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Data warehousing, data mining and data querying: Terms and definitions

Learn the difference between data warehousing, data mining and data querying.

What are the differences between data mining, data warehousing and data querying?

The definitions of data warehousing, data mining and data querying can be confusing because they are related. Learn the differences between the terms below.

A data warehouse is a repository of data designed to facilitate information retrieval and analysis. The data contained within a data warehouse is often consolidated from multiple systems making analysis across those systems quicker and easier.

Data mining and data querying represent two methods of retrieval and analysis.

Data querying is the process of asking questions of data in search of a specific answer. Unlike many forms of search (i.e. Google), queries are normally structured and require specific parameters or code, known as SQL (Structured Query Language). A query could be written to answer questions like, "How many items were sold in Region 2 last month?"

Data mining is the process of sorting through large amounts of data to identify patterns and relationships using statistical algorithms. These relationships may help us to understand which factors affected the outcome of something, or they may be used to predict future outcomes. Data mining might be used to answer questions like, "What factors affected sales in Region 2 last month?" Knowing which factors drive sales in the past could help to predict or make estimates about sales in the future.

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This was first published in May 2008

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