Introduction to SQL for Analytics

Joins, CTEs, and Aggregations

Data Validation Queries

OLAP vs OLTP and Modern Warehouses

Data Modeling Concepts

Building Views in Azure PostgreSQL

Practice

Assignment

Gotchas & Pitfalls

Week 9 Lesson Plan (Teachers)

Data Modeling Concepts

Content coming soon...

Suggested Topics

• The three-layer model: raw (landing), staging (cleaned), marts (business-ready)
• What grain means and why it is the most important modeling decision
• Primary keys, surrogate keys, and natural keys
• Facts: measurable events with numeric metrics (orders, clicks, pipeline runs)
• Dimensions: descriptive context for facts (customers, products, dates)
• Star schema basics: one fact table surrounded by dimension tables
• The relationship between grain and joins: how wrong grain causes duplicated metrics
• Naming conventions and documentation for models
• Date dimension as a standard first dimension: date keys, fiscal periods, and time intelligence
• How these concepts map to the views you will build in Azure PostgreSQL

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