Run a large revenue report on the production database, and it can slow down live traffic. Analytical queries may scan years of history. Production databases are built for small, fast reads and writes. When both run on the same system, they compete for the same CPU, memory, and I/O.

A data warehouse separates those workloads. It stores structured, cleaned, business-ready data for reporting, BI, historical analysis, and shared metrics, away from the databases that serve live users.

Unlike production databases, warehouses are optimized for large scans, joins, and aggregations, not single-row transactions.

This chapter explains how data warehouses differ from production databases, how warehouse design evolved, how schemas and performance tuning work, and how warehouses compare with data lakes and lakehouses.