Databricks

Legacy BI wasn’t built for the way teams work today. Agentic analytics is. Join next week's virtual event with Anthropic and Alex Freberg to see how agents built on a unified data platform can support the full analytics workflow — from data prep to insight. You’ll learn: - How agentic analytics spans data prep to insight - What’s new across Databricks analytics tools - How Genie and Claude deliver agentic insights - How to build end-to-end analytics workflows without BI seats https://lnkd.in/gihYJqwg

Enterprises are ramping up agent development, but this rapid growth poses a new challenge: finding and managing them all. That's why we built a managed orchestration layer that lets you tie together agents and tools. Agent Bricks Supervisor Agent provides a foundation for orchestrating AI agents at scale - and with enterprise governance. Teams can now route intent, govern access, and continuously improve agent quality, all from a single control plane. Create your first agent and connect it to your existing agents and tools → https://lnkd.in/gND7K9zh

Meet Databricks at Mobile World Congress 2026 in Barcelona! Join us to discuss how telecom operators are using unified data and AI to drive measurable outcomes, from improving attach rates and reducing churn to proactive fraud prevention. We're presenting on industry panels, meeting with customers, and sharing real-world examples throughout the week. See you there: https://lnkd.in/ghvs4ygu

Ibotta, a digital rewards platform for everyday cashback purchases, was running a complex and expensive data stack. That’s why the team consolidated those tools to simplify how data and AI work happens across the business. With improved offer relevance in search, Ibotta saw a lift in engagement and reduced latency by 60%, making the experience faster and more personalized. Stronger governance also helps keep partner data isolated and accessible only for the right use cases, while making data and AI easier for more teams to use.

Nasdaq eVestment™ data is now available on Databricks Marketplace via Delta Sharing! Asset managers can now access institutional investor and open mandate intelligence as live, query-ready tables directly in Databricks. This brings mandate data, CRM records, and performance history together in one place, making it easier to identify the right opportunities and prepare with confidence. With Next Best Action scoring, distribution teams can prioritize higher-probability mandates and act with clearer, data-driven insight. Explore Nasdaq eVestment on Databricks Marketplace. https://lnkd.in/g6mAfcQ2

What if you could surface new insights from your enterprise data by just asking questions? Genie Agent Mode is built for forward-looking questions. Here’s how it works: - Ask a question like “How can we optimize bookings revenue?” - Genie builds a research plan - Tests each hypothesis - Iterates as it learns - Summarizes results in natural language, tables, and visuals - Export the full research as a PDF for sharing ✅

Databricks DevConnect is back for 2026! Built for developers, DevConnect is a technical meetup where we’ll go deep into the tools and patterns powering production data and AI workloads. What to expect: - Deep dives on agentic workflows, MLflow 3.0, Unity Catalog, and more - Live demos grounded in real-world use cases - Direct access to Product, DevRel, Field Engineers, and MVPs - Local networking with fellow developers Find your city and register: https://lnkd.in/gUKEh7d2

App development has completely transformed with agents, but the underlying databases have been largely unchanged since the 1980s. Meet: Lakebase. Lakebases are enabled by a fundamentally new design. The core breakthrough is separate storage and compute. Data sits directly in low-cost cloud storage in open formats, while the compute layer runs independently on top. And fully managed, serverless Postgres scales up instantly with demand and down when idle. Learn about this new era of databases: https://lnkd.in/gz7Rn68c

What separates companies that are productionizing AI agents from those that are stagnating? Our usage data from 20,000+ global organizations shows: - Companies that actively use AI governance put 12x more AI projects into production - Companies that are actively using AI evaluation tools put over 6x more AI projects into production Download the report to explore the data: https://lnkd.in/gx6Qt7SD

While some companies are still piloting GenAI, Mastercard is running AI inference on ~160B transactions a year — with just 50ms to score each payment. In this VentureBeat podcast episode, Mastercard’s Johan Gerber and Chris Merz break down Decision Intelligence Pro, their RNN-based “inverse recommender” that predicts legitimate behavior in real time, and how GenAI honeypots help expose mule accounts. They also share why moving to Databricks and the cloud was critical to accelerating model development, cutting innovation cycles from months to hours. https://lnkd.in/gsWSJqcn