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Data Mining For Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel® with XLMiner®, Second Edition by Peter C. Bruce, Nitin R. Patel, Galit Shmueli

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Chapter 1. Introduction

What Is Data Mining?

The field of data mining is still relatively new and in a state of evolution. The first International Conference on Knowledge Discovery and Data Mining (KDD) was held in 1995, and there are a variety of definitions of data mining. A concise definition that captures the essence of data mining is:

Extracting useful information from large data sets.

(Hand et al., 2001)

A slightly longer version is:

Data mining is the process of exploration and analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns and rules.

(Berry and Linoff, 1997, p. 5)

Berry and Linoff later had cause to regret the 1997 reference to "automatic and semi-automatic means," feeling that it shortchanged the role of data exploration and analysis analysis (Berry and Linoff, 2000).

Another definition comes from the Gartner Group, the information technology research firm:

[Data Mining is] the process of discovering meaningful correlations, patterns and trends by sifting through large amounts of data stored in repositories. Data mining employs pattern recognition technologies, as well as statistical and mathematical techniques.

(http://www.gartner.com/6-help/glossary, accessed May 14, 2010)

A summary of the variety of methods encompassed in the term data mining is given at the beginning of Chapter 2.

Where Is Data Mining Used?

Data mining is used in a variety of fields and applications. The military use data mining to learn what ...

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