NDLI: Taxonomy of data quality problems in multidimensional Data Warehouse models

Content Provider	IEEE Xplore Digital Library
Author	Gongora de Almeida, W. de Sousa, R.T. de Deus, F.E. Amvame Nze, G.D. Lopes de Mendonca, F.L.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Univ. of Brasilia, Brasilia, Brazil (Gongora de Almeida, W.; de Sousa, R.T.; de Deus, F.E.; Amvame Nze, G.D.; Lopes de Mendonca, F.L.)
Abstract	The impact of poor data quality on the process of decision making, organizational trust and customer satisfaction is well known. In today's organizations, Data Warehousing (DW) have offered support to business management and become part of natural and logical evolution for any decision support systems. In this scenario, DW solutions deployments have failed due to poor data quality implementations. Although some research has been devoted to investigating these problems, none has performed complete and thoroughly focused on examining quality issues manifests in its core component, i.e., the DW repository. This article presents a taxonomy for data quality issues, in the context of multidimensional data models, characteristic of DW. Finally, this work demonstrates that the proposed Taxonomy provides a more appropriate coverage to the problems of data quality and proposes its use in future works for quality measurements.
Starting Page	1
Ending Page	7
File Size	183187
Page Count	7
File Format	PDF
ISBN	9789899843400
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-19
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	AISTI
Subject Keyword	Dirty data Accuracy Taxonomy Organizations Data warehouses Data Warehouse Data models Data quality Proposals
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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