Course Outline

? Day 1: Cloud Data Warehousing Concepts & Snowflake Fundamentals

Session 1: Introduction to Data Warehousing in the Cloud

• Data warehousing concepts and architecture
• Traditional vs. cloud data warehouses
• Key features of Snowflake and BigQuery

Session 2: Getting Started with Snowflake

• Snowflake architecture and components
• Creating accounts, warehouses, databases, and schemas
• Loading data: bulk loading, file formats, and staging areas

Session 3: Querying and Managing Data in Snowflake

• Snowflake SQL basics: SELECT, filtering, joins
• Time travel, zero-copy cloning, and data sharing
• User management and role-based access control

Lab Activities:

• Set up a Snowflake account and warehouse
• Load CSV and JSON data into Snowflake tables
• Write queries with joins and filters; explore time travel

? Day 2: Google BigQuery Essentials & Data Integration

Session 1: Overview of Google BigQuery

• BigQuery architecture and serverless model
• Creating datasets, tables, and partitions
• Understanding storage and compute separation

Session 2: Loading and Querying Data in BigQuery

• Loading data via UI, CLI, and APIs
• SQL querying: Standard SQL dialect, joins, window functions
• Using partitions and clustering for performance

Session 3: Data Transformation and ETL Pipelines

• Writing efficient SQL transformations
• Integrating BigQuery with Dataflow, Cloud Composer, and third-party tools
• Best practices for pipeline design and monitoring

Lab Activities:

• Load sample data into BigQuery tables
• Write complex queries using window functions and joins
• Partition and cluster tables to improve query speed

? Day 3: Performance Optimization, Security & Governance

Session 1: Query Optimization and Cost Management

• Query execution plans and monitoring
• Best practices to optimize query performance in Snowflake and BigQuery
• Cost controls and budgeting strategies

Session 2: Security and Compliance

• Access control and data masking in Snowflake
• IAM roles and dataset/table permissions in BigQuery
• Data encryption and audit logging

Session 3: Advanced Features and Real-World Use Cases

• Materialized views, streams, and tasks in Snowflake
• BigQuery ML and geospatial analysis overview
• Designing multi-cloud or hybrid data warehouse solutions

Lab Activities:

• Analyze query performance and tune SQL queries
• Set up role-based access controls and data masking
• Explore BigQuery ML by building a simple prediction model