Reducing the frequency and severity of accidents in industrial processes is a continuous open challenge. Learning from previous events represents a crucial instrument to ensure an improved design of industrial plants, especially considering the complexity arising in everyday operations. This article is grounded on a database of industrial accidents involving hazardous substances and materials. The Major Hazard Incident Data Service (MHIDAS) was developed in 1986 by the Health and Safety Executive (HSE) to provide a reliable source of data on major hazard incidents and to learn for the past accidents. The database has more than 9000 accident reports covering the periods from 1950 to the end of the 1990s caused by hazardous substances/materials. This paper aims are to provide an understanding of MHIDAS data through quantitative analyses that can be obtained by exploiting the information collected through appropriate data management tools. Therefore, Information Technology (IT) services such as Business Intelligence (BI) tools have been used in this research. The paper describes the process of creating a BI model for data management on MHIDAS database to generate useful information on previous industrial safety events, allowing a detailed search engine as well through any event stored in MHIDAS.