Autonomous vehicles are on the rise, with 12 million fully autonomous vehicles anticipated by 2035 according to Boston Consulting Group (BCG). However, as it turns out, teaching cars to drive is an incredibly data intensive endeavor. Traditional data management approaches are straining to cope with the demands imposed by autonomous driving research.
This session investigates the role of data in teaching cars to drive and the data management challenges that automakers must overcome in achieving this objective. Finally, a modern data architecture, leveraging the latest advances in data management technologies is proposed to facilitate the promise of a self-driving future.