The Challenge – Removing the operational burden of data streaming

To handle an abundance of data, BMW Group initially replaced its old batch model with Kafka. However, while open source Kafka allowed BMW Group to add more applications without having to tack on additional clusters within their data streaming platform, it proved to be an operational burden.

Kafka was costly and not reliable enough to meet the demands of a global business, where applications must run 7x24x365. BMW Group needed a way to seamlessly integrate all its data—generated by machines, sensors, and other sources—and make it accessible in real time as a self-service product across the business.
The OEM recognized the importance of shifting to a central, cloud-based data system to enable teams across the organization to leverage realtime data at scale, and build a future-proof data streaming architecture that would support innovative use cases.

By partnering with Confluent and Microsoft Azure, BMW Group harnesses their data streaming capabilities and offers these to hundreds of different teams and applications across the organization

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