401,5 +429,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -414,6 +446,10 @@       <td>%cm%</td>       <td>%cm%</td>-      <td></td>-      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>       <td></td>     </tr>@@ -423,5 +459,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -435,5 +475,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -446,5 +490,9 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>       <td></td>@@ -458,7 +506,11 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td>\*</td>       <td></td>+      <td></td>     </tr>     <tr>@@ -469,6 +521,10 @@       <td></td>       <td></td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>     </tr>@@ -480,6 +536,10 @@       <td></td>       <td></td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>     </tr>@@ -491,6 +551,10 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td>\*</td>+      <td></td>       <td>\*</td>     </tr>@@ -502,7 +566,11 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td>\*</td>       <td></td>+      <td></td>     </tr>     <tr>@@ -513,7 +581,11 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>       <td>\*</td>       <td>\*</td>       <td></td>+      <td></td>     </tr>     <tr>@@ -524,6 +596,10 @@       <td></td>       <td></td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>     </tr>@@ -538,4 +614,8 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -545,7 +625,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>     </tr>@@ -556,7 +640,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>     </tr>@@ -568,6 +656,10 @@       <td></td>       <td></td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td></td>     </tr>@@ -582,4 +674,8 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -588,4 +684,8 @@       <td>%cm%</td>       <td></td>+      <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>       <td></td>       <td></td>@@ -604,4 +704,8 @@       <td></td>       <td></td>+      <td></td>+      <td></td>+      <td></td>+      <td></td>     </tr>     <tr>@@ -611,7 +715,11 @@       <td>%cm%</td>       <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>-      <td>%cm%</td>+      <td></td>+      <td></td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td>%cm%</td>+      <td></td>       <td>%cm%</td>     </tr>@@ -621,4 +729,8 @@       <td>%cm%</td>       <td>%cm%</td>+      <td></td>+      <td></td>+      <td></td>+      <td></td>       <td></td>       <td></td> 

--- ahttps://docs.snowflake.com/en/user-guide/cost-anomalies+++ bhttps://docs.snowflake.com/en/user-guide/cost-anomalies@@ -13,17 +13,160 @@ <a id="label-cost-anomaly-level"></a> -## Account-level vs. organization-level cost anomalies+## Cost anomaly monitoring scope++Snowflake detects cost anomalies at three scopes. Account-level and organization-level detection is always on and requires no+configuration. Anomaly monitors let you define your own narrower scope.++<dl>+<dt>Account-level cost anomalies</dt>+<dd>  An account-level cost anomaly occurs when the consumption in a single account falls outside the expected range of consumption for that account. +</dd>+<dt>Organization-level cost anomalies</dt>+<dd>+ An organization-level cost anomaly occurs when the consumption in the entire organization falls outside the expected range of consumption-for the organization. It is based on the aggregate consumption of all accounts in the organization. For example, if there is a significant-consumption spike in one account, but a dip in another, the two might offset each other such that it is not flagged as an organization-level-anomaly. To help investigate organization-level anomalies, Snowflake provides tools to identify which accounts had the biggest increase or-decrease in consumption on a specific day.+for the organization. An organization-level anomaly is based on the aggregate consumption of all accounts in the organization. For example, a+spike in one account and+a dip in another can offset each other, so no organization-level anomaly is flagged.  To identify and investigate organization-level cost anomalies, you need to be signed in to the [organization account](/user-guide/organization-accounts) or an [ORGADMIN-enabled account](#label-enabling-orgadmin-role-for-account).++</dd>+<dt>Anomaly monitors</dt>+<dd>++An anomaly monitor is a named, custom scope that you define yourself. Instead of watching a whole account, a monitor watches only the+consumption that matches the [object tags](/user-guide/object-tagging/introduction) and+[service types](/sql-reference/service-types) you choose. Snowflake attributes consumption to each monitor daily, runs the same+detection algorithm against it, and can email a notification list that is specific to that monitor.++Use monitors when account-level detection is too coarse. For example, you can create a monitor for each business unit, cost center, team,+or project so a spike inside one team's warehouses is flagged even when total account consumption looks normal.++Anomaly monitors are a preview feature. For more information, see [](#label-cost-anomaly-monitors).++</dd>+</dl>++<a id="label-cost-anomaly-monitors"></a>++## Anomaly monitors++Available to all accounts.++An anomaly monitor is scoped by a configuration that contains the following:++<dl>+<dt>Object tags</dt>+<dd>++Tag and value pairs. Consumption from any resource that carries a matching tag is attributed to the monitor, as long as that consumption+belongs to the monitor's [credit family](#label-cost-anomaly-monitor-credit-family).++Only resource-level [object tags](/user-guide/object-tagging/introduction) are supported, which means tags applied directly to a resource+such as a warehouse, database, or table. Monitors don't support the following:++- **User tags.** You can't scope a monitor by tagging users. A monitor evaluates tags on resources only.+- **Shared resource attribution.** When a resource is used by more than one team, a monitor attributes all of that resource's consumption+  to the monitor. A monitor can't attribute only the share consumed by specific users.++[Budgets](/user-guide/budgets) support both of these. If you need to attribute the consumption of a shared resource by user, use a budget+instead. For more information, see [](/user-guide/budgets/budget-shared-resources).++To include a tag in a monitor's scope, you need the `APPLYBUDGET` privilege on that tag. For more information, see+[](/user-guide/cost-anomalies-access-control).++</dd>+<dt>Service types</dt>+<dd>++Account-level [service types](/sql-reference/service-types). Consumption for a service type you include is attributed to+the monitor in full, for the whole account, regardless of the tags in the monitor's scope. Include service types when you want a monitor+to cover consumption that isn't attributable to a tagged resource.++</dd>+<dt>Credit family</dt>+<dd>++Either `CREDITS` or `AI-CREDITS`. See [](#label-cost-anomaly-monitor-credit-family).++</dd>+</dl>++A monitor's scope must include at least one object tag or at least one service type. You can use tags on their own, service types on their+own, or a combination of both, but a monitor can't have an empty scope. A monitor can include up to 20 tag and value pairs and up to 20+service types.++A monitor's scope is the union of everything in it. Consumption is attributed to the monitor if it matches any tag in the scope or belongs to+any service type in the scope. Tags aren't combined, so a resource doesn't need to carry every tag to be included. When a resource matches+more than one part of the scope, the monitor counts its consumption once, so nothing is double counted.++Monitors are scoped to a single account, so you can't create a monitor that spans all accounts in an organization. Each account can have+up to 20 monitors.++<a id="label-cost-anomaly-monitor-credit-family"></a>++### Credit families++Credits and AI credits are different units of measure and can't be added together. Because of this, each monitor tracks exactly one+credit family, which you choose when you create the monitor:++<div className="colwidths-given">++  <colgroup>+    <col style={{width: "25.0%"}} />+    <col style={{width: "75.0%"}} />+  </colgroup>+  <thead>+    <tr>+      <th>Credit family</th>+      <th>Description</th>+    </tr>+  </thead>+  <tbody>+    <tr>+      <td><code>CREDITS</code></td>+      <td>++Traditional consumption, such as virtual warehouse compute, serverless tasks, and Snowpipe.++</td>+    </tr>+    <tr>+      <td><code>AI-CREDITS</code></td>+      <td>++Consumption for AI-related services, such as Cortex Search, Cortex Agents, and AI functions.++</td>+    </tr>+  </tbody>++</div>++The credit family you choose determines which service types you can add to the monitor. You can only add service types that are billed+in that credit family. To find the credit family for a service type, see the `Unit` column in [](/sql-reference/service-types). A unit of+`Credits` corresponds to the `CREDITS` credit family, and `AI Credits` corresponds to `AI-CREDITS`.++The credit family also filters the consumption that a monitor's tags attribute. A tagged resource can consume both credits and AI credits,+but a monitor counts only the consumption that belongs to its own credit family. Consumption in the other credit family is excluded, even+though the tag matches.++To track both traditional consumption and AI consumption for the same set of tags, create two monitors, one for each credit family.++### Keep a monitor up to date++Snowflake recomputes each monitor's consumption daily, so a change to a tag's definition is reflected within 24 hours. Retagging resources+is different: Snowflake can't detect that a resource gained or lost a tag, so if you retag resources and want the monitor's history+refreshed immediately, you can force a recalculation. For more information, see+[](/user-guide/cost-anomalies-ui) or [](/user-guide/cost-anomalies-class).++Before you save a monitor, you can also test a combination of tags and service types and see the anomalies it would produce. Test+configurations aren't saved and are lost when your session ends. To save one, select **Create new monitor from config**.  ## Get started@@ -48,4 +191,6 @@   [](/user-guide/cost-anomalies-access-control). +Anomaly monitors... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/migrations/snowconvert-docs/general/release-notes/release-notes/README+++ bhttps://docs.snowflake.com/en/migrations/snowconvert-docs/general/release-notes/release-notes/README@@ -2,4 +2,167 @@  The SnowConvert AI tool is subject to the [Conversion Software Terms of Use](https://www.snowflake.com/en/legal/technical-services-and-education/conversion-software-terms/).++## Version 2.41.1 (Aug 20, 2026)++### CLI++#### New Features++- Added `--resume-compute-pool` flag for `data orchestrator` and `data worker` commands.+- Added `--renamingfile` support for Druid conversions on the CLI.+- Added `--dbt-repointing` CLI flag for dbt project repointing during conversion.+- Added `--json` and `--yes` support for data orchestrator and worker agent updates.++#### Improvements++- Added a warning when starting a local orchestrator while an SPCS orchestrator is already configured.+- Improved `doctor` command to validate DEW-config Snowflake account connectivity and block start on errors.+- Improved local data migration performance by lowering poll intervals.+- Scoped `data start` doctor checks to `--local` mode and moved grant checks to setup.+- Resolved Snowflake metadata for all assessment commands.+- Added data identity affinity axis to data commands.++#### Bug Fixes++- Fixed DECIMAL key repair to stay within declared precision.+- Fixed `enum_domain` unsolved constraints to gate on branch predicate and join edge relevance.++### Conversion Engine++#### New Features++##### General++- Added Hybrid Table conversion support.+- Added dbt repointing integration into the conversion pipeline with ETL and BI repointing report generation.++##### Druid++- Extended the renaming file format to support table-scoped column mappings.++##### Power BI++- Added pre-scan and validated dependent-connection repointing with renaming bridge for Teradata sources.++##### SQL Server++- Added inlining of certain multi-statement dynamic SQL batches as `BEGIN...END` blocks.++#### Bug Fixes++##### Oracle++- Fixed parsing of `NORMALIZE` as an identifier.+- Fixed parsing of `CONSTRAINT` and `RENAME` as unquoted identifiers.+- Fixed parsing and transformation of `XMLPI(NAME ...)`.+- Fixed parsing of `DIMENSION` as an unquoted identifier in procedures.+- Fixed parsing of indexed collection elements as `BULK COLLECT INTO` targets.+- Fixed chained `PIVOT` parsing where `AsClause` consumed the next `PIVOT`.+- Fixed parsing of newline `/` as division before a parenthesized operand.+- Fixed parsing of `EXTERNAL C` callouts in package procedures.+- Fixed `OverallProcedure` parsing errors.+- Fixed parsing of nested indexed collection method calls like `map(key)(i).EXTEND`.+- Fixed parsing of `MATCH_RECOGNIZE PATTERN` star quantifier and `ALL ROWS PER MATCH`.+- Fixed record-collection `BULK COLLECT` mapping to `ARRAY` of `OBJECT`s with unified dense-collection index handling.+- Fixed demoted-UDF temp variable name qualification.++##### SQL Server++- Fixed `MERGE INTO` with updatable CTE to rewrite to base table reference.+- Fixed `WITH` clause comment-out when only `DATA_COMPRESSION` option remains.+- Added `SSC-EWI-0073` warning for `MEMORY_OPTIMIZED` table option.+- Fixed `sp_executesql` OUTPUT parameter collision producing doubled `INTO` clause.+- Fixed `FORMAT` function conversion for `'0,,'` scale and `'00 - '` zero-pad with literal tail patterns.++##### Tableau++- Fixed identifier casing preservation and statement terminator stripping in Tableau embedded SQL for Oracle sources.++##### Teradata++- Fixed `HybridTableConversionMode` to default to `Standard` when unset.++##### General++- Fixed conversion state isolation by building a fresh task manager per conversion job.++### Data Validation++#### New Features++- Added IBM DB2 platform support for data validation, data migration orchestrator, and data exchange agent.+- Added Iceberg table support for DMVF workflows including Iceberg-aware runtime writers and SPCS environment integration.+- Added Iceberg example workflows and documentation.++#### Improvements++- Improved large table partition boundary analysis by sampling before NTILE computation.+- Added support for snake_case YAML configuration keys and improved SQL Server index key inference.+- Changed `cleanUpTransientResources` default to `on-success` for improved resource management.+- Added per-table column selection support for L2 metrics.+- Adopted the native `redshift_connector` for Redshift connections in the Data Exchange Agent.++#### Bug Fixes++- Fixed an issue where DV L2 coverage was incorrectly disabled by the metrics exclude-list bug.+- Fixed Oracle data migration and data validation type mapping inconsistencies and aligned DM CREATE with SnowConvert output.+- Fixed an issue where VARCHAR partition keys containing only digits were not reliably used in WHERE clauses for partitioned queries.++### Others++#### Testing Framework++##### New Features++- Added target-side zero-copy-clone isolation for ETL test runs in `scai test`.+- Added source-side backup and restore isolation for the ETL write-set in `scai test etl-validate`, gated on a write-privilege pre-check.+- Added per-side column selection support for test comparisons.+- Added query ID recording for result-set procedure CALL executions.+- Added `SELECT * FROM` emission for table-valued functions in `scai test seed`.++##### Improvements++- Improved test-YAML validation block shape checking at the discovery boundary.+- Improved test seeding to run against the physical target database.+- Improved testing results isolation by separating the results database and rewriting logical names.+- Improved ETL validation to verify Snowflake source tables for non-equivalent validations in `scai test etl-validate`.+- Resolved the source dialect from the SCAI project configuration in the test runner.+- Resolved the DVF comparison source for Teradata and failed declared-but-uncomparable tables.+- Quoted identifiers across the clone isolation chain.+- Re-paired registry `targetName` with its own source parameter.++##### Bug Fixes++- Fixed LOGGER warnings and errors not appearing on stderr for user visibility.++#### Migration Plugin++##### New Features++- Added Dynamic SQL Assessment dashboard with API endpoints and visualization.+- Added Anti-Patterns report to the Assessment dashboard.+- Added Dependencies tab to the Assessment waves view, including overview KPIs, impact tables, and detail modal with export.+- Added data migration and validation strategy capture during the setup phase.++##### Improvements++- Improved DMV infrastructure lifecycle with down guard, readiness gate, and idempotent startup.+- Added session ownership information to object claims.+- Accepted `group` as an alias for `group_id` in `migration_status` tool calls.++##### Bug Fixes++- Fixed SCAI project defaults resolution from the app startup path.+- Fixed spurious `plugin.yml` creation at the current working directory for `dashboard_port`.++#### Code Unit Registry++##### New Features++- Made user-initiated registry renames durable on Windows.++##### Bug Fixes++- Fixed directory sync on Windows skipping `fsync` to prevent registry corruption.  ## Version 2.40.1 (Aug 13, 2026) 

--- ahttps://docs.snowflake.com/en/sql-reference/snowflake-db-roles+++ bhttps://docs.snowflake.com/en/sql-reference/snowflake-db-roles@@ -84,4 +84,38 @@     <tr>       <td>+        [AGGREGATE_ACCESS_HISTORY+        view](/sql-reference/account-usage/aggregate_access_history)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [AGGREGATE_QUERY_HISTORY+        view](/sql-reference/account-usage/aggregate_query_history)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [AGGREGATION_POLICIES+        view](/sql-reference/account-usage/aggregation_policies)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [ANOMALIES_DAILY view](/sql-reference/account-usage/anomalies_daily)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [APPLICATION_CALLBACK_HISTORY+        view](/sql-reference/account-usage/application_callback_history)+      </td>+      <td>SECURITY_VIEWER</td>+    </tr>+    <tr>+      <td>         [APPLICATION_CONFIGURATIONS         view](/sql-reference/account-usage/application_configurations)@@ -91,38 +125,4 @@     <tr>       <td>-        [AGGREGATE_ACCESS_HISTORY-        view](/sql-reference/account-usage/aggregate_access_history)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [AGGREGATE_QUERY_HISTORY-        view](/sql-reference/account-usage/aggregate_query_history)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [AGGREGATION_POLICIES-        view](/sql-reference/account-usage/aggregation_policies)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [ANOMALIES_DAILY view](/sql-reference/account-usage/anomalies_daily)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [APPLICATION_CALLBACK_HISTORY-        view](/sql-reference/account-usage/application_callback_history)-      </td>-      <td>SECURITY_VIEWER</td>-    </tr>-    <tr>-      <td>         [APPLICATION_CONFIGURATION_VALUE_HISTORY         view](/sql-reference/account-usage/application_configuration_value_history)@@ -301,4 +301,18 @@     <tr>       <td>+        [CORTEX_PROVISIONED_THROUGHPUT_USAGE_HISTORY+        view](/sql-reference/account-usage/cortex_provisioned_throughput_usage_history)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [CORTEX_REST_API_USAGE_HISTORY+        view](/sql-reference/account-usage/cortex_rest_api_usage_history)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>         [CORTEX_SEARCH_BATCH_QUERY_USAGE_HISTORY         view](/sql-reference/account-usage/cortex_search_batch_query_usage_history)@@ -315,18 +329,4 @@     <tr>       <td>-        [CORTEX_PROVISIONED_THROUGHPUT_USAGE_HISTORY-        view](/sql-reference/account-usage/cortex_provisioned_throughput_usage_history)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [CORTEX_REST_API_USAGE_HISTORY-        view](/sql-reference/account-usage/cortex_rest_api_usage_history)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>         [CORTEX_SEARCH_SERVING_USAGE_HISTORY         view](/sql-reference/account-usage/cortex_search_serving_usage_history)@@ -582,5 +582,6 @@     <tr>       <td>-        [ACCOUNT_USAGE.ONLINE_FEATURE_TABLE_REFRESH_HISTORY](/sql-reference/account-usage/online_feature_table_refresh_history)+        [ONLINE_FEATURE_TABLE_REFRESH_HISTORY+        view](/sql-reference/account-usage/online_feature_table_refresh_history)       </td>       <td>USAGE_VIEWER</td>@@ -883,5 +884,5 @@       <td>         [SNOWFLAKE_COWORK_USAGE_HISTORY-        view](/sql-reference/account-usage/snowflake_cowork_usage_history_view)+        view](/sql-reference/account-usage/snowflake_cowork_usage_history)       </td>       <td>USAGE_VIEWER</td> 

--- ahttps://docs.snowflake.com/en/sql-reference/account-usage+++ bhttps://docs.snowflake.com/en/sql-reference/account-usage@@ -1617,4 +1617,38 @@     <tr>       <td>+        [AGGREGATE_ACCESS_HISTORY+        view](/sql-reference/account-usage/aggregate_access_history)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [AGGREGATE_QUERY_HISTORY+        view](/sql-reference/account-usage/aggregate_query_history)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [AGGREGATION_POLICIES+        view](/sql-reference/account-usage/aggregation_policies)+      </td>+      <td>GOVERNANCE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [ANOMALIES_DAILY view](/sql-reference/account-usage/anomalies_daily)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [APPLICATION_CALLBACK_HISTORY+        view](/sql-reference/account-usage/application_callback_history)+      </td>+      <td>SECURITY_VIEWER</td>+    </tr>+    <tr>+      <td>         [APPLICATION_CONFIGURATIONS         view](/sql-reference/account-usage/application_configurations)@@ -1624,38 +1658,4 @@     <tr>       <td>-        [AGGREGATE_ACCESS_HISTORY-        view](/sql-reference/account-usage/aggregate_access_history)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [AGGREGATE_QUERY_HISTORY-        view](/sql-reference/account-usage/aggregate_query_history)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [AGGREGATION_POLICIES-        view](/sql-reference/account-usage/aggregation_policies)-      </td>-      <td>GOVERNANCE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [ANOMALIES_DAILY view](/sql-reference/account-usage/anomalies_daily)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [APPLICATION_CALLBACK_HISTORY-        view](/sql-reference/account-usage/application_callback_history)-      </td>-      <td>SECURITY_VIEWER</td>-    </tr>-    <tr>-      <td>         [APPLICATION_CONFIGURATION_VALUE_HISTORY         view](/sql-reference/account-usage/application_configuration_value_history)@@ -1834,4 +1834,18 @@     <tr>       <td>+        [CORTEX_PROVISIONED_THROUGHPUT_USAGE_HISTORY+        view](/sql-reference/account-usage/cortex_provisioned_throughput_usage_history)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>+        [CORTEX_REST_API_USAGE_HISTORY+        view](/sql-reference/account-usage/cortex_rest_api_usage_history)+      </td>+      <td>USAGE_VIEWER</td>+    </tr>+    <tr>+      <td>         [CORTEX_SEARCH_BATCH_QUERY_USAGE_HISTORY         view](/sql-reference/account-usage/cortex_search_batch_query_usage_history)@@ -1848,18 +1862,4 @@     <tr>       <td>-        [CORTEX_PROVISIONED_THROUGHPUT_USAGE_HISTORY-        view](/sql-reference/account-usage/cortex_provisioned_throughput_usage_history)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>-        [CORTEX_REST_API_USAGE_HISTORY-        view](/sql-reference/account-usage/cortex_rest_api_usage_history)-      </td>-      <td>USAGE_VIEWER</td>-    </tr>-    <tr>-      <td>         [CORTEX_SEARCH_SERVING_USAGE_HISTORY         view](/sql-reference/account-usage/cortex_search_serving_usage_history)@@ -2115,5 +2115,6 @@     <tr>       <td>-        [ACCOUNT_USAGE.ONLINE_FEATURE_TABLE_REFRESH_HISTORY](/sql-reference/account-usage/online_feature_table_refresh_history)+        [ONLINE_FEATURE_TABLE_REFRESH_HISTORY+        view](/sql-reference/account-usage/online_feature_table_refresh_history)       </td>       <td>USAGE_VIEWER</td>@@ -2416,5 +2417,5 @@       <td>         [SNOWFLAKE_COWORK_USAGE_HISTORY-        view](/sql-reference/account-usage/snowflake_cowork_usage_history_view)+        view](/sql-reference/account-usage/snowflake_cowork_usage_history)       </td>       <td>USAGE_VIEWER</td> 

--- ahttps://docs.snowflake.com/en/release-notes/preview-features+++ bhttps://docs.snowflake.com/en/release-notes/preview-features@@ -79,4 +79,32 @@   <tbody>     <tr>+      <td>Anomaly monitors for cost anomalies</td>+      <td>Open</td>+      <td>August 2026</td>+      <td>[](#label-cost-anomaly-monitors)</td>+      <td>Define a custom cost anomaly detection scope using object tags and account-level service types, so you can monitor a business unit, cost center, or project instead of a whole account. Manage monitors in %sf-web-interface% or with new ANOMALY_INSIGHTS class methods.</td>+    </tr>+    <tr>+      <td>DCM Projects extensions</td>+      <td>Open</td>+      <td>August 2026</td>+      <td>[](/user-guide/dcm-projects/dcm-projects-supported-entities), [](/user-guide/dcm-projects/dcm-projects-use), [](/user-guide/dcm-projects/dcm-projects-pipelines)</td>+      <td>+        <ul>+          <li>[`DEFINE PIPE`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-pipe): Declaratively manage pipes in %dcm% definition files.</li>+          <li>[`DEFINE SHARE`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-share): Declaratively manage share objects and their grants in %dcm% definition files, controlling which objects are exposed to the share.</li>+          <li>[`DEFINE STREAM`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-stream): Declaratively manage streams in %dcm% definition files.</li>+          <li>[`DEFINE MASKING POLICY`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-masking-policy): Declaratively manage masking policies in %dcm% definition files. Attaching to tables or views isn't yet supported.</li>+          <li>[`DEFINE ROW ACCESS POLICY`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-row-access-policy): Declaratively manage row access policies in %dcm% definition files. Attaching to tables or views isn't yet supported.</li>+          <li>[`DEFINE SEMANTIC VIEW`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-semantic-view): Declaratively manage semantic views in %dcm% definition files.</li>+          <li>[`ATTACH TAG`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-attach-tag): Declaratively assign Snowflake object tags to %dcm%-managed entities; %dcm% reconciles declared tag assignments on every deployment.</li>+          <li>[Inherited grants](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-inherited-grants): Declaratively define a single `GRANT INHERITED` statement on a container (`ACCOUNT`, `DATABASE`, or `SCHEMA`) that automatically applies to every current and future object of a specified type within it.</li>+          <li>[Container-level `MANAGE GRANTS`](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-container-manage-grants): Delegate grant administration for a database or schema to a role that manages all grant types on objects inside that container.</li>+          <li>[%dcm% `TEST` and `PREVIEW` commands](/user-guide/dcm-projects/dcm-projects-pipelines): Test data quality expectations attached to managed objects, and return sample rows from tables, views, or dynamic tables defined in a %dcm-object% before or after deployment.</li>+          <li>[%dcm% GitHub Actions](/user-guide/dcm-projects/dcm-projects-use#label-dcm-github-actions): Reusable composite GitHub Actions (`dcm-parse-manifest`, `dcm-connection-test`, `dcm-plan`, and `dcm-deploy`) that automate %dcm% CI/CD pipelines.</li>+        </ul>+      </td>+    </tr>+    <tr>       <td>Snowflake ODBC Driver 4.x, built on the Universal Core</td>       <td>Open</td>@@ -126,4 +154,18 @@       <td>[](/user-guide/snowflake-cortex/snowflake-cowork/automations)</td>       <td>Turn a one-time report into a recurring one that re-runs your question with fresh data and emails you the results, set up and managed conversationally or from the Automations tab.</td>+    </tr>+    <tr>+      <td>User skills in %sf-intelligence%</td>+      <td>Open</td>+      <td>August 2026</td>+      <td>[](/user-guide/snowflake-cortex/snowflake-cowork/user-skills)</td>+      <td>Create reusable workflows conversationally, from the UI (+ menu > Skills > Create new), or by uploading a skill folder, then run them explicitly with / or from Skills menus, or implicitly when a conversation matches the skill. Chat creation and scripted skills require the Cortex Agent code execution tool.</td>+    </tr>+    <tr>+      <td>Document generation in %sf-intelligence%</td>+      <td>Open</td>+      <td>August 2026</td>+      <td>[](/user-guide/snowflake-cortex/snowflake-cowork/document-generation)</td>+      <td>Generate shareable files such as PDF documents and PowerPoint presentations from your analysis. Upload a PowerPoint template to match your organization's style, or customize behavior with a user or agent skill. Requires the Cortex Agent code execution tool.</td>     </tr>     <tr>@@ -198,11 +240,4 @@     </tr>     <tr>-      <td>Organization Hub</td>-      <td>Open</td>-      <td>June 2026</td>-      <td>[](/user-guide/organization-hub)</td>-      <td>A dashboard for organization accounts that consolidates cost management, security posture, query health, and storage growth metrics across all accounts in your organization. Requires an organization account with premium views enabled. Access requires the GLOBALORGADMIN role.</td>-    </tr>-    <tr>       <td>Cortex Agent tool evaluation metrics (TSA and TEA)</td>       <td>Open</td>@@ -277,5 +312,5 @@  </td>-      <td>Additional commands that create an object if it doesn't exist, or alters it according to the object definition.</td>+      <td>Additional commands that create an object if it doesn't exist, or alter it according to the object definition.</td>     </tr>     <tr>@@ -400,37 +435,9 @@     </tr>     <tr>-      <td>%dcm% TEST and PREVIEW commands</td>-      <td>Open</td>-      <td>March 2026</td>-      <td>[](/user-guide/dcm-projects/dcm-projects-pipelines), [](/developer-guide/snowflake-cli/command-reference/dcm-commands/test), [](/developer-guide/snowflake-cli/command-reference/dcm-commands/preview)</td>-      <td>Test data quality expectations attached to managed objects, and return sample rows from tables, views, or dynamic tables defined in a %dcm-object% before or after deployment.</td>-    </tr>-    <tr>-      <td>%dcm% GitHub Actions</td>-      <td>Open</td>-      <td>March 2026</td>-      <td>[](/user-guide/dcm-projects/dcm-projects-use#label-dcm-github-actions)</td>-      <td>Reusable composite GitHub Actions (`dcm-parse-manifest`, `dcm-connection-test`, `dcm-plan`, and `dcm-deploy`) that automate %dcm% CI/CD pipelines.</td>-    </tr>-    <tr>-      <td>`DEFINE PIPE` and `DEFINE STREAM` in %dcm%</td>-      <td>Open</td>-      <td>March 2026</td>-      <td>[](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-pipe), [](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-stream)</td>-      <td>Declaratively manage pipes and streams in %dcm% definition files.</td>-    </tr>-    <tr>-      <td>`DEFINE MASKING POLICY` and `DEFINE ROW ACCESS POLICY` in %dcm%</td>-      <td>Open</td>-      <td>July 2026</td>-      <td>[](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-masking-policy), [](/user-guide/dcm-projects/dcm-projects-supported-entities#label-dcm-projects-object-type-row-access-policy)</td>-      <td>Declaratively manage masking policies and row access policies in %dcm% definition files. Attaching these policies to tables or views isn't yet supported.</td>-    </tr>-    <tr>-      <td>`ATTACH TAG` in %dcm%<... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/parse-document+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/parse-document@@ -48,16 +48,4 @@ Documents can be processed directly from object storage to avoid unnecessary data movement. -<div className="previewfeat sidebar">--<div className="sidebar-title">--%logo-snowflake-black% [Preview Feature](/release-notes/preview-features) — Open--</div>--Available to all accounts.--</div>- AI_PARSE_DOCUMENT supports documents on stages that use client-side or server-side encryption, including in accounts that use PrivateLink or other [network policies](/user-guide/network-policies) that restrict public network access to stages.@@ -95,5 +83,5 @@ </div> -To view either of the these images at a more legible size, select it by clicking or tapping.+To view either of these images at a more legible size, select it by clicking or tapping.  The following is the SQL command to process the original document:@@ -230,5 +218,5 @@ </div> -To view either of the these images at a more legible size, select it by clicking or tapping.+To view either of these images at a more legible size, select it by clicking or tapping.  The following is the SQL command to process the original document:@@ -344,5 +332,5 @@ </div> -To view either of the these images at a more legible size, select it by clicking or tapping.+To view either of these images at a more legible size, select it by clicking or tapping.  The following is the SQL command to process the original document:@@ -410,5 +398,5 @@ </div> -To view either of the these images at a more legible size, select it by clicking or tapping.+To view either of these images at a more legible size, select it by clicking or tapping.  The following is the SQL command to process the original document. Since the document has a single page,@@ -427,5 +415,5 @@   "metadata": {     "pageCount": 1-  }+  },   "content": "![img-0.jpeg](img-0.jpeg)\n\nSchulen haben es verdient, gute Orte zu sein. Hier sollen wir Wissen und Fähigkeiten   erlernen, die uns durch das Leben tragen. Hier verbringen viele einen Großteil ihres Tages, und das in einer Lebensphase, in@@ -517,5 +505,5 @@  This example demonstrates using the `page_filter` option to extract specific pages from a document, specifically-the first page of a 55-page research paper. Keep in mind that page indexes starts at 0 and ranges are inclusive of+the first page of a 55-page research paper. Keep in mind that page indexes start at 0 and ranges are inclusive of the start value but exclusive of the end value. For example, `start: 0, end: 1` returns only the first page (index 0). @@ -782,5 +770,5 @@ ## Input requirements -AI_PARSE_DOCUMENT is optimized for documents both digital-born and scanned. The following table lists the limitations and+AI_PARSE_DOCUMENT is optimized for both digital-born and scanned documents. The following table lists the limitations and requirements of input documents: @@ -915,14 +903,14 @@ Support for AI_PARSE_DOCUMENT is available to accounts in the following Snowflake regions: -| AWS                          | Azure                  | Google Cloud Platform         |-| ---------------------------- | ---------------------- | ----------------------------- |-| US West 2 (Oregon)           | East US 2 (Virginia)   | US Central 1 (Iowa)           |-| US East (Ohio)               | West US 2 (Washington) | Middle East Central2 (Dammam) |-| US East 1 (N. Virginia)      | Europe (Netherlands)   |                               |-| Europe (Ireland)             |                        |                               |-| Europe Central 1 (Frankfurt) |                        |                               |-| Europe West 2 (London)       |                        |                               |-| Asia Pacific (Sydney)        |                        |                               |-| Asia Pacific (Tokyo)         |                        |                               |+| AWS                          | Azure                  | Google Cloud Platform          |+| ---------------------------- | ---------------------- | ------------------------------ |+| US West 2 (Oregon)           | East US 2 (Virginia)   | US Central 1 (Iowa)            |+| US East (Ohio)               | West US 2 (Washington) | Middle East Central 2 (Dammam) |+| US East 1 (N. Virginia)      | Europe (Netherlands)   |                                |+| Europe (Ireland)             |                        |                                |+| Europe Central 1 (Frankfurt) |                        |                                |+| Europe West 2 (London)       |                        |                                |+| Asia Pacific (Sydney)        |                        |                                |+| Asia Pacific (Tokyo)         |                        |                                |  AI_PARSE_DOCUMENT has cross-region support in other Snowflake regions. For information on enabling Cortex AI cross-region support, see [](/user-guide/snowflake-cortex/cross-region-inference). 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-teradata+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-teradata@@ -9,5 +9,5 @@ - **Teradata connectivity on Workers**: Same as data migration. Prefer **`teradatasql`** when available; otherwise set **`odbc_driver`** to the exact registered driver name. Optional **`dbc_name`**, port **1025** by default, optional **`authentication`** (TD2, LDAP, KRB5). - **HASH_MD5 UDF (required for L3 row fingerprinting)**: See [HASH_MD5 UDF](#hash_md5-udf) below.-- **No WRITE_NOS or TPT for validation-only Workers**: Validation reads the source over SQL (L2/L3). You don't need **`write_nos_*`** TOML or **`tbuild`** on a host solely running validation, unless the same Worker also executes migration **`tpt`** or **`write_nos`** tasks.+- **No WRITE_NOS or TPT for validation-only Workers**: Validation reads the source over SQL (metrics and row-level validation). You don't need **`write_nos_*`** TOML or **`tbuild`** on a host solely running validation, unless the same Worker also executes migration **`tpt`** or **`write_nos`** tasks.  <a id="hash_md5-udf"></a>@@ -15,13 +15,9 @@ ## HASH_MD5 UDF -Teradata does not provide a built-in SQL function that Cloud Data Validation can use for L3 row fingerprinting. Instead, validation generates SQL that calls a custom user-defined function named **`HASH_MD5`**.+Teradata does not provide a built-in SQL function that Cloud Data Validation can use for row fingerprinting. Instead, validation generates SQL that calls a custom user-defined function named **`HASH_MD5`**.  ### What HASH_MD5 does -**`HASH_MD5`** is a **C language UDF** you install on Teradata. It accepts a string expression and returns an **MD5 message digest** (hex-encoded) for that input.--In **L3 row validation** (the default when `row_validation` is enabled), and when `row_validation_mode` is **`row`**, the Worker runs row-hash SQL on Teradata that normalizes each row's cell values, concatenates them, and passes the result to **`HASH_MD5(...)`**. Snowflake runs a matching **`MD5(...)`** expression on the target side. Validation compares the two digests to detect row-level mismatches before optional cell drilldown.--**L1 schema** validation and **L2 metrics** validation do **not** call **`HASH_MD5`**. **L3 cell** mode compares individual cell values and also does not depend on this UDF.+**`HASH_MD5`** is a C language UDF you install on Teradata. Row-level validation uses it to fingerprint each source row and compares the result against a matching hash on the Snowflake target. Schema and metrics validation don't use it.  ### Where the UDF must be installed@@ -55,5 +51,5 @@ ``` -A successful call returns an MD5 hex string. If the UDF is missing or not visible in the session default database, Teradata typically returns parser errors such as **3706** (function not found or invalid argument) or **3707** (syntax errors in generated hash SQL). Enable Worker **`application.debug_mode = true`** in TOML to log the full failing SELECT at DEBUG.+A successful call returns an MD5 hex string. If the call fails, the UDF is likely missing from the session's default database. Reinstall it there and retry.  Optional catalog check (replace the database name):@@ -90,5 +86,5 @@ | Topic | Data migration (load) | Cloud Data Validation | | --- | --- | --- |-| **Purpose** | Move data with `regular`, `write_nos`, or `tpt` | Compare live Teradata tables/views to Snowflake with L1/L2/L3 |+| **Purpose** | Move data with `regular`, `write_nos`, or `tpt` | Compare live Teradata tables/views to Snowflake with schema, metrics, and row-level validation | | **`write_nos_*` TOML** | Required when strategy is `write_nos` | **Not** required for validation-only workloads | | **`tbuild` / TTU** | Required for `tpt` migration tasks | **Not** required for validation-only Workers |@@ -96,9 +92,9 @@ ## Validation levels and Teradata behavior -**Schema validation on views (L1):** For Teradata **views**, L1 is a **reduced** comparison (column existence and datatype via `HELP COLUMN` metadata). Precision, scale, length, nullability, and ordinal checks aren't available for Teradata views. Use L2/L3 for deeper assurance.+**Schema validation on views:** For Teradata **views**, schema validation is a **reduced** comparison (column existence and datatype via `HELP COLUMN` metadata). Precision, scale, length, nullability, and ordinal checks aren't available for Teradata views. Use metrics and row-level validation for deeper assurance. -**Metrics validation (L2):** Full support for tables. Full support for views.+**Metrics validation:** Full support for tables. Full support for views. -**Row validation (L3):** Default L3 behavior and **`row_validation_mode: row`** require the [**HASH_MD5 UDF**](#hash_md5-udf). Use **`index_column_list`** for row alignment. Set **`column_names_to_partition_by`** and **`target_partition_size_mb`** or **`target_partition_size_rows`** on wide tables.+**Row validation:** Requires the [**HASH_MD5 UDF**](#hash_md5-udf). Use **`indexColumnList`** for row alignment. Set **`column_names_to_partition_by`** and **`target_partition_size_mb`** or **`target_partition_size_rows`** on wide tables.  **Example validation workflow excerpt:**@@ -120,5 +116,5 @@     target_schema: PUBLIC     target_name: SALES_TRANSACTIONS-    index_column_list:+    indexColumnList:       - TRANSACTION_ID     column_names_to_partition_by:@@ -129,5 +125,5 @@     target_schema: PUBLIC     target_name: SALES_SUMMARY_VIEW-    index_column_list:+    indexColumnList:       - ID     target_partition_size_rows: 50000@@ -149,13 +145,13 @@ | TIMESTAMP WITH TIME ZONE | TIMESTAMP_TZ | Yes | | | CHAR, VARCHAR | VARCHAR | Yes | |-| BOOLEAN | BOOLEAN | No | |-| CLOB | TEXT | No | |-| BYTE, VARBYTE, BLOB | BINARY | No | |-| JSON, XML | VARIANT | No | |-| ST_GEOMETRY | GEOGRAPHY | No | |+| BOOLEAN | | No | |+| CLOB | | No | |+| BYTE, VARBYTE, BLOB | | No | |+| JSON, XML | | No | |+| ST_GEOMETRY | | No | | | INTERVAL types | INTERVAL | Yes | Native `INTERVAL` comparison by default. See [INTERVAL data type handling](../manual-migration/data-validation-configuration-reference#interval-data-type-handling). |-| PERIOD types | VARCHAR | No | |-| ARRAY | ARRAY | No | |-| LONG VARCHAR, GRAPHIC, VARGRAPHIC, UNICODE types | VARCHAR | No | Metrics not supported |+| PERIOD types | | No | |+| ARRAY | | No | |+| LONG VARCHAR, GRAPHIC, VARGRAPHIC, UNICODE types | VARCHAR | Partial | Row-level and metrics validation not supported |  Use `comparison_configuration.type_mapping_file_path` to supply a custom mapping file when needed.@@ -163,5 +159,5 @@ ## Platform-specific considerations -- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (L1/L2/L3 per table).+- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (schema validation, metrics validation, and row-level validation, per table).    **Prompt:**@@ -172,6 +168,6 @@  - **After `tpt` or `write_nos` migrations**: Validation still reads the source over SQL. Ensure Teradata objects you validate are reachable and match the validation workflow names.-- **L3 cost control**: Default L3 fingerprints rows before cell drilldown, which is usually cheaper than `row_validation_mode: cell` on large tables. Enable **`early_stopping`** and tune **`max_failed_rows_number`** per table.-- **Partitioning**: Use **`column_names_to_partition_by`** so wide tables don't time out on L2/L3 scans.+- **L3 cost control**: Enable **`early_stopping`** and tune **`max_failed_rows_number`** per table to avoid scanning partitions on a table that has clearly failed.+- **Partitioning**: Use **`column_names_to_partition_by`** so wide tables don't time out on metrics and row-level validation scans.... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices+++ bhttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices@@ -26,5 +26,5 @@ ### Increase parallelism with threads -Configure the `threads` parameter in your `profiles.yml` to control how many models dbt runs concurrently within a single execution. To be compatible with most Snowflake warehouses, Snowflake recommends setting your threads to 8. A higher thread count than 1 allows independent models to execute in parallel, reducing total wall-clock time for a given run.+Configure the `threads` parameter in [`dbt_projects_profiles.yml`](#label-dbt-projects-profiles-file) or `profiles.yml` to control how many models dbt runs concurrently within a single execution. To be compatible with most Snowflake warehouses, Snowflake recommends setting your threads to 8. A higher thread count than 1 allows independent models to execute in parallel, reducing total wall-clock time for a given run.  ```yaml@@ -60,7 +60,7 @@  1. **The calling role**: the active role of the session (or task owner role) that issues the `EXECUTE DBT PROJECT` statement. This role must have the EXECUTE DBT PROJECT privilege on the dbt project object.-2. **The profiles.yml role**: the role specified in your `profiles.yml` target. This role defines what the dbt run can actually access (databases, schemas, tables, warehouses) during execution.--Both roles must have USAGE on the warehouse. The calling role must also be able to USE the profiles.yml role. Operations during execution are restricted to the privileges that both roles have in common.+2. **The profile role**: the role specified in the target in your project's `dbt_projects_profiles.yml` or `profiles.yml`. The profile role defines what the dbt run can actually access (databases, schemas, tables, warehouses) during execution.++Both roles must have USAGE on the warehouse. The calling role must also be able to use the profile role. Operations during execution are restricted to the privileges that both roles have in common.  This two-role model applies whether you run dbt interactively (a human running `EXECUTE DBT PROJECT` in a worksheet) or through a scheduled task. The difference is:@@ -69,5 +69,5 @@ - **Task execution:** The task runs as a system service with the privileges of the **task owner role** (the role that has OWNERSHIP on the task). No specific user is associated with the run. -You can simplify this setup with an `env.yml` file instead of hardcoding a role in `profiles.yml`. Define a variable such as `DBT_CURRENT_ROLE: "{{ select CURRENT_ROLE() }}"` in `env.yml`, then reference it from `profiles.yml` with `role: "{{ env_var('DBT_CURRENT_ROLE') }}"`. The `profiles.yml` role then resolves to the calling role on every run. For more information, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-environment-variables).+You can simplify this setup with an `env.yml` file instead of hardcoding a role in `dbt_projects_profiles.yml` or `profiles.yml`. Define a variable such as `DBT_CURRENT_ROLE: "{{ select CURRENT_ROLE() }}"` in `env.yml`, then reference it from the profile file with `role: "{{ env_var('DBT_CURRENT_ROLE') }}"`. The profile role then resolves to the calling role on every run. For more information, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-environment-variables).  ### Use a dedicated service account@@ -81,5 +81,5 @@ ### Align your warehouse configuration -Use the same warehouse in both your task definition and your `profiles.yml` target to avoid waking two warehouses for a single orchestration run:+Use the same warehouse in both your task definition and the target in `dbt_projects_profiles.yml` or `profiles.yml` to avoid waking two warehouses for a single orchestration run:  ```sql@@ -100,7 +100,7 @@ ``` -If the task uses `warehouse_a` but your profiles.yml specifies `warehouse_b`, both warehouses wake up for one run.--To keep them aligned automatically, use an `env.yml` file instead of hardcoding the warehouse. Define a variable such as `DBT_CURRENT_WH: "{{ select CURRENT_WAREHOUSE() }}"` in `env.yml`, then reference it from `profiles.yml` with `warehouse: "{{ env_var('DBT_CURRENT_WH') }}"`. The `profiles.yml` warehouse then matches the calling task warehouse on every run.+If the task uses `warehouse_a` but your profile file specifies `warehouse_b`, both warehouses wake up for one run.++To keep them aligned automatically, use an `env.yml` file instead of hardcoding the warehouse. Define a variable such as `DBT_CURRENT_WH: "{{ select CURRENT_WAREHOUSE() }}"` in `env.yml`, then reference it from the profile file with `warehouse: "{{ env_var('DBT_CURRENT_WH') }}"`. The profile warehouse then matches the calling task warehouse on every run.  ### Use task graphs for multi-step pipelines@@ -230,5 +230,5 @@ - **Build on another team's models:** Depend on models that a different team owns and maintains. -dbt Core supports importing from both a single monorepo or separate repositories.+dbt Core supports importing from either a single monorepo or separate repositories.  ### How it works@@ -324,5 +324,24 @@ | Local IDE + Snowflake CLI                    | Teams with established local dbt Core workflows               | Familiar tools, deploy to Snowflake via CI/CD            | -All three environments support the same dbt project files and produce the same results when deployed.+All three environments support standard dbt Core and produce the same results when deployed.++<a id="label-dbt-projects-profiles-file"></a>++### Use dbt_projects_profiles.yml for a unified development-to-production experience++Teams migrating from self-hosted dbt Core often already have a `~/.dbt/profiles.yml` that their entire local workflow depends on. Previously, dbt Projects on Snowflake required a `profiles.yml` in the project root, and because dbt Core checks the project directory before `~/.dbt/`, that file silently took over for local runs too. Your team was stuck overwriting personal profiles, passing `--profiles-dir` by hand on every local command, or forcing everyone onto the same workflow.++The `dbt_projects_profiles.yml` file solves this:++- It works the same way as `profiles.yml` but is specifically for dbt Projects on Snowflake.+- dbt Projects on Snowflake supports both file names. If both files are present, Snowflake uses `dbt_projects_profiles.yml` and ignores `profiles.yml` during deployment, compilation, and subsequent commands. If `dbt_projects_profiles.yml` isn't present, Snowflake uses `profiles.yml` as before.+- Standard dbt doesn't recognize `dbt_projects_profiles.yml`. The local dbt CLI reads only `profiles.yml`, so adding `dbt_projects_profiles.yml` never disrupts anyone's existing local dbt workflow, including a personal `~/.dbt/profiles.yml`.+- It works across Workspaces, Cortex Code Desktop (Snowflake-managed mode), and deployed dbt project objects. In Workspaces and Cortex Code Desktop, the profile picker displays targets from `dbt_projects_profiles.yml` when present.++Hybrid teams can maintain both workflows side by side: some engineers can use the local dbt CLI with their personal `~/.dbt/profiles.yml`, while others use Workspaces or Cortex Code Desktop with the in-project `dbt_projects_profiles.yml`. Both groups can share one Git-versioned project without reconfiguring connections and can switch between local and Snowflake-managed development. The deployed dbt project object also uses `dbt_projects_profiles.yml`, so admins can configure production connection settings in a single version-controlled file.++After your team deploys with `dbt_projects_profiles.yml`, pair it with `env.yml` to take advantage of Snowflake's SQL in YAML capability, which standard dbt Core doesn't offer on its own. Use SQL functions to compute time intervals for incremental processing, query control tabl... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/developer-guide/snowflake-cli/data-pipelines/dbt-projects+++ bhttps://docs.snowflake.com/en/developer-guide/snowflake-cli/data-pipelines/dbt-projects@@ -20,9 +20,9 @@  The [snow dbt deploy](/developer-guide/snowflake-cli/command-reference/dbt-commands/deploy) command uploads local files to a temporary stage and creates a new dbt project object or updates it by-making a new version. A valid dbt project must contain two files:+making a new version. A valid dbt project must contain `dbt_project.yml` and one of the supported profile files:  - `dbt_project.yml`: A standard dbt configuration file that specifies the profile to use.-- `profiles.yml`: A dbt connection profile definition referenced in `dbt_project.yml`. `profiles.yml` must define the database, role, schema, and type.-  - By default, %sf-dbt% uses your target schema (`target.schema`) specified from your dbt environment or profile. When you execute a dbt project object, dbt attempts to create the target schema specified in `profiles.yml` if it doesn't already exist. For more information, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-schema-customization).+- [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml`: A dbt connection profile definition referenced in `dbt_project.yml`. The selected profile file must define the database, role, schema, and type. If both files are present, Snowflake uses `dbt_projects_profiles.yml` and ignores `profiles.yml` during deployment, compilation, and subsequent commands.+  - By default, %sf-dbt% uses your target schema (`target.schema`) specified from your dbt environment or profile. When you execute a dbt project object, dbt attempts to create the target schema specified in `dbt_projects_profiles.yml` or `profiles.yml` if it doesn't already exist. For more information, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-schema-customization).    ```yaml@@ -34,4 +34,5 @@         role: <role_name>         schema: <schema_name>+        warehouse: <warehouse_name>         type: snowflake   ```@@ -47,15 +48,15 @@   ``` -- Deploy a project named `jaffle_shop` from a specified directory, using a `profiles.yml` from a separate directory. The CLI copies that `profiles.yml` into the root of the deployed project object, overwriting any existing `profiles.yml` in this location:--  ```snowcli-  snow dbt deploy jaffle_shop --source /path/to/dbt/directory --profiles-dir ~/.dbt/-  ```--- Deploy a project named `jaffle_shop` from a specified directory, supplying a `profiles.yml` from outside the project, setting a default target, pinning a dbt version, and enabling [external access integrations](/developer-guide/external-network-access/creating-using-external-network-access):+- Deploy a project named `jaffle_shop` from a specified directory, using a profile file from a separate directory. The CLI looks for `dbt_projects_profiles.yml` first and uses `profiles.yml` only if `dbt_projects_profiles.yml` isn't present. The CLI copies the file into the root of the deployed project object with the same filename, overwriting a file with the same name in this location:++  ```snowcli+  snow dbt deploy jaffle_shop --source /path/to/dbt/directory --profiles-dir ~/my_profiles/+  ```++- Deploy a project named `jaffle_shop` from a specified directory, supplying a profile file from outside the project, setting a default target, pinning a dbt version, and enabling [external access integrations](/developer-guide/external-network-access/creating-using-external-network-access):    ```snowcli   snow dbt deploy jaffle_shop --source /path/to/dbt/directory \-    --profiles-dir ~/.dbt/ \+    --profiles-dir ~/my_profiles/ \     --default-target prod \     --dbt-version 1.11.11 \@@ -176,10 +177,9 @@ 1. Prepare your dbt project:    1. Download your dbt project or start a new one.-      - Ensure that the main project directory contains the `dbt_project.yml` and `profiles.yml` files.-      - Verify that the profile name referenced in `dbt_project.yml` is defined in `profiles.yml`.---        Snowflake's dbt project objects don't need passwords, so if `profiles.yml` contains any, deployment stops until-        they are removed.+      - Ensure that the main project directory contains `dbt_project.yml` and either [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml`.+      - Verify that the profile name referenced in `dbt_project.yml` is defined in `dbt_projects_profiles.yml` or `profiles.yml`. If both files are present, Snowflake uses `dbt_projects_profiles.yml`.+++        Ensure that credentials are excluded from the profile file. Leave `account` and `user` as placeholder strings and let your CI/CD platform supply the connection through secrets or environment variables.   

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-oracle+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-oracle@@ -120,5 +120,9 @@ ### Incremental sync -Oracle supports **`none`** and **`watermark`**. **`checksum` is not supported** for Oracle. When there's no reliable updated-at column, the watermark can be a pseudo-column such as **`ORA_ROWSCN`**.+Oracle supports all three strategies: **`none`**, **`watermark`**, and **`checksum`**.++For **`watermark`**, if your tables don't have a reliable updated-at column, consider using **`ORA_ROWSCN`** — Oracle's built-in system change number pseudo-column that advances whenever a row is modified. It's a good default for watermark-based incremental sync on Oracle.++For **`checksum`**, AIM DMV computes a partition checksum over the normalized columns. Some Oracle types are excluded from the default hash, so review [Changes a checksum may not detect](../manual-migration/data-migration-configuration-reference#changes-a-checksum-may-not-detect) before relying on checksum sync.  **Prompt:**@@ -136,18 +140,22 @@ | FLOAT, REAL, BINARY_FLOAT, BINARY_DOUBLE | FLOAT | Yes | | | DOUBLE PRECISION | FLOAT | Yes | |-| VARCHAR2, NVARCHAR2, CHAR, NCHAR, VARCHAR | VARCHAR / CHAR | Yes | Oracle treats empty string as NULL |-| CLOB, NCLOB | TEXT | Yes | Very large LOBs may need workflow-level type overrides |+| VARCHAR2, NVARCHAR2, VARCHAR | VARCHAR | Yes | Oracle treats empty string as NULL |+| CHAR, NCHAR | VARCHAR | Yes | |+| CLOB, NCLOB | VARCHAR | Yes | Truncated at 4000 characters | | LONG | VARCHAR | Yes | | | RAW, BLOB, LONG RAW | BINARY | Yes | |-| BFILE | VARCHAR | Yes | |-| DATE | TIMESTAMP_NTZ | Yes | Oracle DATE includes time; maps to TIMESTAMP_NTZ |-| TIMESTAMP | TIMESTAMP_NTZ | Yes | Nanoseconds truncated to microseconds |+| BFILE | VARCHAR | Yes | Requires a server `DIRECTORY` object |+| DATE | TIMESTAMP_NTZ | Yes | |+| TIMESTAMP | TIMESTAMP_NTZ | Yes | | | TIMESTAMP WITH TIME ZONE | TIMESTAMP_TZ | Yes | |-| TIMESTAMP WITH LOCAL TIME ZONE | TIMESTAMP_LTZ | Yes | Converted using the session time zone |+| TIMESTAMP WITH LOCAL TIME ZONE | TIMESTAMP_LTZ | Yes | | | INTERVAL YEAR TO MONTH, INTERVAL DAY TO SECOND | INTERVAL | Yes | Native `INTERVAL` by default. See [INTERVAL data type handling](../manual-migration/data-migration-configuration-reference#interval-data-type-handling). |-| ROWID, UROWID | VARCHAR | Yes | |-| JSON, XMLTYPE | VARIANT | Yes | |-| SDO_GEOMETRY | (unmapped) | No | |-| BOOLEAN, VECTOR | (unmapped) | No | |+| ROWID | VARCHAR(18) | Yes | Stored as the hex string representation of the physical row address |+| UROWID | VARCHAR(4000) | Yes | |+| XMLTYPE | VARIANT | Yes | |+| JSON | VARIANT | Yes | Requires Oracle 21c or later |+| BOOLEAN | BOOLEAN | Yes | Requires Oracle 23ai or later |+| VECTOR | VECTOR(_element_type_, _n_) | Yes | Requires Oracle 23ai or later |+| SDO_GEOMETRY | GEOGRAPHY | Yes | Requires Oracle Spatial. Extracted as Well-Known Text. Non-geographic (projected or planar) geometries may not load as `GEOGRAPHY`; per-SRID routing to `GEOMETRY` is not available. Map the column to `VARCHAR` using `columnTypeMappings` and convert after the load if geometries are non-geographic. |  ## Platform-specific considerations@@ -168,6 +176,5 @@  - **Wallet-based TLS**: Use `wallet_directory` and `wallet_password` in Worker TOML when your Oracle environment requires wallet authentication.-- **No checksum sync**: Plan incremental loads with **`watermark`** instead of **`checksum`**, which is not supported for Oracle.-- **Anti-locking**: AIM DMV adds an automatic `PARALLEL` optimizer hint on large Oracle tables. Override with `queryModifiers.selectModifier`, or set `selectModifier` to `"NONE"` to disable. See [Anti-locking and query modifiers](../manual-migration/data-migration-configuration-reference#anti-locking-and-query-modifiers).+- **Performance hints**: AIM DMV adds an automatic `PARALLEL` optimizer hint on large Oracle tables to speed up scans. Override with `queryModifiers.selectModifier`, or set `selectModifier` to `"NONE"` to disable. See [Anti-locking and query modifiers](../manual-migration/data-migration-configuration-reference#anti-locking-and-query-modifiers).  ## Related content 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/required-privileges+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/required-privileges@@ -216,6 +216,9 @@ | Validation result Snowpipes | `SNOWCONVERT_AI.TEMP` | Per-workflow, auto-cleaned. | | Target tables | `<target_db>.<target_schema>` | Persistent. |-| `PREFLIGHT_<id>` schema | `<target_db>` | Per-workflow, auto-dropped. |+| `PREFLIGHT_<id>` schema | `<target_db>` | Per-workflow, dropped when the workflow ends unless `preflightKeepSchema` is `true`. See [Preflight: a bounded dry run](../manual-migration/data-migration-configuration-reference#preflight-bounded-dry-run). | | Transient staging tables | `<target_db>.<target_schema>` | Per-partition, auto-dropped. |+| Staged intermediate files | `TASK_RESULTS` stage, and external stages used by server-side extraction | Per-workflow, governed by `cleanUpTransientResources`. See [Cleaning up transient resources](../manual-migration/data-migration-configuration-reference#cleaning-up-transient-resources). |++If a workflow fails or is canceled, its staged files stay behind when `cleanUpTransientResources` is `on-success` (the default). That's deliberate, so you can inspect them. Set the property to `always` when you'd rather not accumulate them.  ## Customizing metadata database and schema names@@ -231,4 +234,8 @@ | `CUSTOM_SNOWFLAKE_SCHEMA_FOR_TEMP_METADATA` | `TEMP` | Temp and pipe schema name. | +Workers need matching values in their own configuration, because they read these locations from Worker TOML rather than from the Orchestrator's environment. See [Matching metadata locations between the Orchestrator and Workers](../manual-migration/data-migration-configuration-reference#matching-metadata-locations).++For the other environment variables AIM DMV reads, including metadata storage mode, secret resolution, and Teradata TPT paths, see [Environment variables](../manual-migration/data-migration-configuration-reference#environment-variables).+ ## Source platform privileges @@ -242,9 +249,9 @@ | --- | --- | --- | --- | | Oracle | `SELECT` on source tables | Automatic (`ALL_*` views) | `EXECUTE ON DBMS_CRYPTO` (LOB columns only) |-| SQL Server | `SELECT` on source schema and `VIEW DATABASE STATE` | `VIEW DEFINITION` | None (uses `HASHBYTES`) |+| SQL Server | `SELECT` on source schema and `VIEW DATABASE STATE` | `VIEW DEFINITION` | None | | Azure Synapse | Same as SQL Server | Same as SQL Server | CETAS extraction needs `CREATE EXTERNAL TABLE` |-| Amazon Redshift | `SELECT` on source tables and `USAGE` on schema | Automatic (`information_schema`) | None (uses an MD5 function) |+| Amazon Redshift | `SELECT` on source tables and `USAGE` on schema | Automatic (`information_schema`) | None | | Teradata | `SELECT` on source database and `SELECT` on `DBC` | Explicit `SELECT` on `DBC.*V` views | `HASH_MD5` UDF and `EXECUTE FUNCTION` |-| PostgreSQL | `SELECT` on source tables and `USAGE` on schema | Automatic (`pg_catalog`, `information_schema`) | None (uses an MD5 function) |+| PostgreSQL | `SELECT` on source tables and `USAGE` on schema | Automatic (`pg_catalog`, `information_schema`) | None |  ### Oracle@@ -288,5 +295,4 @@ - `SELECT` on the source tables is the primary requirement. The `ALL_*` views populate automatically once the user has object access. - `USER_SEGMENTS` is used for size estimation when the table owner matches the connected user. For cross-schema tables, size defaults to 0 and partitioning falls back to `COUNT(*)`.-- `ALL_SEGMENTS` isn't used, because it's unavailable on the Oracle Autonomous Database free tier. - `COUNT(*)` runs on each source table for accurate row counts (used for partitioning), which requires `SELECT` on the table. @@ -303,16 +309,16 @@ | Table size | `SELECT ... FROM USER_SEGMENTS WHERE segment_name = ...` | Own schema only; otherwise returns 0 | | Data extraction | `SELECT <columns> FROM <owner>.<table> [WHERE ...]` | `SELECT` on table |-| L3 checksum (validation) | `SELECT RAWTOHEX(DBMS_CRYPTO.HASH(col, 2)) ...` | `SELECT` and `EXECUTE ON DBMS_CRYPTO` (LOBs only) |+| L3 row hashing (validation) | `SELECT RAWTOHEX(DBMS_CRYPTO.HASH(col, 2)) ...` | `SELECT` and `EXECUTE ON DBMS_CRYPTO` (LOBs only) |  #### Data validation requirements -For L3 hybrid row validation with LOB columns:+For L3 row validation with LOB columns:  | Requirement | Detail | | --- | --- | | `EXECUTE ON DBMS_CRYPTO` | Required only for tables with `CLOB`, `NCLOB`, or `BLOB` columns. |-| Purpose | Computes an MD5 hash of the full LOB content server-side (`RAWTOHEX(DBMS_CRYPTO.HASH(col, 2))`). |-| Without the grant | L3 fails with `ORA-00904: "DBMS_CRYPTO"."HASH": invalid identifier`. |-| Non-LOB tables | Don't need this grant; `STANDARD_HASH` is used for non-LOB types. |+| Purpose | Hashes the full LOB content on the source for row-level comparison. |+| Without the grant | Row-level validation fails for LOB columns. |+| Non-LOB tables | Don't need this grant. |  #### Identifier handling@@ -409,5 +415,5 @@ | Key inference | `SELECT ... FROM sys.indexes JOIN sys.index_columns ...` | `VIEW DEFINITION` | | Data extraction | `SELECT <columns> FROM [schema].[table] ...` | `SELECT` on table |-| L3 checksum (validation) | `SELECT HASHBYTES('MD5', ...) FROM ...` | `SELECT` on table |+| L3 row hashing (validation) | `SELECT HASHBYTES('MD5', ...) FROM ...` | `SELECT` on table |  ### Azure Synapse@@ -501,5 +507,5 @@ - `DBC` views require explicit `SELECT` grants on Teradata, unlike Oracle's `ALL_*` views. - `DBC.TableStatsV.RowCount` depends on collected statistics. If it's stale or NULL, AIM DMV falls back to `COUNT(*)`.-- `HASH_MD5` isn't a built-in function. A DBA must install it in the same database the Worker uses as its default. Without it, L3 validation fails with error 3706 or 3707.+- `HASH_MD5` isn't a built-in function. A DBA must install it in the same database the Worker uses as its default, or row-level validation fails. - `HELP COLUMN` is used for view schema discovery instead of `DBC.ColumnsV`. - Teradata identifiers are case-insensitive by default; AIM DMV normalizes them to the `DBC` spelling.@@ -511,5 +517,5 @@ | `HASH_MD5` UDF | Must exist in the Worker's default database; used for L3 row-hash validation. | | `EXECUTE FUNCTION` privilege | Granted on the `HASH_MD5` UDF. |-| Not built-in | Must be provisioned by a DBA. Contact your SnowConvert support channel. |+| Not built-in | A DBA must install the `HASH_MD5` UDF before row-level validation can run. |  ### PostgreSQL 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-sql-server+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-sql-server@@ -21,12 +21,5 @@ ``` -## Validation behavior--- **Datetime precision**: SQL Server datetime types can carry sub-microsecond precision (a seventh fractional digit). Validation readback truncates that digit, which can surface as L2/L3 differences on high-precision columns.-- **Fixed-width character types**: L3 normalization applies **`TRIM`** to **`NCHAR`** columns when comparing to Snowflake `VARCHAR` targets.-- **UNIQUEIDENTIFIER**: Compared as an uppercase string representation in L3.-- **Limited L3 coverage**: **`TEXT`**, **`NTEXT`**, **`XML`**, and **`SQL_VARIANT`** have no L3 normalization. **`GEOGRAPHY`** and **`GEOMETRY`** are validated at the schema level only.--Set `source_platform: sqlserver` in the validation workflow YAML. For partitioning, L3 alignment, and tolerance settings that apply to all platforms, see [Data validation configuration reference](../manual-migration/data-validation-configuration-reference).+Set `source_platform: sqlserver` in the validation workflow YAML. For partitioning, row alignment, and tolerance settings that apply to all platforms, see [Data validation configuration reference](../manual-migration/data-validation-configuration-reference).  **Example workflow excerpt:**@@ -48,11 +41,11 @@     column_names_to_partition_by:       - ID-    index_column_list:+    indexColumnList:       - ID     validation_configuration:       row_validation: true-      row_validation_mode: cell       max_failed_rows_number: 500-    where_clause: "is_deleted = 0"+    sourceWhereClause: "is_deleted = 0"+    targetWhereClause: "is_deleted = 0" ``` @@ -62,14 +55,16 @@ | --- | --- | --- | --- | | BIT, integers, DECIMAL, MONEY, FLOAT, REAL | NUMBER / FLOAT | Yes | |-| DATE, TIME, DATETIME types | DATE / TIME / TIMESTAMP | Yes | Sub-microsecond precision (7th digit) is truncated |+| DATE, TIME, DATETIME types | DATE / TIME / TIMESTAMP | Yes | | | CHAR, VARCHAR, NCHAR, NVARCHAR | VARCHAR | Yes | | | BINARY, VARBINARY, UNIQUEIDENTIFIER | BINARY / VARCHAR | Yes | UUID compared as an uppercase string |-| TEXT, NTEXT | VARCHAR | No | Row comparison not supported |-| XML, SQL_VARIANT | VARIANT | No | Schema-level comparison only |-| GEOGRAPHY, GEOMETRY | GEOGRAPHY | No | Schema-level comparison only |+| TEXT, NTEXT | VARCHAR | Yes | Row-level comparison reads the full value; very large values may hit memory limits |+| XML, SQL_VARIANT | VARIANT | Partial | Schema-level comparison only |+| GEOGRAPHY | GEOGRAPHY | Yes | Compared as despaced Well-Known Text |+| GEOMETRY | GEOMETRY | Yes | Compared as despaced Well-Known Text |+| VECTOR | VECTOR(_element_type_, _n_) | Yes | Row-level validation compares element by element |  ## Platform-specific considerations -- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (L1/L2/L3 per table).+- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (schema validation, metrics validation, and row-level validation, per table).    **Prompt:**@@ -79,8 +74,4 @@   ``` -- **Migration vs validation extraction**: Validation always reads the source over ODBC. The `use_bcp` Worker setting applies to migration only.-- Review L2/L3 results on **`DATETIME`**, **`DATETIME2`**, and **`DATETIMEOFFSET`** columns when sub-microsecond precision matters in the source.-- For **`NCHAR`** columns, expect possible whitespace-related L2 drift; L3 applies **`TRIM`** normalization.-- Plan validation depth by type: rely on L1 for **`XML`** and **`SQL_VARIANT`**; treat **`GEOGRAPHY`** / **`GEOMETRY`** as schema-level only until WKT normalization is available. - **Anti-locking**: Hints are off by default. On busy source tables, set `queryModifiers.objectModifier` to `" WITH (NOLOCK)"` to avoid blocking on source locks, at the cost of dirty reads that can cause false `MISMATCH` results. See [Anti-locking and query modifiers](../manual-migration/data-validation-configuration-reference#anti-locking-and-query-modifiers).  

--- ahttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight/changelog+++ bhttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight/changelog@@ -2,4 +2,35 @@  This page documents notable changes to Cortex Code in Snowsight.++## August 2026++| Date   | Feature                                       | Phase           |+| ------ | --------------------------------------------- | --------------- |+| Aug 20 | Restrict this chat (restricted session scope) | Private Preview |+| Aug 14 | Automations                                   | Private Preview |+| Aug 10 | Per-turn file changes summary                 | GA              |+| Aug 4  | Agent-requested plan mode                     | GA              |+| Aug 3  | Multi-image drag-and-drop upload              | GA              |++## July 2026++| Date   | Feature                                       | Phase |+| ------ | --------------------------------------------- | ----- |+| Jul 30 | Sticky scroll for prompts                     | GA    |+| Jul 28 | Chat pinning and archiving                    | GA    |+| Jul 22 | Concurrent chats and fullscreen               | GA    |+| Jul 22 | Cloud Agents                                  | GA    |+| Jul 20 | Response copying                              | GA    |+| Jul 20 | Account-wide default model via settings agent | GA    |+| Jul 15 | Queued prompts                                | GA    |+| Jul 13 | Infinite conversation scroll                  | GA    |+| Jul 7  | Conversation sharing                          | GA    |++## June 2026++| Date   | Feature                      | Phase |+| ------ | ---------------------------- | ----- |+| Jun 26 | Automatic context management | GA    |+| Jun 18 | Chat history search          | GA    |  ## May 2026 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-postgres/postgres-data-mirroring+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-postgres/postgres-data-mirroring@@ -25,5 +25,5 @@ Every insert, update, delete, and schema change on the source appears on the target automatically, without ETL pipelines, batch jobs, or third-party connectors that traditionally sat between OLTP and OLAP systems.-Data Mirroring leverages pg_lake, an open source Postgres extension from Snowflake, to drastically simplify and+Data mirroring leverages pg_lake, an open source Postgres extension from Snowflake, to drastically simplify and reduce the cost of moving data between Postgres and Snowflake. @@ -46,12 +46,11 @@   Ongoing apply uses delete-then-append instead of `MERGE`, so insert-only batches skip the   target-table scan that `MERGE`-based CDC tools pay on every run.-- **Sub-minute lag.** Data Mirroring applies changes into Snowflake at configurable intervals. Even when you configure a longer refresh interval, changes to the table are available through the `$live` view that contains+- **Sub-minute lag.** Data mirroring applies changes into Snowflake at configurable intervals. Even when you configure a longer refresh interval, changes to the table are available through the `$live` view. This view contains   not-yet-merged changes with an approximately 30-second lag.-- **Robust data type mapping.** Most PostgreSQL types map directly to Snowflake types. Types+- **Robust data type mapping.** Most Postgres types map directly to Snowflake types. Types   without a direct equivalent such as `jsonb`, `hstore`, and ranges are automatically cast to   `VARCHAR`, `BINARY`, or `VARIANT` types. Arrays and composite types are surfaced as Snowflake `ARRAY` and `OBJECT`.   See the [Type mapping reference](/user-guide/snowflake-postgres/postgres-data-mirroring-type-mapping) for the full mapping.-- **Schema evolution.** Schema changes and DDL like columns added to or removed from a mirrored schema on Postgres-  appear in Snowflake without reconfiguring the mirror.+- **Schema evolution.** Schema changes such as adding or removing columns from a mirrored Postgres schema appear in Snowflake without reconfiguring the mirror. - **Queryable 7-day change feed.** Every mirrored table has a `$changes` companion that exposes   inserts, updates, and deletes for the last 7 days, queryable from both Snowflake and Postgres.@@ -64,16 +63,16 @@ ## How mirroring works -Mirroring is built on Postgres primitives you already trust — a publication, a logical replication-slot, and standard WAL decoding — combined with two open building blocks that keep the pipeline+Mirroring is built on Postgres primitives you already trust: a publication, a logical replication+slot, and standard WAL decoding, combined with two open building blocks that keep the pipeline transparent end-to-end. **Apache Iceberg** is the open table format the change log is stored in, and **[pg_lake](/user-guide/snowflake-postgres/postgres-pg_lake)**, an open-source Postgres extension from Snowflake, is what writes those Iceberg tables directly from Postgres. No proprietary wire format, no external CDC service to operate. Less infrastructure to run, no-vendor lock-in on your change data — it lives in open Iceberg tables — and full SQL visibility+vendor lock-in on your change data (it lives in open Iceberg tables) and full SQL visibility from both sides.  A mirror consists of the following components: -- A **publication** on the source PostgreSQL instance, created by the `snowflake_cdc` extension.+- A **publication** on the source Postgres instance, created by the `snowflake_cdc` extension. - A **replication slot** (logical decoding) on the source, managed by a background CDC worker. - Per-source-table **change log tables** (Iceberg, suffix `$changes`) written by the CDC worker@@ -85,5 +84,5 @@   combine the target with pending change log entries. -The `$changes` tables are the same Iceberg objects on both ends — readable from Postgres and from+The `$changes` tables are the same Iceberg objects on both ends: readable from Postgres and from Snowflake without a copy step in between. Low-latency `$live` views expose not-yet-merged change log entries on top of the target tables so you can query the latest committed state without waiting@@ -95,8 +94,8 @@ ### Data flow -The CDC worker on the source PostgreSQL instance captures changes using logical decoding and writes+The CDC worker on the source Postgres instance captures changes using logical decoding and writes change records to per-table `$changes` tables and a metalog through pg_lake. These Iceberg tables auto-refresh on the Snowflake side, so new rows become visible to Snowflake queries within roughly-30 seconds — no pull-based polling loop to tune. A scheduled apply procedure reads the metalog and+30 seconds, with no pull-based polling loop to tune. A scheduled apply procedure reads the metalog and applies pending changes to the target tables in a single Snowflake transaction; if an apply run fails, the transaction rolls back and the next run resumes from the same metalog position, so@@ -115,5 +114,5 @@ ## Transactional guarantees -PostgreSQL transactions are collected into batches and applied to the target database+Postgres transactions are collected into batches and applied to the target database transactionally. All row changes from a single source transaction become visible on Snowflake at the same time, and any number of consecutive source transactions merged into one batch are also applied@@ -132,5 +131,5 @@ ## Understanding mirroring costs -Mirroring's architecture gives it inherent cost advantages over most other approaches of moving data between Postgres and Snowflake. We use native Postgres logical replication and write to open Iceberg tables that Snowflake reads directly, making it simpler and more efficient.+Mirroring's architecture gives it inherent cost advantages over most other approaches to moving data between Postgres and Snowflake. It uses native Postgres logical replication and writes to open Iceberg tables that Snowflake reads directly, making it simpler and more efficient.  ### Cost drivers@@ -213,4 +212,4 @@ - [Query mirrored data](/user-guide/snowflake-postgres/postgres-data-mirroring-query) — query target tables, the `$changes` feed, and the `$live` view. - [Manage and monitor mirrors](/user-guide/snowflake-postgres/postgres-data-mirroring-manage) — alter, drop, inspect, and monitor mirrors, plus troubleshooting.-- [Type mapping reference](/user-guide/snowflake-postgres/postgres-data-mirroring-type-mapping) — how PostgreSQL types map to Iceberg on the target.+- [Type mapping reference](/user-guide/snowflake-postgres/postgres-data-mirroring-type-mapping) — how Postgres types map to Iceberg on the target. - [Mirror procedures reference](/user-guide/snowflake-postgres/postgres-data-mirroring-reference) — the `snowflake.postgres` procedures and `$changes` schema. 

--- ahttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-environment-variables+++ bhttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-environment-variables@@ -7,10 +7,10 @@ - **[Concepts](#concepts):** How the `env.yml` file works, the `env:` and `secrets:` sections, environments and value precedence, and the naming and casing rules. - **[Admin setup](#admin-setup):** Importing private Git packages (shared macros, sub-projects in a monorepo, or another team's dbt project) by configuring a Snowflake secret, network rule, and external access integration. This is how cross-project references work at the dbt Core level.-- **[Using environment variables](#start-using-environment-variables):** Authoring an `env.yml` file to define one or more environments (for example, dev and prod), configuring your `profiles.yml` to read them, writing a model that consumes them, and running your project in Workspaces and as a dbt project object with SQL.+- **[Using environment variables](#start-using-environment-variables):** Authoring an `env.yml` file to define one or more environments (for example, dev and prod), configuring [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml` to read them, writing a model that consumes them, and running your project in Workspaces and as a dbt project object with SQL. - **[Use the Snowflake CLI](#label-dbt-env-vars-cli):** Wiring environment variables into CI/CD workflows. - **[Observability](#observability):** Seeing which environment and variable overrides each run used. - **[Reference](#reference):** Supported context functions and Jinja helpers, environment selection and value precedence tables, and naming rules. -Administrators set up the shared building blocks (Snowflake secrets, the network rule, and the external access integration) in [Admin setup](#admin-setup). Data engineers author the project files (`env.yml`, `profiles.yml`, `packages.yml`, and models) and run the project, starting with [Start using environment variables](#start-using-environment-variables).+Administrators set up the shared building blocks (Snowflake secrets, the network rule, and the external access integration) in [Admin setup](#admin-setup). Data engineers author the project files (`env.yml`, `dbt_projects_profiles.yml` or `profiles.yml`, `packages.yml`, and models) and run the project, starting with [Start using environment variables](#start-using-environment-variables).  The `env.yml` file works across Workspaces, deployed dbt project objects (through SQL and the Snowflake CLI), and CoCo Desktop in Snowflake-managed mode. For how it works in CoCo Desktop, see [](/user-guide/cortex-code/cortex-code-desktop/dbt-integration#label-coco-desktop-dbt-env-vars).@@ -23,5 +23,5 @@  - **Runs before dbt Core or dbt Fusion execution begins:** When you run your project, Snowflake resolves the `env.yml` file first and injects the resulting environment variables into the run. Only then does dbt Core start. This is why values can come from live SQL (for example, the current timestamp) and from Snowflake secrets: they're computed at the start of the run, before your models execute.-- **Uses your Snowflake execution context, not your profiles.yml:** Context functions like `CURRENT_ROLE()`, `CURRENT_USER()`, and `CURRENT_WAREHOUSE()` resolve based on the role, user, and warehouse of the outer session that runs `EXECUTE DBT PROJECT` (whether that's a Workspaces session, a Snowflake Task, or a Snowflake CLI call), not the role defined in your `profiles.yml`. The same applies to every Snowflake secret resolution and SELECT query.+- **Uses your Snowflake execution context, not your profile file:** Context functions like `CURRENT_ROLE()`, `CURRENT_USER()`, and `CURRENT_WAREHOUSE()` resolve based on the role, user, and warehouse of the outer session that runs `EXECUTE DBT PROJECT` (whether that's a Workspaces session, a Snowflake Task, or a Snowflake CLI call), not the role defined in `dbt_projects_profiles.yml` or `profiles.yml`. The same applies to every Snowflake secret resolution and SELECT query. - **Lives at the root of your dbt project:** Place `env.yml` in the same folder as your `dbt_project.yml`. During execution, Workspaces and the dbt project object expect to find it there. - **Git-versioned and auditable:** Unlike `.env` files that live on a developer's machine, `env.yml` is version-controlled. An admin can adjust the set of env vars a team needs and commit the change so the whole team benefits from this unified configuration.@@ -50,5 +50,5 @@ Each environment entry has two optional sections that serve different purposes. -**`env:` values** dynamically configure a dbt execution. You can use env vars to create per-developer schemas. This allows large eng teams to avoid collisions during development. Also, Snowflake's SQL in YAML capabilities can compute Airflow-style data-window timestamps at run time without an orchestrator or to wire up CI/CD pipelines to dynamically create and run against a database named after a pull request number, all without changing a single line in your dbt models.+**`env:` values** dynamically configure a dbt execution. You can use env vars to create per-developer schemas. This allows large eng teams to avoid collisions during development. Also, Snowflake's SQL in YAML capabilities can compute Airflow-style data-window timestamps at run time without an orchestrator or wire up CI/CD pipelines to dynamically create and run against a database named after a pull request number, all without changing a single line in your dbt models.  Values can be plain text or any SQL query that returns one row and one column of type `VARCHAR`, including full table queries like `SELECT column FROM your_control_table` and stored procedures called with `SELECT * FROM TABLE(...)`. Wrap any SQL query in double quotes so Jinja parses it correctly. For start-of-day and end-of-day time-window examples, see [Author your env.yml file](#label-dbt-env-vars-author-envyml). For stored procedure examples, see [Call stored procedures from env.yml](#call-stored-procedures-from-envyml).@@ -427,7 +427,7 @@ ``` -### Configure your profiles.yml file--Your `profiles.yml` file reads the environment variables you defined in `env.yml` using `env_var()`. Wrap each `env_var()` call in double quotes so Jinja parses it correctly. With this setup, the same `profiles.yml` produces a different connection target for each engineer in dev, because the values come from their injected environment.+### Configure your profile file++Your `dbt_projects_profiles.yml` or `profiles.yml` file reads the environment variables you defined in `env.yml` using `env_var()`. Wrap each `env_var()` call in double quotes so Jinja parses it correctly. With this setup, the same profile file produces a different connection target for each engineer in dev, because the values come from their injected environment. Snowflake uses `dbt_projects_profiles.yml` when both files are present.  ```yaml@@ -476,5 +476,5 @@ If your `env.yml` includes a `secrets:` block, running the project requires you to select an external access integration each time you run a command, and the executing role needs `READ` or `OWNERSHIP` on the secret to use it in a run. -In Workspaces, you run your project on a selected environment. Snowflake resolves your `env.yml` first to inject environment variables and secrets. Context functions like `CURRENT_WAREHOUSE()` use your default database and resolve without needing a running warehouse. The resolved values then flow into your `profiles.yml`, and the project runs on whatever warehouse `profiles.yml` specifies.+In Workspaces, you run your project on a selected environment. Snowflake resolves your `env.yml` first to inject environment variables and secrets. `CURRENT_WAREHOUSE()` uses your curren... (truncated) 

差分が長いため、途中まで表示しています。

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-code-execution-tool+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-code-execution-tool@@ -1,5 +1,5 @@ # Cortex Agent code execution tool -Support for this feature is currently not in production and is available only to selected accounts.+Available to all accounts.  - [](/user-guide/snowflake-cortex/cortex-agents)@@ -22,13 +22,19 @@ The agent uses the code execution alongside other configured tools and skills. During orchestration, the agent evaluates the user's query and determines whether code execution is the best approach. If so, the agent invokes the code execution tool. -The agent then generates code and executes it in a secure sandbox. By default, the code execution tool environment is isolated and can only access data passed into the session. The sandbox has read-only SQL access (it can execute `SELECT` and `SHOW` commands but not DML operations like `INSERT`, `UPDATE`, `DELETE`, `MERGE` or DDL operations like `CREATE`, `ALTER`, `DROP`). The sandbox can also write to Snowflake stages.+The agent then generates code and executes it in a secure sandbox. By default, the code execution tool environment is isolated and can only access data passed into the session, plus the workspace stage mounted into the sandbox.++The sandbox doesn't query your data. When the agent needs data from Snowflake, it runs the query with its SQL tools, outside the sandbox, and the sandbox works with the results.  ### Default access scope -The code execution tool's sandbox persists for a single session. Data provided in the conversation context is what's available to the code execution tool for operation. The sandbox persists imports, variables, and intermediate results across multiple executions within the session.+The sandbox has read and write access to the workspace stage location mounted into it, which is your default user workspace. The agent sees that workspace as a regular directory. Stages mounted for skills are read-only. Beyond those mounts, the sandbox can't reach data that wasn't passed into the session.++Because the workspace is backed by a stage, files the agent writes there outlive the sandbox. The sandbox itself is scoped to a conversation thread and is reused across requests on that thread, but it isn't shared between threads, and it suspends after a period of inactivity. Don't rely on in-memory state, such as imported modules or variables, surviving between separate code executions: persist anything you need to reuse as a file in the workspace.  ## Enabling the code execution tool -To use the code execution tool with a Cortex Agent, the agent must have both the required access control permissions and agent specification section describing the code execution tool.+To use the code execution tool with a Cortex Agent, the agent must have the code execution tool specified in its tools.++Calls to agents that use owner's rights don't support code execution. When an agent is invoked from an owner's rights stored procedure, the code execution tools are removed from the request and no sandbox is created, even when the tool is enabled in the agent specification. The response includes a warning saying so. Invoke the agent with caller's rights if it needs code execution.  ### Required Cortex Agent permissions@@ -65,4 +71,6 @@   code_execution: ```++If configuring an agent through the UI, the Code Execution tool toggle for an agent adds the required fields specified previously. New agents created through the UI have this toggle switched on by default.  For full information on the agent specification format and instructions on how to modify an existing agent's specification, see [Create and manage agents](/user-guide/snowflake-cortex/cortex-agents-manage).@@ -113,5 +121,5 @@ ## Default available libraries -The default execution environment for the code execution tool uses Python 3.12, with the Python standard library available. Common data-processing libraries, including `numpy` and `pandas`, are also preinstalled. To use additional packages, retrieve them from PyPI through the Artifact Repository, as described in the following section.+The default execution environment for the code execution tool uses Python 3.12, with the Python standard library available. Common data-processing and plotting libraries are also preinstalled, including `numpy`, `pandas`, `scipy`, `pyarrow`, `matplotlib`, and `plotly`. To use additional packages, retrieve them from PyPI through the Artifact Repository, as described in the following section.  ## Adding libraries through Artifact Repository@@ -134,4 +142,6 @@ Cortex Agent code execution tool is subject to the following known limitations: -- **Single-session scope**: By default, the code execution tool can only access data in the current session. State isn't shared between sessions or across separate invocations. To persist information produced by the code execution tool, you'll need your own persistence store on Snowflake that the code execution tool has read and write access to.-- **Access inheritance**: The code execution tool operates with the role privileges of the Cortex Agent owner. Make sure that the owner role of any agent with the code execution enabled is appropriately scoped.+- **Thread-scoped sandbox**: A sandbox is scoped to a single conversation thread. It isn't shared across threads, and in-memory state isn't preserved between separate code executions. Files written to the mounted workspace do persist, because the workspace is backed by a stage.+- **No owner's rights support**: Calls to agents that use owner's rights don't support code execution. See [Enabling the code execution tool](#enabling-the-code-execution-tool).+- **No SQL in the sandbox**: The sandbox doesn't query your data. The agent runs SQL with its SQL tools instead, outside the sandbox.+- **Limited stage access**: The sandbox can only read and write the workspace stage mounted into it, not arbitrary stages in your account. 

--- ahttps://docs.snowflake.com/en/user-guide/cost-exploring-compute+++ bhttps://docs.snowflake.com/en/user-guide/cost-exploring-compute@@ -52,5 +52,5 @@ You can use tags to [attribute the cost](/user-guide/cost-attributing) of using resources to a logical unit within your organization. A tag is a Snowflake object that can have one or more values associated with it. A user with the-appropriate privileges applies a tag/value pair to each resource that is used by a cost center or other logical unit (e.g. the Development+appropriate privileges applies a tag/value pair to each resource that is used by a cost center or other logical unit (for example, the Development environment, a business unit, or business line). Once resources have been tagged, you can isolate costs based on a specific tag/value pair, allowing you to attribute this cost to a specific logical unit.@@ -71,5 +71,5 @@ tagged with `COST_CENTER = SALES` while excluding all other usage from the dashboard. -You can also display all resources with a tag regardless of their tag value. Use the drop down to select a+You can also display all resources with a tag regardless of their tag value. Use the drop-down to select a tag, then choose **All** instead of a specific value. @@ -555,6 +555,6 @@ - [Query: Credit consumption by warehouse over specific time period](#label-cost-explore-query-warehouse-time) - [Query: Warehouse usage over m-day average](#label-cost-explore-query-warehouse-utilization)-- [Query: Warehouse cost attribution by query tag](#label-cost-attribute-tag-sql-resources-shared-apps).-- [Query: Warehouse cost attribution by user](#label-cost-attribute-tag-sql-resources-shared).+- [Query: Warehouse cost attribution by query tag](#label-cost-attribute-tag-sql-resources-shared-apps)+- [Query: Warehouse cost attribution by user](#label-cost-attribute-tag-sql-resources-shared)  </dd>@@ -566,5 +566,5 @@ - [Query: Cloud services cost for queries of a given type](#label-cost-explore-query-cloud-services-query-type) - [Query: Warehouses with high cloud services usage](#label-cost-explore-query-cloud-services-warehouse)-- [Query: Cloud services cost sorted by portion of query time](#label-cost-explore-query-cloud-services-by-query-component)+- [Query: Cloud services usage sorted by portion of query time](#label-cost-explore-query-cloud-services-by-query-component)  </dd>@@ -901,5 +901,5 @@ <dd> -This query returns all queries run within the last minute and sorts them by parts of total query execution time (e.g. compilation time vs. queue time).+This query returns all queries run within the last minute and sorts them by parts of total query execution time (for example, compilation time vs. queue time).  ```sql@@ -1355,5 +1355,5 @@ <dd> -This query identifies which of Snowflake's partner tools/solutions (e.g. BI, ETL, etc.) are consuming the most credits. This can help+This query identifies which of Snowflake's partner tools/solutions (for example, BI and ETL) are consuming the most credits. This can help identify partner solutions that are consuming more credits than anticipated, which can be a starting point for additional investigation. @@ -1525,5 +1525,5 @@  This query shows the training credit consumption for each Cortex Fine-tuning,-aggregated in one hour increments.+aggregated in one-hour increments.  ```sql@@ -1542,5 +1542,5 @@ <dd> -This query shows the credit consumption for each Cortex function call, aggregated in one hour increments based on+This query shows the credit consumption for each Cortex function call, aggregated in one-hour increments based on function and model. @@ -1571,5 +1571,5 @@ <dd> -This query shows the credit consumption for each Cortex functions query, aggregated in one hour increments based on+This query shows the credit consumption for each Cortex functions query, aggregated in one-hour increments based on function and model. @@ -1625,5 +1625,5 @@  This query shows the serving credit consumption for each Cortex Search Service,-aggregated in one hour increments.+aggregated in one-hour increments.  ```sql@@ -1662,5 +1662,5 @@ SELECT *   FROM SNOWFLAKE.ACCOUNT_USAGE.CORTEX_DOCUMENT_PROCESSING_USAGE_HISTORY-  WHERE CREDITS_USED > 0.072+  WHERE CREDITS_USED > 0.072; ```  

--- ahttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-desktop/dbt-integration+++ bhttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-desktop/dbt-integration@@ -48,5 +48,13 @@ confirms which mode is active. The project picker selects which dbt project to run; the profile picker selects which **target** (within the profile defined in your project's-`dbt_project.yml`) the next run will use.+`dbt_project.yml`) the next run will use. In Snowflake-managed mode, the picker reads targets from+[`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) when that file is present in the project root. Otherwise, it reads+targets from `profiles.yml`.++For hybrid teams (teams where some members run dbt with the local dbt CLI and others use+Workspaces), this lets you keep both files in the project and switch between Local and+Snowflake-managed mode without editing connection settings: local runs use the `profiles.yml`+commonly found in your `~/.dbt/` folder, and Snowflake-managed runs use `dbt_projects_profiles.yml`+in the root of the project.  For the underlying Snowflake feature, see@@ -79,5 +87,5 @@ 3. **Executes the dbt command** on Snowflake via `EXECUTE DBT PROJECT FROM WORKSPACE`. The    warehouse, database, schema, and role specified in the active target (selected in the-   profile picker, defined in `profiles.yml` under the `profile:` named in `dbt_project.yml`)+   profile picker, defined in `dbt_projects_profiles.yml` or `profiles.yml` under the `profile:` named in `dbt_project.yml`)    are used for the run. 4. **Downloads the generated artifacts** back to your local project directory so the Compiled@@ -124,5 +132,5 @@ When you run a command, Snowflake resolves `env.yml` before the run to inject the environment variables. -You can select a named environment and override individual environment variables for a single run. The resolved values flow into your `profiles.yml`.+You can select a named environment and override individual environment variables for a single run. The resolved values flow into `dbt_projects_profiles.yml` when that file is present, or into `profiles.yml` otherwise.  For env.yml authoring, environment selection, value precedence, secrets, and the full reference, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-environment-variables).@@ -132,10 +140,10 @@ - **An active Snowflake connection** signed in via the connection picker. -- **A `profiles.yml`** in each dbt project folder. The `type` must be `snowflake` and the+- **A `dbt_projects_profiles.yml` or `profiles.yml` file** in each dbt project folder. The `type` must be `snowflake` and the   `warehouse`, `database`, `schema`, and `role` fields must be set. Unlike dbt Core, the   `account` and `user` fields can be left empty or with arbitrary values — the workspace runs   under your current Snowflake user and account context. See   [Workspaces for dbt projects on Snowflake](/user-guide/data-engineering/dbt-projects-on-snowflake-using-workspaces#label-dbt-requirements-workspaces)-  for the full requirements.+  for the full requirements. If both files are present, Snowflake uses `dbt_projects_profiles.yml` and ignores `profiles.yml` for compilation and subsequent commands. For more information, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file).  - **Personal databases enabled** on your account. Snowflake workspaces are created in a@@ -263,7 +271,3 @@ Docs, Compiled, and Preview tabs. -A valid `profiles.yml` is required in both modes. In **Local** mode the project runs through-the local `dbt` CLI, which uses `profiles.yml` exactly as documented by dbt. In-**Snowflake-managed** mode the workspace also reads `profiles.yml` for `warehouse`,-`database`, `schema`, and `role`, but the `account` and `user` fields can be empty or-arbitrary because the workspace runs under your current Snowflake context.+A valid profile file is required in both modes. In **Local** mode, the project runs through the local `dbt` CLI, which reads only `profiles.yml`, exactly as documented by dbt. In **Snowflake-managed** mode, the workspace reads `dbt_projects_profiles.yml` when present and falls back to `profiles.yml`. This split is deliberate: both files can live in the project root at once, and the local `dbt` CLI doesn't recognize `dbt_projects_profiles.yml`, so adding it never disrupts anyone's existing local dbt workflow. Hybrid teams can share one Git-versioned project without reconfiguring connections for each other. The profile file supplies `warehouse`, `database`, `schema`, and `role`, but the `account` and `user` fields can be empty or arbitrary because the workspace runs under your current Snowflake context. 

--- ahttps://docs.snowflake.com/en/sql-reference/functions/sys_context_snowflake_application+++ bhttps://docs.snowflake.com/en/sql-reference/functions/sys_context_snowflake_application@@ -13,5 +13,5 @@ [Snowflake Native App](/developer-guide/native-apps/native-apps-about). -<a id="label-sys-content-snowflake-application-contexts"></a>+<a id="label-sys-context-snowflake-application-contexts"></a>  You can call this function in the following contexts:@@ -29,10 +29,10 @@ <dd> -[](/sql-reference/functions/sys_context) ,-[](/sql-reference/functions/sys_context_snowflake_environment) ,-[](/sql-reference/functions/sys_context_snowflake_organization) ,-[](/sql-reference/functions/sys_context_snowflake_organization_session) ,-[](/sql-reference/functions/sys_context_snowflake_session) ,-[](/sql-reference/functions/is_application_role_activated)+[SYS_CONTEXT](/sql-reference/functions/sys_context),+[SYS_CONTEXT (SNOWFLAKE$ENVIRONMENT namespace)](/sql-reference/functions/sys_context_snowflake_environment),+[SYS_CONTEXT (SNOWFLAKE$ORGANIZATION namespace)](/sql-reference/functions/sys_context_snowflake_organization),+[SYS_CONTEXT (SNOWFLAKE$ORGANIZATION_SESSION namespace)](/sql-reference/functions/sys_context_snowflake_organization_session),+[SYS_CONTEXT (SNOWFLAKE$SESSION namespace)](/sql-reference/functions/sys_context_snowflake_session),+[IS_APPLICATION_ROLE_ACTIVATED](/sql-reference/functions/is_application_role_activated)  </dd>@@ -127,7 +127,7 @@       <td> -`TRUE` if the application is in [development mode](#label-native-apps-dev-mode-about); otherwise, `FALSE`.--To compare this value against the BOOLEAN value TRUE or FALSE, [cast](#label-data-type-explicit-casting) the value+`TRUE` if the application is in [development mode](/developer-guide/native-apps/installing-testing-application#label-native-apps-dev-mode-about); otherwise, `FALSE`.++To compare this value against the BOOLEAN value TRUE or FALSE, [cast](/sql-reference/data-type-conversion#label-data-type-explicit-casting) the value to BOOLEAN. For example: @@ -150,5 +150,5 @@ Name of the function that you want to call. You can call the following functions: -- [](/sql-reference/functions/is_application_role_activated)+- [IS_APPLICATION_ROLE_ACTIVATED](/sql-reference/functions/is_application_role_activated)  </dd>@@ -169,5 +169,5 @@   [the function that you are calling](#label-sys-context-snowflake-application-function). - If you call SYS_CONTEXT with the SNOWFLAKE$APPLICATION namespace outside of-  [any of the supported contexts](#label-sys-content-snowflake-application-contexts), the function returns NULL.+  [any of the supported contexts](#label-sys-context-snowflake-application-contexts), the function returns NULL.  When the [2026_06 behavior change bundle](/release-notes/bcr-bundles/2026_06_bundle) is [enabled in your account](/release-notes/bcr-bundles/managing-behavior-change-releases#label-manage-bcr-check-status), the `CURRENT_PATCH` and `INSTALLED_PATCH` properties return `NUMBER`, and the 

--- ahttps://docs.snowflake.com/en/user-guide/security-column-intro+++ bhttps://docs.snowflake.com/en/user-guide/security-column-intro@@ -28,5 +28,5 @@ Snowflake supports masking policies as a schema-level object to protect sensitive data from unauthorized access while allowing authorized users to access sensitive data at query runtime. This means that sensitive data in Snowflake is not modified in an existing table (i.e. no static masking). Rather, when users execute a query in which a masking policy applies, the masking policy conditions determine whether unauthorized users see masked, partially masked, obfuscated, or tokenized data. Masking policies as a schema-level object also provide flexibility in choosing a centralized, decentralized, or hybrid management approach. For more information, see [Managing Column-level Security](#managing-column-level-security) (in this topic). -Masking policies can include conditions and functions to transform the data at query runtime when those conditions are met. The policy-driven approach supports segregation of duties to allow security teams to define policies that can limit sensitive data exposure, even to the owner of an object (i.e. the role with the OWNERSHIP privilege on the object, such as a table or view) who normally have full access to the underlying data.+Masking policies can include conditions and functions to transform the data at query runtime when those conditions are met. The policy-driven approach supports segregation of duties to allow security teams to define policies that can limit sensitive data exposure, even to the owner of an object (i.e. the role with the OWNERSHIP privilege on the object, such as a table or view) who normally has full access to the underlying data.  <blockquote>@@ -470,5 +470,5 @@     </tr>     <tr>-      <td>Pre-load tokenized Data.</td>+      <td>Pre-load tokenized data.</td>       <td></td>       <td>%cm%</td>@@ -488,5 +488,5 @@     </tr>     <tr>-      <td>Ease of use and Change management.</td>+      <td>Ease of use and change management.</td>       <td>%cm%</td>       <td>%cm%</td>@@ -806,5 +806,5 @@ same column cannot be specified in both a masking policy signature and a row access policy signature at the same time. -This behavior also applies to column used as conditional columns in a masking policy.+This behavior also applies to columns used as conditional columns in a masking policy.  For more information, see [](/sql-reference/sql/create-masking-policy) and [](/sql-reference/sql/create-row-access-policy).@@ -857,5 +857,5 @@ 2. If a masking policy is set on an underlying table column and a materialized view is created from that table, the    materialized view only contains columns that are not protected by a masking policy. Snowflake also returns the following error message-   if the attempting to include one or more columns protected by a masking policy:+   when attempting to include one or more columns protected by a masking policy:    ```    Unsupported feature 'CREATE ON MASKING POLICY COLUMN'.@@ -890,5 +890,5 @@ </blockquote> -Execute a [](/sql-reference/sql/desc-table) or [](/sql-reference/sql/desc-view) statement to view the masking policy on column in a table or view.+Execute a [](/sql-reference/sql/desc-table) or [](/sql-reference/sql/desc-view) statement to view the masking policy on a column in a table or view.  ### Object Tagging and masking policies@@ -902,7 +902,7 @@ ### Hashing, cryptographic, and encryption functions in masking policies -[Hashing](/sql-reference/functions-hash-scalar) and [cryptographic/checksum](/sql-reference/functions-string) can be used in masking policies to mask sensitive data.--For a more information, see [](/user-guide/security-column-advanced).+[Hashing](/sql-reference/functions-hash-scalar) and [cryptographic/checksum](/sql-reference/functions-string) functions can be used in masking policies to mask sensitive data.++For more information, see [](/user-guide/security-column-advanced).  <a id="label-security-column-intro-ext-table"></a>@@ -929,5 +929,5 @@   table. -  If this property is not already set, execute a CREATE OR REPLACE statement on the masking policy the protects the VALUE column and+  If this property is not already set, execute a CREATE OR REPLACE statement on the masking policy that protects the VALUE column and   specify the `EXEMPT_OTHER_POLICIES` property. The virtual column inherits the policy that protects the VALUE column, and this property   allows the policy on the virtual column to override the inherited policy. For details, see@@ -940,5 +940,5 @@   The data type in the policy that protects the virtual column depends on the data type of the virtual column. -Regarding conditional columns in a masking policy, a virtual column can be listed as an conditional column argument to determine whether+Regarding conditional columns in a masking policy, a virtual column can be listed as a conditional column argument to determine whether the first column argument should be masked or tokenized. However, a virtual column cannot be specified as the first column to mask or tokenize.@@ -1482,5 +1482,5 @@ - Account-level query: -  Use the Account Usage [POLICY_REFERENCES](/sql-reference/account-usage/tag_references) view to determine all of the columns+  Use the Account Usage [POLICY_REFERENCES](/sql-reference/account-usage/policy_references) view to determine all of the columns   that have a masking policy. For example:  

--- ahttps://docs.snowflake.com/en/user-guide/tag-based-aggregation-policies+++ bhttps://docs.snowflake.com/en/user-guide/tag-based-aggregation-policies@@ -336,5 +336,5 @@ </div> -#### Privileges for tag owners+### Privileges for tag owners  A tag owner must have the APPLY AGGREGATION POLICY privilege to unset an aggregation policy from the tag.@@ -363,5 +363,5 @@   - The global APPLY TAG privilege. -  For more information, see [tag privileges](#label-object-tags-ddl-privilege-summary).+  For more information, see [tag privileges](/user-guide/object-tagging/work#label-object-tags-ddl-privilege-summary).  - The `aggregation_admin` custom role has the following privileges:@@ -372,5 +372,5 @@   - The global APPLY TAG privilege, to assign the tag (with the aggregation policies) to objects. -  For more information, see [aggregation policy privileges](#label-aggregation-policy-ddl-privilege-summary).+  For more information, see [aggregation policy privileges](/user-guide/aggregation-policies#label-aggregation-policy-ddl-privilege-summary).  - The `data_admin` custom role has the following privileges:@@ -427,8 +427,8 @@    CREATE OR REPLACE AGGREGATION POLICY employee_agg_policy    AS () RETURNS AGGREGATION_CONSTRAINT ->-     CASE+    CASE     WHEN CURRENT_ROLE() = 'DATA_ADMIN' THEN NO_AGGREGATION_CONSTRAINT()     ELSE AGGREGATION_CONSTRAINT(MIN_GROUP_SIZE => 3)-     END;+    END;    ``` @@ -464,5 +464,5 @@ ### Example 2: Protect table data based on the tag string value -This example uses a tag-based aggregation policy to determine aggregation requirements based upon the string value of the tag assigned+This example uses a tag-based aggregation policy to determine aggregation requirements based on the string value of the tag assigned to a table. The aggregation policy dynamically evaluates the tag string value by calling the [](/sql-reference/functions/system_get_tag) function in the aggregation policy conditions.@@ -488,5 +488,5 @@    CREATE AGGREGATION POLICY sensitivity_agg_policy    AS () RETURNS AGGREGATION_CONSTRAINT ->-     CASE+    CASE     WHEN SYSTEM$GET_TAG('governance.tags.sensitivity_level',                         CURRENT_DATABASE() || '.' || CURRENT_SCHEMA() || '.' ||@@ -498,5 +498,5 @@       THEN AGGREGATION_CONSTRAINT(MIN_GROUP_SIZE => 5)     ELSE AGGREGATION_CONSTRAINT(MIN_GROUP_SIZE => 3)-     END;+    END;    ``` @@ -547,11 +547,10 @@ - A tag can have only one aggregation policy. You can't attach a second aggregation policy to the same tag, even with a different entity   key.-- A policy cannot be assigned to a system tag.+- A policy can't be assigned to a system tag. - When multiple tags with tag-based aggregation policies apply to the same table or view, see   [Cross-tag behavior](#label-tag-based-agg-cross-tag) (in this topic).-- If a different type of data protection policy — for example, a masking policy — is assigned to a tag, you can't attach an aggregation+- If a different type of data protection policy (for example, a masking policy) is assigned to a tag, you can't attach an aggregation   policy to the same tag. - A tag-based aggregation policy can be applied to a table or view that is assigned other tag-based policies, for example, a tag-based   projection policy. Query results reflect the cumulative effect of all policies when they are evaluated at runtime.-- Tag-based aggregation policies interact with other Snowflake features the same as other aggregation policies. See-  [](#label-aggregation-policies).+- Tag-based aggregation policies interact with other Snowflake features the same as other aggregation policies. See [aggregation policies](/user-guide/aggregation-policies#label-aggregation-policies). 

--- ahttps://docs.snowflake.com/en/release-notes/2026/10_29+++ bhttps://docs.snowflake.com/en/release-notes/2026/10_29@@ -11,13 +11,8 @@ <a id="about-listing-consumers"></a> -# 10.29 Release Notes (Preview)+# 10.29 Release Notes: Aug 15, 2026 - Aug 19, 2026 -Content on this page is available in advance of the completion of the 10.29 release, which is currently-either *pending* or *in progress* and is scheduled for completion on Aug 18, 2026 (subject to change).--Features, updates, or behavior changes described on this page might not be available in your accounts-until the release is complete.--For updates to these release notes, see [](#label-rel-notes-change-log-10-29).+This release has completed. For differences between the in-advance and final versions of these release+notes, see [](#label-rel-notes-change-log-10-29).  ## Cost management updates@@ -26,6 +21,5 @@  Per-user quotas are now generally available. Per-user quotas let quota admins set monthly and-daily credit limits for individual users, and notify users at various configurable thresholds. Quotas can target all users in an account or a tag-filtered subset, and cover both warehouse compute and AI feature domains, including AI Functions, Snowflake CoCo, Cortex Agents, and Snowflake CoWork.-For AI features, admins can configure quotas to automatically block AI access for users who reach their AI quota limit and release the block when the cycle resets.+daily credit limits for individual users, and notify users at various configurable thresholds. Quotas can target all users in an account or a tag-filtered subset, and cover both warehouse compute and AI feature domains, including AI Functions, Snowflake CoCo, Cortex Agents, and Snowflake CoWork. For AI features, admins can configure quotas to automatically block AI access for users who reach their AI quota limit and release the block when the cycle resets.  With general availability, the following updates are included:@@ -47,6 +41,6 @@ - `GET_ACTIVE_BLOCKS()` is replaced by `GET_ACTIVE_BLOCKS_V2()`. - `GET_PER_USER_USAGE_PREVIEW()` and `SET_REFRESH_TIER()` are no longer available. Quota-  evaluation now occurs within minutes for all accounts; a separate refresh tier setting is not-  required.+  evaluation now occurs within minutes for all accounts; a separate refresh tier+  setting is not required.  For more information, see [Per-user quotas](/user-guide/budgets/per-user-quotas).@@ -54,5 +48,5 @@ ### Anomaly monitors for cost anomalies (*Preview*) -With this release, Snowflake is pleased to announce the public preview of anomaly monitors. Until now,+With this release, Snowflake is pleased to announce the public preview of [anomaly monitors](#label-cost-anomaly-monitors). Until now, Snowflake detected cost anomalies for a whole account or a whole organization, which could be too coarse to catch a spike inside a single team or project. An anomaly monitor lets you define your own scope using [object tags](/user-guide/object-tagging/introduction) and@@ -68,8 +62,10 @@   recalculate a monitor after you retag resources. +  For more information, see [](#label-cost-anomaly-monitors-ui).  - **ANOMALY_INSIGHTS class:** New methods create, update, read, and delete monitors, manage each monitor's notification list, and test a   configuration without saving it. +  For more information, see [](#label-cost-anomaly-monitors-class).  <a id="label-rel-notes-change-log-10-29"></a>@@ -83,4 +79,5 @@ | Release notes                            | Initial publication (preview)          | Aug 13, 2026 | | *Per-user quotas (General availability)* | **Added** to *Cost management updates* | Aug 14, 2026 |+| Release notes                            | Final publication                      | Aug 20, 2026 |  </div> 

--- ahttps://docs.snowflake.com/en/user-guide/security-access-control-privileges+++ bhttps://docs.snowflake.com/en/user-guide/security-access-control-privileges@@ -123,5 +123,5 @@     </tr>     <tr>-      <td>APPLY SNAPSHOT RETENTION LOCK — *Deprecated\*</td>+      <td>APPLY SNAPSHOT RETENTION LOCK — *Deprecated*</td>       <td>Global</td>       <td>Grants the ability to create and apply [snapshot](/user-guide/backups) policies with retention lock. This privilege is granted to the ACCOUNTADMIN role and can be delegated. Deprecated: use APPLY BACKUP RETENTION LOCK instead.</td>@@ -310,5 +310,5 @@       <td>MANAGE ORGANIZATION USER GROUPS</td>       <td>Global</td>-      <td>Grant the ability to manage [organization user groups](#label-org-users-groups).</td>+      <td>Grants the ability to manage [organization user groups](#label-org-users-groups).</td>     </tr>     <tr>@@ -385,10 +385,10 @@       <td>MODIFY SESSION TRACE LEVEL</td>       <td>Global</td>-      <td>Enables setting the level of trace events captured for stored procedures and UDFs invoked in the current session.  When tracing events, you must also set the LOG_LEVEL parameter to one of its supported values. For more information, see [](#label-trace-level).</td>+      <td>Enables setting the level of trace events captured for stored procedures and UDFs invoked in the current session. When tracing events, you must also set the LOG_LEVEL parameter to one of its supported values. For more information, see [](#label-trace-level).</td>     </tr>     <tr>       <td>MODIFY TRACE LEVEL</td>       <td>Global</td>-      <td>Enables setting the level of trace events captured for stored procedures and UDFs in the current account.  When tracing events, you must also set the LOG_LEVEL parameter to one of its supported values. For more information, see [](#label-trace-level).</td>+      <td>Enables setting the level of trace events captured for stored procedures and UDFs in the current account. When tracing events, you must also set the LOG_LEVEL parameter to one of its supported values. For more information, see [](#label-trace-level).</td>     </tr>     <tr>@@ -613,5 +613,5 @@     </tr>     <tr>-      <td>APPLY SNAPSHOT RETENTION LOCK — *Deprecated\*</td>+      <td>APPLY SNAPSHOT RETENTION LOCK — *Deprecated*</td>       <td>Grants the ability to create and apply snapshot policies with retention lock. This privilege is granted to the ACCOUNTADMIN role and can be delegated. <br /> <br /> Deprecated: use APPLY BACKUP RETENTION LOCK instead.</td>       <td></td>@@ -1857,9 +1857,9 @@     </tr>     <tr>-      <td>CREATE SNAPSHOT POLICY — *Deprecated\*</td>+      <td>CREATE SNAPSHOT POLICY — *Deprecated*</td>       <td>Grants the ability to create a snapshot policy in a schema. The role granting this privilege must have the OWNERSHIP privilege on the schema. Deprecated: use CREATE BACKUP POLICY instead.</td>     </tr>     <tr>-      <td>CREATE SNAPSHOT SET — *Deprecated\*</td>+      <td>CREATE SNAPSHOT SET — *Deprecated*</td>       <td>Grants the ability to create a snapshot set in a schema. The role granting this privilege must have the OWNERSHIP privilege on the schema. Deprecated: use CREATE BACKUP SET instead.</td>     </tr>@@ -3526,5 +3526,5 @@     <tr>       <td>MONITOR</td>-      <td>Enables viewing compute pool usage (number of services and jobs running), properties, and listing compute pool in the account  for which the role has access privileges.</td>+      <td>Enables viewing compute pool usage (number of services and jobs running), properties, and listing compute pool in the account for which the role has access privileges.</td>     </tr>     <tr>@@ -3557,5 +3557,5 @@     <tr>       <td>READ</td>-      <td>Enable listing and downloading images from an image repository.</td>+      <td>Enables listing and downloading images from an image repository.</td>     </tr>     <tr>@@ -3588,5 +3588,5 @@     <tr>       <td>OPERATE</td>-      <td>Enable suspending or resuming a service, upgrading service, and modifying service properties.</td>+      <td>Enables suspending or resuming a service, upgrading service, and modifying service properties.</td>     </tr>     <tr>@@ -3596,5 +3596,5 @@     <tr>       <td>MONITOR</td>-      <td>Enable monitoring a service and getting runtime status.</td>+      <td>Enables monitoring a service and getting runtime status.</td>     </tr>   </tbody> 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-redshift+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-redshift@@ -29,5 +29,5 @@ - **Iceberg targets**: Validation compares whatever is in Snowflake (native or Iceberg). Iceberg targets don't change L2/L3 SQL on the Redshift side. -For partitioning and `index_column_list`, see [Data validation configuration reference](../manual-migration/data-validation-configuration-reference).+For partitioning and `indexColumnList`, see [Data validation configuration reference](../manual-migration/data-validation-configuration-reference).  **Example workflow excerpt:**@@ -47,5 +47,5 @@     column_names_to_partition_by:       - order_id-    index_column_list:+    indexColumnList:       - order_id     validation_configuration:@@ -60,15 +60,17 @@ | BOOLEAN, DATE, TIMESTAMP | BOOLEAN / DATE / TIMESTAMP_NTZ | Yes | | | CHAR, VARCHAR | VARCHAR | Yes | |-| VARBYTE / BINARY VARYING | BINARY | Yes | |-| TIMESTAMPTZ | TIMESTAMP_TZ | No | |-| TIME, TIMETZ | TIME | No | |+| VARBYTE / BINARY VARYING | BINARY | Yes | Compared as uppercase hexadecimal |+| TIMESTAMPTZ | TIMESTAMP_TZ | Partial | Row-level validation not yet supported |+| TIME | TIME | Yes | |+| TIMETZ | TIMESTAMP_TZ | Partial | Row-level validation not yet supported | | INTERVALY2M, INTERVALD2S | INTERVAL | Yes | Native `INTERVAL` comparison by default. See [INTERVAL data type handling](../manual-migration/data-validation-configuration-reference#interval-data-type-handling). |-| GEOMETRY, GEOGRAPHY | GEOGRAPHY | No | Schema-level comparison only |-| HLLSKETCH | VARCHAR | No | No Snowflake equivalent |-| SUPER | VARIANT | No | |+| GEOMETRY | GEOMETRY | Yes | Compared as despaced Well-Known Text |+| GEOGRAPHY | GEOGRAPHY | Yes | Compared as despaced Well-Known Text |+| HLLSKETCH | | No | |+| SUPER | VARIANT | Yes | |  ## Platform-specific considerations -- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (L1/L2/L3 per table).+- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (schema validation, metrics validation, and row-level validation, per table).    **Prompt:**@@ -86,5 +88,4 @@   ``` -- Keep large partition result sets within Redshift **timeout and spool limits** when running L2/L3 against wide tables. - **Anti-locking**: No automatic hint is added on Redshift. Set `queryModifiers` only when you need custom source SQL hints. See [Anti-locking and query modifiers](../manual-migration/data-validation-configuration-reference#anti-locking-and-query-modifiers).  

--- ahttps://docs.snowflake.com/en/user-guide/account-replication-intro+++ bhttps://docs.snowflake.com/en/user-guide/account-replication-intro@@ -21,5 +21,5 @@  Customers can replicate across all regions within a [region group](#label-region-groups). To replicate between regions in-different region groups, (that is, from a Snowflake commercial region to a Snowflake government or Virtual Private Snowflake region),+different region groups (that is, from a Snowflake commercial region to a Snowflake government or Virtual Private Snowflake region), please contact [Snowflake Support](https://docs.snowflake.com/user-guide/contacting-support). @@ -209,5 +209,5 @@  If `roles` are replicated (in the same or different replication or failover group), the database refresh also synchronizes the-privilege grants on the secondary database and the objects in the database (schemas, tables, views, etc.) to roles in the account.+privilege grants on the secondary database and the objects in the database (schemas, tables, views, and so on) to roles in the account. Refer to [](#label-privileges-on-replicated-database-objects) for more details. @@ -224,5 +224,5 @@ For specific usage information about these objects, see [](/user-guide/account-replication-considerations). -Objects that are *not* supported for replication are skipped during replication and won't be available in the target account post failover.+Objects that are *not* supported for replication are skipped during replication and won't be available in the target account after failover.  <div className="colwidths-given">@@ -341,5 +341,5 @@       <td>Views</td>       <td>%cm%</td>-      <td>If a view references any object in another database (e.g. table columns, other views, UDFs, or stages), <br /> both databases must be replicated.</td>+      <td>If a view references any object in another database (for example, table columns, other views, UDFs, or stages), <br /> both databases must be replicated.</td>     </tr>     <tr>@@ -522,10 +522,4 @@       <td>%cm%</td>       <td>For replication of network policies that use network rules, see [](#label-account-replication-network-policy).</td>-    </tr>-    <tr>-      <td>Backups</td>-      <td></td>-      <td></td>-      <td></td>     </tr>     <tr>@@ -714,9 +708,9 @@ This feature supports replicating account-level parameters and object parameters. Object parameters are replicated when the object is included in the replication group. For example, if `WAREHOUSES` are replicated, warehouse-specific parameters-(e.g. [](#label-statement-timeout-in-seconds)) are replicated. For a full list, see [](#label-object-parameters).+(for example, [](#label-statement-timeout-in-seconds)) are replicated. For a full list, see [](#label-object-parameters).  Account-level parameter replication includes all [](#label-account-parameters) and [parameters set on the account](/user-guide/admin-account-management).-Account-level parameters (e.g. [](#label-data-retention-time-in-days)) are replicated when `ACCOUNT PARAMETERS` is included in+Account-level parameters (for example, [](#label-data-retention-time-in-days)) are replicated when `ACCOUNT PARAMETERS` is included in the list of object types for a replication group. @@ -877,5 +871,5 @@ [Snowflake Support](https://docs.snowflake.com/user-guide/contacting-support). -This feature supports replicating warehouses, including interactive warehouses. Snowflake also replaces privileges granted on+This feature supports replicating warehouses, including interactive warehouses. Snowflake also replicates privileges granted on warehouses to roles (if `roles` are replicated). The state of the primary warehouse is not replicated. Warehouses are replicated in the suspended state to each target account 

--- ahttps://docs.snowflake.com/en/sql-reference/classes/anomaly_insights+++ bhttps://docs.snowflake.com/en/sql-reference/classes/anomaly_insights@@ -9,5 +9,5 @@ <a id="label-anomaly-insights-methods"></a> -## ANOMALY_INSIGHTS methods+## Account-level and organization-level cost anomaly methods  - [](/sql-reference/classes/anomaly-insights/methods/add_notification_integration)@@ -25,2 +25,19 @@ - [](/sql-reference/classes/anomaly-insights/methods/set_account_notification_emails) - [](/sql-reference/classes/anomaly-insights/methods/set_org_notification_emails)++## Anomaly monitor methods++Available to all accounts.++- [](/sql-reference/classes/anomaly-insights/methods/adhoc_calculate_anomalies_from_config)+- [](/sql-reference/classes/anomaly-insights/methods/create_monitor)+- [](/sql-reference/classes/anomaly-insights/methods/drop_monitor)+- [](/sql-reference/classes/anomaly-insights/methods/get_monitor_anomalies)+- [](/sql-reference/classes/anomaly-insights/methods/get_monitor_config)+- [](/sql-reference/classes/anomaly-insights/methods/get_monitor_notification_emails)+- [](/sql-reference/classes/anomaly-insights/methods/get_monitor_notification_log)+- [](/sql-reference/classes/anomaly-insights/methods/list_monitors)+- [](/sql-reference/classes/anomaly-insights/methods/recalculate_anomalies)+- [](/sql-reference/classes/anomaly-insights/methods/rename_monitor)+- [](/sql-reference/classes/anomaly-insights/methods/set_monitor_notification_emails)+- [](/sql-reference/classes/anomaly-insights/methods/update_monitor_config) 

--- ahttps://docs.snowflake.com/en/user-guide/tag-based-projection-policies+++ bhttps://docs.snowflake.com/en/user-guide/tag-based-projection-policies@@ -194,5 +194,5 @@ </div> -#### Privileges for tag owners+### Privileges for tag owners  A tag owner must have the APPLY PROJECTION POLICY privilege to unset a projection policy from the tag.@@ -221,5 +221,5 @@   - The global APPLY TAG privilege. -  For more information, see [tag privileges](#label-object-tags-ddl-privilege-summary).+  For more information, see [tag privileges](/user-guide/object-tagging/work#label-object-tags-ddl-privilege-summary).  - The `projection_admin` custom role has the following privileges:@@ -230,5 +230,5 @@   - The global APPLY TAG privilege, to assign the tag (with the projection policies) to objects. -  For more information, see [projection policy privileges](#label-projection-policy-ddl-privilege-summary).+  For more information, see [projection policy privileges](/user-guide/projection-policies#label-projection-policy-ddl-privilege-summary).  - The `data_admin` custom role has the following privileges:@@ -265,5 +265,5 @@ </blockquote> -Create a tag-based projection policy to protect the EMAIL columns as follows:+Create a tag-based projection policy to protect the EMAIL column as follows:  1. Create a tag named `data_protection` in the schema named `governance.tags`.@@ -298,5 +298,5 @@    ``` -5. Query the table to verify the tag-based projection policy protects the columns as intended.+5. Query the table to verify the tag-based projection policy protects the column as intended.    ```sql    USE ROLE analyst;@@ -351,5 +351,5 @@  -   This policy uses the fully-qualified name for the tag in the function argument. Snowflake returns an error at query runtime if the+   This policy uses the fully qualified name for the tag in the function argument. Snowflake returns an error at query runtime if the    system function argument in the policy conditions contains a tag name that is not sufficiently qualified. @@ -376,5 +376,5 @@    ``` -   Returns all columns including EMAIL (because tag value is 'restricted' and role is DATA_ADMIN):+   Returns all columns including EMAIL (because tag value is 'restricted' and role is DATA_ADMIN).  6. Change the tag value to `'public'` to allow all roles to project the column:@@ -387,5 +387,5 @@    ``` -   Returns all columns including EMAIL (because tag value is now 'public'):+   Returns all columns including EMAIL (because tag value is now 'public').  ## Limitations and considerations@@ -400,4 +400,3 @@ - A tag-based projection policy can be applied to a table or column that is assigned other tag-based policies, for example, a tag-based row   access policy. Query results reflect the cumulative effect of all policies when they are evaluated at runtime.-- Tag-based projection policies interact with other Snowflake features the same as other projection policies. See-  [](#label-projection-policy-snowflake-features).+- Tag-based projection policies interact with other Snowflake features the same as other projection policies. See [projection policies](/user-guide/projection-policies#label-projection-policy-snowflake-features). 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-postgresql+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/validate-postgresql@@ -43,5 +43,5 @@     column_names_to_partition_by:       - order_id-    index_column_list:+    indexColumnList:       - order_id     validation_configuration:@@ -61,12 +61,13 @@ | bytea | BINARY | Yes | | | uuid | VARCHAR | Yes | |-| json, jsonb, xml | VARIANT | No | |-| money | NUMBER | No | |-| bit, bit varying | BINARY | No | |-| point | GEOMETRY | No | |-| oid | VARCHAR | No | |+| json, jsonb, xml | | No | |+| money | | No | |+| bit, bit varying | | No | |+| point | | No | |+| oid | | No | | | interval | INTERVAL or VARCHAR | Yes | Depends on `intervalHandling`. Match the setting used for migration. See [INTERVAL columns and intervalHandling](#interval-columns-and-intervalhandling). |-| range types | VARCHAR | No | Compared as VARCHAR text |-| PostGIS geometry/geography | GEOMETRY / GEOGRAPHY | No | |+| range types | VARCHAR | Yes | Compared as VARCHAR text |+| pgvector vector | VECTOR(_element_type_, _n_) | Yes | Row-level validation compares element by element |+| PostGIS geometry/geography | | No | |  ## INTERVAL columns and intervalHandling@@ -93,5 +94,5 @@ ## Platform-specific considerations -- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (L1/L2/L3 per table).+- **Starting validation**: Ask the agent to generate a validation workflow with the depth you need (schema validation, metrics validation, and row-level validation, per table).    **Prompt:** 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/glossary+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/glossary@@ -45,5 +45,7 @@ ## Hybrid table -Snowflake table type used for `SNOWCONVERT_AI` metadata when your account supports them (for example the task queue). When Hybrid Tables are not available, AIM DMV creates equivalent metadata as standard tables, which works but is slower. See [Prerequisites](./overview#prerequisites) on the overview page.+Snowflake table type used for `SNOWCONVERT_AI` metadata when your account supports them (for example the task queue). When Hybrid Tables are not available, AIM DMV creates equivalent metadata as standard tables, which works but is slower and limits how far you can scale out Workers. See [Prerequisites](./overview#prerequisites) on the overview page.++This is unrelated to L3 row validation. See [L1 / L2 / L3](#l1--l2--l3).  ## L1 / L2 / L3@@ -83,4 +85,16 @@ Provisional L3 row result recorded when a table defines accepted transformations and row hashing finds a mismatch. Reconcile promotes genuine problems to `MISMATCH` or removes accepted-only rows. Should not remain on a completed workflow. See [Caveat: POSSIBLE_MISMATCH after the workflow finishes](./data-validation-advanced-configuration#caveat-possible_mismatch-after-the-workflow-finishes). +## Preflight++A bounded migration dry run (`preflight: true`). Each table is capped at one partition and the data lands in a transient `PREFLIGHT_<workflowId>` schema instead of the configured target, so the whole pipeline is exercised without writing to production tables. Distinct from `scai data doctor`, which checks infrastructure and configuration health before a run starts. See [Preflight: a bounded dry run](../manual-migration/data-migration-configuration-reference#preflight-bounded-dry-run).++## Rate limit++A rule in the `RATE_LIMIT` metadata table that caps how many concurrently executing tasks can match a scope pattern. Used to protect a busy source system or a shared resource. The cap is a target rather than a hard ceiling. See [Rate limiting](../manual-migration/data-migration-configuration-reference#rate-limiting).++## Re-validation++A child workflow that re-runs only the failed partitions and levels of a finished validation workflow, created with `scai data validate revalidate`. Distinct from incremental validation, which skips unchanged partitions. See [Re-validating what failed](./data-validation#re-validating-what-failed).+ ## Query tag @@ -101,5 +115,5 @@ ## Sync strategy -Incremental migration mode: **none** (full load), **watermark** (track changes by a watermark column), or **checksum** (platform-dependent).+Incremental mode: **none** (validate or load in full), **watermark** (track changes by a monotonically increasing column), or **checksum** (compare a per-partition hash or custom aggregate). Used by data migration for incremental sync and by data validation for [incremental validation](../manual-migration/data-validation-configuration-reference#incremental-validation).  ## Task / task queue 

--- ahttps://docs.snowflake.com/en/user-guide/tag-based-join-policies+++ bhttps://docs.snowflake.com/en/user-guide/tag-based-join-policies@@ -221,5 +221,5 @@ </div> -#### Privileges for tag owners+### Privileges for tag owners  A tag owner must have the APPLY JOIN POLICY privilege to unset a join policy from the tag.@@ -247,5 +247,5 @@   - The global APPLY TAG privilege. -  For more information, see [tag privileges](#label-object-tags-ddl-privilege-summary).+  For more information, see [tag privileges](/user-guide/object-tagging/work#label-object-tags-ddl-privilege-summary).  - The `join_policy_admin` custom role has the following privileges:@@ -256,5 +256,5 @@   - The global APPLY TAG privilege, to assign the tag (with the join policies) to objects. -  For more information, see [join policy privileges](#label-join-policy-ddl-privilege-summary).+  For more information, see [join policy privileges](/user-guide/join-policies#label-join-policy-ddl-privilege-summary).  - The `data_admin` custom role has the following privileges:@@ -308,8 +308,8 @@    CREATE OR REPLACE JOIN POLICY partner_join_policy    AS () RETURNS JOIN_CONSTRAINT ->-     CASE+    CASE     WHEN CURRENT_ROLE() = 'DATA_ADMIN' THEN JOIN_CONSTRAINT(JOIN_REQUIRED => FALSE)     ELSE JOIN_CONSTRAINT(JOIN_REQUIRED => TRUE)-     END;+    END;    ``` @@ -375,5 +375,5 @@    CREATE JOIN POLICY access_join_policy    AS () RETURNS JOIN_CONSTRAINT ->-     CASE+    CASE     WHEN SYSTEM$GET_TAG('governance.tags.access_level',                         CURRENT_DATABASE() || '.' || CURRENT_SCHEMA() || '.' ||@@ -385,5 +385,5 @@       THEN JOIN_CONSTRAINT(JOIN_REQUIRED => TRUE)     ELSE JOIN_CONSTRAINT(JOIN_REQUIRED => TRUE)-     END;+    END;    ``` @@ -432,7 +432,7 @@ - A policy cannot be assigned to a system tag. - A table can't be associated with more than one tag-based join policy.-- If a different type of data protection policy — for example, a masking policy — is assigned to a tag, you can't attach a join policy to+- If a different type of data protection policy (for example, a masking policy) is assigned to a tag, you can't attach a join policy to   the same tag. - A tag-based join policy can be applied to a table or view that is assigned other tag-based policies, for example, a tag-based projection   policy. Query results reflect the cumulative effect of all policies when they are evaluated at runtime.-- Tag-based join policies interact with other Snowflake features the same as other join policies. See [](#label-join-policy).+- Tag-based join policies interact with other Snowflake features the same as other join policies. See [join policies](/user-guide/join-policies#label-join-policy). 

--- ahttps://docs.snowflake.com/en/sql-reference/sql/desc-integration+++ bhttps://docs.snowflake.com/en/sql-reference/sql/desc-integration@@ -11,5 +11,5 @@ <dd> -[](/sql-reference/sql/create-integration) , [](/sql-reference/sql/drop-integration) , [](/sql-reference/sql/alter-integration) , [](/sql-reference/sql/show-integrations)+[](/sql-reference/sql/create-integration), [](/sql-reference/sql/drop-integration), [](/sql-reference/sql/alter-integration), [](/sql-reference/sql/show-integrations)  </dd>@@ -20,5 +20,5 @@ <dd> -[](/sql-reference/sql/alter-api-integration) , [](/sql-reference/sql/create-api-integration)+[](/sql-reference/sql/alter-api-integration), [](/sql-reference/sql/create-api-integration)  </dd>@@ -26,5 +26,5 @@ <dd> -[](/sql-reference/sql/alter-catalog-integration) , [](/sql-reference/sql/create-catalog-integration)+[](/sql-reference/sql/alter-catalog-integration), [](/sql-reference/sql/create-catalog-integration)  </dd>@@ -32,5 +32,5 @@ <dd> -[](/sql-reference/sql/alter-external-access-integration) , [](/sql-reference/sql/create-external-access-integration)+[](/sql-reference/sql/alter-external-access-integration), [](/sql-reference/sql/create-external-access-integration)  </dd>@@ -38,5 +38,5 @@ <dd> -[](/sql-reference/sql/alter-notification-integration) , [](/sql-reference/sql/create-notification-integration)+[](/sql-reference/sql/alter-notification-integration), [](/sql-reference/sql/create-notification-integration)  </dd>@@ -44,5 +44,5 @@ <dd> -[](/sql-reference/sql/alter-security-integration) , [](/sql-reference/sql/create-security-integration)+[](/sql-reference/sql/alter-security-integration), [](/sql-reference/sql/create-security-integration)  </dd>@@ -50,5 +50,5 @@ <dd> -[](/sql-reference/sql/alter-storage-integration) , [](/sql-reference/sql/create-storage-integration)+[](/sql-reference/sql/alter-storage-integration), [](/sql-reference/sql/create-storage-integration)  </dd>@@ -107,5 +107,5 @@   [API key](#label-external-functions--api-key) was entered. (This does not display either the original unencrypted key or the   encrypted version of the key.)-- If the security integration has the `TYPE` property set to `OAUTH` (i.e. Snowflake OAuth), Snowflake returns two additional security+- If the security integration has the `TYPE` property set to `OAUTH` (that is, Snowflake OAuth), Snowflake returns two additional security   integration properties in the query result that cannot be set with either a CREATE SECURITY INTEGRATION or an ALTER SECURITY INTEGRATION   command: 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/deploy-workers+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/deploy-workers@@ -24,4 +24,11 @@ Whichever option you choose, every Worker needs the same three things: a path to the source system, a path to Snowflake, and a Worker configuration file (TOML) describing both. See [Data migration configuration reference: Worker configuration](../manual-migration/data-migration-configuration-reference#worker-configuration) for the file format. +### Keeping source credentials out of Worker TOML++Worker configuration examples show source credentials inline for readability. How you avoid that in practice depends on where the Worker runs:++- **On SPCS**, source credentials come from Snowflake `SECRET` objects bound into the service specification. The agent or CLI creates them for you. See [Network access objects](../manual-migration/manual-spcs-worker-setup#network-access-objects).+- **On your own hosts or in Kubernetes**, the Worker can resolve credentials at startup from an external secret store, referencing them in the connection fields instead of storing a password. See [Resolving credentials from an external secret manager](../manual-migration/data-migration-configuration-reference#external-secret-manager).+ ## Snowpark Container Services @@ -42,4 +49,12 @@  The agent or CLI then typically creates the Worker **secret**, **network rule**, **external access integration**, and **service**. Avoid recreating those by hand unless you have a reason to. Full SQL templates live on the [manual SPCS worker setup](../manual-migration/manual-spcs-worker-setup) page.++### How many Worker instances++More Worker instances mean more concurrent extraction and load, which increases throughput. The source system is usually the constraint — keep adding Workers until you see diminishing returns or the source starts to struggle, then scale back.++Each instance runs up to `MAX_PARALLEL_TASKS` tasks concurrently (default `4`). Total concurrency against your source is roughly the instance count multiplied by that value, so tune both to what the source can absorb. When the source is struggling, prefer [rate limiting](../manual-migration/data-migration-configuration-reference#rate-limiting) to keep Workers up while holding back specific extraction tasks.++Prefer more Workers with a lower `MAX_PARALLEL_TASKS` (5 or fewer) over fewer Workers with many threads each. Size each instance at roughly **1–2 vCPU and 1–2 GB per `MAX_PARALLEL_TASKS` thread**. See [Instance count and resource sizing](../manual-migration/manual-spcs-worker-setup#instance-count-and-resource-sizing).  ### Orchestrator vs Worker services 

--- ahttps://docs.snowflake.com/en/user-guide/cortex-code/bundled-skills+++ bhttps://docs.snowflake.com/en/user-guide/cortex-code/bundled-skills@@ -693,4 +693,16 @@ - Publish a Native App to the Snowflake Marketplace with a consumer-facing listing +<a id="label-bundled-skill-marketplace-provider"></a>++### `marketplace-provider`++End-to-end guidance for Snowflake Marketplace providers: listing type guidance, create and manage listings, configure pricing plans and offers for paid listings, make listings Cortex AI Ready, troubleshooting, provider success, and more.++Ways to use it:++- Get started as a provider with privilege checks, profile creation, and a step-by-step guide to getting listed on the Marketplace+- Create and manage listings, configure pricing plans and offers, and submit for Snowflake review+- Troubleshoot provider issues, evaluate how to make your listing AI Ready, and query data sharing usage views with natural language+ <a id="label-bundled-skill-marketplace-search"></a> @@ -739,4 +751,6 @@ Manage a Snowflake organization: accounts, org users, org-wide spending analysis, security posture, MFA readiness, and ORGANIZATION_USAGE views. +To invoke this skill, type `/organization-management` in Cortex Code, then describe what you want to analyze.+ Ways to use it:  

--- ahttps://docs.snowflake.com/en/user-guide/kafka-connector/classic/overview+++ bhttps://docs.snowflake.com/en/user-guide/kafka-connector/classic/overview@@ -13,5 +13,5 @@ # Overview of the Kafka connector -This topic provides an overview of the Apache Kafka and the Snowflake Connector for Kafka.+This topic provides an overview of Apache Kafka and the Snowflake Connector for Kafka.  The Kafka connector is subject to the [Connector Terms](https://www.snowflake.com/legal/snowflake-connector-terms).@@ -60,5 +60,5 @@  - Lowercase topic names are converted to uppercase table names.-- If the first character in the topic name is not a letter (`a-z`, or `A-Z`) or an underscore character (`_`), then the connector prepends an underscore to the table name.+- If the first character in the topic name is not a letter (`a-z` or `A-Z`) or an underscore character (`_`), then the connector prepends an underscore to the table name. - If any character inside the topic name is not a legal character for a Snowflake table name, then that character is replaced with the underscore character. For more information about which characters are valid in table names, see [](/sql-reference/identifiers-syntax). @@ -89,8 +89,8 @@  A Kafka message has an internal structure that depends upon the information being sent. For example, a message from an IoT (Internet of Things) weather sensor-might include the timestamp at which the data was recorded, the location of the sensor, the temperature, humidity, etc. A message from an inventory system+might include the timestamp at which the data was recorded, the location of the sensor, the temperature, humidity, and so on. A message from an inventory system might include the product ID and the number of items sold, perhaps along with a timestamp indicating when they were sold or shipped. -Typically, each message in a specific topic has the same basic structure. Different topics typically use different structure.+Typically, each message in a specific topic has the same basic structure. Different topics typically use different structures.  Each Kafka message is passed to Snowflake in JSON format or Avro format. The Kafka connector stores that formatted information in a single column of@@ -172,5 +172,5 @@       <td>OBJECT</td>       <td>No</td>-      <td>A header is a user-defined key-value pair associated with the record.  Each record can have 0, 1, or multiple headers.</td>+      <td>A header is a user-defined key-value pair associated with the record. Each record can have 0, 1, or multiple headers.</td>     </tr>   </tbody>@@ -252,5 +252,5 @@ 1. One or more applications publish JSON or Avro records to a Kafka cluster. The records are split into one or more topic partitions. 2. The Kafka connector buffers messages from the Kafka topics. When a threshold (time or memory or number of messages) is reached, the connector writes the messages to a temporary file in the internal stage. The connector triggers [Snowpipe](/user-guide/data-load-snowpipe-intro) to ingest the temporary file. Snowpipe copies a pointer to the data file into a queue.-3. A Snowflake-provided virtual warehouse loads data from the staged file into the target table (i.e. the table specified in the configuration file for the topic) via the pipe created for the Kafka topic partition.+3. A Snowflake-provided virtual warehouse loads data from the staged file into the target table (that is, the table specified in the configuration file for the topic) via the pipe created for the Kafka topic partition. 4. (<span className="emph">Not shown</span>) The connector monitors Snowpipe and deletes each file in the internal stage after confirming that the file data was loaded into the table. @@ -323,5 +323,5 @@ - `com.snowflake.kafka.connector.records.SnowflakeAvroConverterWithoutSchemaRegistry` -When neither `key.converter` or `value.converter` is set, then most SMTs are supported, with the current exception of `regex.router`.+When neither `key.converter` nor `value.converter` is set, then most SMTs are supported, with the current exception of `regex.router`.  Although the Snowflake converters do not support SMTs, Kafka connector version 1.4.3 (or higher) supports many community-based converters such as the following: 

--- ahttps://docs.snowflake.com/en/sql-reference/functions/sys_context_snowflake_session_attributes+++ bhttps://docs.snowflake.com/en/sql-reference/functions/sys_context_snowflake_session_attributes@@ -10,5 +10,5 @@ # SYS_CONTEXT (SNOWFLAKE$SESSION_ATTRIBUTES namespace) -Returns a custom session attribute that was set using [](/sql-reference/functions/set_sys_context) in the+Returns a custom session attribute that was set using [SET_SYS_CONTEXT](/sql-reference/functions/set_sys_context) in the `SNOWFLAKE$SESSION_ATTRIBUTES` namespace. @@ -21,6 +21,6 @@ <dd> -[](/sql-reference/functions/sys_context) ,-[](/sql-reference/functions/set_sys_context)+[SYS_CONTEXT](/sql-reference/functions/sys_context),+[SET_SYS_CONTEXT](/sql-reference/functions/set_sys_context)  </dd>@@ -58,5 +58,5 @@  - The value of the specified attribute if it has been set in the current session using-  [](/sql-reference/functions/set_sys_context).+  [SET_SYS_CONTEXT](/sql-reference/functions/set_sys_context). - NULL if the attribute has not been set. @@ -76,5 +76,5 @@ ## Usage notes -- Attributes must be set using [](/sql-reference/functions/set_sys_context) before they can be retrieved.+- Attributes must be set using [SET_SYS_CONTEXT](/sql-reference/functions/set_sys_context) before they can be retrieved. - Attribute names are **case-sensitive**. `app_context` and `APP_CONTEXT` are treated as   different attributes.@@ -98,5 +98,5 @@ ```text +---------------------------------------------------------------+-| SYS_CONTEXT('SNOWFLAKE$SESSION_ATTRIBUTES', 'app_context')   |+| SYS_CONTEXT('SNOWFLAKE$SESSION_ATTRIBUTES', 'app_context')    | |---------------------------------------------------------------| | production                                                    |@@ -112,5 +112,5 @@ ```text +------------------------------------------------------------------+-| SYS_CONTEXT('SNOWFLAKE$SESSION_ATTRIBUTES', 'nonexistent_attr') |+| SYS_CONTEXT('SNOWFLAKE$SESSION_ATTRIBUTES', 'nonexistent_attr')  | |------------------------------------------------------------------| | NULL                                                             | 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-sql-server+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-sql-server@@ -70,5 +70,5 @@ | DATE | DATE | Yes | | | TIME(n) | TIME | Yes | |-| DATETIME, DATETIME2(n), SMALLDATETIME | TIMESTAMP_NTZ | Yes | |+| DATETIME, DATETIME2(n), SMALLDATETIME | TIMESTAMP_NTZ | Yes | NULL `DATETIME` values may appear as `1970-01-01 00:00:00` on the target when BCP extraction is used | | DATETIMEOFFSET(n) | TIMESTAMP_TZ | Yes | | | CHAR(n), VARCHAR(n), NCHAR(n), NVARCHAR(n) | VARCHAR | Yes | |@@ -77,9 +77,11 @@ | SYSNAME | VARCHAR | Yes | | | TEXT, NTEXT | VARCHAR | Yes | |-| IMAGE | BINARY | Yes | |+| IMAGE | | No | | | XML, SQL_VARIANT | VARIANT | Yes | |-| HIERARCHYID | VARCHAR | Yes | Stored as its hierarchy path string |-| ROWVERSION, TIMESTAMP | BINARY | Yes | SQL Server TIMESTAMP is a synonym for ROWVERSION, not a datetime |-| GEOGRAPHY, GEOMETRY | GEOGRAPHY | Yes | |+| HIERARCHYID | VARCHAR(4000) | Yes | Stored as its hierarchy path string |+| ROWVERSION, TIMESTAMP | BINARY(8) | Yes | SQL Server TIMESTAMP is a synonym for ROWVERSION, not a datetime |+| GEOGRAPHY | GEOGRAPHY | Yes | Extracted as Well-Known Text |+| GEOMETRY | GEOMETRY | Yes | Extracted as Well-Known Text |+| VECTOR | VECTOR(_element_type_, _n_) | Yes | |  ## Platform-specific considerations@@ -93,5 +95,4 @@   ``` -- **BCP caveats**: BCP exports a NULL `DATETIME` as the Unix epoch (`1970-01-01 00:00:00`) because BCP has no NULL sentinel for date types. ODBC returns a proper NULL instead. BCP also preserves trailing spaces on `CHAR(n)` columns, while ODBC strips them. - **Partitioning**: Tune `columnNamesToPartitionBy` and `partitionSize` for large or uneven tables.  

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/overview+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/overview@@ -31,6 +31,16 @@ - **Snowflake access**: Connections for the Orchestrator and Workers in your Snowflake `config.toml` or `connections.toml`, using a role that can create the `SNOWCONVERT_AI` database and its objects. See [Required privileges](./required-privileges) for the full list of grants that role needs. - **Source connectivity**: Platform-specific drivers on Workers. See the per-platform pages under [Data migration](./data-migration) and [Data validation](./data-validation).-- **Hybrid Tables**: On bootstrap, AIM DMV probes whether Hybrid Tables are enabled and available in your Snowflake account and region. When they are, `SNOWCONVERT_AI` metadata objects (for example the task queue) are created as Hybrid Tables. When they are not, AIM DMV falls back to standard tables instead. Workflows still run in both cases, but metadata operations are slower without Hybrid Tables. Review [Hybrid Tables](https://docs.snowflake.com/en/user-guide/tables-hybrid) and [Hybrid Tables limitations](https://docs.snowflake.com/en/user-guide/tables-hybrid-limitations).+- **Hybrid Tables**: On bootstrap, AIM DMV probes whether Hybrid Tables are enabled and available in your Snowflake account and region. When they are, `SNOWCONVERT_AI` metadata objects (for example the task queue) are created as Hybrid Tables. When they are not, AIM DMV falls back to standard tables instead. Workflows still run and produce correct results in both cases, but the fallback has real operational consequences: see [Running without Hybrid Tables](#running-without-hybrid-tables). - **Snowpark Container Services (optional)**: Required only when you deploy the Orchestrator or Workers on Snowflake compute. See the [Snowpark Container Services overview](https://docs.snowflake.com/en/developer-guide/snowpark-container-services/overview).++### Running without Hybrid Tables++<a id="running-without-hybrid-tables"></a>++AIM DMV falls back to standard `TRANSIENT` metadata tables on accounts without Hybrid Tables. Workflows produce correct results, but the task queue has lower throughput and higher latency. This is unrelated to row-level validation.++See [Metadata storage mode](../manual-migration/data-migration-configuration-reference#metadata-storage-mode) for details on what changes, environment-variable overrides, and in-place conversion constraints.++Background reading: [Hybrid Tables](https://docs.snowflake.com/en/user-guide/tables-hybrid) and [Hybrid Tables limitations](https://docs.snowflake.com/en/user-guide/tables-hybrid-limitations).  ## Connecting to Snowflake with a PAT 

--- ahttps://docs.snowflake.com/en/collaboration/provider-listings-auto-fulfillment+++ bhttps://docs.snowflake.com/en/collaboration/provider-listings-auto-fulfillment@@ -74,8 +74,8 @@  - Private listings are auto-fulfilled after the specified consumers get your listing.-- Public listing shared on %sf-marketplace% are auto-fulfilled after a consumer in the specific region+- Public listings shared on %sf-marketplace% are auto-fulfilled after a consumer in the specific region   gets the listing. -When your data product is auto-fulfilled to a new region for the first time, it's transferred to an SSA in that region Auto-fulfillment can be configured with SUB_DATABASE or SUB_DATABASE_WITH_REFERENCE_USAGE settings.+When your data product is auto-fulfilled to a new region for the first time, it's transferred to an SSA in that region. Auto-fulfillment can be configured with SUB_DATABASE or SUB_DATABASE_WITH_REFERENCE_USAGE settings.  - SUB_DATABASE allows selected objects to be available on-demand.@@ -167,8 +167,8 @@ database will adhere to the same refresh schedule. -Scheduled-based data refresh is recommended for use cases where listing updates need to occur at a specific timestamp and schedule.-For example, data providers who need to offer a predictable timestamp for when refreshes are available to all consumers.--Interval-based and scheduled-based data refreshes cannot be used simultaneously. If both are set up, one will override the+Schedule-based data refresh is recommended for use cases where listing updates need to occur at a specific timestamp and schedule.+For example, data providers who need to offer a predictable timestamp for when refreshes are available to all consumers can use schedule-based data refresh.++Interval-based and schedule-based data refreshes cannot be used simultaneously. If both are set up, one will override the other. For example, if a cron expression is set up for a scheduled refresh that already has a refresh interval, it will be overridden to support scheduled refresh. See [](#label-listing-api-manifest-auto-fulfillment) for details. 

--- ahttps://docs.snowflake.com/en/user-guide/security-row-intro+++ bhttps://docs.snowflake.com/en/user-guide/security-row-intro@@ -37,5 +37,5 @@ Row access policies do not currently prevent rows from being inserted, or prevent visible rows from being updated or deleted. -A row access policy can be added to a table or view either when the object is created or after the object is created. For more information, see, [Apply a Row Access Policy to a Table or View](#apply-a-row-access-policy-to-a-table-or-view) (in this topic).+A row access policy can be added to a table or view either when the object is created or after the object is created. For more information, see [Apply a Row Access Policy to a Table or View](#apply-a-row-access-policy-to-a-table-or-view) (in this topic).  In some cases, error messages related to row access policies might be redacted. For more information, see@@ -66,5 +66,5 @@    protected by the policy. 2. Snowflake creates a dynamic secure view (i.e. a secure inline view) of the database object.-3. The values of the columns specified in the ALTER TABLE or ALTER VIEW command (i.e when adding a row access policy to a table or view)+3. The values of the columns specified in the ALTER TABLE or ALTER VIEW command (that is, when adding a row access policy to a table or view)    are bound to the corresponding parameters in the policy, and the policy expression is evaluated. 4. Snowflake generates the query output for the user, and the query output only contains rows based on the policy definition evaluating@@ -188,5 +188,5 @@ ### Policy performance guidelines -Row Access Policies are designed to perform well in a wide variety of real-world scenarios. Use the following tips to secure data and enhance performance:+Row access policies are designed to perform well in a wide variety of real-world scenarios. Use the following tips to secure data and enhance performance:  <dl className="field-list">@@ -455,5 +455,5 @@ apply the policy to the VALUE column. -You can apply the row access policy to VALUE column of an existing external table by executing an [](/sql-reference/sql/alter-table)+You can apply the row access policy to the VALUE column of an existing external table by executing an [](/sql-reference/sql/alter-table) statement on the external table. @@ -910,5 +910,5 @@ - Account-level query: -  Use the Account Usage [POLICY_REFERENCES](/sql-reference/account-usage/tag_references) view to determine all of the tables+  Use the Account Usage [POLICY_REFERENCES](/sql-reference/account-usage/policy_references) view to determine all of the tables   that have a row access policy. For example: @@ -1129,5 +1129,5 @@       <td>Cannot update a row access policy (Unsupported token).</td>       <td>Unsupported feature 'TOK_ROW_ACCESS_POLICY'.</td>-      <td>`TOK` refers to token, which can be returned if an query is unsupported and/or inaccurate; Snowflake's SQL compiler does not know how to process the given query. <br /> For example `alter row access policy p1_test set comment = 'test policy 1';`. In this example, the `ALTER` command cannot be used on the policy object directly; use an ALTER TABLE or ALTER VIEW command instead as shown in [Summary of DDL Commands, Operations, and Privileges](#summary-of-ddl-commands-operations-and-privileges) (in this topic).</td>+      <td>`TOK` refers to token, which can be returned if a query is unsupported and/or inaccurate; Snowflake's SQL compiler does not know how to process the given query. <br /> For example `alter row access policy p1_test set comment = 'test policy 1';`. In this example, the `ALTER` command cannot be used on the policy object directly; use an ALTER TABLE or ALTER VIEW command instead as shown in [Summary of DDL Commands, Operations, and Privileges](#summary-of-ddl-commands-operations-and-privileges) (in this topic).</td>     </tr>   </tbody> 

--- ahttps://docs.snowflake.com/en/user-guide/tutorials/dbt-projects-on-snowflake-getting-started-tutorial+++ bhttps://docs.snowflake.com/en/user-guide/tutorials/dbt-projects-on-snowflake-getting-started-tutorial@@ -176,7 +176,9 @@ ### Verify the contents of the profiles.yml file in your dbt project root -Each dbt project folder in your Snowflake workspace must contain a `profiles.yml` file that specifies a target `warehouse`, `database`, `schema`, and `role` in Snowflake for the project. The `type` must be set to `snowflake`. dbt requires an `account` and `user`, but these can be left with an empty or arbitrary string because the dbt project runs in Snowflake under the current account and user context.--When you run dbt commands, your workspace reads the `profiles.yml` file. When you have at least one valid `target` specified in `profiles.yml`, each target is available to select from the **Profile** list in the menu bar above the workspace editing pane. When you run a dbt command, the workspace uses the selected profile (`target`) to run the command.+Each dbt project folder in your Snowflake workspace must contain a `dbt_projects_profiles.yml` or `profiles.yml` file that specifies a target `warehouse`, `database`, `schema`, and `role` in Snowflake for the project. The `type` must be set to `snowflake`. dbt requires an `account` and `user`, but these can be left with an empty or arbitrary string because the dbt project runs in Snowflake under the current account and user context.++This tutorial uses `profiles.yml`. Alternatively, hybrid teams can use [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file), which takes precedence if both files are present.++When you run dbt commands, your workspace reads `dbt_projects_profiles.yml` if it's present. Otherwise, it reads `profiles.yml`. Each target is listed in the **Profile** dropdown. When you run a dbt command, the workspace uses the selected profile (`target`) to run the command.  Open the `tasty_bytes_dbt_demo/profiles.yml` file, and then verify that your contents match the following example. If you specified different database or warehouse names earlier, replace them with your own.@@ -331,5 +333,5 @@ Executing the dbt `run` command executes your compiled SQL against the target database and schema using the Snowflake warehouse and role that are specified in the `profiles.yml` file of the project. In this step, you'll materialize the output of the `Dev` target in your dbt demo project. You then create a SQL worksheet named `dbt_sandbox.sql` in the workspace where you can run SQL to verify object creation. -Choosing the dbt **Run** or **Build** command for a project from within a workspace materializes target output using the `role` defined in the project's `profiles.yml` file. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` that are specified in the project's `profiles.yml` file, and perform operations on any other Snowflake objects that the dbt model specifies.+Choosing the dbt **Run** or **Build** command for a project from within a workspace materializes target output using the `role` defined in the project's [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml` file. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` that are specified in the profile file, and perform operations on any other Snowflake objects that the dbt model specifies. Snowflake uses `dbt_projects_profiles.yml` when both files are present.  1. From the **Profile** list, select **Dev**.@@ -348,5 +350,5 @@    In the **Status and Results** pane, you should see the tables CUSTOMER_LOYALTY_METRICS, ORDERS, and SALES_METRICS_BY_LOCATION. -6. To see the views that your dbt project run created, run the following command :+6. To see the views that your dbt project run created, run the following command:    ```sql    SHOW VIEWS IN DATABASE tasty_bytes_dbt_db; 

--- ahttps://docs.snowflake.com/en/user-guide/budgets/budget-shared-resources-warehouses+++ bhttps://docs.snowflake.com/en/user-guide/budgets/budget-shared-resources-warehouses@@ -66,8 +66,8 @@ 2. In the navigation menu, select **Admin** %raa% **Cost management**. 3. Select the **Budgets** tab.-4. Select **+ Budget** on the top right corner.+4. Select **+ Budget** in the top right corner. 5. On the **Basic Information** page, complete the required fields. 6. On the **Budget scope** page, add the objects that you want to include in the budget.-7. For setting budgets on warehouses, move to the **Budgets Scope** page and update as follows.+7. For setting budgets on warehouses, move to the **Budget scope** page and update as follows.     In the **Tags on users** section:@@ -79,5 +79,5 @@    In the **Select resources to monitor** section, enable **Warehouses**. -8. Configure Warehouses.+8. Configure warehouses.    - By default, all warehouses are selected, and any warehouses created in the future are      automatically included.@@ -109,5 +109,5 @@ ### Attribution semantics -This warehouse budget tracks a user's share of interactively-issued query costs:+This warehouse budget tracks a user's share of interactively issued query costs: **not** their share of total warehouse cost. The following types of spend are not attributed to individual users and are therefore not included in the budget measurement:@@ -133,5 +133,5 @@  Data for warehouse budgets is available with higher latency than other budget types.-For shared warehouses (this feature), data freshness is up to 11 hours for standard budgets and up to 6 hours for low latency budgets.+For shared warehouses (this feature), data freshness is up to 11 hours for standard budgets and up to 6 hours for low-latency budgets.  Plan alert thresholds and reporting cadences accordingly.@@ -152,5 +152,5 @@   to individual users. See [Attribution semantics](#label-wh-budget-attribution) above. - End-to-end data freshness for shared warehouses is up to approximately 11 hours for standard-  budgets and up to 6 hours for low latency budgets. See+  budgets and up to 6 hours for low-latency budgets. See   [Data freshness](#label-wh-budget-pipeline) above for details. - Configuration changes (adding/removing warehouses or user tags) take up to approximately 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/document-extraction+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/document-extraction@@ -26,16 +26,4 @@ AI_EXTRACT scales automatically with your workload by processing multiple documents simultaneously. Documents can be processed directly from object storage to avoid unnecessary data movement.--<div className="previewfeat sidebar">--<div className="sidebar-title">--%logo-snowflake-black% [Preview Feature](/release-notes/preview-features) — Open--</div>--Available to all accounts.--</div>  AI_EXTRACT supports documents on stages that use client-side or server-side encryption, including in accounts that use 

--- ahttps://docs.snowflake.com/en/user-guide/admin-security-fed-auth-overview+++ bhttps://docs.snowflake.com/en/user-guide/admin-security-fed-auth-overview@@ -6,8 +6,6 @@ - [](/user-guide/errors-saml) -This topic describes the components that comprise a federated environment for authenticating users, and the SSO (single sign-on) workflows supported by+This topic describes the components that make up a federated environment for authenticating users, and the SSO (single sign-on) workflows supported by Snowflake.--Snowflake supports federated authentication using SAML 2.0 and [OpenID Connect (OIDC)](/user-guide/admin-security-fed-auth-oidc) security integrations.  ## What is a federated environment?@@ -113,10 +111,10 @@        You can configure Snowflake so that a user accessing Snowflake with a URL is redirected to the IdP to authenticate without seeing-      the Snowflake sign in page. For more information, see+      the Snowflake sign-in page. For more information, see       [](/user-guide/admin-security-fed-auth-idp-redirect).     2. User chooses to log in using the IdP configured for your account (Okta, %microsoft-idp-short%, or a custom IdP).-  3. User authenticates with the IdP using their IdP credentials (e.g. email address and password).+  3. User authenticates with the IdP using their IdP credentials (for example, email address and password).   4. If authentication is successful, the IdP sends a SAML response to Snowflake to initiate a session and displays the Snowflake web      interface.@@ -126,5 +124,5 @@ To log in through the IdP for your account: -1. User goes to the IdP site/application and authenticates using their IdP credentials (e.g. email address and password).+1. User goes to the IdP site/application and authenticates using their IdP credentials (for example, email address and password). 2. In the IdP, user selects the Snowflake application (if using Okta or %microsoft-idp-short%) or the custom application that has been defined in the IdP (if using    another IdP).@@ -213,5 +211,5 @@   [](/user-guide/admin-security-privatelink) and [](/user-guide/privatelink-azure). - If your Snowflake account is on GCP, you <span className="emph">must</span> contact-  [Snowflake Support](https://docs.snowflake.com/user-guide/contacting-support) and provide the+  [Snowflake Support](/user-guide/contacting-support) and provide the   Snowflake account URL to use with [](/user-guide/private-service-connect-google).  

--- ahttps://docs.snowflake.com/en/sql-reference/functions/ai_extract+++ bhttps://docs.snowflake.com/en/sql-reference/functions/ai_extract@@ -583,16 +583,4 @@ - You can request optional extraction scores by using named arguments and passing `scores => TRUE`.   For details, see [](#label-ai-extract-scores).--<div className="previewfeat sidebar">--<div className="sidebar-title">--%logo-snowflake-black% [Preview Feature](/release-notes/preview-features) — Open--</div>--Available to all accounts.--</div>  AI_EXTRACT supports documents on stages that use client-side or server-side encryption, including in accounts that use 

--- ahttps://docs.snowflake.com/en/sql-reference/functions/system_get_snowflake_egress_ip_ranges+++ bhttps://docs.snowflake.com/en/sql-reference/functions/system_get_snowflake_egress_ip_ranges@@ -59,6 +59,7 @@   {     "ipv4_prefix": "153.45.139.0/24",-    "effective": "2026-05-19T00:00:00Z",-    "published": "2026-07-15T14:38:56.923Z",+    "effective": "2026-08-19T00:00:00Z", // Allowlist this IP range before this date+    "published": "2026-07-15T14:38:56.923Z", // This IP range was published on this date, refresh allowlists if updated before this date.+    "expires": "2026-11-17T00:00:00Z",     "usage": [       "Network Identifier - use for Azure services such as Storage, Key Vault",@@ -68,6 +69,7 @@   {     "ipv4_prefix": "153.45.182.0/24",-    "effective": "2026-05-19T00:00:00Z",-    "published": "2026-07-15T14:38:56.923Z",+    "effective": "2026-08-19T00:00:00Z", // Allowlist this IP range before this date+    "published": "2026-07-15T14:38:56.923Z", // This IP range was published on this date, refresh allowlists if updated before this date.+    "expires": "2026-11-17T00:00:00Z",     "usage": [       "Network Identifier - use for Azure services such as Storage, Key Vault"@@ -77,5 +79,5 @@ ``` -On Azure, the output includes the standard `ipv4_prefix` and `effective` fields, plus two additional fields:+On Azure, the output includes the standard `ipv4_prefix`, `effective`, and `expires` fields. The output also includes two additional fields:  - `published`: The date when Snowflake published this IP range. Refresh your allowlist if you last updated it before this date. 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/ai-function-studio+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/ai-function-studio@@ -91,5 +91,5 @@ in the Snowsight **AI & ML** %raa% **AI Functions** page. -Created Custom AI Functions can also be listed via SNOWFLAKE.ACCOUNT_USAGE query with their associated built-in tag+Created Custom AI Functions can also be listed via a SNOWFLAKE.ACCOUNT_USAGE query with their associated built-in tag  ```sql@@ -298,5 +298,5 @@ In addition to custom AI functions, AI Function Studio can help you use Snowflake's built-in Cortex AI functions directly. If your task maps to a built-in function, you can get immediate-results with no setup — just SQL.+results with no setup: just SQL.  Supported built-in functions: AI_CLASSIFY, AI_FILTER, AI_EXTRACT, AI_COMPLETE,@@ -317,8 +317,8 @@ ## Cost considerations -- **Development phase:** Authoring, evaluation, and optimization are billed by two parts:+- **Development phase:** Authoring, evaluation, and optimization are billed in two parts:    - The tokens processed by the models used during the experimentation process.-  - [Cortex Code usages](/user-guide/cortex-code/cortex-code).+  - [Cortex Code usage](/user-guide/cortex-code/cortex-code).  - **Production phase:** Once registered, a Custom AI Function is billed according to the@@ -334,5 +334,5 @@ - **Cost/quality tradeoffs:** During optimization, AI Function Studio evaluates multiple models   across different cost and performance tiers. This allows teams to select configurations that-  balance accuracy requirements against per-token costs — for example, using a smaller model that+  balance accuracy requirements against per-token costs, for example, using a smaller model that   achieves acceptable accuracy at significantly lower cost.  

--- ahttps://docs.snowflake.com/en/user-guide/aggregation-policies+++ bhttps://docs.snowflake.com/en/user-guide/aggregation-policies@@ -25,5 +25,5 @@ consumer of a table to aggregate the data rather than retrieve individual records. -When creating an aggregation policy, the provider's policy administrator specifies a minimum group size (i.e. the number of rows that must+When creating an aggregation policy, the provider's policy administrator specifies a minimum group size (that is, the number of rows that must be aggregated together into a group). The larger the minimum group size, the less likely it is that a consumer could use the query results to deduce the contents of a single record.@@ -393,5 +393,5 @@ are two different syntax options: -1. Return a row for each object (i.e. table or view) that has the specified aggregation policy set on it:+1. Return a row for each object (that is, table or view) that has the specified aggregation policy set on it:    ```sql    USE DATABASE my_db;@@ -468,5 +468,5 @@  A query against an aggregation-constrained table must aggregate data into groups of a minimum size. It can use an explicit grouping-statement (i.e. a GROUP BY clause) or a scalar aggregation function that aggregates the entire data set (for example, `COUNT(*)`).+statement (that is, a GROUP BY clause) or a scalar aggregation function that aggregates the entire data set (for example, `COUNT(*)`).  </dd>@@ -505,5 +505,5 @@ ``` -The query will return:+The query returns:  ```text@@ -592,5 +592,5 @@ other policies, such as masking and projection policies: -1. If you are using a centralized management approach, create a custom role (e.g. `agg_policy_admin`) to manage the policy. Alternatively,+1. If you are using a centralized management approach, create a custom role (for example, `agg_policy_admin`) to manage the policy. Alternatively,    you can use an existing role. 2. Grant this role the privileges to create and assign an aggregation policy. 

--- ahttps://docs.snowflake.com/en/sql-reference/organization-usage/access_history+++ bhttps://docs.snowflake.com/en/sql-reference/organization-usage/access_history@@ -311,6 +311,6 @@       <td> -A JSON array of data objects such as user-defined functions (i.e. UDFs and UDTFs), stored procedures, tables, views, and columns-directly named in the query explicitly or through shortcuts such as using an asterisk (i.e. `*`).+A JSON array of data objects such as user-defined functions (that is, UDFs and UDTFs), stored procedures, tables, views, and columns+directly named in the query explicitly or through shortcuts such as using an asterisk (that is, `*`).  Virtual columns can be returned in this field.@@ -358,5 +358,5 @@  Specifies the DDL operation on a database, schema, table, view, and column. These operations also include statements that specify a-row access policy on a table or view, a masking policy on a column, and tag updates (e.g. set a tag, change a tag value) on the+row access policy on a table or view, a masking policy on a column, and tag updates (for example, set a tag, change a tag value) on the object or column. @@ -381,5 +381,5 @@       <td>`root_query_id`</td>       <td>VARCHAR</td>-      <td>The query ID of the top most job in the chain or NULL if the job does not have a parent.</td>+      <td>The query ID of the topmost job in the chain or NULL if the job does not have a parent.</td>     </tr>     <tr> 

--- ahttps://docs.snowflake.com/en/sql-reference/account-usage/access_history+++ bhttps://docs.snowflake.com/en/sql-reference/account-usage/access_history@@ -251,6 +251,6 @@       <td> -A JSON array of data objects such as user-defined functions (i.e. UDFs and UDTFs), stored procedures, tables, views, and columns-directly named in the query explicitly or through shortcuts such as using an asterisk (i.e. `*`).+A JSON array of data objects such as user-defined functions (that is, UDFs and UDTFs), stored procedures, tables, views, and columns+directly named in the query explicitly or through shortcuts such as using an asterisk (that is, `*`).  Virtual columns can be returned in this field.@@ -298,5 +298,5 @@  Specifies the DDL operation on a database, schema, table, view, and column. These operations also include statements that specify a-row access policy on a table or view, a masking policy on a column, and tag updates (e.g. set a tag, change a tag value) on the+row access policy on a table or view, a masking policy on a column, and tag updates (for example, set a tag, change a tag value) on the object or column. @@ -321,5 +321,5 @@       <td>`root_query_id`</td>       <td>VARCHAR</td>-      <td>The query ID of the top most job in the chain or NULL if the job does not have a parent.</td>+      <td>The query ID of the topmost job in the chain or NULL if the job does not have a parent.</td>     </tr>     <tr> 

--- ahttps://docs.snowflake.com/en/release-notes/2024/other/2024-09-26-dcr+++ bhttps://docs.snowflake.com/en/release-notes/2024/other/2024-09-26-dcr@@ -47,6 +47,6 @@ For more information, see one of the following: -- If you are an administrator who needs to configure the LiveRamp connector, see [](#label-cleanrooms-activation-admin-liveramp).-- If you are a clean room user who wants to activate data to LiveRamp, see [the LiveRamp documentation](/user-guide/cleanrooms/connector-activation#label-cleanrooms-activation-admin-liveramp).+- If you are an administrator who needs to configure the LiveRamp connector, see [the activation connectors guide](/user-guide/cleanrooms/connector-activation).+- If you are a clean room user who wants to activate data to LiveRamp, see [the activation connectors guide](/user-guide/cleanrooms/connector-activation).  ## The Trade Desk CRM activation@@ -57,6 +57,6 @@ For more information, see one of the following: -- If you are an administrator who needs to configure the The Trade Desk connector, see [](#label-cleanrooms-activation-admin-ttd-crm).-- If you are a clean room user who wants to activate data to The Trade Desk, see [](#label-cleanrooms-activation-admin-ttd).+- If you are an administrator who needs to configure the The Trade Desk connector, see [the activation connectors guide](/user-guide/cleanrooms/connector-activation).+- If you are a clean room user who wants to activate data to The Trade Desk, see [the activation connectors guide](/user-guide/cleanrooms/connector-activation).  ## Managed account credit limit and monitoring 

--- ahttps://docs.snowflake.com/en/sql-reference/functions/model-monitor-performance-metric+++ bhttps://docs.snowflake.com/en/sql-reference/functions/model-monitor-performance-metric@@ -157,5 +157,5 @@ <dd> -Additional arguments for segment-specific queries. This parameter is optional - if not provided, the query returns metrics for all data (non-segment query). The segment queries are not supported for gateway model monitors.+Additional arguments for segment-specific queries. This parameter is optional: if not provided, the query returns metrics for all data (non-segment query). The segment queries are not supported for gateway model monitors.  Valid values: A string in JSON format specifying segment column and value pairs: `'{"SEGMENTS": [{"column": "<segment_column_name>", "value": "<segment_value>"}]}'`@@ -258,7 +258,7 @@ </div> -## Usage Notes--If value you've specified for `model_monitor_name` is case-sensitive or contains special characters or spaces, enclose it in double quotes.+## Usage notes++If the value you've specified for `model_monitor_name` is case-sensitive or contains special characters or spaces, enclose it in double quotes. You must enclose the double quotes within single quotes. For example, `'"<example_model_monitor_name>"'`.  

--- ahttps://docs.snowflake.com/en/user-guide/kafka-connector/classic/install+++ bhttps://docs.snowflake.com/en/user-guide/kafka-connector/classic/install@@ -120,5 +120,5 @@  - The Kafka connector is built for use with Kafka Connect API 3.9.0. Any newer versions of Kafka Connect API have not been tested. Any versions older than 3.9.0 are compatible with the connector. For more information, see [Kafka Compatibility](https://kafka.apache.org/protocol.html#protocol_compatibility).-- When you have both the Kafka connector and the JDBC driver jar files in your environment, make sure your JDBC version matches the `snowflake-jdbc` version specified in the `pom.xml` file of your intended Kafka connector version. You can go to your preferred Kafka connector release version, for example, [v2.0.1](https://github.com/snowflakedb/snowflake-kafka-connector/releases/tag/v2.0.1). Then browse `pom.xml` file to find out the version of `snowflake-jdbc`.+- When you have both the Kafka connector and the JDBC driver jar files in your environment, make sure your JDBC version matches the `snowflake-jdbc` version specified in the `pom.xml` file of your intended Kafka connector version. You can go to your preferred Kafka connector release version, for example, [v2.0.1](https://github.com/snowflakedb/snowflake-kafka-connector/releases/tag/v2.0.1). Then browse the `pom.xml` file to find out the version of `snowflake-jdbc`. - If you use Avro format for ingesting data:   - Use the Avro parser, version 1.8.2 (or higher), available from [https://central.sonatype.com/artifact/org.apache.avro/avro](https://central.sonatype.com/artifact/org.apache.avro/avro).@@ -420,5 +420,5 @@ If the records are formatted in JSON, this should be `"com.snowflake.kafka.connector.records.SnowflakeJsonConverter"`. -`"com.snowflake.kafka.connector.records.SnowflakeJsonConverter"` deserializes the records as is. Every json field is considered to be a record field and no special treatment is applied to a schema or any other field containing metadata.+`"com.snowflake.kafka.connector.records.SnowflakeJsonConverter"` deserializes the records as is. Every JSON field is considered to be a record field and no special treatment is applied to a schema or any other field containing metadata.  If the records are formatted in Avro and use Kafka's Schema Registry Service, this should be `"com.snowflake.kafka.connector.records.SnowflakeAvroConverter"`.@@ -439,5 +439,5 @@ <dd> -If the value of this parameter is not empty, the Kafka uses this phrase to try to decrypt the private key.+If the value of this parameter is not empty, the Kafka connector uses this phrase to try to decrypt the private key.  </dd>@@ -445,5 +445,5 @@ <dd> -Number of tasks, usually the same as the number of CPU cores across the worker nodes in the Kafka Connect cluster. To achieve best performance, Snowflake recommends setting the number of tasks equal to the total number of Kafka partitions, but not exceeding the number of CPU cores. High number of tasks may result in an increased memory consumption and frequent rebalances.+Number of tasks, usually the same as the number of CPU cores across the worker nodes in the Kafka Connect cluster. To achieve best performance, Snowflake recommends setting the number of tasks equal to the total number of Kafka partitions, but not exceeding the number of CPU cores. High number of tasks may result in increased memory consumption and frequent rebalances.  </dd> 

--- ahttps://docs.snowflake.com/en/user-guide/account-replication-security-integrations+++ bhttps://docs.snowflake.com/en/user-guide/account-replication-security-integrations@@ -23,5 +23,5 @@ This topic provides information on how to replicate security integrations, along with using failover/failback with each of these objects, and assumes familiarity with replication and failover/failback with other account-level objects-(e.g. users, roles, warehouses).+(for example, users, roles, warehouses).  For details, see [](/user-guide/account-replication-intro).@@ -587,5 +587,5 @@ This procedural example does the following: -- Replicates network policies along with the network rules that is uses to restrict network traffic.+- Replicates network policies along with the network rules that it uses to restrict network traffic. - Replicates a security integration to which the network policy is assigned. - Refreshes the failover group.@@ -722,5 +722,5 @@    show security integrations;    show api integrations;-   show database;+   show databases;    show tables in database destdb;    show roles;@@ -745,5 +745,5 @@ 5. If you completed the previous step, reverify that you can connect to each Snowflake account. -   At this point, the target account contains the replicated objects and users can login. However, there are additional steps in the target+   At this point, the target account contains the replicated objects and users can log in. However, there are additional steps in the target    account to use the connector.  

--- ahttps://docs.snowflake.com/en/collaboration/provider-listings-auto-fulfillment-troubleshoot-setup+++ bhttps://docs.snowflake.com/en/collaboration/provider-listings-auto-fulfillment-troubleshoot-setup@@ -60,5 +60,5 @@ <a id="label-laf-troubleshoot-missing-share-privileges"></a> -## A role missing privileges on a share+## A role is missing privileges on a share  <dl className="field-list">@@ -120,5 +120,5 @@  - Verify that the listings in the group of listings that have errors include only-  supported object types for cross-region auto-fulfillment,+  supported object types for cross-region auto-fulfillment. - Verify that none of the objects make reference to unsupported object types. You might have to check multiple levels of   dependencies to identify the root cause of the issue, for example, a view calling BUILD_SCOPED_FILE_URL which itself calls@@ -201,5 +201,5 @@ - Remove the reference database, and objects referring to the reference database, from the share. - Use a different database that has all of the objects required for the share. You might need to recreate tables in the new database-  and view & function definitions updated.+  and update view and function definitions. - Use manual fulfillment instead. Only some listings can be manually fulfilled. See [Manually replicate data to fulfill a listing request](https://other-docs.snowflake.com/en/collaboration/provider-listings-managing#label-manually-replicate-listing). @@ -221,5 +221,5 @@ The shared objects below are incompatible. -The objects below in shared database are incompatible.+The objects below in the shared database are incompatible.  </dd> 

--- ahttps://docs.snowflake.com/en/user-guide/tag-based-row-access-policies+++ bhttps://docs.snowflake.com/en/user-guide/tag-based-row-access-policies@@ -247,5 +247,5 @@ </div> -#### Privileges for tag owners+### Privileges for tag owners  A tag owner must have the APPLY ROW ACCESS POLICY privilege to unset a row access policy from the tag.@@ -274,5 +274,5 @@   - The global APPLY TAG privilege. -  For more information, see [tag privileges](#label-object-tags-ddl-privilege-summary).+  For more information, see [tag privileges](/user-guide/object-tagging/work#label-object-tags-ddl-privilege-summary).  - The `row_access_admin` custom role has the following privileges:@@ -283,5 +283,5 @@   - The global APPLY TAG privilege, to assign the tag (with the row access policies) to objects. -  For more information, see [row access policy privileges](#label-security-row-privilege-command-summary).+  For more information, see [row access policy privileges](/user-guide/security-row-intro#label-security-row-privilege-command-summary).  - The `data_admin` custom role has the following privileges:@@ -414,5 +414,5 @@  -   This policy uses the fully-qualified name for the tag in the function argument. Snowflake returns an error at query runtime if the+   This policy uses the fully qualified name for the tag in the function argument. Snowflake returns an error at query runtime if the    system function argument in the policy conditions contains a tag name that is not sufficiently qualified.  

--- ahttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-orchestration+++ bhttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-orchestration@@ -52,5 +52,5 @@     <tr>       <td>Dynamic parameters</td>-      <td>`ENV_VARS` on `EXECUTE DBT PROJECT`, `--vars` in the `ARGS` string of `EXECUTE DBT PROJECT`, or with dynamic per-run values from task `CONFIG`. See [Pass dynamic configuration at run time](#label-dbt-orchestration-pass-dynamic-config).</td>+      <td>`ENV_VARS` on `EXECUTE DBT PROJECT`, `--vars` in the `ARGS` string of `EXECUTE DBT PROJECT`, or dynamic per-run values from task `CONFIG`. See [Pass dynamic configuration at run time](#label-dbt-orchestration-pass-dynamic-config).</td>       <td>[Airflow Jinja templates](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/operators.html#jinja-templating) interpolated into SQL or CLI commands.</td>     </tr>@@ -225,5 +225,5 @@ - **Account**: Your Snowflake account identifier (for example, `myorg-myaccount`) - **Login**: The user or service account name-- **Authentication**: Key pair authentication is recommended for production. You can also use password.+- **Authentication**: Key pair authentication is recommended for production. You can also use a password. - **Warehouse**: The warehouse to use for the `EXECUTE DBT PROJECT` command - **Database**: The database containing your dbt project object@@ -428,7 +428,7 @@   when creating a task that executes the EXECUTE DBT PROJECT command. - **The two-role model applies regardless of orchestrator:** Every `EXECUTE DBT PROJECT` statement-  involves a calling role (the task owner or Airflow connection role) and the `profiles.yml` role (which+  involves a calling role (the task owner or Airflow connection role) and the profile role from [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml` (which   controls what the dbt run can access). For details, see the orchestration section in   [Best practices for dbt Projects on Snowflake](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#orchestration). - **Align your warehouse configuration:** Use the same warehouse in both your task definition (or Airflow-  connection) and your `profiles.yml` target. If they differ, both warehouses wake up for a single run.+  connection) and the target in `dbt_projects_profiles.yml` or `profiles.yml`. If the warehouses differ, both warehouses wake up for a single run. 

--- ahttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-access-control+++ bhttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-access-control@@ -35,5 +35,5 @@ ## Roles and privileges for dbt project deployment -Deployment happens in two phases: an initial phase that creates or updates the dbt project object, and a compilation phase where dbt resolves Jinja, validates SQL, and optionally installs dependencies. Each phase can use a different role: the initial phase uses whichever role is active in your SQL worksheet, selected in the Snowsight deploy dialog, or configured in your Snowflake CLI's `connection.toml`, while the compilation phase uses the role from your `profiles.yml` target.+Deployment happens in two phases: an initial phase that creates or updates the dbt project object, and a compilation phase where dbt resolves Jinja, validates SQL, and optionally installs dependencies. Each phase can use a different role: the initial phase uses whichever role is active in your SQL worksheet, selected in the Snowsight deploy dialog, or configured in your Snowflake CLI's `connection.toml`, while the compilation phase uses the role from the target in [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml`.  <div className="colwidths-auto">@@ -47,5 +47,5 @@ </div> -If `DEFAULT_TARGET` is set on the project object, it takes precedence over the target defined in `profiles.yml` for the compilation phase.+For the compilation phase, `DEFAULT_TARGET` takes precedence over the target defined in the profile file. When both profile files are present, [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) takes precedence over `profiles.yml`.  ## Roles and privileges for dbt project execution@@ -55,9 +55,9 @@ ### Execution from SQL or CLI -The dbt command specified in EXECUTE DBT PROJECT runs with the privileges of the `role` specified in the `outputs` block of the projects `profiles.yml` file. Operations are further restricted to only those privileges granted to the Snowflake user calling EXECUTE DBT PROJECT. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` specified in the project's `profiles.yml` file, and perform operations on any other Snowflake objects that the dbt model specifies.+The dbt command specified in EXECUTE DBT PROJECT runs with the privileges of the `role` specified in the `outputs` block of the project's [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml` file. Operations are further restricted to only those privileges granted to the Snowflake user calling EXECUTE DBT PROJECT. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` specified in the profile file, and perform operations on any other Snowflake objects that the dbt model specifies. Snowflake uses `dbt_projects_profiles.yml` when both files are present.  ### Execution from within Workspaces -Choosing the dbt **Run** or **Build** command for a project from within a workspace materializes target output using the `role` defined in the project's `profiles.yml` file. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` that are specified in the project's `profiles.yml` file, and perform operations on any other Snowflake objects that the dbt model specifies.+Choosing the dbt **Run** or **Build** command for a project from within a workspace materializes target output using the `role` defined in the project's [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml` file. Both the user and the role specified must have the required privileges to use the `warehouse`, perform operations on the `database` and `schema` that are specified in the profile file, and perform operations on any other Snowflake objects that the dbt model specifies. Snowflake uses `dbt_projects_profiles.yml` when both files are present.  ### Scheduled execution from within Workspaces 

--- ahttps://docs.snowflake.com/en/user-guide/budgets/per-user-quotas+++ bhttps://docs.snowflake.com/en/user-guide/budgets/per-user-quotas@@ -141,5 +141,5 @@     <tr>       <td>AI FUNCTION</td>-      <td>Credit usage for AI Functions operations attributed to the user.</td>+      <td>Credit usage for AI functions operations attributed to the user.</td>     </tr>     <tr>@@ -217,5 +217,5 @@ - Each email address used for notifications must be verified. If a user's email is not available,   an informational event is logged in the event table. By default events are logged in-  `snowflake.telemetry.events`, but you can configure your own event table. You can verify a whole email domain using [SYSTEM$VERIFY_DNS_DOMAIN] (/sql-reference/functions/system_verify_dns_domain)+  `snowflake.telemetry.events`, but you can configure your own event table. You can verify a whole email domain using [SYSTEM$VERIFY_DNS_DOMAIN](/sql-reference/functions/system_verify_dns_domain).  The following limitations apply to [block enforcement](#label-per-user-quota-enforcement):@@ -412,5 +412,5 @@ automatically unblocked within approximately 5-10 minutes. -The second argument determines whether end users should receive notifications once they're blocked. To disable end user notifications when they're blocked, set it to 'FALSE'.+The second argument determines whether end users should receive notifications once they're blocked. To disable end user notifications when they're blocked, set it to `FALSE`.  ### Enforceable domains@@ -537,5 +537,5 @@ - The threshold type: `PROJECTED` (default) or `ACTUAL`. - Whether to notify the user directly (`TRUE` or `FALSE`).-- Whether to the projected or actual spend threshold for notification is based on monthly or daily limit ('MONTHLY' or 'DAILY').+- Whether the notification should be based on monthly or daily ('MONTHLY' or 'DAILY') limit.  Add a notification threshold: 

--- ahttps://docs.snowflake.com/en/user-guide/tables-iceberg-externally-managed-writes+++ bhttps://docs.snowflake.com/en/user-guide/tables-iceberg-externally-managed-writes@@ -552,8 +552,7 @@ - For the AWS Glue Data Catalog: Dropping an externally managed table through Snowflake doesn't delete   the underlying table files. This behavior is specific to the AWS Glue Data Catalog implementation.-- Position [row-level deletes](https://iceberg.apache.org/spec/#row-level-deletes) are supported for tables stored on+- [Position row-level deletes](https://iceberg.apache.org/spec/#row-level-deletes) are supported for tables stored on   Amazon S3, Azure, or Google Cloud. Row-level deletes with equality delete files aren't supported. For more information about row-level deletes,-  see [](#label-tables-iceberg-row-level-deletes). To turn off position deletes, which enable-  running the DML operations in copy-on-write mode, set the+  see [](#label-tables-iceberg-row-level-deletes). To run DML operations in copy-on-write mode by disabling position deletes, set the   `ICEBERG_MERGE_ON_READ_BEHAVIOR` parameter to `'DISABLED'` at the table, schema, or database level. - The following features aren't currently supported when you use Snowflake to write to externally managed Iceberg tables:@@ -585,3 +584,3 @@ - Sharing:   - Sharing with a listing isn't currently supported.-  - Direct sharing isn’t currently supported.+  - Direct sharing isn't currently supported. 

--- ahttps://docs.snowflake.com/en/user-guide/tables-iceberg+++ bhttps://docs.snowflake.com/en/user-guide/tables-iceberg@@ -639,8 +639,7 @@ - For the AWS Glue Data Catalog: Dropping an externally managed table through Snowflake doesn't delete   the underlying table files. This behavior is specific to the AWS Glue Data Catalog implementation.-- Position [row-level deletes](https://iceberg.apache.org/spec/#row-level-deletes) are supported for tables stored on+- [Position row-level deletes](https://iceberg.apache.org/spec/#row-level-deletes) are supported for tables stored on   Amazon S3, Azure, or Google Cloud. Row-level deletes with equality delete files aren't supported. For more information about row-level deletes,-  see [](#label-tables-iceberg-row-level-deletes). To turn off position deletes, which enable-  running the DML operations in copy-on-write mode, set the+  see [](#label-tables-iceberg-row-level-deletes). To run DML operations in copy-on-write mode by disabling position deletes, set the   `ICEBERG_MERGE_ON_READ_BEHAVIOR` parameter to `'DISABLED'` at the table, schema, or database level. - The following features aren't currently supported when you use Snowflake to write to externally managed Iceberg tables:@@ -672,5 +671,5 @@ - Sharing:   - Sharing with a listing isn't currently supported.-  - Direct sharing isn’t currently supported.+  - Direct sharing isn't currently supported.  </blockquote> 

--- ahttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-redshift+++ bhttps://docs.snowflake.com/en/migrations/aim-for-datawarehouses/data-migration-validation/migrate-redshift@@ -142,8 +142,9 @@ | TIMESTAMPTZ | TIMESTAMP_TZ | Yes | | | TIME | TIME | Yes | |-| TIMETZ | TIME | Yes | |+| TIMETZ | TIMESTAMP_TZ | Yes | The date component is set to `1970-01-01` | | INTERVALY2M, INTERVALD2S | INTERVAL | Yes | Native `INTERVAL` by default. See [INTERVAL data type handling](../manual-migration/data-migration-configuration-reference#interval-data-type-handling). |-| GEOMETRY, GEOGRAPHY | GEOGRAPHY | Yes | |-| HLLSKETCH | VARCHAR | No | |+| GEOMETRY | GEOMETRY | Yes | Extracted as Well-Known Text |+| GEOGRAPHY | GEOGRAPHY | Yes | Extracted as Well-Known Text |+| HLLSKETCH | | No | | | SUPER | VARIANT | Yes | |  

--- ahttps://docs.snowflake.com/en/sql-reference/sql/set+++ bhttps://docs.snowflake.com/en/sql-reference/sql/set@@ -7,5 +7,5 @@ <dd> -[](/sql-reference/sql/show-variables) , [](/sql-reference/sql/unset)+[](/sql-reference/sql/show-variables), [](/sql-reference/sql/unset)  </dd>@@ -42,6 +42,6 @@ - If you specify complex expressions, a running virtual warehouse might be required in the session. - The number of expressions must match the number of variables to initialize.-- The size of string or binary variables is limited to 16KB.-- The identifier (i.e. name) for a SQL variable is limited to 256 characters.+- The size of string or binary variables is limited to 16 KB.+- The identifier (that is, name) for a SQL variable is limited to 256 characters. - Variable names such as `CURRENT` or `PUBLIC` are reserved for future use by Snowflake and cannot be used.  

--- ahttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/preview+++ bhttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/preview@@ -9,5 +9,5 @@ Available to all accounts. -Returns rows from any table, view, dynamic table.+Returns rows from any table, view, or dynamic table.  ## Syntax@@ -65,5 +65,5 @@ <dd> -Identifier of DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *–target* or *default_target* is defined in the manifest.+Identifier of DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *--target* or *default_target* is defined in the manifest.  </dd>@@ -283,5 +283,5 @@  </dd>-<dt>`--format [TABLE%JSON%JSON_EXT|CSV]`</dt>+<dt>`--format [TABLE|JSON|JSON_EXT|CSV]`</dt> <dd>  

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst/rest-api+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst/rest-api@@ -443,10 +443,10 @@ This improves the perceived responsiveness of your application, especially for long-running queries, because users begin seeing output much sooner. Streaming responses also provide status information that can help you understand where %cortex-analyst% is in the process of generating a response, and-warnings that can help understand what went wrong when %cortex-analyst% doesn't work as you expected.+warnings that can help you understand what went wrong when %cortex-analyst% doesn't work as you expected.  To receive a streaming response, set the `stream` field in the request body to `true`. Streaming responses use [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events). -%cortex-analyst% sends five distinct types of events in a streaming response:+%cortex-analyst% sends six distinct types of events in a streaming response:  - `status`: Conveys status updates about the SQL generation process.@@ -459,5 +459,5 @@ Of these, the `message.content.delta` events are the most crucial to understand, because they contain the actual response content. Each `delta` contains tokens from some field in the complete response. It is possible for each-`delta` event to contain anywhere between a single character to the full response, and they may be of different lengths. You receive these tokens as they+`delta` event to contain anywhere from a single character to the full response, and they may be of different lengths. You receive these tokens as they are generated; it is up to you to assemble them into the final response.  

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst-evaluations+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst-evaluations@@ -9,5 +9,5 @@ %cortex-analyst% evaluations let you measure and improve the performance of your semantic views that are used for SQL generation. Evaluations work by testing your semantic views against their own verified queries as the ground truth. This gives confidence that your semantic view can handle queries that users rely on, which can also translate to higher accuracy for SQL in general. -Evaluations measure accuracy by executing the SQL generated by %cortex-analyst% and comparing the results against your verified queries. Regression metrics are aggregated to track verified queries that were previously answered correctly but are now failing. In addition to these correctness metrics, latency is recorded to track performance of queries. These metrics can be used to identify weaknesses and iteratively refine your semantic views to improve SQL accuracy while preventing regressions.+Evaluations measure accuracy by executing the SQL generated by %cortex-analyst% and comparing the results against your verified queries. Regression metrics are aggregated to track verified queries that were previously answered correctly but are now failing. In addition to these correctness metrics, latency is recorded to track the performance of queries. These metrics can be used to identify weaknesses and iteratively refine your semantic views to improve SQL accuracy while preventing regressions.  <a id="label-analyst-evaluation-access-control"></a>@@ -204,5 +204,5 @@       <td>ERROR</td>       <td>VARCHAR</td>-      <td>Information about any errors which occurred during the request.</td>+      <td>Information about any errors that occurred during the request.</td>     </tr>     <tr>@@ -329,5 +329,5 @@  1. **Run an evaluation** to establish a baseline accuracy score.-2. **Inspect a completed run** by selecting it from the **Evaluations** tab to review the expected vs generated SQL for each query.+2. **Inspect a completed run** by selecting it from the **Evaluations** tab to review the expected versus generated SQL for each query. 3. **Optimize your semantic view** by selecting **Improve** in the **Accuracy** summary box. This starts semantic view optimization, which analyzes the evaluation failures and automatically suggests changes to your semantic view. For more information, see [](/user-guide/snowflake-cortex/cortex-analyst/analyst-optimization). 4. **Re-run the evaluation** to measure the impact of the changes. 

--- ahttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/drop+++ bhttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/drop@@ -60,5 +60,5 @@ <dd> -Identifier of DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *–target* or *default_target* is defined in the manifest.+Identifier of DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *--target* or *default_target* is defined in the manifest.  </dd>@@ -251,5 +251,5 @@ <dd> -Enables a silent re-authentication when the actual access token becomes outdated. Default: *False*.+Enables a silent re-authentication when the current access token becomes outdated. Default: *False*.  </dd>@@ -266,5 +266,5 @@  </dd>-<dt>`--format [TABLE%JSON%JSON_EXT|CSV]`</dt>+<dt>`--format [TABLE|JSON|JSON_EXT|CSV]`</dt> <dd>  

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents@@ -37,5 +37,5 @@  While Snowflake strives to provide high-quality responses, the accuracy of the LLM responses or-the citations provided are not guaranteed. You should review all answers from the Agents API before serving them to your users.+the citations provided is not guaranteed. You should review all answers from the Agents API before serving them to your users.  <a id="label-cortex-agents-concepts"></a>@@ -113,5 +113,5 @@ ## Tools -Cortex Agents support the following tools:+Cortex Agents supports the following tools:    <thead>@@ -180,5 +180,5 @@ ## Cost considerations -Cortex Agents incur charges for orchestration and for the tools the agent uses:+Cortex Agents incurs charges for orchestration and for the tools the agent uses:  - Orchestration is charged based on the tokens used. 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/automations+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork/automations@@ -91,5 +91,5 @@ ## Manage your automations -You can list, edit, reschedule, pause, resume, and delete automations two ways:+You can list, edit, reschedule, pause, resume, and delete automations in two ways:  - **From the Automations tab:** select the **Automations** tab in the left navigation. The Automations page lists each report's schedule, delivery channel, and status, and lets you edit, pause, resume, or delete them.@@ -128,7 +128,7 @@ ## Enable or disable automations -Automations is on by default for all users. It works by granting the EXECUTE AGENT TASK privilege to the PUBLIC role, which allows %sf-intelligence% to schedule and run tasks on your behalf. Agent tasks are Snowflake tasks that run on a user's behalf to re-execute a question and deliver the result on a schedule.+The Automations feature is on by default for all users. It works by granting the EXECUTE AGENT TASK privilege to the PUBLIC role, which allows %sf-intelligence% to schedule and run tasks on your behalf. Agent tasks are Snowflake tasks that run on a user's behalf to re-execute a question and deliver the result on a schedule. -Administrators can opt out at any time by running the SQL command shown below, and can disable or restrict automations at any time by revoking this privilege.+Administrators can opt out at any time by running the SQL command shown below, and can disable or restrict automations by revoking this privilege.  To disable Automations for all users: 

--- ahttps://docs.snowflake.com/en/sql-reference/sql/alter-task+++ bhttps://docs.snowflake.com/en/sql-reference/sql/alter-task@@ -9,5 +9,5 @@ <dd> -[](/sql-reference/sql/create-task) , [](/sql-reference/sql/drop-task) , [](/sql-reference/sql/show-tasks) , [](/sql-reference/sql/desc-task)+[](/sql-reference/sql/create-task), [](/sql-reference/sql/drop-task), [](/sql-reference/sql/show-tasks), [](/sql-reference/sql/desc-task)  </dd>@@ -225,5 +225,5 @@  Generally the compute time to validate the condition is insignificant compared to task execution time. As a best practice, align-scheduled and actual task runs as closely as possible. Avoid task schedules that are wildly out of synch with actual task runs. For+scheduled and actual task runs as closely as possible. Avoid task schedules that are wildly out of sync with actual task runs. For example, if data is inserted into a table with a stream roughly every 24 hours, don't schedule a task that checks for stream data every minute. The charge to validate the WHEN expression with each run is generally insignificant, but the charges are cumulative.@@ -381,5 +381,5 @@ ``` -The following example removes the current predecessor tasks for the `mytask` child task (`pred_task1`, `pred_task2`) and replace them+The following example removes the current predecessor tasks for the `mytask` child task (`pred_task1`, `pred_task2`) and replaces them with a different predecessor task (`pred_task3`):  

--- ahttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/list-deployments+++ bhttps://docs.snowflake.com/en/developer-guide/snowflake-cli/command-reference/dcm-commands/list-deployments@@ -7,5 +7,5 @@ - [](#label-dcm-projects-deployment-history) -Lists deployments of given DCM Project.+Lists deployments of a given DCM Project.  ## Syntax@@ -60,5 +60,5 @@ <dd> -Identifier of DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *–target* or *default_target* is defined in the manifest.+Identifier of a DCM Project. Example: MY_DB.MY_SCHEMA.MY_PROJECT. Supports fully qualified (recommended) or simple names. If unqualified, it defaults to the connection's database and schema. Optional if *--target* or *default_target* is defined in the manifest.  </dd>@@ -260,5 +260,5 @@  </dd>-<dt>`--format [TABLE%JSON%JSON_EXT|CSV]`</dt>+<dt>`--format [TABLE|JSON|JSON_EXT|CSV]`</dt> <dd>  

--- ahttps://docs.snowflake.com/en/migrations/snowconvert-docs/general/getting-started/download-and-access+++ bhttps://docs.snowflake.com/en/migrations/snowconvert-docs/general/getting-started/download-and-access@@ -9,5 +9,5 @@ ## System requirements -Before you start, make sure that your system meets the minimum requirements list given here:+Before you start, make sure that your system meets the minimum requirements listed here:  - MacOS@@ -41,9 +41,9 @@  Ensure that your VPN is connected and you have access to your MFA device for authentication.-SnowConvert AI does not support authentication via passkeys or time-based one time password (TOTP) authentication methods.+SnowConvert AI does not support authentication via passkeys or time-based one-time password (TOTP) authentication methods.  To resolve any sign in or authentication issues, contact snowconvert-info@snowflake.com -### Supported Platforms+### Supported platforms  Refer to [SnowConvert About](https://docs.snowflake.com/en/migrations/snowconvert-docs/general/about) 

--- ahttps://docs.snowflake.com/en/sql-reference/data-type-conversion+++ bhttps://docs.snowflake.com/en/sql-reference/data-type-conversion@@ -76,5 +76,5 @@    - The following statement coerces the INTEGER value in column `my_integer_column` to FLOAT so that the value can be-    compared to the value `my_float_column` by using the `<` comparison operator:+    compared to the value in `my_float_column` by using the `<` comparison operator:     ```sql     SELECT ...@@ -872,5 +872,5 @@ Except where stated otherwise, the following rules apply to both explicit casting and implicit casting: -- Conversion depends not only on the data type, but also the value, of the source; for example:+- Conversion depends not only on the data type, but also on the value, of the source; for example:   - The VARCHAR value `'123'` can be converted to a numeric value, but the VARCHAR value `'xyz'` can't be converted to     a numeric value.@@ -976,3 +976,3 @@   own conversion and formatting rules when they display data. For example, SnowSQL displays BINARY values as a string that contains   only hexadecimal digits; that string is generated by implicitly calling a conversion function. Therefore, the data that SnowSQL-  displays might not unambiguously indicate which data conversions that Snowflake coerced.+  displays might not unambiguously indicate which data conversions Snowflake performed. 

--- ahttps://docs.snowflake.com/en/user-guide/tag-based-policies+++ bhttps://docs.snowflake.com/en/user-guide/tag-based-policies@@ -187,5 +187,5 @@ ## Example: Protect schema columns when an agent is active -This example assigns a masking policy that call [IS_AGENT_ACTIVATED](/sql-reference/functions/is_agent_activated) to a tag and then assigns+This example assigns a masking policy that calls [IS_AGENT_ACTIVATED](/sql-reference/functions/is_agent_activated) to a tag and then assigns the tag to a schema. Tag inheritance protects all table and view columns in the schema whose data types match the data types in the policies. When an AI agent is active in the execution context, Snowflake masks the protected column values even if the user's role would@@ -362,9 +362,9 @@     <tr>       <td>Create a policy</td>-      <td>CREATE &lt;POLICY_TYPE&gt; on the schema (e.g., CREATE MASKING POLICY)</td>+      <td>CREATE &lt;POLICY_TYPE&gt; on the schema (for example, CREATE MASKING POLICY)</td>     </tr>     <tr>       <td>Set a policy on a tag</td>-      <td>APPLY &lt;POLICY_TYPE&gt; on the account (e.g., APPLY MASKING POLICY)</td>+      <td>APPLY &lt;POLICY_TYPE&gt; on the account (for example, APPLY MASKING POLICY)</td>     </tr>     <tr> 

--- ahttps://docs.snowflake.com/en/user-guide/dcm-projects/dcm-projects-enterprise+++ bhttps://docs.snowflake.com/en/user-guide/dcm-projects/dcm-projects-enterprise@@ -36,5 +36,5 @@  If a %dcm-object% defines a range of objects that are and should remain mostly similar, it is generally more convenient to define them once-as parameterized template.+as a parameterized template.  The following is an example scenario:@@ -60,8 +60,8 @@ ![Reviewing and merging changes](/static/images/dcm-projects/dcm-project-deployment-multi-environments.png) -### Separate accounts vs. separate databases+### Separate accounts compared with separate databases  Snowflake generally recommends setting up each environment as a separate Snowflake account. This ensures complete separation of production-infrastructure from any experimental development and and guarantees restricted developer access to production data.+infrastructure from any experimental development and guarantees restricted developer access to production data.  However, with careful access management, you can successfully manage multiple environments on one Snowflake account. This is easier when the 

--- ahttps://docs.snowflake.com/en/release-notes/2024/other/2024-09-12-dcr+++ bhttps://docs.snowflake.com/en/release-notes/2024/other/2024-09-12-dcr@@ -12,7 +12,7 @@  - If you are an administrator who is configuring the connector so clean room users can activate to Yahoo DSP, see-  [](#label-cleanrooms-activation-admin-yahoo-dsp).+  [the activation connectors guide](/user-guide/cleanrooms/connector-activation). - If you are a clean room user who is using the Activation Hub after running an analysis, see-  [](#label-cleanrooms-activation-admin-yahoo-dsp).+  [the activation connectors guide](/user-guide/cleanrooms/connector-activation).  ## Integration with Google PAIR and Google DV 360@@ -21,3 +21,3 @@ identifiers, then push the results to their Google DV 360 account for activation without ever exposing unencrypted sensitive data. -For more information, see [](#label-cleanrooms-activation-admin-google-dv360-pair).+For more information, see [the activation connectors guide](/user-guide/cleanrooms/connector-activation). 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/snowflake-cowork@@ -41,5 +41,6 @@ - **Artifacts**: A persistent chart or table object that %sf-intelligence% generates in response to a question. Save, share, and revisit tables and charts without regenerating them. For more information, see [](/user-guide/snowflake-cortex/snowflake-cowork/artifacts). - **Automations**: Turn a one-time report into a recurring one that re-runs your question with fresh data and emails you the results. Set up and manage automations conversationally or from the **Automations** tab. For more information, see [](/user-guide/snowflake-cortex/snowflake-cowork/automations).-- **Skills and plugins**: Discover and install shared Cortex Code skills and plugins directly from %sf-intelligence%. For more information, see [Share skills and plugins](/user-guide/snowflake-cortex/skill-catalog).+- **User skills**: Codify a repeatable workflow once, then reuse it explicitly with `/` or from the Skills menus, or implicitly when your conversation matches the skill. Create skills conversationally, from the **+** menu (**Create new**), or by uploading a skill folder. For more information, see [](/user-guide/snowflake-cortex/snowflake-cowork/user-skills).+- **Document generation**: Turn analysis into shareable files such as PDF documents and PowerPoint presentations. Upload a PowerPoint template to match your organization's style, or customize behavior with a user or agent skill. Requires code execution on the associated agent. For more information, see [](/user-guide/snowflake-cortex/snowflake-cowork/document-generation). - **Seamless governance**: Automatically inherits and respects all existing Snowflake data governance   controls, including row-access policies and column-level security.@@ -94,4 +95,6 @@ extended thinking in the chat window. With extended thinking, the agent will be more thorough, but the process might take more time and use more tokens. This setting remains selected.++<a id="label-snowflake-cowork-zero-setup-file-upload"></a>  #### Zero-setup file upload 

--- ahttps://docs.snowflake.com/en/release-notes/bcr-bundles/2026_06/bcr-2342+++ bhttps://docs.snowflake.com/en/release-notes/bcr-bundles/2026_06/bcr-2342@@ -66,6 +66,6 @@  Existing %sis% apps are not affected. Only new [CREATE STREAMLIT](/sql-reference/sql/create-streamlit) commands issued after the-bundle is enabled. For all of the failures listed below, you can also resolve them by adding-`RUNTIME_NAME = 'SYSTEM$WAREHOUSE_RUNTIME'` to opt back into warehouse runtime instead.+bundle is enabled are affected. You can also resolve all the failures listed below by adding+`RUNTIME_NAME = 'SYSTEM$WAREHOUSE_RUNTIME'` to opt back into warehouse runtime.  If your statements use features specific to warehouse runtime, they will fail after the bundle 

--- ahttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-in-your-editor+++ bhttps://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-in-your-editor@@ -33,2 +33,6 @@  For details, see [Cortex Code in Claude Code](/user-guide/cortex-code/cortex-code-claude-code).++## Monitor usage++Because all editor integrations build on the Cortex Code CLI, usage from these integrations is recorded in the [CORTEX_CODE_CLI_USAGE_HISTORY](/sql-reference/account-usage/cortex_code_cli_usage_history) view. To query usage across all Cortex Code surfaces in a single view, use [SNOWFLAKE_COCO_USAGE_HISTORY](/sql-reference/account-usage/snowflake_coco_usage_history). 

--- ahttps://docs.snowflake.com/en/user-guide/kafka-connector/setup-kafka+++ bhttps://docs.snowflake.com/en/user-guide/kafka-connector/setup-kafka@@ -39,5 +39,5 @@ - When you have both the Kafka connector and the JDBC driver jar files in your environment,   ensure your JDBC version matches the `snowflake-jdbc` version specified in the `pom.xml` file of your intended Kafka connector version.-  You can go to your preferred Kafka connector release version, for example, [v4.0.0](https://github.com/snowflakedb/snowflake-kafka-connector/releases/tag/v4.0.0). Then browse `pom.xml` file to find out the version of `snowflake-jdbc`.+  You can go to your preferred Kafka connector release version, for example, [v4.0.0](https://github.com/snowflakedb/snowflake-kafka-connector/releases/tag/v4.0.0). Then browse the `pom.xml` file to find out the version of `snowflake-jdbc`. - If you are using Avro format for ingesting data:   - Use the Avro parser, version 1.8.2 (or higher), available from [https://central.sonatype.com/artifact/org.apache.avro/avro](https://central.sonatype.com/artifact/org.apache.avro/avro).@@ -1273,5 +1273,5 @@    and is encrypted using the passphrase you specified in the previous step; however,    the file should still be protected from unauthorized access using the file permission mechanism provided by your-   operating system. It is the users responsibility to secure the file when it is not in use.+   operating system. It is the user's responsibility to secure the file when it is not in use. 4. Log into Snowflake. Assign the public key to the Snowflake user using [](/sql-reference/sql/alter-user).  

--- ahttps://docs.snowflake.com/en/sql-reference/local/data_quality_monitoring_expectation_status+++ bhttps://docs.snowflake.com/en/sql-reference/local/data_quality_monitoring_expectation_status@@ -38,5 +38,5 @@       <td> -The time the DMF trigger operation occurred, or `None` if the DMF is not scheduled to run by a trigger operation.+The time the DMF trigger operation occurred, or NULL if the DMF is not scheduled to run by a trigger operation.  For information about the trigger operation, see [](#label-data-quality-schedule).@@ -62,5 +62,5 @@       <td>`table_schema`</td>       <td>VARCHAR</td>-      <td>Name of the schema name that contains the table that is associated with the DMF.</td>+      <td>Name of the schema that contains the table that is associated with the DMF.</td>     </tr>     <tr> 

--- ahttps://docs.snowflake.com/en/user-guide/data-integration/zero-copy/sap-sql/publish-data+++ bhttps://docs.snowflake.com/en/user-guide/data-integration/zero-copy/sap-sql/publish-data@@ -5,5 +5,5 @@ - [](/user-guide/data-integration/zero-copy/sap-sql/security) -The [`manage-zerocopy-sapbdc`](/user-guide/cortex-code/bundled-skills#label-bundled-skill-manage-zerocopy-sapbdc) skill manages the end-to-end lifecycle of the SAP and Snowflake Zero-Copy Integration and connector — creating connectors, consuming data products from SAP® BDC, publishing Snowflake data to SAP® BDC, analyzing shared data, and troubleshooting issues, all through a conversational, step-by-step workflow. This skill is now bundled with Cortex Code (CoCo), and you can use it to automate the steps in this topic.+The [`manage-zerocopy-sapbdc`](/user-guide/cortex-code/bundled-skills#label-bundled-skill-manage-zerocopy-sapbdc) skill manages the end-to-end lifecycle of the SAP and Snowflake Zero-Copy Integration and connector: creating connectors, consuming data products from SAP® BDC, publishing Snowflake data to SAP® BDC, analyzing shared data, and troubleshooting issues, all through a conversational, step-by-step workflow. This skill is now bundled with Cortex Code (CoCo), and you can use it to automate the steps in this topic.  This topic describes how to publish Snowflake data back to %sapbdc% by@@ -242,5 +242,5 @@  Fully qualified name of the Zerocopy Connector-(e.g., `my_db.my_schema.my_sap_connector`).+(for example, `my_db.my_schema.my_sap_connector`).  </td> 

--- ahttps://docs.snowflake.com/en/user-guide/snowflake-cortex/ai-multimodal+++ bhttps://docs.snowflake.com/en/user-guide/snowflake-cortex/ai-multimodal@@ -281,5 +281,5 @@ |   "RELATIVE_PATH": "content_video_4.mp4",           | |   "SIZE": 1270501,                                  |-|   "STAGE": "@.MY_VIDEOS"                            |+|   "STAGE": "@MY_VIDEOS"                            | | }                                                   | +-----------------------------------------------------+@@ -717,5 +717,5 @@ | Request failed for external function SYSTEM$COMPLETE_WITH_IMAGE_INTERNAL with remote service error: 400 '"invalid image path"                                    | Either the file extension or the file itself is not accepted by the model. The message might also mean that the file path is incorrect; that is, the file does not exist at the specified location. Filenames are case-sensitive. | | Error in secure object                                                                                                                                           | May indicate that the stage does not exist. Check the stage name and ensure that the stage exists and is accessible. Be sure to use the at (@) sign at the beginning of the stage path, such as `@myimages`.                      |-| Request failed for external function _COMPLETE_WITH_PROMPT with remote service error: 400 '"invalid request parameters: unsupported image format: image/**       | Unsupported image format given to `claude-sonnet-4-6`, i.e. other than .jpeg, .png, .webp, or .gif.                                                                                                                               |+| Request failed for external function _COMPLETE_WITH_PROMPT with remote service error: 400 '"invalid request parameters: unsupported image format: image/\*\*     | Unsupported image format given to `claude-sonnet-4-6`, that is, other than .jpeg, .png, .webp, or .gif.                                                                                                                           | | Request failed for external function _COMPLETE_WITH_PROMPT with remote service error: 400 '"invalid request parameters: Image data exceeds the limit of 5.00 MB" | The provided image given to `claude-sonnet-4-6` exceeds 5 MB.                                                                                                                                                                     |  

--- ahttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-schedule-project-execution+++ bhttps://docs.snowflake.com/en/user-guide/data-engineering/dbt-projects-on-snowflake-schedule-project-execution@@ -31,5 +31,5 @@    - Under **dbt properties**:      - For **Operation**, select the dbt command that you want to execute on a schedule. For a list of supported commands, see [](/user-guide/data-engineering/dbt-projects-on-snowflake-supported-commands).-     - For **Profile**, select one of the profiles defined in the `profiles.yml` file of your dbt project.+     - For **Profile**, select one of the profiles defined in [`dbt_projects_profiles.yml`](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#label-dbt-projects-profiles-file) or `profiles.yml`. Snowflake uses `dbt_projects_profiles.yml` when both files are present.      - For **Additional flags**, enter any additional [command-line options](https://docs.getdbt.com/reference/global-configs/about-global-configs#available-flags) for the dbt command. @@ -65,5 +65,5 @@ ``` -The warehouse you specify for the task is billed for the duration of each scheduled run. To keep costs consolidated, use the same warehouse here as the one set in the target's `profiles.yml`. For more information, see [Align your warehouse configuration](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#align-your-warehouse-configuration).+The warehouse you specify for the task is billed for the duration of each scheduled run. To keep costs consolidated, use the same warehouse here as the one set in the target in `dbt_projects_profiles.yml` or `profiles.yml`. For more information, see [Align your warehouse configuration](/user-guide/data-engineering/dbt-projects-on-snowflake-best-practices#align-your-warehouse-configuration).  Then, the following SQL creates a task that executes the dbt `test` command after each completion of the previous `run_dbt_project` task. 

--- ahttps://docs.snowflake.com/en/user-guide/kafka-connector/index+++ bhttps://docs.snowflake.com/en/user-guide/kafka-connector/index@@ -146,4 +146,4 @@ ## Next steps -Review [how the connector works](/user-guide/kafka-connector/how-the-connector-works) topic for more information about how the connector works with tables and pipes. <br />-Review [](/user-guide/kafka-connector/setup-tasks) topic for the steps to set up the %kafkaofhp%.+Review [how the connector works](/user-guide/kafka-connector/how-the-connector-works) for more information about tables and pipes. <br />+Review [](/user-guide/kafka-connector/setup-tasks) for the steps to set up the %kafkaofhp%. 

--- ahttps://docs.snowflake.com/en/developer-guide/snowflake-ml/inference/gateway-monitor-and-ab-testing+++ bhttps://docs.snowflake.com/en/developer-guide/snowflake-ml/inference/gateway-monitor-and-ab-testing@@ -1,5 +1,5 @@ <a id="label-gateway-monitor-and-ab-testing"></a> -# Gateway Monitoring & A/B Testing+# Gateway monitoring & A/B testing  - [MODEL MONITOR SQL reference](/sql-reference/commands-model-monitor)@@ -170,5 +170,5 @@ ## Known limitations -The following limitations apply to gateway monitoring & A/B testing.+The following limitations apply to gateway monitoring and A/B testing.  - Only single-output binary classification, regression, and multi-class classification models are supported. 

--- ahttps://docs.snowflake.com/en/sql-reference/functions/data_quality_monitoring_expectation_status+++ bhttps://docs.snowflake.com/en/sql-reference/functions/data_quality_monitoring_expectation_status@@ -85,5 +85,5 @@       <td> -The time the DMF trigger operation occurred, or `None` if the DMF is not scheduled to run by a trigger operation.+The time the DMF trigger operation occurred, or NULL if the DMF is not scheduled to run by a trigger operation.  For information about the trigger operation, see [](#label-data-quality-schedule).@@ -109,5 +109,5 @@       <td>`table_schema`</td>       <td>VARCHAR</td>-      <td>Name of the schema name that contains the table that is associated with the DMF.</td>+      <td>Name of the schema that contains the table that is associated with the DMF.</td>     </tr>     <tr>