Shift left to write data once, read as tables or streams

Shift Left is a rethink of how we circulate, share and manage data in our organizations using DataStreams, Change Data Capture, FlinkSQL and Tableflow. It addresses the challenges with multi-hop and medallion architectures using batch pipelines by shifting the data preparation, cleaning and schemas to the point where data is created and as a result, you can build fresh trustworthy datasets as streams for operational use cases or Apache Iceberg tables for analytical use cases. For more information and resources on Shift Left, go here: https://cnfl.io/3Zk0oia RELATED RESOURCES ► Read more about building data products as close to the source as possible, which unlocks both near-real-time and batch-based use cases: https://cnfl.io/3XhswQh ► Checkout the playlist "Data Architecture Basics with Adam Bellemare" for more videos like this one: https://www.youtube.com/playlist?list=PLa7VYi0yPIH0QypJnW0OXOnbLvzJRP34C CHAPTERS 0:00 - Introduction 01:05 - Multi-Hop & Medallion Architectures 04:06 - The Problems with Multi-Hop 08:26 - Shift Left with Streams and Tables 12:37 - Plugging in Data 13:57 - Data Evolution and Consistency 16:05 - Conclusion – 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. #apachekafka #kafka #confluent