Databricks

#DataAIWorldTour kicks off this week! 🗓️ Join data leaders, practitioners, and innovators to explore the latest in AI agents, Agent Bricks, Lakebase, and more — plus insights you can put into action today First up: 📍 São Paulo – September 3 📍 Dallas – September 4 📍 Singapore – September 10 📍 Mumbai – September 19 📍 Los Angeles – September 23 Secure your spot today: https://lnkd.in/gFPPNQUm

For years, Apache Spark™ Structured Streaming has powered mission-critical pipelines. Now, with real-time mode, it extends to workloads that process events in milliseconds — like fraud detection, live personalization, and real-time ML feature serving. Explore real-time mode in Public Preview today ➡️ https://lnkd.in/g96KHjY6

How does an automotive leader keep up with soaring EV demand and rising customer expectations? By turning siloed data into AI-powered experiences with Databricks, Cycle & Carriage gave employees instant access to critical insights—like technical manuals and customer histories—so they can serve customers faster and more accurately. The result: smoother EV buying and ownership experiences, smarter business decisions, 99% model accuracy, and a 100% boost in user experience. https://lnkd.in/gk_MuefJ

Building apps on Databricks just got a lot easier! 🏗️ Learn how Lakebase can serve as the transactional data layer for Databricks Apps. - Unified stack: Build apps on top of data in your lakehouse with Databricks Apps + Lakebase - Secure & serverless: Native auth, governance, and access controls included - Practical guide: Walkthrough the setup of building an App https://lnkd.in/gHf6HJia

Delivering AI-ready data is harder than ever — too many tools, manual code, and pipelines that don’t scale. Join Databricks’ Bilal Aslam and Simon Whiteley, CTO at Advancing Analytics, to see how a unified, declarative platform helps you: - Replace repetitive code with tested pipelines - Support batch, streaming, and unstructured data - Monitor pipeline health with built-in quality checks, schema evolution, and error handling You’ll leave with a clear plan to simplify your stack, scale your workflows, and deliver reliable data for AI: https://lnkd.in/g2U4gW9h

Ever hit a frustrating coding error and wished for a smarter, faster solution? That’s what Databricks intern Ilana Nguyen worked on all summer. She helped improve Databricks Assistant’s Quick Fix by generating multiple fix suggestions and training a reward model to pick the best one — boosting both quality and speed. Explore the Databricks Assistant and get a peek into our intern experience: https://lnkd.in/gwEwuA8P

Databricks has been named to Madrona's 2025 Intelligent Applications 40 list! We are honored to be recognized for our innovative approach to helping organizations build high-quality, trustworthy AI agents. Featured today on the NYSE floor, alongside other #IA40 honorees — explore the full list here: ia40.com/the-list

What if you could reliably monitor, evaluate, and control your AI’s behavior with a single, adaptable tool – no deep expertise required? Databricks’ new Prompt-Guided Reward Model brings together reward modeling and judging to do just that. PGRM is your AI’s quality control inspector. Judge, calibrate, and fine-tune your AI with one prompt. Explore the benchmark results and how we built PGRM: https://lnkd.in/gPk88Juy

Equip teams to better automate and orchestrate any ETL, analytics, and AI workflow with deep observability, high reliability, and broad task type support See how it works in practice: setting up tasks, adding quality checks, triggering jobs when new data arrives, and monitoring performance—all within Lakeflow Jobs: https://lnkd.in/gD2JsZCb

If you’re using AI in dev workflows, treat prompting as security, not just a productivity hack. Our research shows prompting makes a difference: self-reflection, security prompts, and language-specific guidance all cut insecure code in large benchmarks without hurting quality. 👉 Learn more: https://lnkd.in/guaENtJ2