How to Build Real-Time, Event-Driven Automation for Business Insights

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This post details how to build real-time, event-driven automation for business insights using event-driven workflows and AI agents. It outlines the architectural components, including event brokers (Apache Kafka) and processing layers (Apache Flink/Kafka Streams), and provides best practices for implementation such as using Schema Registry, testing under real load, and planning for anomalies. It also presents real-world use cases like fraud detection, customer churn prevention, and inventory optimization, emphasizing the benefits of immediate responsiveness, scalability, and personalization.