Managing data quality in business intelligence applications

Florian Daniel, Fabio Casati, Themis Palpanas, Oleksiy Chayka

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Business Intelligence (BI) solutions conunonly aim at assisting decision-making processes by providing a comprehensive view- over a company's core business data and suitable abstractions thereof. Decision-making based on BI solutions therefore builds on the assumption that providing users with targeted, problem- specific fact data enables them to make informed and. hence, better decisions in then everyday businesses. In order to really provide users with all the necessary details to make informed decisions, we however believe that - in addition to conventional reports - it is essential to also provide users with information about the quality, i.e. with quality metadata, regarding the data from which reports are generated. Identifying a lack of support for quality metadata management in conventional BI solutions, in tins paper we propose the idea of quality-aware reports and a possible architecture for quality-aware BI, able to involve the users themselves into the quality metadata management process, by explicitly solicitmg and exploiting user feedback.

Original languageEnglish
Pages (from-to)133-144
Number of pages12
JournalCTIT workshop proceedings series
VolumeWP 08
Issue number02
Publication statusPublished - 2008
Externally publishedYes

Fingerprint

Competitive intelligence
data quality
Metadata
metadata
quality management
Decision making
Industry
decision making
Tin
abstraction
decision-making process
tin
Feedback
lack

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development

Cite this

Daniel, F., Casati, F., Palpanas, T., & Chayka, O. (2008). Managing data quality in business intelligence applications. CTIT workshop proceedings series, WP 08(02), 133-144.

Managing data quality in business intelligence applications. / Daniel, Florian; Casati, Fabio; Palpanas, Themis; Chayka, Oleksiy.

In: CTIT workshop proceedings series, Vol. WP 08, No. 02, 2008, p. 133-144.

Research output: Contribution to journalArticle

Daniel, F, Casati, F, Palpanas, T & Chayka, O 2008, 'Managing data quality in business intelligence applications', CTIT workshop proceedings series, vol. WP 08, no. 02, pp. 133-144.
Daniel, Florian ; Casati, Fabio ; Palpanas, Themis ; Chayka, Oleksiy. / Managing data quality in business intelligence applications. In: CTIT workshop proceedings series. 2008 ; Vol. WP 08, No. 02. pp. 133-144.
@article{67e6c4393fad4c4b916fc36c0558d8be,
title = "Managing data quality in business intelligence applications",
abstract = "Business Intelligence (BI) solutions conunonly aim at assisting decision-making processes by providing a comprehensive view- over a company's core business data and suitable abstractions thereof. Decision-making based on BI solutions therefore builds on the assumption that providing users with targeted, problem- specific fact data enables them to make informed and. hence, better decisions in then everyday businesses. In order to really provide users with all the necessary details to make informed decisions, we however believe that - in addition to conventional reports - it is essential to also provide users with information about the quality, i.e. with quality metadata, regarding the data from which reports are generated. Identifying a lack of support for quality metadata management in conventional BI solutions, in tins paper we propose the idea of quality-aware reports and a possible architecture for quality-aware BI, able to involve the users themselves into the quality metadata management process, by explicitly solicitmg and exploiting user feedback.",
author = "Florian Daniel and Fabio Casati and Themis Palpanas and Oleksiy Chayka",
year = "2008",
language = "English",
volume = "WP 08",
pages = "133--144",
journal = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives",
issn = "1682-1750",
number = "02",

}

TY - JOUR

T1 - Managing data quality in business intelligence applications

AU - Daniel, Florian

AU - Casati, Fabio

AU - Palpanas, Themis

AU - Chayka, Oleksiy

PY - 2008

Y1 - 2008

N2 - Business Intelligence (BI) solutions conunonly aim at assisting decision-making processes by providing a comprehensive view- over a company's core business data and suitable abstractions thereof. Decision-making based on BI solutions therefore builds on the assumption that providing users with targeted, problem- specific fact data enables them to make informed and. hence, better decisions in then everyday businesses. In order to really provide users with all the necessary details to make informed decisions, we however believe that - in addition to conventional reports - it is essential to also provide users with information about the quality, i.e. with quality metadata, regarding the data from which reports are generated. Identifying a lack of support for quality metadata management in conventional BI solutions, in tins paper we propose the idea of quality-aware reports and a possible architecture for quality-aware BI, able to involve the users themselves into the quality metadata management process, by explicitly solicitmg and exploiting user feedback.

AB - Business Intelligence (BI) solutions conunonly aim at assisting decision-making processes by providing a comprehensive view- over a company's core business data and suitable abstractions thereof. Decision-making based on BI solutions therefore builds on the assumption that providing users with targeted, problem- specific fact data enables them to make informed and. hence, better decisions in then everyday businesses. In order to really provide users with all the necessary details to make informed decisions, we however believe that - in addition to conventional reports - it is essential to also provide users with information about the quality, i.e. with quality metadata, regarding the data from which reports are generated. Identifying a lack of support for quality metadata management in conventional BI solutions, in tins paper we propose the idea of quality-aware reports and a possible architecture for quality-aware BI, able to involve the users themselves into the quality metadata management process, by explicitly solicitmg and exploiting user feedback.

UR - http://www.scopus.com/inward/record.url?scp=84882970045&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84882970045&partnerID=8YFLogxK

M3 - Article

VL - WP 08

SP - 133

EP - 144

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SN - 1682-1750

IS - 02

ER -