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Overview
This three-day course for Architects and Technical Leaders provides the skills, knowledge, and Snowflake recommended best practices to deploy and operate Snowflake, insights and recommendations based upon real-world customer experiences, and the confidence to get the most out of Snowflake’s technology.
Examine the trade-offs 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-recommended best practices to maximize performance and efficient use of resources during data ingestion, transformation, and end user queries. Analyze Snowflake metadata to identify performance and cost issues and recommend remedial action.
Solution Architects Data Architects Database Architects Enterprise Data Architects Senior Data Engineers Technical Team Leads
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Module 1: Architecture Overview Snowflake Architecture Snowflake’s Layered Architecture Module 2: Deployment Considerations Organization Geographic Account Considerations Snowflake Security Domains Environment Deployment Options Cross Environment Data Transfer Data Transfer Options Environment Separation Logical Data Architecture (Layers) Physical Architecture Options Database Considerations Database Reference Options Summary and Recommendations Module 3: Data Architecture Overall Data Flow Reference Data Architecture Handling Raw History Integration With a Data Lake Create External Table Query External Table Partitioned External Tables External Network Access Change Data Capture, Creating and Managing Streams Snow pipe Streaming Overview Dynamic Tables Hybrid Tables Apache Iceberg™ Tables in Snowflake Apache Polaris™ and Snowflake Open Catalog Module 4: Virtual Warehouse Management Objectives Workload Challenges Scale Up for Large Workloads Key Concepts: Diminishing Elapsed Time Improvements Scale Out for Multiple Concurrent Users Right-Sizing Virtual Warehouses Virtual Warehouse Deployment Approach Measuring Workloads Summary Module 5: Snowpark Snowpark Container Services What is a Container? Use Cases Module 6: Compute Pools Snowflake AI/ML Batch Why Snowflake for AI/ML Incorporating into the Batch Cycle Benefits Module 7: Data Security Framework Data Security Framework Data Classification Identify Data Sensitivity Module 8: Role-Based Access Control (RBAC) Overview RBAC Requirements RBAC Hierarchy Design RBAC Role Design Naming Standards RBAC Script Building Snowflake-recommended RBAC Best Practices Snowflake User-based Access Control (UBAC) Module 9: Data Governance Features Data Masking and Row Access Policies Dynamic Data Masking Row Access Policies Summary Module 10: Sharing Architecture Use Case Direct Share With Replication Data Products in Snowflake Auto-fulfilment How Auto-fulfilment Works Native Apps Native Apps Demo Module 11: Snowflake Data Storage Data Storage Standard Tables Data Storage Hybrid Tables Snowflake Data Storage Management Data Storage Implications Data Storage DML Implications Time Travel KeyPoint Clones Data Recovery Agile Data Management Development System Testing Deployment Module 12: Table Clustering What is Table Clustering? Partition Pruning (Elimination) Overlapping Values Evaluating Clustering Implement and Test Clustering Keys Module 13: Performance Optimization Search Optimization How Does It Work? Materialized Views Materialized View Use Cases Query Acceleration Service (QAS)
Module 1: Architecture Overview
Module 2: Deployment Considerations
Module 3: Data Architecture
Module 4: Virtual Warehouse Management
Module 5: Snowpark
Snowpark Container Services
Module 6: Compute Pools
Snowflake AI/ML Batch
Module 7: Data Security Framework
Module 8: Role-Based Access Control (RBAC)
Module 9: Data Governance Features
Module 10: Sharing Architecture
Module 11: Snowflake Data Storage
Module 12: Table Clustering
Module 13: Performance Optimization
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