During the 1990s, the Brazilian electricity sector underwent profound changes in its operational model. The Brazilian state began to assume a less developmental and more regulatory role, leading to the creation of the National Electric Energy Agency (ANEEL). One of the roles of ANEEL is to ensure the quality of service provided by sector agents (energy generation, transmission, and distribution companies). When an agent does not meet established standards, ANEEL can apply penalties. In this sense, the improvement of maintenance processes plays a crucial role in ensuring the reliability and efficiency of electrical systems and consequently reducing penalties. Predictive maintenance is being adopted, in addition to more traditional methodologies (reactive and preventive). However, this methodology represents a fundamental change compared to previous ones, as it seeks to anticipate failures based on data and analysis. In this sense, the incorporation of predictive maintenance into maintenance processes presupposes the availability of operating and maintenance data of the equipment, as well as the technological resources that enable the analysis of these data. This dissertation proposes a reference technological architecture that enables the development of these analyzes, considering aspects of management, governance, and corporate compliance practiced by the sector s agents.