The application of machine learning and data mining has seen a rise over the past decade thanks to their recent success in different fields, ranging from computer vision, biomedical data analyses to natural language processing. The field of computer networks and network maintenance has also observed the application of such concepts. This thesis is a result of an ongoing collaboration with TIM SpA. Overall, the studies presented in this manuscript consist in the analysis of the alarms raised by TIM network devices both in mobile and transmission domains, with the ultimate goal of developing a real-time environment that can help technicians to quickly determine faults within their network and solve them faster.