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Data Science Glossary: What is a Data Warehouse?

A data warehouse is a system used to do quick analysis of business trends using data from many sources. Data Warehouses are designed to make it easy for people to answer important statistical questions without a Ph.D. in database architecture.

In computing, a data warehouse, also known as an enterprise data warehouse, is a system used for reporting and data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources.

A data warehouse architecture is made up of tiers. The top tier is the front-end client that presents results through reporting, analysis, and data mining tools. The middle tier consists of the analytics engine that is used to access and analyze the data. The bottom tier of the architecture is the database server, where data is loaded and stored. Data is stored in two different types of ways: 1) data that is accessed frequently is stored in very fast storage (like SSD drives) and 2) data that is infrequently accessed is stored in a cheap object store, like Amazon S3. The data warehouse will automatically make sure that frequently accessed data is moved into the “fast” storage so query speed is optimized.

Benefits of a data warehouse include the following:

  • Informed decision making
  • Consolidated data from many sources
  • Historical data analysis
  • Data quality, consistency, and accuracy
  • Separation of analytics processing from transactional databases, which improves performance of both systems

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