A data warehouse is a centralized system optimized for storing and querying large volumes of structured, historical data. Unlike transactional databases designed for frequent small updates, data warehouses are optimized for analytical queries that scan millions of rows. They power dashboards, business intelligence tools, and advanced analytics by organizing data in columnar formats and precomputed aggregates.
Why it matters
Organizations rely on data warehouses to support decision-making, trend analysis, and performance reporting. Warehouses improve query performance, standardize metrics, and serve as a foundation for data science. They integrate tightly with data pipelines that clean and load data from operational systems.
Examples
Snowflake, BigQuery, and Amazon Redshift are widely used cloud warehouses. Lessons like Data Warehousing Concepts explain warehouse architecture and use cases.