What is Data Warehouse?
A large database optimised for storing and analysing historical data from multiple sources.
Why It Matters
Data warehouses enable complex business intelligence queries across all your data without slowing down production systems.
Real-World Example
Combining sales, marketing, and customer data in a warehouse to analyse business performance over the past year.
“Understanding terms like Data Warehouse matters because it helps you have better conversations with developers and make smarter decisions about your software. You do not need to be technical. You just need to know enough to ask the right questions.”
Related Terms
Data Lake
A storage system that holds large amounts of raw data in its original format until it is needed.
ETL (Extract, Transform, Load)
A process that extracts data from sources, transforms it into a useful format, and loads it into a destination.
OLAP (Online Analytical Processing)
Database systems optimised for complex analytical queries across large volumes of historical data.
Data Pipeline
An automated series of steps that moves and processes data from one system to another.
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Related Terms
Data Lake
A storage system that holds large amounts of raw data in its original format until it is needed.
ETL (Extract, Transform, Load)
A process that extracts data from sources, transforms it into a useful format, and loads it into a destination.
Data Pipeline
An automated series of steps that moves and processes data from one system to another.
OLAP (Online Analytical Processing)
Database systems optimised for complex analytical queries across large volumes of historical data.
Database
An organised collection of data that your application can store, retrieve, and update
SQL
A language for communicating with databases, used to create, read, update, and delete data