Based on the SNOWPRO ADVANCED: ARCHITECT EXAM STUDY GUIDE (version 2022/9/7), this maps reference documentation to items in the exam guide. Note that the SNOWPRO ADVANCED: ARCHITECT EXAM STUDY GUIDE is frequently updated and sometimes has broken links. Also, since the exam is only in English, I plan to read English manuals and materials to get familiar with the terminology.
Official Guide
https://www.snowflake.com/certifications/?lang=ja
Exam Guide
1.0 Domain: Account and Security
1.1 Design a Snowflake account and database strategy, based on business requirements.
-
Create and configure Snowflake parameters based on a central account and any additional accounts.
-
List the benefits and limitations of one Snowflake account as compared to multiple Snowflake accounts.
1.2 Design an architecture that meets data security, privacy, compliance, and governance requirements.
-
Configure Role Based Access Control (RBAC) hierarchy
-
System roles and associated best practices
-
Data Access
-
Data Security
-
Compliance
1.3 Outline Snowflake security principles and identify use cases where they should be applied.
Managing Security in Snowflake — Snowflake Documentation
-
Encryption
-
Network security
-
User, Role, Grants provisioning
-
Authentication
Items listed as reference materials in the STUDY GUIDE whose mapping to 1.1~1.3 is unclear
WhitePaper/Read Assets
- Cloud Data Platform Security: How Snowflake Sets the Standard
Lab Guides
- Snowflake Pattern - Security - Access to Sensitive Objects
- Snowflake Pattern - Security - Authentication
- Snowflake Pattern - Security - Network Architecture
2.0 Domain:Snowflake Architecture
2.1 Outline the benefits and limitations of various data models in a Snowflake environment.
- Data models
2.2 Design data sharing solutions, based on different use cases.
-
Use Cases
- Sharing within the same organization/same Snowflake account
- Sharing within a cloud region
- Sharing across cloud regions
- Sharing between different Snowflake accounts
- Sharing to a non-Snowflake customer
- Sharing Across platforms
-
Data Exchange
-
Data Sharing Methods
2.3 Create architecture solutions that support Development Lifecycles as well as workload requirements.
-
Data Lake and Environments
-
Workloads
-
Development lifecycle support
2.4 Given a scenario, outline how objects exist within the Snowflake Object hierarchy and how the hierarchy impacts an architecture.
-
Roles
-
Warehouses
-
Object hierarchy
-
Database
2.5 Determine the appropriate data recovery solution in Snowflake and how data can be restored.
-
Backup/Recovery
-
Disaster Recovery
Lab Guides
- Building an application on Snowflake with data from Snowflake Data Marketplace
- Getting Started with Time Travel
- Data Modeling | Snowflake
WhitePaper/Read Assets
- SNO-eBook-7-Reference-Architectures-for-Application-Builders-AppHealth-SecurityAna.pdf
- Support Multiple Data Modeling Approaches with Snowflake
- Data Modeling in the Age of JSON and Schema-on-Read - Snowflake Blog
- Different Types of Objects in Snowflake
3.0 Domain: Data Engineering
3.1 Determine the appropriate data loading or data unloading solution to meet business needs.
- Data sources
- Ingestion of the data
- Architecture Changes
- Data unloading
3.2 Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.
-
Connectors
-
Connectors & Drivers — Snowflake Documentation
- Kafka
- Spark
- Python
-
Drivers
- JDBC
- OBDC
- API endpoints
- SnowSQL
3.3 Determine the appropriate data transformation solution to meet business needs.
-
Materialized Views, Views and Secure Views
-
Staging layers and tables
-
Querying semi-structured data
-
Data processing
-
Stored Procedures
-
Streams and Tasks
-
Functions
WhitePaper/Read Assets
- Snowflake For Data Engineering - Easily Ingest, Transform, And Deliver Data For Up-To-The-Moment Ins
- Using Streams and Tasks in Snowflake
- Masking Semi-Structured Data with Snowflake - Snowflake Blog
- Easy Continuous Data Pipelines with GA of Streams and Tasks - Snowflake Blog
Lab Guides
- Building a Real-Time Data Vault in Snowflake
- Enrich Salesforce data with Snowflake to deliver your Customer 360
- Auto-Ingest Twitter Data into Snowflake
- Build a Recommendation Engine with AWS SageMaker
- Getting Started with Snowpipe
- Accelerating Data Teams with dbt Cloud & Snowflake
- Getting Started With User-Defined SQL Functions
- Getting Started with Python
- Getting Started with SnowSQL
4.0 Domain: Performance Optimization
4.1 Outline performance tools, best practices, and appropriate scenarios where they should be applied.
-
Query profiling
-
Virtual Warehouse configuration
-
Clustering
-
Search Optimization
-
Caching
-
Query rewrite
4.2 Troubleshoot performance issues with existing architectures.
-
JOIN explosions
-
Warehouse selection (scaling up as compared to scaling out)
-
Best practices and optimization techniques
-
Duplication of data
WhitePaper/Read Assets
Lab Guides
- Resource Optimization: Performance
- Resource Optimization: Billing Metrics
- Resource Optimization: Setup & Configuration
- Resource Optimization: Usage Monitoring
- Automating Data Pipelines to Drive Marketing Analytics with Snowflake & Fivetran
- Building a Data Application
- DevOps: Database Change Management with schemachange and GitHub