Toward uncertain business intelligence: The case of key indicators

Carlos Rodríguez, Florian Daniel, Fabio Casati, Cinzia Cappiello

Research output: Contribution to journal › Article

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.

Original language	English
Article number	5445071
Pages (from-to)	32-40
Number of pages	9
Journal	IEEE Internet Computing
Volume	14
Issue number	4
DOIs	https://doi.org/10.1109/MIC.2010.59
Publication status	Published - Jul 2010
Externally published	Yes

Fingerprint

Keywords

cooperative processes
data quality
possible worlds
uncertain business intelligence
uncertain key indicators

ASJC Scopus subject areas

Computer Networks and Communications

Cite this

Rodríguez, C., Daniel, F., Casati, F., & Cappiello, C. (2010). Toward uncertain business intelligence: The case of key indicators. IEEE Internet Computing, 14(4), 32-40. [5445071]. https://doi.org/10.1109/MIC.2010.59

@article{476ec20674fb4871a7bd3e697216db79,

title = "Toward uncertain business intelligence: The case of key indicators",

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.",

keywords = "cooperative processes, data quality, possible worlds, uncertain business intelligence, uncertain key indicators",

author = "Carlos Rodr{\'i}guez and Florian Daniel and Fabio Casati and Cinzia Cappiello",

year = "2010",

month = "7",

doi = "10.1109/MIC.2010.59",

language = "English",

volume = "14",

pages = "32--40",

journal = "IEEE Internet Computing",

issn = "1089-7801",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

TY - JOUR

T1 - Toward uncertain business intelligence

T2 - The case of key indicators

AU - Rodríguez, Carlos

AU - Daniel, Florian

AU - Casati, Fabio

AU - Cappiello, Cinzia

PY - 2010/7

Y1 - 2010/7

N2 - 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.

AB - 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.

KW - cooperative processes

KW - data quality

KW - possible worlds

KW - uncertain business intelligence

KW - uncertain key indicators

UR - http://www.scopus.com/inward/record.url?scp=77954342321&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77954342321&partnerID=8YFLogxK

U2 - 10.1109/MIC.2010.59

DO - 10.1109/MIC.2010.59

M3 - Article

AN - SCOPUS:77954342321

VL - 14

SP - 32

EP - 40

JO - IEEE Internet Computing

JF - IEEE Internet Computing

SN - 1089-7801

IS - 4

M1 - 5445071

ER -

Access to Document

10.1109/MIC.2010.59