This document summarizes Joey Echeverria's presentation on embeddable data transformation for real-time streams. Some key points include: - Stream processing requires the ability to perform common data transformations like filtering, extracting, projecting, and aggregating on streaming data. - Tools like Apache Storm, Spark, and Flink can be used to build stream processing topologies and jobs, but also have limitations for embedding transformations. - Rocana Transform provides a library and DSL for defining reusable data transformation configurations that can be run within different stream processing systems or in batch jobs. - The library supports common transformations as well as custom actions defined through Java. Configurations can extract metrics, parse logs, and perform