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Business Intelligence

In: Handbook on Decision Support Systems 2

Author

Listed:
  • Solomon Negash

    (Kennesaw State University)

  • Paul Gray

    (Claremont Graduate University)

Abstract

Business intelligence (BI) is a data-driven DSS that combines data gathering, data storage, and knowledge management with analysis to provide input to the decision process. The term originated in 1989; prior to that many of its characteristics were part of executive information systems. Business intelligence emphasizes analysis of large volumes of data about the firm and its operations. It includes competitive intelligence (monitoring competitors) as a subset. In computer-based environments, business intelligence uses a large database, typically stored in a data warehouse or data mart, as its source of information and as the basis for sophisticated analysis. Analyses ranges from simple reporting to slice-and-dice, drill down, answering ad hoc queries, real-time analysis, and forecasting. A large number of vendors provide analysis tools. Perhaps the most useful of these is the dashboard. Recent developments in BI include business performance measurement (BPM), business activity monitoring (BAM), and the expansion of BI from being a staff tool to being used by people throughout the organization (BI for the masses). In the long-term, BI techniques and findings will be imbedded into business processes.

Suggested Citation

  • Solomon Negash & Paul Gray, 2008. "Business Intelligence," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 2, chapter 45, pages 175-193, Springer.
    • Handle: RePEc:spr:ihichp:978-3-540-48716-6_9
    DOI: 10.1007/978-3-540-48716-6_9
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    Citations

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    Cited by:

    1. Cullen, Andrew C. & Alpcan, Tansu & Kalloniatis, Alexander C., 2022. "Adversarial decisions on complex dynamical systems using game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    2. Larson, Deanne & Chang, Victor, 2016. "A review and future direction of agile, business intelligence, analytics and data science," International Journal of Information Management, Elsevier, vol. 36(5), pages 700-710.
    3. Jaklič, Jurij & Grublješič, Tanja & Popovič, Aleš, 2018. "The role of compatibility in predicting business intelligence and analytics use intentions," International Journal of Information Management, Elsevier, vol. 43(C), pages 305-318.

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