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
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
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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.
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