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Learn how to efficiently implement Change Data Capture (CDC) using Databricks' Delta Live Tables (DLT) in this 38-minute conference talk. Discover how CDC provides an efficient method for extracting only changed data from transactional systems for analytics, while understanding the common challenges that arise during CDC data ingestion, including handling out-of-order events and maintaining global order across multiple streams. Explore how DLT's Apply Changes function simplifies CDC ingestion by automatically handling global ordering across multiple change feeds, eliminating the need for manual state management or advanced streaming concepts like watermarks. Examine support for both snapshot-based inputs from cloud storage and continuous change feeds from message bus systems, and understand how this approach reduces complexity for common streaming use cases. Gain insights from Jacob Gollub, Software Engineer at Square, and Ray Zhu, Director of Product Management at Databricks, as they demonstrate practical solutions for implementing production-ready CDC pipelines that bridge transactional systems and analytics platforms.
