Abstract
Traditional Business Intelligence applications have focused on providing a one shop stop to integrate the enterprise information. The resulting applications are only capable of providing descriptive information viz: standard and ad-hoc reporting and drill-down capability. As part of an effort to provide prescriptive and predictive capability, we demonstrate a new architecture, methodology and implementation. Based on Cognos Business Intelligence platform and ILOG optimization engine, we showcase a truly predictive application that enables an optimal decision making in real-time analytical scenario.
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 subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Nocedal, J., Wright, S.: Numerical Optimization, 2nd edn. Springer, New York (2006) ISBN 978-0-387-30303
Lu, Y.D., Sharma, M., Squillante, M.: Stochastic Analytics and Optimization for Workforce Evolution, Technical Report, IBM Research (2006)
Kumar, T., Parija, G., Haifeng, X., Keller, D.: Strategic Planning of Preparedness Budgets for Wildland Fire Management. IBM Journal of Research and Development 51(3/4) (May/July 2007)
Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. John Wiley & Sons, Inc., Hoboken (1988)
IBM ILOG Optimization, http://www-01.ibm.com/software/websphere/products/optimization/
Cognos Business Intelligence and Financial Performance Management, http://www-01.ibm.com/software/data/cognos/
Star Schema, http://publib.boulder.ibm.com/infocenter/rbhelp/v6r3/index.jsp?topic=/com.ibm.redbrick.doc6.3/wag/wag32.htm
Open Database Connectivity Overview (ODBC), http://support.microsoft.com/kb/110093
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiang, C., Jensen, D.L., Cao, H., Kumar, T. (2010). Building Business Intelligence Applications Having Prescriptive and Predictive Capabilities. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds) Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14246-8_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-14246-8_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14245-1
Online ISBN: 978-3-642-14246-8
eBook Packages: Computer ScienceComputer Science (R0)