This document summarizes Ellen Friedman's presentation on streaming data and architectures. The key points are:
1) Streaming data is becoming mainstream as technologies for distributed storage and stream processing mature. Real-time insights from streaming data provide more value than static batch analysis.
2) MapR Streams is part of MapR's converged data platform for message transport and can support use cases like microservices with its distributed, durable messaging capabilities.
3) Apache Flink is a popular open source stream processing framework that provides accurate, low-latency processing of streaming data through features like windowing, event-time semantics, and state management.