A data warehouse is a database geared towards the business intelligence requirements of an enterprise. The data warehouse integrates data from the various operational systems and is typically loaded from these systems at regular intervals. Data warehouses contain historical information that enables analysis of business performance over time.

While operational systems are optimized for simplicity and speed of modification (online transaction processing, or OLTP) through heavy use of database normalization and an entity-relationship model, the data warehouse is optimized for reporting and analysis (on line analytical processing, or OLAP). Frequently data in data warehouses is heavily denormalised, summarised and/or stored in a dimension-based model but this is not always required to achieve acceptable query response times.

Our definition for data warehouse is:

• Subject-oriented: meaning that the data in the database is organized so that all the data elements relating to the same real-world event or object are linked together.
• Time-variant: meaning that the changes to the data in the database are tracked and recorded so that reports can be produced showing changes over time.
• Non-volatile: meaning that data in the database is never over-written or deleted, once committed, the data is static, read-only, but retained for future reporting.
• Integrated: meaning that the database contains data from most or all of an organization's operational applications, and that this data is made consistent.