Abstract
IT-based decision support is in the heart of business intelligence. It should be based on a successful integration of data analysis techniques and certain system engineering (like system dynamics) concepts. This contribution introduces in the large realm of IT-based decision support and its meaning for a modern business strategy. Central is the relationship to Business Intelligence with its own characteristics and requirements. The relevant data mining techniques are summarized and characterized by its special role within traditional business intelligence approaches.
As an holistic approach this chapter tends to combine a classical data-centric approach with a modern system-engineering concept (“system of systems”-thinking). As a result, this new approach leads to an advanced concept of Adaptive Business Intelligence. It will be characterized and described by several successful examples.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Albrecht, J.: The future role of photovoltaics: a learning curve versus portfolio perspective. Energy Policy 35, 2296–2304 (2007)
Anderson-Lehman, R., Watson, H., Wixom, B., Hoffer, J.: Continental airlines flies high with real-time business intelligence. MIS Q. Exec. 3(4), 163–176 (2004)
Arnott, D., Pervan, G.: Eight key issues for the decision support systems discipline. Decis. Support Syst. 44(3), 657–672 (2008). doi:10.1016/j.dss.2007.09.003
Arnth-Jensen, N.: Applied Data Mining for Business Intelligence. Kongens Lyngby (2006)
Awerbuch, S., Jansen, J., Beurskens, L.: Portfolio-Based Electricity Generation Planning: The Role of Renewables in Enhancing Energy Diversity and Security in Tunisia. United Nations Environment Programme (2005)
Azevedo, A., Santos, M.: Business intelligence: state of the art, trends, and open issues. In: Proceedings of the First International Conference on Knowledge Management and Information Sharing, KMIS 2009, pp. 296–300 (2009)
Berner, E.: Clinical Decision Support Systems: State of the Art. AHRQ Publication No. 09-0069-EF. Agency for Healthcare Research and Quality, Rockville (2006)
Berson, A., Smith, S., Thearling, K.: Building Data Mining Applications for CRM. McGraw-Hill, New York (1999)
Bruce, P.: Decision-making in airline operations: the importance of identifying decision considerations. Int. J. Aviation Manag. 1(1,2), 89–104 (2011)
Clark, T., Jones, M., Armstrong, C.: The dynamic structure of management support systems: theory development, research, focus, and direction. Manag. Inf. Syst. Q. 31(3), 579–615 (2007)
Cooper, K., Mullen, T.: Swords and plowshares: the rework cycles of defense and commercial software development projects. Am. Program. 6(5), 41–51 (1993)
Drucker, H., Wu, D., Vapnik, V.: Support vector machines for spam categorization. IEEE Trans. Neural Netw. 10(5), 1048–1054 (1999)
Grabmeier, J., Rudolph, A.: Techniques of cluster algorithms in data mining. Data Min. Knowl. Discov. 6, 303–360 (2002)
Hannula, M., Pirttimäki, V.: Business intelligence empirical study on the top 50 finish companies. J. Am. Acad. Bus. 2(2), 593–599 (2003)
Hoffman, T.: 9 hottest skills for ’09. Comput. World 1(1), 26–27 (2009)
Kemper, H.G., Mehanna, W., Unger, C.: Business Intelligence – Grundlagen und praktische Anwendungen, 2. Aufl. Vieweg, Wiesbaden (2006)
Khan, R., Quadri, S.: Business intelligence: an integrated approach. Bus. Intell. J. 5(1), 64–70 (2012)
Kudyba, S., Hoptroff, R.: Data Mining and Business Intelligence: A Guide to Productivity. Idea Group Publishing, Hershey (2001)
Lunh, H.: A business intelligence system. IBM J. Res. Dev. 2(4), 314–319 (1958). doi:10.1147/rd.24.0314
Lyneis, J., Cooper, K., Els, S.: Strategic management of complex projects: a case study using system dynamics. Syst. Dyn. Rev. 17, 237–260 (2001)
Maier, M.: Architecting principles for system of systems. Syst. Eng. 1(4), 267–284 (1998)
Markowitz, H.: Portfolio selection. J. Finance 7(1), 77–91 (1952)
Markowitz, H.: Portfolio Selection: Efficient Diversification of Investments. Wiley, New York (1959)
Michalewicz, Z., Schmidt, M., Michalewicz, M., Chiriac, C.: Adaptive Business Intelligence. Springer, Berlin (2007)
Moss, L., Shaku, A.: Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Pearson Education, Upper Saddle River (2003)
Negash, S.: Business intelligence. Commun. Assoc. Inf. Syst. 13(1), 177–195 (2004)
Nemati, H., Steiger, D., Iyer, L., Herschel, R.: Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decis. Support Syst. 33(1), 143–161 (2002). doi:10.1016/S0167-9236(01)00141-5
Raisinghani, M.: Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks. Idea Group Publishing, Hershey (2004)
Richardson, J., Schlegel, K., Hostmann, B.: Magic quadrant for business intelligence platforms. Core research note: G00163529, Gartner (2009)
Richardson, J., Schlegel, K., Hostmann, B., McMurchy, N.: Magic quadrant for business intelligence platforms. Core research note: G00154227, Gartner (2008)
Shim, J., Warkentin, M., Courtney, J., Power, D., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decis. Support Syst. 32(1), 111–126 (2002). doi:10.1016/S0167-9236(01)00139-7
Sterman, J.: System dynamics modeling for project management (1992). http://web.mit.edu/jsterman/www/SDG/project.pdf, visited 11.08.2011
Sterman, J.: Business Dynamics – Systems Thinking and Modeling for a Complex World. McGraw-Hill, New York (2000)
Thierauf, R.: Effective Business Intelligence Systems. Quorum Books, West Port (2001)
Thomsen, E.: BI’s promised land. Intell. Enterprise 6(4), 21–25 (2003)
Turban, E., Sharda, R., Aroson, J., King, D.: Business Intelligence: A Managerial Approach. Pearson, Upper Sadle River (2008)
www.airliners.de (2012). Continental und United unter einem Dach. http://www.airliners.de/management/strategie/continental-und-united-unter-einem-dach/22288, visited September 2012
www.pcpcc.net (2010). Clinical decision support in the medical home – an overview. http://www.pcpcc.net/files/clinical-decision.pdf, visited September 2012
Xing, Z., Pei, J., Yu, P.S.: Early prediction on time series: a nearest neighbor approach. In: Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 1297–1302 (2009)
Zhu, L., Fan, Y.: Optimization of china’s generating portfolio and policy implications based on portfolio theory. Energy 35, 1391–1402 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
Görgülü, ZK., Pickl, S. (2013). Adaptive Business Intelligence: The Integration of Data Mining and Systems Engineering into an Advanced Decision Support as an Integral Part of the Business Strategy. In: Rausch, P., Sheta, A., Ayesh, A. (eds) Business Intelligence and Performance Management. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-4866-1_4
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4866-1_4
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4865-4
Online ISBN: 978-1-4471-4866-1
eBook Packages: Computer ScienceComputer Science (R0)