{"title":"Data Governance Capabilities; Empirical Validation in Case Studies of Large Organisations","authors":"Jan R. Merkus, Remko W. Helms, Rob J. Kusters","doi":"10.18690/um.fov.6.2023.3","DOIUrl":null,"url":null,"abstract":"The exponential growth of data within organisations necessitates the implementation of effective data management practices, which in turn necessitates the establishment of data governance. The evaluation of the maturity of data governance can be carried out using maturity models. However, the existing data governance maturity models are limited in their consistency in terms of data governance capabilities used and lack empirical validation. To address this gap, this study aims to validate the set of data governance capabilities identified in prior research within large organisations. This study employs a case study research design, using semi-structured interviews with experts in data governance. As a basis for the semi-structured interviews, maturity models are designed as questionnaires to discuss the relevance of each data governance capability. The results of this study provide empirical validation of the set of data governance capabilities and contribute to the advancement of both data governance research and practice by providing a comprehensive, validated set of data governance capabilities for maturity model design to advance data governance within and between organisations.","PeriodicalId":504907,"journal":{"name":"36th Bled eConference – Digital Economy and Society: The Balancing Act for Digital Innovation in Times of Instability: June 25 – 28, 2023, Bled, Slovenia, Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"36th Bled eConference – Digital Economy and Society: The Balancing Act for Digital Innovation in Times of Instability: June 25 – 28, 2023, Bled, Slovenia, Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18690/um.fov.6.2023.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The exponential growth of data within organisations necessitates the implementation of effective data management practices, which in turn necessitates the establishment of data governance. The evaluation of the maturity of data governance can be carried out using maturity models. However, the existing data governance maturity models are limited in their consistency in terms of data governance capabilities used and lack empirical validation. To address this gap, this study aims to validate the set of data governance capabilities identified in prior research within large organisations. This study employs a case study research design, using semi-structured interviews with experts in data governance. As a basis for the semi-structured interviews, maturity models are designed as questionnaires to discuss the relevance of each data governance capability. The results of this study provide empirical validation of the set of data governance capabilities and contribute to the advancement of both data governance research and practice by providing a comprehensive, validated set of data governance capabilities for maturity model design to advance data governance within and between organisations.