Towards quality-oriented data warehouse usage and evolution

Vassiliadis, P; Bouzeghoub, M; Quix, C

dc.contributor.author	Vassiliadis, P	en
dc.contributor.author	Bouzeghoub, M	en
dc.contributor.author	Quix, C	en
dc.date.accessioned	2014-03-01T01:15:57Z
dc.date.available	2014-03-01T01:15:57Z
dc.date.issued	2000	en
dc.identifier.issn	0306-4379	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/13842
dc.subject	data warehousing	en
dc.subject	repositories	en
dc.subject	evolution	en
dc.subject	data quality	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.other	SYSTEMS	en
dc.title	Towards quality-oriented data warehouse usage and evolution	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0306-4379(00)00011-9	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0306-4379(00)00011-9	en
heal.language	English	en
heal.publicationDate	2000	en
heal.abstract	As a decision support information system, a data warehouse must provide high level quality of data and services. In the DWQ project (Foundations of Data Warehouse Quality), we have proposed how semantically rich meta-information of a data warehouse can be stored in a metadata repository. This static representation of the various perspectives of data warehouse components and their linkage to quality factors is complemented by an operational methodology on how to use these quality factors and achieve the quality goals of the users. This approach is an extension of the Goal-Question-Metric (GQM) approach, based on the idea that a quality goal is operationally defined over a concrete set of questions, i.e., algorithmic steps. The proposed approach covers the full lifecycle of the data warehouse, allows capturing the interrelationships between different quality factors and helps the interested user to organize them in order to fulfill specific quality goals. Furthermore, we prove how the quality management of the data warehouse can guide the process of data warehouse evolution, by tracking the interrelationships between the components of the data warehouse. Finally, we present a case study, as a proof of concept for the proposed methodology. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	INFORMATION SYSTEMS	en
dc.identifier.doi	10.1016/S0306-4379(00)00011-9	en
dc.identifier.isi	ISI:000087383600003	en
dc.identifier.volume	25	en
dc.identifier.issue	2	en
dc.identifier.spage	89	en
dc.identifier.epage	115	en