Week 9 - SQL for Analytics

Introduction to SQL for Analytics

2. Joins, CTEs, and Aggregations

3. Data Validation Queries

4. Data Modeling Concepts

5. Building Views in Azure PostgreSQL

6. Gotchas & Pitfalls

4. OLAP vs OLTP and Modern Warehouses

OLAP vs OLTP and Modern Warehouses

Content coming soon...

Suggested Topics

OLTP systems: optimized for transactions, row-oriented storage, normalized schemas
OLAP systems: optimized for analytics, columnar storage, denormalized or star schemas
Why you should not run analytical queries on production OLTP databases
Columnar vs row-oriented storage and how it affects query performance
Modern cloud data warehouses: Snowflake, BigQuery, Amazon Redshift, Microsoft Fabric
Key warehouse features: separation of compute and storage, auto-scaling, pay-per-query
Azure PostgreSQL as a stepping stone: how it compares to full warehouse solutions
The data warehouse in the broader data platform: ELT, orchestration, BI
When a data warehouse is overkill: small teams, low data volume, simple use cases

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