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This lecture introduces the concepts of data stream processing, focusing on the differences between batch and stream processing, the importance of stream processing, and its applications in various fields such as computing, fraud detection, and predictive maintenance. The lecture covers tools like Apache Storm, Flink, and Kafka, and explains the operations and challenges involved in stream processing. Students will also learn about related concepts like event time, processing time, and window operations, as well as how to work with streaming data using Spark Streaming.