Big Data and the Automotive Sector’s new Challenges
In the next decade, the automotive industry will face a magnitude of change that has not been seen in a century. This change will be driven primarily by four mutually reinforcing trends, i.e., autonomous, connected, electric, and shared vehicles. These will result in shifting different user behaviors and mobility preferences, shifting value pools, business models and the appearance of new entrants in automotive (EV-startups, Tier 0.5-s etc.). To meet these demands major OEM-s and TIER 1-s have recognized the importance of data intelligence and identified opportunities along the entire value chain, ranging from marketing, over quality enhancement in production, supply chain optimization to virtualization and automation of design and engineering.
Gaining access to vehicle information is not new and in such a way it is common using diagnostic tools in the garages and dealer workshops. However, integrating this with information about a vehicle’s operating environment at a given moment in time can be a changing factor. To gain access to this data more and more vehicles are already being fitted with sensors and connectivity solutions natively integrated.
Connected cars will provide a steady stream of data on vehicle, engine, driving behavior and ambient conditions. Extracting insights from this mass of mixed data generated at incredible velocity, variety and volume is no easy task. The challenge is now how to better capture those data-in-motion, analyzing the huge amount of data and redistributing insights to the relevant recipients in real time.