Optimalizace tabulárního modelu ve vybrané společnosti

This thesis focuses on the optimization of tabular OLAP models in the context of modern business intelligence in retail, with a special emphasis on the healthcare sector. The theoretical part presents the basics of retail, trends in digitalization and the role of semantic layers in data analysis. It also examines different approaches to OLAP and their impact on organizational efficiency. The practical part applies these concepts to the analysis and optimization of a tabular model in a specific organizational environment. Using advanced tools such as Tabular Editor and Power BI, the project successfully reduced the size of the model and accelerated loading, while also reducing annual operating costs. This result was achieved by removing unused objects, restructuring report dependencies and implementing scalable cloud solutions. The conclusions of the thesis indicate significant potential for extending similar optimization procedures to other instances in wider regional operations, which promises even greater savings and improved operational efficiency.