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

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Author(s): Te-Wei Wang (University of Illinois at Springfield, USA), Yuriy Verbitskiy (University of South Australia, Australia)and William Yeoh (Deakin University, Australia)
Copyright: 2019
Pages: 14
Source title: Applying Business Intelligence Initiatives in Healthcare and Organizational Settings
Source Author(s)/Editor(s): Shah J. Miah (The University of Newcastle, Australia)and William Yeoh (Deakin University, Australia)
DOI: 10.4018/978-1-5225-5718-0.ch016

Keywords: Business & Management / Business and Organizational Research / Business Intelligence / Business Science Reference

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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 the analysis by proposing a BI data quality framework.

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

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