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. © 2006 IEEE.

Toward Uncertain Business Intelligence: The Case of Key Indicators

Daniel, Florian;Casati, Fabio;
2010-01-01

Abstract

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. © 2006 IEEE.
2010
4
C., Rodríguez; Daniel, Florian; Casati, Fabio; C., Cappiello
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/85189
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 9
  • OpenAlex ND
social impact