Snowflake Architect
Mastering Architecture, Performance Optimization, and Best Practices in Snowflake
Duration
3 Days
Level
Intermediate Level
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This three-day course for Architects and Technical Leaders provides the skills, knowledge, and Snowflake best practices to deploy and operate Snowflake, insights and recommendations based upon real-world customer experiences, and the confidence to get the very best out of Snowflake’s technology.
ACQUIRED SKILLS
- Examine the tradeoffs associated with the available environment and Snowflake Account deployment
- options.
- Use the Snowflake data security framework to balance the often-conflicting needs of protecting sensitive
- data while democratizing access and facilitating sharing.
- Apply Snowflake best practices to maximize performance and efficient use of resources during data inges-
- tion, transformation, and end user queries.
- Analyze Snowflake metadata to identify performance and cost issues and recommend remedial action.
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- Solution Architects
- Data Architects
- Database Architects
- Enterprise Data Architects
- Senior Data Engineers
- Technical Team Leads
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- Snowflake Architecture
- Snowflake’s Layered Architecture
- Organization
- Geographic Account Considerations
- Snowflake Security Domains
- Environment Deployment Options
- Cross Environment Data Transfer
- Options
- Environment Separation
- Logical Data Architecture (Layers)
- Physical Architecture Options
- Database Considerations
- Database Reference Options
- Summary and Recommendations
- Overall Data Flow
- Reference Data Architecture
- Handling Raw History
- Integration with Data Lake
- Create External Table
- Query External Table
- Partitioned External Tables
- Snowpipe Streaming Overview
- External Network Access
- Native Apps
- Change Data Capture, Creating and Managing Streams
- Dynamic Tables
- Hybrid Tables
- Iceberg Tables in Snowflake
- Objectives
- Workload Challenges
- Scale Up for Large Workloads
- Key Concepts: Scaling Up
- Key Concepts: Diminishing Elapsed Time Improvements
- Scale Out for Multiple Concurrent Users
- Speed vs. Throughput
- Right-Sizing Virtual Warehouses
- Virtual Warehouse Deployment Approach
- Measuring Workloads
- Summary
- Case Study
- Data Security Framework
- Data Classification
- Identify Data Sensitivity
- Overview
- RBAC Requirements
- RBAC Hierarchy Design
- RBAC Role Design
- Naming Standards
- RBAC Script Building
- Snowflake RBAC Best Practices
- Data Masking and Row Access Policies
- Dynamic Data Masking
- Row Access Policies
- Summary
- Use Case
- Direct Share
- With Replication
- Data Mesh
- Relevant Snowflake Capabilities for a Data Mesh
- Data Mesh Architecture Options with Snowflake
- Data Products in Snowflake
- Auto-fulfillment
- How Auto-fulfillment Works
- Data Storage Methods
- Snowflake Data Storage
- Data Storage Implications
- Time Travel
- Key Point
- Time Travel and Storage
- Clones
- Data Recovery
- Agile Data Management
- Development
- System Testing
- Deployment
- What Is Table Clustering?
- Partition Pruning (Elimination)
- Overlapping Values
- Evaluating Clustering
- Implement and Test Clustering Keys
- Search Optimization
- How Does It Work?
- Materialized Views
- Materialized View Use Cases
- Query Acceleration Service (QAS)
- Observability on Snowflake
- Outbound Notifications
- Snowflake Alerts
- Observability Within Snowsight
- Budgets
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- SQL skills, a background in database management, and, ideally, experience in designing and deploying
- analytic-based systems are required.
- Completion of “Snowflake Fundamentals” or equivalent Snowflake knowledge.