Transforming Data in Flink | Building Flink Applications in Java

► TRY THIS YOURSELF: https://cnfl.io/flink-java-apps-module-1 "How do you transform data in Flink, and what are the main transformation types? One of Flink's biggest advantages is its ability to transform data in a distributed streaming pipeline. It contains a variety of operators that enable both the transformation and the distribution of data. These operators include common functions such as map, flat map, and filter, but they also include more advanced techniques. This video will show a few of the basic operations that can be performed on a Flink datastream as well as how they might fit into a streaming pipeline." For a complete IMMERSIVE HANDS-ON EXPERIENCE: https://cnfl.io/flink-java-apps-module-1 -- ABOUT CONFLUENT Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io. #flink #java #streamprocessing #confluent