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Learn how to build streaming data flows that handle inserts, updates, and deletes using Delta Lake Tables (DLT), Delta Lake, and change data feed capabilities in this 31-minute conference talk from Databricks. Discover how 84.51 processes approximately 8 million daily sales transactions with 80 million purchased items by combining streaming checkpoints with materialized views and Enzyme incremental refresh for an efficient, low-code solution. Explore the challenges of traditional streaming architectures when data sources include updates and deletes rather than just append-only operations, and understand how to create robust end-to-end data flows that maintain streaming performance while handling complex data changes. Gain insights into real-world implementation strategies for retail data processing at scale, including how to leverage first-party retail data from 60 million households through loyalty card programs to drive customer-centric analytics and decision-making.
