Apache Kafka for Government and Citizen Services in the Public Sector
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Apache Kafka in the Public Sector – Part 3: Government and Citizen Services

The public sector includes many different areas. Some groups leverage cutting-edge technology, like military leverage. Others like the public administration are years or even decades behind. This blog series explores both edges to show how data in motion powered by Apache Kafka adds value for innovative new applications and modernizing legacy IT infrastructures. This is part 3: Use cases and architectures for Government and Citizen Services.
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Apache Kafka in the Insurance Industry
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Apache Kafka in the Insurance Industry

The rise of data in motion in the insurance industry is visible across all lines of business including life, healthcare, travel, vehicle, and others. Apache Kafka changes how enterprises rethink data. This blog post explores use cases and architectures for insurance-related event streaming. Real-world examples from Generali, Centene, Humana, and Tesla show innovative data integration and stream processing in real-time.  
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Apache Kafka Hard vs Soft Real Time for Industrial IoT Robots and Connected Vehicles
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Apache Kafka is NOT Hard Real Time BUT Used Everywhere in Automotive and Industrial IoT

Apache Kafka is NOT hard real-time in Industrial IoT or vehicles (such as autonomous cars) but integrates the OT/IT world for near real-time data correlation and analytics in hybrid architectures across factories at the edge, multiple clouds, and over countries.
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Postmodern ERP with Apache Kafka
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Building a Postmodern ERP with Apache Kafka

Postmodern ERP represents the next generation of ERP architectures. It is real-time, scalable, and open by using a combination of open source technologies and proprietary standard software. This blog post explores why and how companies, both software vendors and end-users, leverage event streaming with Apache Kafka to implement a Postmodern ERP.
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IoT Live Demo – 100.000 Connected Cars with Kubernetes, Kafka, MQTT, TensorFlow

Live Demo – 100.000 Connected Cars – Real Time Processing and Analytics with Kubernetes, Kafka, MQTT and TensorFlow leveraging Confluent and HiveMQ.
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