The document discusses windowing data in big data streams. It describes how windowing allows analyzing data based on a time interval, such as the number of invalid login attempts in the last 5 minutes. It then covers different streaming data technologies like Spark Streaming, Spark Structured Streaming, Kafka Streams, Flink, and Akka Streams that can be used to perform windowing. Each technology handles aspects such as event time, watermarks, triggers, and state management slightly differently. In the end, the document notes that windowing is one part of streaming and other factors like processing guarantees and state management also need consideration.