MY ONE BLOGby Manishdai
Data & Analytics

What is Data Warehouse?

Quick answer

A system that stores cleaned, structured data from many sources, optimized for reporting and business analysis.

Data Warehouse, explained

A data warehouse brings together information from sales systems, marketing tools, finance software, and other sources into one consistent, organized store. Data is usually cleaned and modeled before it is loaded, an approach called schema-on-write, so analysts can run fast, reliable queries.

For example, a retailer might combine point-of-sale data, online orders, and inventory records in a warehouse to build dashboards showing sales by region and product. Warehouses are typically queried with SQL and power business intelligence tools. Cloud data warehouses separate storage from compute, letting teams scale each independently. Compared with a data lake, a warehouse is more structured and governed but less flexible for raw or unstructured data.

Related terms

Business Intelligence

Tools and practices that collect, analyze, and present business data, usually through reports and dashboards, to support decisions.

Data Lake

A central repository that stores large volumes of raw data in its original format until it is needed for analysis.

Data Lakehouse

A data architecture that combines the low-cost, flexible storage of a data lake with the structure and query performance of a data warehouse.

Data Mesh

An approach to data architecture that gives business domains ownership of their own data, shared as products across the organization.

Data Pipeline

An automated series of steps that moves data from one or more sources, transforms it, and delivers it to a destination for use.

ETL

Extract, Transform, Load: a process that pulls data from sources, cleans and reshapes it, and loads it into a destination such as a data warehouse.

SQL

Structured Query Language: the standard language for storing, querying, and managing data in relational databases.

Guides that mention Data Warehouse