Abstract
In this chapter, we provide definitions of Business Intelligence (BI) and outline the development of BI over time, particularly carving out current questions of BI. Different scenarios of BI applications are considered and business perspectives and views of BI on the business process are identified. Further, the goals and tasks of BI are discussed from a management and analysis point of view and a method format for BI applications is proposed. This format also gives an outline of the book’s contents. Finally, examples from different domain areas are introduced which are used for demonstration in later chapters of the book.
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References
Amit R, Zott Ch (2012) Strategy in changing markets: new business models—creating values through business model innovation. MIT Sloan Manag Rev 53(3):41–49
Azevedo A, Santos MF (2008) KDD, SEMMA and CRISP-DM: a parallel overview. In: Weghorn H, Abraham AP (eds) IADIS’08: European conference data mining. IADIS Publications, pp 182–185, Pedreira, Portugal
Bassil S, Keller RK, Kropf P (2004) A workflow-oriented system architecture for the management of container transportation. In: Desel J, Pernici B, Weske M (eds) BPM’04: international conference on business process management. Lecture notes in computer science, vol 3080. Springer, Heidelberg, pp 116–131
Chapman PJ, Clinton J, Kerber R, Khabaza T, Reinartz T, Shearer C, Wirth R (2000) CRISP-DM 1.0 Step-by-step data mining guide. http://www.the-modeling-agency.com/crisp-dm.pdf. Accessed 20 December 2014
Davenport TH (1992) Process innovation: engineering work through information technology. Reissued edition. Harvard Business Press, Boston
Davenport TH (2006) Competing on analytics. Harv Bus Rev 84(1):98–107
Derntl M, Mangler J (2004) Web services for blended learning patterns. In: Looi K, Sutinen E, Sampson DG, Aedo I, Uden L, Kähkönen E (eds) ICALT’04: international conference on advanced learning technologies. IEEE, New York, pp 614–618
Dumas M, La Rosa M, Mendling J, Reijers HA (2013) Fundamentals of business process management. Springer, Berlin/Heidelberg
Dunkl R, Rinderle-Ma S, Grossmann W, Fröschl KA (2014) Decision point analysis of time series data in process-aware information systems. In: Nurcan S, Pimenidis E, Pastor O, Vassiliou Y (eds) CaISE Forum: joint proceedings of the CAiSE 2014 Forum and CAiSE 2014 Doctoral Consortium, CEUR workshop proceedings 1164, CEUR-WS.org, pp 33–40
Džeroski S (2007) Towards a general framework for data mining. In: Dzeroski S, Struyf J (eds) KDID’07: knowledge discovery in inductive databases. Lecture notes in computer science, vol 4747. Springer, Heidelberg, pp 259–300
Han J, Kamber M (2011) Data mining: concepts and techniques. Morgan Kaufmann series in data management systems. Morgan Kaufmann, Waltham, MA
Kimball R, Ross M (2010) The Kimball Group Reader: relentlessly practical tools for data warehousing and business intelligence, vol 1. Wiley, New York
Laursen G, Thorlund J (2010) Business analytics for managers: taking business intelligence beyond reporting. Wiley & SAS Business, New Jersey
Luhn HP (1958) A business intelligence system. IBM J Res Dev 2(4):314–319
Ly LT, Indiono C, Mangler J, Rinderle-Ma S (2012) Data transformation and semantic log purging for process mining. In: Ralyté J, Franch F, Brinkkemper S, Wrycza S (eds) CaISE’12: international conference on advanced information systems engineering. Lecture notes in computer science, vol 7328. Springer, Heidelberg, pp 238–253
Mitchell T (1997) Machine learning. McGraw Hill, New York
Moss LT, Atre S (2003) Business intelligence roadmap: the complete project lifecycle for decision-support applications. Addison-Wesley Professional, Boston
Negash S (2004) Business intelligence. Commun Assoc Inf Syst 13(1):177–195
Power DJ (2007) A brief history of decision support systems. DSSResources. COM, http://dssresources.com/history/dsshistory.html. Accessed 20 Dec 2014
Rausch P, Sheta AF, Ayesh A (eds) (2013) Business intelligence and performance management: theory, systems and industrial applications. Springer, Berlin/Heidelberg
Roebuck K (2011) Business intelligence (BI): high-impact strategies—what you need to know: definitions, adoptions, impact, benefits, maturity, vendors. Emereo, ISBN: 9781743046289
Trujillo J, Maté A (2012) Business intelligence 2.0: a general overview. In: Aufaure M-A, Zimanyi E (eds) Business intelligence. Lecture notes in business information processing, vol 96. Springer, Heidelberg, pp 98–116
van der Aalst WMP (2011) Process mining—discovery, conformance and enhancement of business processes. Springer, New York/Berlin
van der Aalst WMP et al (2012) Process mining manifesto. In Daniel F, Barkaoui K, Dustdar S (eds) Business process management workshops. Lecture notes in business information processing, vol 99. Springer, Heidelberg, pp 169–194
Weske M (2012) Business process management: concepts, languages, architectures. Springer, Berlin/Heidelberg
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Grossmann, W., Rinderle-Ma, S. (2015). Introduction. In: Fundamentals of Business Intelligence. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46531-8_1
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DOI: https://doi.org/10.1007/978-3-662-46531-8_1
Publisher Name: Springer, Berlin, Heidelberg
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