Measuring data quality in the internal knowledge base through reporting

The main objective of this thesis is to report the status of data quality in the knowledge base. This is a knowledge base that is located in a corporate and stores important information about projects and employees. Secondary objectives were to design and implement a reporting solution, define metrics and develop a scoring system. In order to achieve the stated main objective and secondary objectives, a literature search was conducted to delve into the topic of knowledge management, knowledge bases, data quality and to link these areas to create a comprehensive view of the issue of data quality in knowledge bases. Before defining the data quality and reporting requirements, the knowledge base environment was described to facilitate understanding of the needs. Then, the actual requirements definition, scoring system and metrics description were performed. Subsequently, the data warehouse architecture, ETL pumps and interfacing with Power BI were described. Within this architecture, the source database was also described, as well as the individual tables of the data warehouse. After that the creation of dashboards in Power BI was described. Finally, the evaluation of both the reporting solution itself and the results from it, i.e. the assessment of the data quality in the knowledge base, was performed. Thus, the contribution of the whole work was the created reporting solution for monitoring data quality in the enterprise knowledge base system. This solution is still used for monitoring.