The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Perspective on Data Mining Integration with Business Intelligence
Abstract
Business Intelligence (BI) is an emergent area of the Decision Support Systems (DSS) discipline. Over the past years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. The purpose of this chapter is to discuss the relevance of DM integration with BI, and its importance to business users. From the literature review, it was observed that the definition of an underlying structure for BI is missing, and therefore a framework is presented. It was also observed that some efforts are being done that seek the establishment of standards in the DM field, both by academics and by people in the industry. Supported by those findings, this chapter introduces an architecture that can conduct to an effective usage of DM in BI. This architecture includes a DM language that is iterative and interactive in nature. This chapter suggests that the effective usage of DM in BI can be achieved by making DM models accessible to business users, through the use of the presented DM language.
Related Content
|
Murray Eugene Jennex.
© 2020.
29 pages.
|
|
Ronald John Lofaro.
© 2020.
18 pages.
|
|
Mark E. Nissen.
© 2020.
23 pages.
|
|
Ronel Davel, Adeline S. A. Du Toit, Martie Mearns.
© 2020.
32 pages.
|
|
Murray Eugene Jennex.
© 2020.
23 pages.
|
|
Michael J. Zhang.
© 2020.
21 pages.
|
|
Toshali Dey, Susmita Mukhopadhyay.
© 2020.
23 pages.
|
|
|