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

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

Te-Wei Wang, Yuriy Verbitskiy, William Yeoh
Copyright: © 2016 |Volume: 7 |Issue: 2 |Pages: 12
ISSN: 1947-3591|EISSN: 1947-3605|EISBN13: 9781466692237|DOI: 10.4018/IJBIR.2016070102
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MLA

Wang, Te-Wei, et al. "Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework." IJBIR vol.7, no.2 2016: pp.20-31. http://doi.org/10.4018/IJBIR.2016070102

APA

Wang, T., Verbitskiy, Y., & Yeoh, W. (2016). Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework. International Journal of Business Intelligence Research (IJBIR), 7(2), 20-31. http://doi.org/10.4018/IJBIR.2016070102

Chicago

Wang, Te-Wei, Yuriy Verbitskiy, and William Yeoh. "Depicting Data Quality Issues in Business Intelligence Environment through a Metadata Framework," International Journal of Business Intelligence Research (IJBIR) 7, no.2: 20-31. http://doi.org/10.4018/IJBIR.2016070102

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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 their analysis by proposing a BI data quality framework.

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