Data Governance for Businesses: Challenges, Recommendations, and Critical Success Factors

Abstract

Data governance is the set of roles, processes, policies, and tools that ensure data quality throughout its lifecycle and appropriate usage across an organization. Data governance (DG) empowers users to locate, prepare, utilize, and disseminate dependable datasets independently. This study aims to reveal the challenges that businesses may encounter in the data governance process, propose recommendations, and highlight the critical success factors (CSFs) for data governance. The study's method is qualitative research. Interviews were conducted with 12 experienced volunteer participants in data governance. The data collected from the interviews were analyzed using descriptive and content analysis. The study revealed that the main challenges encountered were a lack of understanding of the impact of the data governance process on other business processes, the complexity of the process, and the role of the process manager. The study revealed that these challenges can be mitigated with effective communii cation, a clear demonstration of the contribution of the data governance process to the business, and leadership support. Furthermore, the study identified 20 critical success factors for DG success. These CSFs are classified into four categories: organization, people, data and technology, and regulations. As a result of the study, suggestions for businesses, managers, and individuals regarding data governance are presented.