Automotive use cases: from the real time data ingestion to the data analysis of connected vehicles.

The growing computerization and the increasing diffusion of data collection and storage technology leads to an increasing availability of data. New modern cars can give their owners many new benefits, thanks to Big Data Analytics. Many supply chains start implementing sensors on cars that, at first, were not planned as connected vehicles. This thesis illustrates the existing infrastructures, architectures and tools in the Big Data field and how these data are analyzed and used in various automotive use cases. The main objective of the thesis is the implementation of a scalable solution, which is not other than a pipeline that includes a series of steps, ranging from the ingestion of real time data to the analysis of the data itself with appropriate machine learning algorithms to provide useful information in terms of real-time vehicle monitoring.