Encyclopedia of Database Systems

Living Edition
| Editors: Ling Liu, M. Tamer Özsu

Business Intelligence

Living reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7993-3_881-2


Business intelligence (often referred to as BI) is a business management term that indicates the capability of adding more intelligence to the way business is done by companies. More precisely, it refers to a set of tools and techniques that enable a company to transform its business data into timely and accurate information for the decisional process, to be made available to the right persons in the most suitable form. Business intelligence systems are used by decision makers to get a comprehensive knowledge of the business and of the factors that affect it, as well as to define and support their business strategies. The goal is to enable data-based decisions aimed at gaining competitive advantage, improving operative performance, responding more quickly to changes, increasing profitability and, in general, creating added value for the company.

Historical Background

Business intelligence was coined as a term in 1958 by Hans P. Luhn, to indicate a system capable of...


Sentiment Analysis Business Intelligence Enterprise Data Business Intelligence System Data Warehousing System 
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Recommended Reading

  1. 1.
    Golfarelli M, Rizzi S, Cella I. Beyond data warehousing: what’s next in business intelligence? In: Proceedings ACM 7th International Workshop on Data Warehousing and OLAP, Washington, DC; 2004. p. 1–6.Google Scholar
  2. 2.
    Vitt E, Luckevich M, Misner S. Business intelligence: making better decisions faster. Microsoft Press; 2002.Google Scholar
  3. 3.
    Trujillo J, Maté A. Business intelligence 2.0: a general overview. In: Aufaure M-A, Zimanyi E, editors. eBISS 2011. LNBIP 96, Paris: Springer; 2012, p. 98–116.Google Scholar
  4. 4.
    Golfarelli M, Mandreoli F, Penzo W, Rizzi S, Turricchia E. OLAP query reformulation in peer-to-peer data warehousing. Inf Syst. 2012;37(5):393–411.CrossRefGoogle Scholar
  5. 5.
    Gallinucci E, Golfarelli M, Rizzi S. Meta-stars: multidimensional modeling for social business intelligence. In: Proceedings 16th International Workshop on Data Warehousing and OLAP, San Francisco; 2013. p. 11–8.Google Scholar
  6. 6.
    Golfarelli M, Mantovani M, Ravaldi F, Rizzi S. Lily: a geo-enhanced library for location intelligence. In: Proceedings 15th International Conference on Data Warehousing and Knowledge Discovery, Prague; 2013. p.72–83.Google Scholar
  7. 7.
    Kozmina N, Niedrite L. Research directions of OLAP personalization. In: Proceedings 19th International Conference on Information Systems Development, Prague; 2010. p. 345–56.Google Scholar
  8. 8.
    Abelló A, Romero O. Service-oriented business intelligence. In: Aufaure M-A, Zimanyi E, editors. eBISS 2011. LNBIP 96, Paris: Springer; 2012. p. 156–85.Google Scholar
  9. 9.
    Chen H, Chiang R, Storey V. Business intelligence and analytics: from big data to big impact. MIS Q. 2012;36(4):1165–88.Google Scholar
  10. 10.
    Rizzi S. Collaborative business intelligence. In: Aufaure M-A, Zimanyi E, editors. eBISS 2011. LNBIP 96. Paris: Springer 2012. p. 186–205.Google Scholar
  11. 11.
    Abelló A, et al. Fusion cubes: towards self-service business intelligence. Int J Data Warehouse Min. 2013;9(2):66–88.CrossRefGoogle Scholar
  12. 12.
    Pedersen, TB. Managing Big Multidimensional Data. In: Proceedings 15ème Conférence Internationale sur l’Extraction et la Gestion des Connaissances. 2015. p. 3–6.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.DISIUniversity of BolognaBolognaItaly