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.
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References
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)
Baars, H., Kemper, H.G.: Business intelligence in the cloud? PACIS 2010 Proceedings, Paper 145 (2010). http://aisel.aisnet.org/pacis2010
Birst: Why cloud BI? The 10 substantial benefits of software-as-a-service business intelligence. White paper, Birst Inc. (2010)
Boateng, O., Singh, J., Singh, G.P.: Data warehousing. Bus. Intell. J. 5(2) (2012)
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)
Davenport, T.H.: Business intelligence and organizational decisions. Int. J. Bus. Intell. Res. 1(1), 1–12 (2010)
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)
Druzdzel, M.J., Flynn, R.R.: Decision support systems. In: Kent, A. (ed.) Encyclopedia of Library and Information Science. Marcel Dekker, New York (1999)
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
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
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
Gartner Symposium 2006: Business Intelligence (2006)
Gartner: Cloud computing. http://www.gartner.com/technology/topics/cloud-computing.jsp
Gartner: By 2017, the hybrid cloud will rule, October 2013. https://community.csc.com/community/cio-engage/blog/2013/10/22/gartner-by-2017-the-hybrid-cloud-will-rule
Gartner: Magic quadrant for business intelligence and analytics platforms, February 2014. http://www.gartner.com/document/2668318?toggle=1
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
Kimball, R.: The Data Warehouse Toolkit. Wiley, New York, ISBN 0-471-15337-0 (1996)
Klipfolio: What is cloud business intelligence. http://www.klipfolio.com/resources/articles/what-is-cloud-business-intelligence
Lachlan, J.: Business Intelligence in Cloud (Part 1 & 2). Yellowfin News & Blog, 6 October 2010
Larson, B.: Delivering Business Intelligence with Microsoft SQL Server. McGraw-Hill Osborne, New York (2008)
Luhn, H.P.: A business intelligence system. IBM J. Res. Dev. 2(4), 314–319 (1958)
McDonald, K., Wilmsmeier, A., Dixon, D.C., Inmon, W.H.: Mastering the SAP Business Information Warehouse, 2nd edn. Wiley, New York (2006)
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
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)
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)
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)
Oracle: Cloud ready business intelligence with oracle business intelligence. An Oracle white paper, October 2010
Parkhill, D.: The Challenge of the Computer Utility. Addison-Wesley, Reading (1966)
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)
Power, D.J.: What is a DSS? On-line Exec. J. Data-Intensive Decis. Support 1(3) (1997)
Power, D.J.: A brief history of decision support systems, Version 4.0 (2007). http://DSSResources.com/history/dsshistory.html
Tata Consultancy Services: Business intelligence on the cloud: overview and use cases. White paper, Tata Consultancy Services Ltd (2012). http://www.tcs.com
Sriram, I, Khajeh-Hosseini, A.: Research agenda in cloud technologies. 1st ACM Symposium on Cloud Computing, SOCC 2010, arXiv:1001.3259 (2010)
Shollo, A., Kautz, K.: Towards an understanding of business intelligence. ACIS 2010 Proceedings, paper 86 (2010)
Vaquero, L., Rodero-Merino, L., Caceres, J., Lindner, M.: A break in the clouds: towards a cloud definition. ACM SIGCOMM Computer Communication Review (2009)
Vassiliades, P.: data warehouse modelling and quality issues. Ph.D. thesis, National Technical University of Athens, Greece (2000)
Watson, H.J.: BI and data warehousing in universities. Bus. Intell. J. 11(3), 4–6 (2006)
Wixom, B.H., Ariyachandra, T.: State of business intelligence in academia 2010. Presented at BI congress II, p. 1 (2011)
Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. (Springer) 1, 7–18 (2010)
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Kazeli, H. (2014). Cloud Business Intelligence. In: Abramowicz, W., Kokkinaki, A. (eds) Business Information Systems Workshops. BIS 2014. Lecture Notes in Business Information Processing, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-319-11460-6_26
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DOI: https://doi.org/10.1007/978-3-319-11460-6_26
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