Big Data


Text Mining on web data

  • Content analysis of web pages, blogs, tweets, social networks and reviews
  • Sentiment Analysis and Web Reputation: how a phenomenon, an entity, a service or a product is perceived on the web
  • Profiling of user behaviour

Collection, processing and delivery of data

  • Structure and socio-demographic and economic profiling of the territories
  • Catering, hospitality, art and culture, leisure
  • Healthcare facilities: interventions, hospitalizations, mortality, etc.
  • Personal data and balance sheets of the Public Administration entities

Infrastructure and transport, land use, satellite images

  • Support to entities in the Open Data area
  • Census, collection, cataloguing and linking of open data
  • Publication of data at the highest levels of quality required by AgID
  • Realization of open data portals federated with
  • Feeding through SDMX the public statistic hub (SISTAN HUB)


Big Data is a term used to describe the exponential growth of data that we are assisting in recent years. Big data includes structured data (e.g. datawarehouse, open data), unstructured data (e.g. social network posts, blogs, videos, photos) and real time data (e.g. weather, GPS, RFID, etc.).

Having large amounts of data available also means having great potential for analysis in various areas. Sistemi Territoriali in recent years has conducted successful projects analyzing the big data on various topics such as:

  • insurance
  • investigative analysis
  • online scams
  • epidemiology
  • asset analysis
  • open data
For these projects Sistemi Territoriali used a mixture of commercial technologies such as relational databases, Graph Engines, Graph Mining and Business Intelligence, but the core of all these projects was the Social Network Analysis, that is the study of social networks, the relationships between the different actors involved.
In addition, with the innovative SAS Visual Analytics and Statistics products, Big Data can be explored interactively, with the possibility of applying descriptive statistical analysis and predictive models to identify relevant hidden information.
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