An Empirical Study for Implementing a Process-Centric Data Quality Control in Data Warehousing
碩士 === 長庚大學 === 資訊管理學研究所 === 96 === Some data have more critical impacts, some do not. Therefore data quality (DQ) should not treat all the errors equally. To effectively understand DQ, process plays a critical role since it is another source for DQ. In this regard a DQ measure has been proposed. Su...
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| Format: | Others |
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2008
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| Online Access: | http://ndltd.ncl.edu.tw/handle/68857838124719699513 |
| Summary: | 碩士 === 長庚大學 === 資訊管理學研究所 === 96 === Some data have more critical impacts, some do not. Therefore data quality (DQ) should not treat all the errors equally. To effectively understand DQ, process plays a critical role since it is another source for DQ. In this regard a DQ measure has been proposed. Such measure realizes DQ by looking at the process of data creation and considering different impacts due to different data fields.
Based on this approach, this study conducts an empirical study regarding the real use of the approach with necessary modification. Several real examples are supplied as well to examine the validity of the approach. Finally, this study implemented CMMI to institutionalize the process of data quality control in data warehousing and provided integrated content of that. Our achievements not only proved that DQ measure can improve a company’s data quality but also provided industry a referable and institutional method.
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