Nowadays, Big Data holds vast potential for improving decision-making in public policy due to the different methodologies for working with complex heterogeneous big data, which allows proposing policies based on real and measurable key performance indicators. This article aims to describe the water resource observatory of the Public Management School of Universidad del Pacífico. The idea behind the observatory is to handle data extracted from non-traditional sources to enhance efficient and responsive government solutions through evidence-based public policies for water regulation. We used Elastic Search stack to centralize and visualize data from different sources, which was standardized using river basins as basic units. Finally, we show a use case of the data gathered to optimize the water supply in new urban zones in Lima’s periphery.