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Introduces data stream processing, covering batch vs stream processing, real-time insights, applications, challenges, and tools like Apache Kafka and Spark Streaming.
Covers data stream processing with Apache Kafka and Spark, including event time vs processing time, stream processing operations, and stream-stream joins.
Covers the fundamentals of data stream processing, including tools like Apache Storm and Kafka, key concepts like event time and window operations, and the challenges of stream processing.
Covers the fundamentals of data stream processing, including real-time insights, industry applications, and practical exercises on Kafka and Spark Streaming.
Explores scalability, persistence, and consistency in database systems and data-intensive applications, emphasizing the importance of state and trade-offs in data management.
