Abstract
Enterprise data—the data that is created, used and shared by a corporation in conducting business—is a critical business resource that must be analyzed, architected and managed with data quality as a guiding principle. This paper presents results, practical insights, and lessons learned from a large scale study conducted in the telecommunications industry that synthesizes data quality issues into an architectural and management approach. We describe the real life case study and show how requirements for data quality were collected, how the data quality metrics were defined, what guidelines were established for intersystem data flows, what COTS (commercial off-the-shelf) technologies were used, and what results were obtained through a prototype effort. As a result of experience gained and lessons learned, we propose a comprehensive data quality approach that combines data quality and data architectures into a single framework with a series of steps, procedures, checklists, and tools. Our approach takes into account the technology, process, and people issues and extends the extant literature on data quality.
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Umar, A., Karabatis, G., Ness, L. et al. Enterprise Data Quality: A Pragmatic Approach. Information Systems Frontiers 1, 279–301 (1999). https://doi.org/10.1023/A:1010006529488
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DOI: https://doi.org/10.1023/A:1010006529488