Big Data Analysis Tool Automotive

Challenge

The increasing connectivity of vehicles and new telematics services are generating vast amounts of data in the fleets of automotive manufacturers. Our client faced the challenge of translating over 4 billion data points from more than 100 markets regarding vehicle usage and load collectives into a dashboard and analysis application for product management and marketing.

Approach

We first established a scalable computing backend in the client's cloud infrastructure using Apache Spark. This was then linked to an intuitive and visually appealing analysis frontend, allowing professionals and management to effortlessly navigate, analyze, and visualize hundreds of millions of data points. By employing technologies such as Docker, R Shiny, Spark, Hive, and Databricks, we achieved a level of performance and scalability in both the backend and frontend that meets the highest standards and efficiently supplies even larger user numbers with the computing power of the Spark cluster. An appealing user interface and intuitive visualizations provide near-real-time access to data analysis on over 8 million vehicles.

Result

By integrating innovative technologies, we developed a tool for the interactive analysis and visualization of several billion data points. This enables almost real-time use of vehicle usage data and load collective information, allowing vehicles to be further customized to meet customer needs.