This Article 
 Bibliographic References 
 Add to: 
Toward Uncertain Business Intelligence: The Case of Key Indicators
July/August 2010 (vol. 14 no. 4)
pp. 32-40
Carlos Rodriguez, University of Trento, Italy
Florian Daniel, University of Trento, Italy
Fabio Casati, University of Trento, Italy
Cinzia Cappiello, Politecnico di Milano, Italy
Enterprises widely use decision support systems and, in particular, business intelligence techniques for monitoring and analyzing operations to understand areas in which the business isn't performing well. These tools often aren't suitable in scenarios involving Web-enabled, intercompany cooperation and IT outsourcing, however. The authors analyze how these scenarios impact information quality in business intelligence applications and lead to nontrivial research challenges. They describe the idea of uncertain events and key indicators and present a model to express and store uncertainty and a tool to compute and visualize uncertain key indicators.

1. B.H. Wixom and H.J. Watson, "An Empirical Investigation of the Factors Affecting Data Warehousing Success," MIS Q., vol. 25, no. 1, 2001, pp. 17–41.
2. R.S. Kaplan and D.P. Norton, The Balanced Scorecard: Translating Strategy into Action, Harvard Business School Press, 1996.
3. F. Daniel et al., "Managing Data Quality in Business Intelligence Applications," Proc. Int'l Workshop on Quality in Databases (QDB 08), Univ. of Twente, 2008, pp. 133–143.
4. M. Weske, Business Process Management: Concepts, Languages, Architectures, Springer, 2007.
5. Y. Wand and R.Y. Wang, "Anchoring Data Quality Dimensions Ontological Foundations," Comm. ACM, vol. 39, no. 11, 1996, pp. 86–95.
6. D. Hollingsworth, The Workflow Reference Model TC00-1003, Workflow Management Coalition, Jan. 1995.
7. C. Rodríguez et al., "Computing Uncertain Key Indicators from Uncertain Data," Proc 14th Int'l Conf. Information Quality (ICIQ 09), Univ. of Potsdam/MIT Press, 2009, pp. 106–120.
8. P. Silveira et al., "On the Design of Compliance Governance Dashboards for Effective Compliance and Audit Management," Proc. 3rd Workshop on Non-Functional Properties and Service Level Agreements Management in Service Oriented Computing (NFPSLAM-SOC 09), Springer, to appear in 2010.
1. D.H. McKnight and N.L. Chervany, The Meanings of Trust, tech. report MISRC Working Paper Series 96-04, Management Information Systems Research Center, Univ. of Minnesota, 1996.
2. A. J⊘sang, R. Ismail, and C. Boyd, "A Survey of Trust and Reputation Systems for Online Service Provision," Decision Support Systems, vol. 43, no. 2, 2007, pp. 618–644.
3. D. Gambetta, Trust: Making and Breaking Cooperative Relations, Basil Blackwell, 1988.
4. M. Fan, Y. Tan, and A.B. Whinston, "Evaluation and Design of Online Cooperative Feedback Mechanisms for Reputation Management," IEEE Trans. Data and Knowledge Eng., vol. 17, no. 2, 2005, pp. 244–254.
5. G. Zacharia and P. Maes, "Collaborative Reputation Mechanisms in Electronic Marketplaces," Proc. 32nd Hawaii Int'l Conf. System Sciences, IEEE CS Press, 1999, p.8026.
6. P. Resnick et al., "Reputation Systems," Comm. ACM, vol. 43, no. 12, 2000, pp. 45–48.
7. C. Ziegler and M. Skubacz, "Towards Automated Reputation and Brand Monitoring on the Web," Proc. 2006 IEEE/WIC/ACM Int'l Conf. Web Intelligence, IEEE CS Press, 2006, pp. 1066–1072.
1. T. Green and V. Tannen, "Models for Incomplete and Probabilistic Information," IEEE Data Eng. Bulletin, vol. 29, no. 1, 2006.
2. R. Cheng, D. Kalashnikov, and S. Prabhakar, "Querying Imprecise Data in Moving Object Environments, IEEE Trans. Knowledge and Data Eng., vol. 16, no. 9, 2004, pp. 17–24.
3. C. Re and D. Suciu, "Managing Probabilistic Data with MystiQ: The Can-Do, the Could-Do, and the Can't-Do," LNCS 5291, Springer-Verlag/Heidelberg, 2008, pp. 5–18.
4. O. Benjelloun et al., "An Introduction to ULDBs and the Trio System," IEEE Data Eng. Bulletin, vol. 29, no. 1, 2006, pp. 953–964.
5. S. Singh et al., "Orion 2.0: Native Support for Uncertain Data," Proc. 2008 Int'l Conf. Management of Data, ACM Press, 2008, pp. 1239–1242.
6. L. Antova et al., "Fast and Simple Relational Processing of Uncertain Data," Proc. 2008 IEEE 24th Int'l Conf. Data Eng. (ICDE 08), IEEE CS Press, 2008, pp. 983–992.

Index Terms:
uncertain business intelligence, uncertain key indicators, cooperative processes, data quality, possible worlds
Carlos Rodriguez, Florian Daniel, Fabio Casati, Cinzia Cappiello, "Toward Uncertain Business Intelligence: The Case of Key Indicators," IEEE Internet Computing, vol. 14, no. 4, pp. 32-40, July-Aug. 2010, doi:10.1109/MIC.2010.59
Usage of this product signifies your acceptance of the Terms of Use.