One of the main causes of the widespread problem of freshwater scarcity lies in unfruitful maintenance of distribution infrastructure, leading to failures with consequent waste of precious resources. It is estimated that more than 25% of the annual loss of water is due to poor conditions of the distribution networks and, in a scenario of continuously increasing demand for water, effects of such inefficiency might be even more dramatic, beyond the merely economic aspect. However, with the rise of data analysis, the awareness of the power of predictive technologies and machine learning techniques, the opportunity to make use of these tools to support decision making has become more than a hope.