| Abstract [eng] |
The main goal of this master's thesis is to create a conceptual data governance factor model that will help organizations to achieve advanced informing. The master's thesis addresses the issue relevant to scientists, researchers and organizations related to the implementation of a data governance initiative as an enterprise program, its critical success factors necessary for organizations to achieve advanced informing in the future. The work consists of three main parts: literature analysis, conducted research and its results, conclusions, and recommendations. After analysing the literature, the author conducted a study of the success factors of the critical data governance program and their influence on the advanced informing of the organization and collected 8 sets of qualitative research answers. Later, the research results were transcribed, coded, divided into topics, and processed using Maxqda and SPSS modeler software. To perform data analysis and search for connections between the DG CSF, BA, BI and information challenges of the DG program, the author of the paper used such methods as clustering, co-occurrence model of attribute codes, creation of a map of response sets, search for associations rules, creation of a decision tree, XGBoost tree attribute prediction importance and attributes determining importance. Pearson's correlation matrix was used to clarify the relationships between the causes of DG failure. During the literature review and research, the author identified relationships between the CSFs of the DG program, BA, BI, and demonstrated their direct impact on advanced informing. The author of the paper discovered that it is recommended to have a special team that encourages DG and actively communicates with all participants of the organization. There should be mandatory, additional DG training, employees should be constantly encouraged to learn. They need to have a clear DG strategy that is aligned with the corporate strategy. While data quality may depend on the system but must be integrated into processes, data access and availability must be accountable, with clear data procedures. It is necessary to encourage that the organizational culture is flexible and that everyone has a common understanding of the data requirements. It is necessary to implement the prepared and approved DG policy. In the conclusions and recommendations, the author summarized the data governance factor model and the results of the research. The author believes that the results of the study could provide useful guidelines for companies that intend to systematize and structure data governance, seek to perform correct analysis, see meaningful business insights, and seek advanced informing. |
