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A Proactive Approach for BI

A Proactive Approach for BI
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Author(s): Stanley Loh (Lutheran University of Brazil (ULBRA), Brazil)
Copyright: 2015
Pages: 15
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.ch005

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Abstract

A framework to develop proactive BI is presented and discussed in this chapter. In a proactive process, analysis develops as a scientific investigation or research, where analysts must discover an initial set of hypotheses and then test or evaluate the hypotheses. The steps of the framework are presented and ways to perform each step are discussed. Data mining techniques are associated to this proactive paradigm, exploring how they can be applied in each step of the framework. Although there are not yet experiments that validate the correctness of this framework, the objective of the chapter is to focus attention on the differences in the paradigms, discuss ways to perform BI in a proactive way, and alert analysts and executives for practical experiences with the proactive paradigm.

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