โDatabricks DevConnect is a technical meetup designed for data engineers to experience an immersive evening of insights, collaborative learning, and community โ hosted by the Databricks Developer Relations team. Bringing together data enthusiasts and innovators, weโll explore the latest advancements in Databricks data engineering, AI, and analytics. Youโll have the chance to dive deep into technical discussions, share real-world experiences, and discover new ways to leverage Databricksโs technologies. Whether youโre a seasoned data engineer or just starting your journey, this event is designed to spark creativity and foster growth in our community. Letโs connect, learn, and push the boundaries of whatโs possible with data โ together!
โโWhy You Can't Miss This Event:
โโ๐ Unlock the Power of Databricks: Discover how our unified platform can power your data engineering and AI initiatives.
โโ๐ง Learn from Experts: Gain actionable insights from Databricks Engineers, Product Managers, DevRel, and MVPs.
โโ๐ป Engaging Technical Sessions: Deepen technical expertise through interactive demos of the Databricks platform, and tools.
โโ๐ค Network with the Community: Connect and build relationships with peers, MVPs, Databricks product managers, developer advocates, and engineers.
โโ5:00 PM: Registration & Mingling
โ6:00 PM: Welcome Remarks by:
โโHolly Smith, Staff Developer Advocate
โโ6:15 PM โก๏ธ Session #1: Format Interoperability with Apache Icebergโข
โโRobert Pack, Staff Developer Advocate
โโ6:45 PM โก๏ธ Session #2: End-to-End Development with Databricks Assistant: From Data Discovery to Production
โโHolly Smith, Staff Developer Advocate
โ7:15 PM โก๏ธ Session #3: Turning the Tables on Tuning your Tables
โBart Samwel, Principal Software Engineer
โโ7:55 PM: Closing Remarks by:
โโRobert Pack, Staff Developer Advocate
โโ8:00 PM: Networking Reception
โโ8:30 PM: Good night
โโFormat Interoperability with Apache Icebergโข: In this technical session, we will showcase and demonstrate how Databricks simplifies data integration across any open data format. Youโll learn how Databricks allows you to connect to any data source allowing you to have full format interoperability from wherever/whatever your data source.
โโEnd-to-End Development with Databricks Assistant: From Data Discovery to Production: In this technical deep dive, weโll explore how developers can leverage the Databricks Assistant to streamline workflows across the entire development lifecycleโfrom data discovery to production deployment. Learn how AI-powered features like Catalog Explorer integration simplify schema exploration and metadata retrieval, while SQL optimization tools help refine query performance. Weโll also showcase new capabilities for diagnosing job errors and troubleshooting DLT pipelines, enabling faster debugging and issue resolution in Python-based workflows. Whether you're authoring SQL queries, troubleshooting Python scripts, or debugging production workflows, discover how the Databricks Assistant accelerates development and enhances operational efficiency.
โTurning the Tables on Tuning your Tables: Traditionally, data engineers spend a lot of time on tuning their tables together with their workloads. Picking partition keys. Choosing whether to use ZORDER or partitioning. Scheduling OPTIMIZE and VACUUM. Planning your schedules carefully to avoid concurrent writes and OPTIMIZES... This talk is about how the Databricks Data Intelligence Platform takes all of those worries out of your hands, so that you can focus on your real job. You'll learn about a number of innovations that combine to make your life easier, including Liquid Clustering, Row-Level Concurrency, and Predictive Optimization. Using these features, you can forget about all that manual tuning and get back to the business at hand!
โโHolly Smith, Staff Developer Advocateโ
โRobert Pack, Staff Developer Advocate
โBart Samwel, Principal Software Engineer