Graph databases and graph networks have gathered significant attention for their success in enriching economic analysis by enabling the visualization and exploration of complex relationships among entities, such as industries and products. In this study, the features of graph networks are exploited to model and analyze the network derived from the input-output system of the Italian economy. Thanks to graph-based algorithms, including community detection and centrality algorithms, we analyzed how the structure of the Italian economy evolved from 2000 to 2014, highlighting the major changes among the key Italian industry sectors and their interconnections.