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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Te-Wei Wang & Yuriy Verbitskiy & William Yeoh, 2016. "Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 7(2), pages 20-31, July.
    • Handle: RePEc:igg:jbir00:v:7:y:2016:i:2:p:20-31
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