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BMW

Optimizing Automotive Data Analysis

Streamlining trace analysis for the BMW Group through custom tool integration

Overview

As modern vehicle technologies evolve, the complexity of data analysis creates significant challenges. For the BMW Group, intive provided smooth integration and optimization of their custom data analysis tools. This streamlined testing workflows and drove efficiency in both development and production.

Client

A leading premium manufacturer of automobiles and motorcycles, renowned for innovation, performance, and sustainability.

Services

Custom data analysis tools

Tool integration and optimization

Microservice based, horizontally scalable ETL pipeline

Big data trace analysis

Reliable infrastructure for accessing board net configuration data

Technical consulting and evaluation for possible internal tools

Teaching and consulting in agile software development practices

A navy blue Audi car set against a landscape.

The Challenge

With vast volumes of trace data generated during vehicle development and testing, the BMW Group needed efficient tools to analyze and manage information spanning from gigabytes to terabytes. This data, crucial for verifying car functionality and maintaining the company’s high-quality standards, required a streamlined approach to handle growing data volumes, support a wide range of automotive protocols, and seamlessly integrate into interconnected workflows.

With deep domain expertise in evolving automotive technologies, intive’s team focused on custom tool integration and optimization for the BMW Group, accelerating complex testing workflows to improve operational efficiency and gain detailed, actionable insights across the entire lifecycle.

Our solutions

To meet the BMW Group’s needs, we formed cross-functional teams of experts skilled in Java, Scala, C++, Python, DevOps, Kubernetes, and network technologies. Our focus was on applying proven software engineering practices to modernize the premium automaker’s tooling ecosystem and deliver reliable, efficient solutions tailored to their requirements. Working closely with the BMW Group, we concentrated on enhancing two core tools essential to their trace analysis processes.

Toolchain for modelling and verification of bus communication behavior

This comprehensive toolchain enables users to model vehicle behaviors and test scenarios against real-world trace data, supporting broad trace analysis across various departments. We enhanced the application’s capabilities by implementing a robust microservice architecture that streamlined data filtering, transformation, and enrichment. These improvements not only increased efficiency but also made the tool adaptable to future requirements. Over time, it evolved into a highly comprehensive platform with over 42 repositories, capable of handling extensive data analysis while leveraging other tools for deeper insights.

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A man wearing glasses and a grey hoodie is focused on his work at a computer.

Application for in-vehicle boardnet communication analysis and visualization

Widely used across the BMW Group, this long-standing solution has been an integral part of the company’s trace analysis ecosystem for years. As one of the earlier tools developed for this purpose, it has played a foundational role in enabling in-depth analysis of communication protocols, processing trace data, and supporting various hardware logger formats. To ensure continued reliability and adaptability, we stabilized and extended its capabilities by addressing legacy issues, implementing missing features, and ensuring compatibility with both modern and older systems. Through advanced software engineering practices, we enhanced its ability to support a wider array of automotive network protocols, reinforcing its essential role in the BMW Group’s operations.

An extensible microservice landscape for trace data processing

In addition to enhancing the tools, we developed a robust microservice landscape to unify and optimize the BMW Group’s data workflows. These microservices not only supported both systems but also integrated with other tools within the leading OEM’s ecosystem. By creating a scalable and adaptable architecture, we ensured the data processing pipeline was future-proof and capable of handling evolving demands.

A close-up view of a car dashboard featuring a modern digital display with indicators and controls.

Since 2016, intive has been a trusted partner to the BMW Group, modernizing their data analysis tools and workflows. These enhancements have allowed the premium automaker to efficiently handle large volumes of trace data across multiple protocols, enabling users to perform accurate and efficient trace analysis across departments globally. The tool for in-depth analysis of vehicle network traffic serves as the core of the BMW Group’s trace analysis efforts, ensuring precise evaluation of communication protocols and enabling critical insights that support the development of error-free vehicles. Meanwhile, the toolchain for data analytics and processing enhances broader trace evaluation workflows, complementing the network analysis tool and streamlining processes across different departments.

To further optimize data workflows, we introduced a scalable microservice architecture, including a Microservice-Based ETL Pipeline that reduced processing time from approximately 10 days to just 4 hours.
This unified architecture not only supports both core tools but also integrates seamlessly with other systems in the BMW Group’s ecosystem, enabling faster testing cycles, quicker adaptation to new requirements, and improved overall data accuracy. Designed with scalability and flexibility in mind, it ensures the tools remain easily extendable, empowering the BMW Group to continue delivering high-quality, reliable vehicles to customers worldwide.

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