A Business Intelligence Model for Road Safety: The Case Study of Roma Capitale with PowerBi

This thesis aims to analyze road accidents in Rome Capital during the period from May to December 2022, using an approach based on the Power BI tool for data modeling and visualization through interactive dashboards. The project, carried out in collaboration with iMoì — a company providing the management system for recording road accident data in Rome Capital — aimed to deliver a prototype of an effective tool for monitoring and understanding the main factors influencing road accidents. This facilitates the identification of recurring patterns and high-risk areas, promoting data-driven decision-making. The dataset used was extracted and partially transformed using T-SQL by the company tutor, then uploaded to Power BI in a static CSV format. Within the platform, the data was further cleaned and enriched through Power Query, enabling the creation of new features relevant to the analysis. The relational model implemented includes the following main tables: Incidente (Incident), Luogo (Location), Strada (Road), Veicolo Coinvolto (Vehicle\_involved), Persona Coinvolta (Person\_Involved), Lesioni (Injuries), Condizioni Esterne (External\_Conditions), and Tipologia\_Incidente (Incident\_Typ), with key relationships structured to ensure query efficiency. The final dashboard provides a clear and detailed overview of the accidents, allowing data to be filtered based on various parameters — such as accident type, vehicle characteristics, time, and location — and offering valuable insights for authorities to define prevention strategies. The results highlight the importance of data-driven analysis for road safety, emphasizing how the integration of Business Intelligence (BI) tools can support more informed and timely decision-making.