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Online Talk

Streaming Data Architectures and Use Cases

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As business priorities continue to shift in a post-pandemic world, there’s no denying the unpredictable nature of data usage. Kai Waehner, Field CTO at Confluent, shares the top real-world data streaming use cases and architectures we expect organizations to adopt.

In addition, he also shares the best technologies that are helping companies leverage real-time data at scale, stay competitive, deliver powerful, real-time experiences, and more through modern, data streaming technologies. Here are the top 5 data streaming use cases and architectures:

  • Kappa architectures have become the de facto standard for big data.
  • Data streams support hyper-personalized, omnichannel experiences.
  • Multicloud architectures maximize data value and disaster recovery.
  • Data processing at the edge delivers instant, scalable insights.
  • Real-time cybersecurity helps organizations proactively address threats.

Kai Waehner is Field CTO at Confluent. He works with customers across the globe and with internal teams like engineering and marketing. Kai’s main area of expertise lies within the fields of Data Streaming, Analytics, Hybrid Cloud Architectures, Internet of Things, and Blockchain. Kai is a regular speaker at international conferences such as Devoxx, ApacheCon and Kafka Summit, writes articles for professional journals, and shares his experiences with new technologies on his blog: www.kai-waehner.de. Contact: kai.waehner@confluent.io / @KaiWaehner / linkedin.com/in/kaiwaehner.

Additional Resources

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Confluent Cloud Demo

Join us for a live demo of Confluent Cloud, the industry’s only fully managed, cloud-native event streaming platform powered by Apache Kafka
kafka microservices

Kafka Microservices

In this online talk series, learn key concepts, use cases and best practices to harness the power of real-time streams for microservices architectures
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e-book: Microservices Customer Stories

See how five organizations across a wide range of industries leveraged Confluent to build a new class of event-driven microservices