Authoring Data Pipelines With the New Lakeflow Declarative Pipelines Editor
Description
We’re introducing a new developer experience for Lakeflow Declarative Pipelines designed for data practitioners who prefer a code-first approach and expect robust developer tooling. The new multi-file editor brings an IDE-like environment to declarative pipeline development, making it easy to structure transformation logic, configure pipelines throughout the development lifecycle and iterate efficiently. Features like contextual data previews and selective table updates enable step-by-step development. UI-driven tools, such as DAG previews and DAG-based actions, enhance productivity for experienced users and provide a bridge for those transitioning to declarative workflows. In this session, we’ll showcase the new editor in action, highlighting how these enhancements simplify declarative coding and improve development for production-ready data pipelines. Whether you’re an experienced developer or new to declarative data engineering, join us to see how Lakeflow Declarative Pipelines can enhance your data practice. Talk By: Adriana Ispas, Sr. Staff Product Manager, Databricks ; Camiel Steenstra, Staff Software Engineer, Databricks Here’s more to explore: Production ready data p…
Description from YouTube. Full content on the video page.
More from Databricks
NewsApache Iceberg V3 on Databricks: From Ingestion to Analytics
The video demonstrates Apache Iceberg v3 on Databricks, showcasing how its new variant column type natively handles semi-structured data and how row-level concurrency enables simultaneous data ingestion and corrections. It also highlights cross-platform data accessibility from open-source Spark via the Iceberg REST catalog, ensuring no vendor lock-in.
NewsDatabricks Genie for Marketing
Databricks' AI BI Genie allows non-technical marketers to converse with their Customer 360 data using natural language, enabling quick insights into marketing performance and campaign optimization. It helps identify issues like audience saturation and recommends budget reallocation by analyzing data and providing reasoning for its suggestions.
NewsGovern MCP servers in Databricks #databricks #mcp #aigovernance
Databricks Unity AI Gateway now governs MCP servers, centralizing their management alongside built-in foundation models and LLMs. This integration allows for easier governance and orchestration of various AI components and agents within Databricks.
NewsHow Suntory Turns Data into Faster Decisions with Databricks
Suntory uses Databricks to integrate diverse datasets, including internal sales, macroeconomic factors, and consumer behavior, into "Project Brain" for faster decision-making and product launches. The company also implements an all-employee upskilling program, "Manabi no Michi," to empower its workforce to leverage AI for improved performance and efficiency.
NewsAIA Group x Databricks: Turning Regulated Data into Real-Time Intelligence
AIA Group leverages Databricks to manage regulated data across 18 markets, addressing challenges like data residency and varying tech maturity with features like Unity Catalog for governance. The platform enables real-time intelligence for investment decisions, fraud detection, and personalized agent coaching, with future plans for conversational analytics and autonomous AI.
TutorialsConnect Google Sheets to Databricks
The Databricks Google Sheets add-in allows users to explore, import, and refresh governed data from the Databricks Lakehouse directly within Google Sheets. It demonstrates how to browse Unity Catalog, select tables or metric views, apply filters, schedule data refreshes, and use direct SQL queries with parameters.