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Data Mining and Business Intelligence: A Comparative, Historical Perspective

Data Mining and Business Intelligence: A Comparative, Historical Perspective
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Author(s): Ana Azevedo (Algoritmi R&D Center/University of Minho, Portugal & Polytechnic Institute of Porto/ISCAP, Portugal)
Copyright: 2015
Pages: 11
Source title: Integration of Data Mining in Business Intelligence Systems
Source Author(s)/Editor(s): Ana Azevedo (Algoritmi R&D Center/University of Minho, Portugal & Polytechnic Institute of Porto/ISCAP, Portugal) and Manuel Filipe Santos (Algoritmi R&D Center/University of Minho, Portugal)
DOI: 10.4018/978-1-4666-6477-7.ch001

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Abstract

Data Mining (DM) is being applied with success in Business Intelligence (BI) environments, and several examples of applications can be found. BI and DM have different roots and, as a consequence, have significantly different characteristics. DM came up from scientific environments; thus, it is not business oriented. DM tools still demand heavy work in order to obtain the intended results. On the contrary, BI is rooted in industry and business. As a result, BI tools are user-friendly. This chapter reflects on this difference from a historical perspective. Starting with a separated historical perspective of each one, BI and DM, the author then discusses how they converged into the current situation, when DM is used, and integrated, in BI environments with success.

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