Integrating Data Mining Into Business Intelligence

Maria Cristina Enache ()
Additional contact information
Maria Cristina Enache: Dunarea de Jos University of Galati, Romania
Authors registered in the RePEc Author Service: Maria Cristina Enache and Cristina Enache

Economics and Applied Informatics, 2006, issue 1, 25-28

Abstract: Data Mining is a broad term often used to describe the process of using database technology, modeling techniques, statistical analysis, and machine learning to analyze large amounts of data in an automated fashion to discover hidden patterns and predictive information in the data. By building highly complex and sophisticated statistical and mathematical models, organizations can gain new insight into their activities. The purpose of this document is to provide users with a background of a few key data mining concepts and business intelligence and about benefits of integrating business intelligence and data mining.

Keywords: Business Intelligence; platform; data mining (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.ann.ugal.ro/eco/Doc%202006/5.%20OK%20Cristina_Enache_Anale.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ddj:fseeai:y:2006:i:1:p:25-28

Access Statistics for this article

More articles in Economics and Applied Informatics from "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Gianina Mihai ().