The DXC Robotic Drive Analyzer is a toolkit capable of running all analytic and automotive workloads in one environment at petabyte scale. The developers, data engineers & scientists can build data processing pipelines, train and productionize machine learning models and obtain insights from automotive data. It connects the big data and machine learning world with the automotive file formats, allowing all the functionality of machine learning and statistical data analytics libraries can be used directly on automotive data. The main purpose and value add of the Robotic Drive Analyzer is to integrate automotive R&D engineering systems and data with modern data science technologies and tools with the required scalability. Native in-vehicle data formats and structures can be analyzed and this data is loaded into Spark Data Frames, which makes the data usable by a variety of powerful data science tools - from statistical function libraries to the newest machine learning software packages such as TensorFlow, PyTorch and MLflow.

On AWS marketplace, we present a demo that supports the following features:

• Perform distributed analysis of rosbag and MDF4 files using the Robotic Drive Analyzer, Apache Zeppelin and Apache Spark on Kubernetes
• Perform datafusion of Spark Dataframes
• Get hands-on experience in exploring data from car drives and their visualization following an exemplary use-case