Flink in Practice: Stream Processing Use Cases for Kafka Users

The text discusses the use of Apache Flink® for stream processing in various industries and applications. It highlights three main categories of use cases: event-driven applications, real-time analytics, and streaming data pipelines. Event-driven applications are used in finance, healthcare, and transportation to automate responses to events as they happen. Real-time analytics involves analyzing real-time data streams to generate important business insights for decision-making. Streaming data pipelines continuously ingest data streams from various sources, perform joins, aggregations, and transformations to create new enriched streams of higher value. The text also mentions how Flink can be used with Kafka as a complete data streaming platform.