Building a Data Lakehouse to Manage PBs of Autonomous Vehicle Data

Building autonomous vehicles is a complex and challenging task that requires a flexible and efficient data and ML platform. This session will show how Scania leveraged the data lakehouse concept to manage and analyze huge volumes of sensor data from different sources and formats. A data lakehouse is a new architecture that combines the advantages of data lakes and data warehouses, such as scalability, reliability, and performance. It allows us to store, process, and query sensor data in a consistent and unified way. We will share our experience and lessons learned from the following aspects: How we built and deployed our data platform architecture using Unity Catalog and Delta Live Tables. How we fostered user adoption and collaboration among various teams and stakeholders. How we are preparing for the future challenges of MLOps, data contracts, and going multi-tenant