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Business Intelligence: Attribute and Feature Demand

Author

Listed:
  • Gerald V. Post

    (University of the Pacific, USA)

  • Albert Kagan

    (Arizona State University, USA)

Abstract

Data mining and business intelligence tools have been adding features and gaining uses, and statistical tools developed for data mining tasks often require advanced knowledge and training to apply. Development of these selected tools requires tradeoffs in ease of use and power. This study asks users to evaluate the various tools and attributes to identify the relative value of the various components and provide direction for improvements and new tools. Evaluating multi-attribute software is a challenging task, and this study provides a method of evaluating the data and analyzing tradeoffs. A structured equation model (SEM) is applied to the process. Each of the existing tools evaluated have different relative strengths, so it is important to match the organization’s primary tasks to the relative strengths of the tool.

Suggested Citation

  • Gerald V. Post & Albert Kagan, 2012. "Business Intelligence: Attribute and Feature Demand," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 3(3), pages 16-28, July.
    • Handle: RePEc:igg:jbir00:v:3:y:2012:i:3:p:16-28
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