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Toward Uncertain Business Intelligence: The Case of Key Indicators

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4 Author(s)
Rodriguez, C. ; Univ. of Trento, Trento, Italy ; Daniel, F. ; Casati, F. ; Cappiello, C.

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.

Published in:

Internet Computing, IEEE  (Volume:14 ,  Issue: 4 )