In 2019, building operations were responsible for about the 28% of the global CO2 emissions, taking into account not only the share directly due to the daily activity, but also the indirect part produced by the generation of power that supplies the building. The buildings consumption is strongly affected by the Energy Performance Gap, which is the deviation of the actual energy performance of the building with respect to the expected and designed one. As a consequence, the scope of improvement is relevant for the buildings and, in this context, an effective energy management has a key role. The aim of this thesis work is to provide a data analytics methodology whose results can be helpful to increase the knowledge about the system and that can be a tool to implement for the energy management.