Research and practice in data quality

Shazia Sadiq*, Xiaofang Zhou, Ke Deng

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

Abstract

According to Gartner, human data-entry errors, and lack of proper corporate data standards result in more than 25 percent of critical data used in large corporations to be flawed. While the issue of data quality is as old as data itself, it is now exposed at a much more strategic level, e.g. through business intelligence (BI) systems, increasing manifold the stakes involved. Corporations routinely operate and make strategic decisions based on remarkably inaccurate or incomplete data. This proves a leading reason for failure of high-profile and high-cost IT projects such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Supply Chain Management (SCM) and others. According to an industry survey [1], the presence of data quality (DQ) problems costs U.S. business more than 600 billion dollars per annum.

Original languageEnglish
Title of host publicationProgress in WWW Research and Development - 10th Asia-Pacific Web Conference, APWeb 2008, Proceedings
Pages41-42
Number of pages2
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event10th Asia Pacific Conference on Web Technology, APWeb 2008 - Shenyang, China
Duration: 26 Apr 200828 Apr 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4976 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Asia Pacific Conference on Web Technology, APWeb 2008
Country/TerritoryChina
CityShenyang
Period26/04/0828/04/08

Fingerprint

Dive into the research topics of 'Research and practice in data quality'. Together they form a unique fingerprint.

Cite this