Component Development and Importance Weight Analysis of Data Governance

Data Governance 구성요소 개발과 중요도 분석

  • Jang, Kyoung-Ae (Seoul National University of Science and Technology) ;
  • Kim, Woo-Je (Seoul National University of Science and Technology)
  • 장경애 (서울과학기술대학교 IT정책전문대학원 산업정보시스템) ;
  • 김우제 (서울과학기술대학교 글로벌융합산업공학과)
  • Received : 2016.05.13
  • Accepted : 2016.06.22
  • Published : 2016.08.31


Data are important in an organization because they are used in making decisions and obtaining insights. Furthermore, given the increasing importance of data in modern society, data governance should be requested to increase an organization's competitive power. However, data governance concepts have caused confusion because of the myriad of guidelines proposed by related institutions and researchers. In this study, we re-established the concept of ambiguous data governance and derived the top-level components by analyzing previous research. This study identified the components of data governance and quantitatively analyzed the relation between these components by using DEMATEL and context analysis techniques that are often used to solve complex problems. Three higher components (data compliance management, data quality management, and data organization management) and 13 lower components are derived as data governance components. Furthermore, importance analysis shows that data quality management, data compliance management, and data organization management are the top components of data governance in order of priority. This study can be used as a basis for presenting standards or establishing concepts of data governance.



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