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Data‐mining algorithms in Oracle9i and Microsoft SQL Server

Margo Hanna (Education Liaison Officer, Knowsley Council, Liverpool, UK)

Campus-Wide Information Systems

ISSN: 1065-0741

Article publication date: 1 July 2004



In today's competitive marketplace, it is crucial that companies manage their most valuable assets – customers and customers' information that is achieved via using data mining applications that sift through massive amounts of data and find hidden information – that help better understand customers and anticipate their behaviour. This paper aims at discussing data mining methods in Oracle, widely used for large corporate business, and Microsoft data mining applications, commonly used within SMEs. It discusses Oracle9i and Microsoft Data Mining algorithms which provides a powerful, scalable infrastructure for building applications that automate the extraction of business intelligence and its integration into other applications. It addresses the capabilities and limitations of data mining tools within Oracle9i and Microsoft, highlighting how the intelligent tools are beneficial for different scales and sectors of business and industry.



Hanna, M. (2004), "Data‐mining algorithms in Oracle9i and Microsoft SQL Server", Campus-Wide Information Systems, Vol. 21 No. 3, pp. 132-138.



Emerald Group Publishing Limited

Copyright © 2004, Emerald Group Publishing Limited

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