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Enterprise Information System and Data Mining

Author

Listed:
  • Kenneth D. Lawrence

    (New Jersey Institute of Technology, USA)

  • Dinesh R. Pai

    (Penn State Lehigh Valley, USA)

  • Ronald Klimberg

    (Saint Joseph’s University, USA)

  • Sheila M. Lawrence

    (Rutgers University, USA)

Abstract

The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data mining as applicable to organizational functions, such as supply chain management (SCM), marketing, and customer relationship management (CRM) in the context of EIS.

Suggested Citation

  • Kenneth D. Lawrence & Dinesh R. Pai & Ronald Klimberg & Sheila M. Lawrence, 2010. "Enterprise Information System and Data Mining," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 1(3), pages 34-41, July.
    • Handle: RePEc:igg:jbir00:v:1:y:2010:i:3:p:34-41
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