Closing the Gap between Data Mining and Business Users of Business Intelligence Systems: A Design Science Approach

Closing the Gap between Data Mining and Business Users of Business Intelligence Systems: A Design Science Approach

Ana Azevedo (Instituto Superior de Contabilidade e Administração do Instituto Politécnico do Porto, Porto, Portugal) and Manuel Filipe Santos (Departamento de Sistemas de Informação, University of Minho, Guimarães, Portugal)
Copyright: © 2012 |Pages: 40
DOI: 10.4018/jbir.2012100102
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Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.
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The research presented in this paper approaches the issue of using Data Mining (DM) languages in the context of Business Intelligence (BI) systems. The aim is to study the viability of developing a DM language oriented to business users and oriented to the BI activities.

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