SQL-First ETL: Building Easy, Efficient Data Pipelines With DLT
Description
This session explores how SQL-based ETL can accelerate development, simplify maintenance and make data transformation more accessible to both engineers and analysts. We'll walk through how Databricks DLT and Databricks SQL warehouse support building production-grade pipelines using familiar SQL constructs. Topics include: Using streaming tables for real-time ingestion and processing Leveraging materialized views to deliver fast, pre-computed datasets Integrating with tools like dbt to manage batch and streaming workflows at scale By the end of the session, you’ll understand how SQL-first approaches can streamline ETL development and support both operational and analytical use cases. Talk By: Meixian Li, Sr Software Engineer, Databricks ; Paul Lappas, Sr Staff Product Manager, Databricks ; Ritwik Yadav, Software Engineer, Databricks Here’s more to explore: Production ready data pipelines for analytics and AI: https://www.databricks.com/solutions/data-engineering The Big Book of Data Engineering: https://www.databricks.com/resources/ebook/big-book-data-engineering-2nd-edition See all the product announcements from Data + AI Summit: https://www.databricks.com/events/dataaisu…
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