Data quality certification using ISO/IEC 25012: Industrial experiences
The most successful organizations in the world are data-driven businesses. Data is at the core of the business of many organizations as one of the most important assets, since the decisions they make cannot be better than the data on which they are based. Due to this reason, organizations need to be...
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Veröffentlicht in: | The Journal of systems and software 2021-06, Vol.176, p.110938, Article 110938 |
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Sprache: | eng |
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Zusammenfassung: | The most successful organizations in the world are data-driven businesses. Data is at the core of the business of many organizations as one of the most important assets, since the decisions they make cannot be better than the data on which they are based. Due to this reason, organizations need to be able to trust their data. One important activity that helps to achieve data reliability is the evaluation and certification of the quality level of organizational data repositories. This paper describes the results of the application of a data quality evaluation and certification process to the repositories of three European organizations belonging to different sectors. We present findings from the point of view of both the data quality evaluation team and the organizations that underwent the evaluation process. In this respect, several benefits have been explicitly recognized by the involved organizations after achieving the data quality certification for their repositories (e.g., long-term organizational sustainability better internal knowledge of data, and a more efficient management of data quality). As a result of this experience, we have also identified a set of best practices aimed to enhance the data quality evaluation process.
•Evaluation and certification contribute to data reliability and trust.•ISO/IEC 25012, 25024 and 25040 are a very good base for a data quality assessment framework.•Data quality evaluation allows organizations to acquire a deeper knowledge of their business processes.•Risks related to data quality could be mitigated by a data quality evaluation process. |
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ISSN: | 0164-1212 1873-1228 |
DOI: | 10.1016/j.jss.2021.110938 |