Development of data governance components using DEMATEL and content analysis
Abstract Organizations gain insight and derive value from data that drive their direction, and so data governance, which is a method of managing competitive data, is becoming more important. Researchers have recognized the importance of data governance and introduced various solutions, but the stand...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jang, Kyoung-ae [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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| Übergeordnetes Werk: |
Enthalten in: The journal of supercomputing - Springer US, 1987, 77(2020), 4 vom: 28. Aug., Seite 3695-3709 |
|---|---|
| Übergeordnetes Werk: |
volume:77 ; year:2020 ; number:4 ; day:28 ; month:08 ; pages:3695-3709 |
| Links: |
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| DOI / URN: |
10.1007/s11227-020-03405-9 |
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OLC2124309471 |
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Abstract Organizations gain insight and derive value from data that drive their direction, and so data governance, which is a method of managing competitive data, is becoming more important. Researchers have recognized the importance of data governance and introduced various solutions, but the standards and scope of data governance vary, and integrated standards for data governance components need to be established. The purpose of this study is to define the concept of complex data governance and develop a framework for it by defining the data governance components. Using the decision-making trial and evaluation laboratory method and content analysis, we identified the data governance components and analyzed the influence of their relationships. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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Abstract Organizations gain insight and derive value from data that drive their direction, and so data governance, which is a method of managing competitive data, is becoming more important. Researchers have recognized the importance of data governance and introduced various solutions, but the standards and scope of data governance vary, and integrated standards for data governance components need to be established. The purpose of this study is to define the concept of complex data governance and develop a framework for it by defining the data governance components. Using the decision-making trial and evaluation laboratory method and content analysis, we identified the data governance components and analyzed the influence of their relationships. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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