Data mining process

Article By:

Mata-Toledo, Ramon A. Department of Computer Science, Rollins College, Winter Park, Florida.

Last reviewed:2003

DOI:https://doi.org/10.1036/1097-8542.YB030495

Data mining is the process of discovering valid, comprehensible, and potentially useful knowledge from large data sources with the purpose of applying this knowledge to making decisions. Although generally driven by competitive business environments, data mining is not specific to any particular industry. In fact, any organization can use data mining to extract information in the form of facts, relationships, trends, or patterns. Data mining can also be used to reveal missing pieces of data, or to discover anomalies or exceptions to assumed relationships between some different pieces of data. For this reason, data mining is sometimes referred to as knowledge discovery in databases (KDD). Data mining and KDD, however, are not synonymous. The KDD concept is generally used to describe the whole process of extracting knowledge, whereas data mining is considered a particular activity within KDD where specific algorithms are used to extract data.

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