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Publication Details Author(s): Carlos Rodriguez, Florian Daniel, Fabio Casati, Cinzia Cappiello Title: Toward Uncertain Business Intelligence: the Case of Key Indicators Reference: Internet Computing, Volume 14, Number 4, July/August 2010, IEEE Press, Pages 32-40. Abstract: Decision support systems and, in particular, business intelligence techniques are widely used by enterprises for monitoring and analyzing operations to understand in which aspects the business is not performing well and even how to improve it. These tools provide valuable results in the context of single departments and business processes, while they are often not suitable in scenarios driven by web-enabled intercompany cooperation and IT outsourcing. In such contexts, the adoption of service-oriented company IT architectures and the use of external web services may prevent the comprehensive view over a distributed business process and raise doubts about the reliability of computed outputs. We analyze how these scenarios impact on information quality in business intelligence applications and lead to non-trivial research challenges. We propose the notions of uncertain events and uncertain key indicators, a model to express and store uncertainty, and a tool to compute with and visualize uncertainty. Download paper