Power BI Solution for Monitoring Data Quality in Logistics

This thesis focuses on the design and implementation of a reporting solution for monitoring data quality in the field of logistics using the Power BI tool. The aim of the thesis is to develop a solution that meets the requirements of the commissioning team while delivering real business value in terms of improved data transparency and time savings in analytical processes. The proposed solution enables users to effectively monitor and analyze rejected EDI messages, identify problematic areas, and record comments directly within the Power BI environment. The solution also includes a notification system that allows users to respond promptly to significant increases in the number of rejected messages, thereby supporting faster resolution of emerging issues. The thesis is based on the Kimball Dimensional Lifecycle methodology, which was used to design the dimensional data model. Furthermore, the work focuses on the implementation of the solution, including the creation of metrics using the DAX language, data modelling, data visualization, and the development of additional functionalities such as automated notifications and a commenting application. The resulting solution contributes to improved data quality management, increased efficiency of analytical processes, and enhanced decision-making in logistics operations.