NetApp : Storing unstructured automotive data in the cloud could cost millions

Today's vehicles are required to capture large amounts of unstructured data, ingested through cameras, lidar, and long-range and short-range radar. Advanced driver-assistance systems (ADAS) need data for features like adaptive cruise control, blind spot detection, emergency braking, and collision avoidance. Level 4 and Level 5 autonomous cars literally depend on data to drive-that is, to drive intelligently and react appropriately.

Auto manufacturing plants are generating more data, too, as they introduce electric vehicles and revamp plant floors to use smart factory technology. Manufacturers use data for visualization, understanding yields, and identifying defects in real time. Production lines are capturing images of welds to ensure quality and images of printed circuit boards to make sure there is no delamination.

Manufacturing engineers and continuous improvement engineers use data to optimize their production and process lines and reduce bottlenecks. Design engineers and developers rely on data to create new cars and applications. Data scientists produce models and test them in simulation environments by using an algorithmic pattern that can later be tested in a real environment.

Automakers also need to hold on to data for compliance reasons-for example, so that insurance companies and transportation boards can review the raw acceleration or stopping data. This data needs to be stored in its original format with flexible levels of retention periods. This storage governance helps authorities determine that the data hasn't been tampered with.

Now multiply all this data by the number of automotive plants and fleets around the globe. These massive amounts of unstructured data need to be stored somewhere that's easy to access. And the quickest way to deal with this data is to push it into the public cloud and worry about restructuring later.