Prediction model for drinking water network failures The large amount of data nowadays available for the companies creates wide business opportunities. Data Science meets application in different domains. Data science processes leverage internal or external resources, such as big data, from which useful insights and predictive models can be obtained, to create value for the company through the significant support that can be provided to the decision making through these data analytics tools. This research traces the foundations of the Data Science approach, Business Intelligence and Big Data. In this context, is placed the PME Project, a Data Science project that proposes a solution for the management of pipeline failures in the drinking water networks.