Subject: Information System Science
Title: Data governance best practices: Developing practical recommendations for case organization
Abstract:
This master’s thesis focuses on best practices in data governance and aims to guide a certain international organization in operating according to these practices. Data governance is always organization-specific, which is why universally applicable, concrete instructions for practical implementation are limited, even though the topic has been extensively covered in scientific literature.
The objective of the research is to determine what kind of concrete measures the organization in question could take to better respond to the data governance best practices identified in the literature. This will be examined by evaluating the organization’s current level of data governance maturity and comparing it to the frameworks presented in the literature. In this way, key areas for development are identified, and targeted recommendations can be provided.
The empirical data consists of results obtained through a questionnaire developed by Marchildon (2019) and validated by experts. The questionnaire was supplemented with interviews conducted simultaneously with the questionnaire completion. In addition, the researcher has observed the organization’s activities for three months while participating in a process digitalization project. This has supported a deeper understanding of the data and the reliability of the results.
Best practices in data governance form a broad entity, in which multiple areas must be considered and applied on an organization-specific basis. Several models have been developed for assessing maturity levels, but based on this study, the model by Marchildon (2019) proved to be the most suitable, as it covers all the areas identified in the literature and enables their subjective assessment. The study found that the organization lacks a unified approach to data governance. To address this, the establishment of a dedicated data governance role and the creation of a unified data governance framework are particularly recommended.
The approach applied in the study proved to be functional and helped to identify clear areas for development. Although the study provides a replicable model for other organizations, further case studies are needed in the future that present successful data governance development projects in a practical manner.
Key words: Data governance, master data, best practices, compliance, maturity, framework.