Advertisement

Cloud Business Intelligence

  • Hariklea Kazeli
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 183)

Abstract

During the last two decades technology evolved in a way that resulted in massive data. Enterprises built expensive infrastructures to turn data into valuable information in support of the management’s decision making, giving rise to Business Intelligence. Even though, the cost of such infrastructures has been significantly reduced, the economic crisis limited the business budgets, especially for small and medium enterprises, in ways that they could not afford setting up high performance infrastructures. The concept of cloud computing addresses the problem of scalability, agility and cost by allowing enterprises to access powerful tools and services without having to purchase the solutions or the infrastructure needed. This paper describes the concept of Cloud Business Intelligence and addresses the benefits, problems and challenges raised when applied in the real business world.

Keywords

Business Intelligence Cloud Computing Cloud Business Intelligence Big Data Data Warehouse and Data Analytics 

References

  1. 1.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I. Zaharia, M.: Above the clouds: a Berkeley view of cloud computing. UC Berkeley technical report (2009)Google Scholar
  2. 2.
    Baars, H., Kemper, H.G.: Business intelligence in the cloud? PACIS 2010 Proceedings, Paper 145 (2010). http://aisel.aisnet.org/pacis2010
  3. 3.
    Birst: Why cloud BI? The 10 substantial benefits of software-as-a-service business intelligence. White paper, Birst Inc. (2010)Google Scholar
  4. 4.
    Boateng, O., Singh, J., Singh, G.P.: Data warehousing. Bus. Intell. J. 5(2) (2012)Google Scholar
  5. 5.
    Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. (Special Issue: Business Intelligence Research) 36(4) (2012)Google Scholar
  6. 6.
    Davenport, T.H.: Business intelligence and organizational decisions. Int. J. Bus. Intell. Res. 1(1), 1–12 (2010)CrossRefGoogle Scholar
  7. 7.
    Davenport, T.H., Harris, J.G., De Long, D.W., Jacobsen, A.L.: Data to knowledge to results: building an analytic capability. Calif. Manag. Rev. 43(2), 117–138 (2001)CrossRefGoogle Scholar
  8. 8.
    Druzdzel, M.J., Flynn, R.R.: Decision support systems. In: Kent, A. (ed.) Encyclopedia of Library and Information Science. Marcel Dekker, New York (1999)Google Scholar
  9. 9.
    Eckerson, W.W.: Implementing BI in the cloud. The Data Warehousing Institute, 23 June 2009. http://tdwi.org/blogs/wayne-eckerson/2009/06/implementing-bi-in-the-cloud.aspx
  10. 10.
    Eckerson, W.W.: Series on cloud computing for business intelligence professionals. BeyeNetwork: Global Coverage of the Business Intelligence Ecosystem. Blog: Wayne Eckerson (2011). http://www.b-eye-network.com/blogs/eckerson/archives/cloud_computing
  11. 11.
    Ereth, J., Dahl, D.: Business intelligence in the cloud: fundamentals for a service-based evaluation concept. Workshop Business Intelligence WSBI 13 (2013). http://ceur-ws.org/Vol1049/paper1.pdf
  12. 12.
    Gartner Symposium 2006: Business Intelligence (2006)Google Scholar
  13. 13.
  14. 14.
  15. 15.
    Gartner: Magic quadrant for business intelligence and analytics platforms, February 2014. http://www.gartner.com/document/2668318?toggle=1
  16. 16.
    Gentile, B.: The BI revolution: cloud BI progress and pitfalls. The Data Warehousing Institute, March 2012. http://tdwi.org/articles/2012/03/13/cloud-bi-progress-and-pitfalls.aspx
  17. 17.
    Kimball, R.: The Data Warehouse Toolkit. Wiley, New York, ISBN 0-471-15337-0 (1996)Google Scholar
  18. 18.
  19. 19.
    Lachlan, J.: Business Intelligence in Cloud (Part 1 & 2). Yellowfin News & Blog, 6 October 2010Google Scholar
  20. 20.
    Larson, B.: Delivering Business Intelligence with Microsoft SQL Server. McGraw-Hill Osborne, New York (2008)Google Scholar
  21. 21.
    Luhn, H.P.: A business intelligence system. IBM J. Res. Dev. 2(4), 314–319 (1958)CrossRefGoogle Scholar
  22. 22.
    McDonald, K., Wilmsmeier, A., Dixon, D.C., Inmon, W.H.: Mastering the SAP Business Information Warehouse, 2nd edn. Wiley, New York (2006)Google Scholar
  23. 23.
    McKendrick, J.: BI, delivered from the cloud. EbizQ net: the insider’s guide to next-generation BPM – BI in action, 31 December 2007 http://www.ebizq.net/blogs/niinaction/2007/12/bi_delivered_from_the_cloud.php
  24. 24.
    Mell, P., Grance, T.: Draft NIST working definition of cloud computing. National Institute of Standards and Technology, Information Technology Laboratory, Version 15, http://www.nist.gov/itl/cloud/upload/cloud-def-v15.pdf (2009)
  25. 25.
    Xu, M., Gao, D., Deng, C., Luo, Z., Sun, S.: Cloud computing boosts business intelligence of telecommunication industry. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) Cloud Computing. LNCS, vol. 5931, pp. 224–231. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  26. 26.
    Mircea, M., Ghilic-Micu, B., Stoica, M.: Combining business intelligence with cloud computing to deliver agility in actual economy. Econ. Comput. Econ. Cybern. Stud. Res. 45(1), 1 (2011)Google Scholar
  27. 27.
    Oracle: Cloud ready business intelligence with oracle business intelligence. An Oracle white paper, October 2010Google Scholar
  28. 28.
    Parkhill, D.: The Challenge of the Computer Utility. Addison-Wesley, Reading (1966)Google Scholar
  29. 29.
    Pondel, M.: Business intelligence as a service in a cloud environment. Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, pp. 1269-1271 (2013)Google Scholar
  30. 30.
    Power, D.J.: What is a DSS? On-line Exec. J. Data-Intensive Decis. Support 1(3) (1997)Google Scholar
  31. 31.
    Power, D.J.: A brief history of decision support systems, Version 4.0 (2007). http://DSSResources.com/history/dsshistory.html
  32. 32.
    Tata Consultancy Services: Business intelligence on the cloud: overview and use cases. White paper, Tata Consultancy Services Ltd (2012). http://www.tcs.com
  33. 33.
    Sriram, I, Khajeh-Hosseini, A.: Research agenda in cloud technologies. 1st ACM Symposium on Cloud Computing, SOCC 2010, arXiv:1001.3259 (2010)Google Scholar
  34. 34.
    Shollo, A., Kautz, K.: Towards an understanding of business intelligence. ACIS 2010 Proceedings, paper 86 (2010)Google Scholar
  35. 35.
    Vaquero, L., Rodero-Merino, L., Caceres, J., Lindner, M.: A break in the clouds: towards a cloud definition. ACM SIGCOMM Computer Communication Review (2009)Google Scholar
  36. 36.
    Vassiliades, P.: data warehouse modelling and quality issues. Ph.D. thesis, National Technical University of Athens, Greece (2000)Google Scholar
  37. 37.
    Watson, H.J.: BI and data warehousing in universities. Bus. Intell. J. 11(3), 4–6 (2006)Google Scholar
  38. 38.
    Wixom, B.H., Ariyachandra, T.: State of business intelligence in academia 2010. Presented at BI congress II, p. 1 (2011)Google Scholar
  39. 39.
    Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. (Springer) 1, 7–18 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Cyprus Telecommunication Authority, IT ProfessionalNicosiaCyprus

Personalised recommendations