How the manufacturing scalability of the Model T brought mobility to the masses over 100 years ago, data science is scaling mobility for lower-income communities today. It makes transportation easily accessible without the high cost of ownership and is facilitating this change for everyone, no matter their class, gender, or ability.

Working with data in the automotive industry

Because of the automotive industry’s maturity and wide reach, there are many opportunities for companies to rebuild around data.

One application is working with data across different data systems and data types. Many data scientists are accustomed to using tabular data, which means the data is in a table format, similar to Excel. But automotive data scientists have a much greater variety of data to work with. For example, raw instrumentation data in the automotive industry is commonly stored as a stream of hexadecimal digits. They may also encounter data from intelligence systems in the form of images and sensor point clouds. And to understand why an autonomous vehicle behaves a certain way and how that varies among vehicle models, an automotive data scientist might combine point clouds with instrumentation data and join that to a set of tables.