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Business Intelligence and Data Mining

Business Intelligence and Data Mining

Zsolt T. Kardkovács
Copyright: © 2013 |Pages: 14
ISBN13: 9781466641815|ISBN10: 1466641819|EISBN13: 9781466641822
DOI: 10.4018/978-1-4666-4181-5.ch003
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MLA

Kardkovács, Zsolt T. "Business Intelligence and Data Mining." Research and Development in E-Business through Service-Oriented Solutions, edited by Katalin Tarnay, et al., IGI Global, 2013, pp. 57-70. https://doi.org/10.4018/978-1-4666-4181-5.ch003

APA

Kardkovács, Z. T. (2013). Business Intelligence and Data Mining. In K. Tarnay, S. Imre, & L. Xu (Eds.), Research and Development in E-Business through Service-Oriented Solutions (pp. 57-70). IGI Global. https://doi.org/10.4018/978-1-4666-4181-5.ch003

Chicago

Kardkovács, Zsolt T. "Business Intelligence and Data Mining." In Research and Development in E-Business through Service-Oriented Solutions, edited by Katalin Tarnay, Sandor Imre, and Lai Xu, 57-70. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-4181-5.ch003

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Abstract

Whenever decision makers find out that they want to know more about how the business works and progresses, or why customers do what they do, then data miners are summoned, and business intelligence is to be built or altered. Data mining aims at retrieving valid, interesting, explicable connection between key factors for either operative reporting or supporting strategic planning. While data mining discovers static connections between factors, business intelligence visualizes relevant data for decision makers in order to make them identify fast changes and analyze precisely business states. In this chapter, the authors give a short introduction for data oriented decision support systems with data mining and business intelligence in it. While these techniques are widely used in business processes, there are much more bad practices than good ones. We try to make an attempt to demystify and clear the myths about these technologies, and determine who should and how (not) to use them.

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