Data warehouse vs Data mining

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What is the difference between data warehousing and data mining?

The question looks a bit absurd if you are an expert BI practitioner. However, that is one of the very basic question most of the beginners unable to answer.

Data warehouse

Data warehousing is the process of collecting data from multi-varied sources of an organizationa and repositing it into one comprehensive and easily manipulated database. And data warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis

Data mining

Data mining (also called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Difference: Datawarehouse vs Data mining

Data warehouse is the database on which we apply data mining. 

Data warehouse Data mining
It consists of historical data, stored in the form of relational database. Data is acquired from different sources. This is the process of finding hidden  information from a large sample of data.
Information about present time can  be obtained. Future information can be predicted.

This system answers questions like:

Who are our customers?

Who is purchasing our products?

This system answers questions like:

Who are not our customers?

Who are not purchasing our products?

 
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