Data Mining: Concepts and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)

Data mining (also known as knowledge discovery and data mining (KDD), knowledge discovery in data, and knowledge discovery in databases), refers to sorting through data to identify patterns and relationships in large relational databases in order to extract and utilize data. Data mining allows data to be extracted and transformed, stored in a data base, accessed, and analyzed by software programs. Additionally, the data retrieved can be presented in various forms, such as in graphs or tables. The types of relationships that are commonly found in data mining include classes, clusters, associations, and sequential patterns.

Data mining focuses on producing a solution that generates useful forecasting through a four-phase process:

1. problem identification
2. exploration of the data
3. pattern discovery
4. knowledge deployment, or application of knowledge to new data to forecast or generate predictions.

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