This lecture covers the management of data streams, including traditional DBMS versus data streams, real-time network applications, stock monitoring examples, and challenges in analyzing packet-level statistics. It also discusses the data stream model, special cases, and the facets of data and time in stream processing. Efficient stream management strategies and scaling-out platforms for real-time requirements are presented, along with examples of platforms like Spark Streaming, Apache Flink, and Apache Kafka.