Normalization (1NF to BCNF) - understand what you're undoing when you denormalize

Views & Materialized Views - database-managed denormalization

Partitioning & Sharding - horizontal scaling alternative to denormalization

Indexing Strategies - sometimes indexes solve the problem without denormalization

Caching Strategies - application-level alternative to database denormalization

Measure query performance before and after denormalizing an orders table with customer and product data

Implement triggers to maintain consistency between normalized and denormalized tables

Create a materialized view for a complex analytics query and measure the performance improvement

Design a pre-aggregated statistics table and implement incremental updates

Build a consistency checker that detects data drift between source and denormalized tables

Explain when you would denormalize a database and what trade-offs you would consider

How would you maintain consistency in a denormalized database?

What is the difference between a view and a materialized view?

Design a denormalization strategy for an e-commerce order listing page that currently takes 2 seconds to load

How would you measure whether denormalization actually improved performance?

Martin Kleppmann - Designing Data-Intensive Applications (Chapter 2: Data Models)

PostgreSQL Documentation - Materialized Views

High Performance MySQL - Denormalization and Caching Strategies

Database Internals - Storage and Indexing Trade-offs