Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework

Te-Wei Wang, Yuriy Verbitskiy and William Yeoh
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Te-Wei Wang: University of Illinois at Springfield, Springfield, IL, USA
Yuriy Verbitskiy: University of South Australia, Adelaide, Australia
William Yeoh: University of South Australia, Mawson Lakes, Australia and Deakin University, Burwood, Australia

International Journal of Business Intelligence Research (IJBIR), 2016, vol. 7, issue 2, 20-31

Abstract: Modern business intelligence systems depend highly on high quality data. The core of data quality management is to identify all possible sources of data quality problems. To achieve this goal, an extensive metadata infrastructure is the most promising solution. Through theoretical metadata model investigation, the authors identified a set of data quality dimensions by carefully examining the data quality management principles and applied those principles to current BI environment. They summarize their analysis by proposing a BI data quality framework.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jbir00:v:7:y:2016:i:2:p:20-31

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