Design and implementation of a BI solution for a local food producer and retailer

This thesis deals with the implementation of a Business Intelligence solution for a micro-enterprise operating in the e-commerce environment. The main objective of the thesis was to design and implement such a solution for a local food producer and retailer. The essence was to prepare a system for the client that would support operational activities, enable informed decisions, and provide insight into the company's performance. The practical part was guided by the CRISP-DM methodology. In the initial phase, after theoretical grounding, Porter's five forces analysis was performed to assess the state of the industry in which the company operates. A PEST analysis was performed to analyze the company. Observation, interviews, and document analysis methods were used for the subsequent analysis of the current state of the company. Based on this preparation, a BI solution was proposed that reflected the defined requirements and information needs of future users. By comparing the largest cloud providers on the market, the use of products within the Google Cloud Platform was chosen for this solution in the context of the specified criteria. The proposed solution was implemented using BigQuery, Dataform, Keboola, and Looker Studio tools. Furthermore, the solution was successfully validated from the perspective of business and technical validation criteria. The result is a functional Business Intelligence solution that takes into account the requirements based on the specificity of the given environment, providing a unified view of the company's operations.