We’re excited to share with you how SAP Business Data Cloud supports Delta Sharing to share SAP data securely and seamlessly with Databricks—no complex ETL or data duplication required. This enables organizations to securely share SAP data for analytics and AI in Databricks while also supporting bidirectional data sharing back to SAP.In this session, we’ll demonstrate the integration in action, followed by a discussion of how the global beauty group, Natura, will leverage this solution. Whether you’re looking to bring SAP data into Databricks for advanced analytics or build AI models on top of trusted SAP datasets, this session will show you how to get started — securely and efficiently.

Enterprises generate massive amounts of unstructured data — from support tickets and PDFs to emails and product images. But extracting insight from that data requires brittle pipelines and complex tools. Databricks AI Functions make this simpler. In this session, you’ll learn how to apply powerful language and vision models directly within your SQL and ETL workflows — no endpoints, no infrastructure, no rewrites. We’ll explore practical use cases and best practices for analyzing complex documents, classifying issues, translating content, and inspecting images — all in a way that’s scalable, declarative, and secure. What you’ll learn: How to run state-of-the-art LLMs like GPT-4, Claude Sonnet 4, and Llama 4 on your data How to build scalable, multimodal ETL workflows for text and images Best practices for prompts, cost, and error handling in production Real-world examples of GenAI use cases powered by AI Functions

Discover how Adobe is redefining its Data Supply Chain through an AI-first, agentic solution that transforms the entire Data Development and Delivery Lifecycle (DDLC). This next-generation engineering workbench empowers data engineers, analysts, and practitioners with intelligent automation, context-aware assistance, and seamless collaboration to accelerate and streamline every phase of the data supply chain — from capturing business intent and sourcing data to building pipelines, validating quality, and delivering trusted, actionable insights.

Blue Origin is revolutionizing space exploration with a mission-critical data strategy powered by Databricks on AWS GovCloud. Learn how they leverage Databricks to meet ITAR and FedRAMP High compliance, streamline manufacturing and accelerate their vision of a 24/7 factory. Key use cases include predictive maintenance, real-time IoT insights and AI-driven tools that transform CAD designs into factory instructions. Discover how Delta Lake, Structured Streaming and advanced Databricks functionalities like Unity Catalog enable real-time analytics and future-ready infrastructure, helping Blue Origin stay ahead in the race to adopt generative AI and serverless solutions.

Feastables, founded by YouTube sensation MrBeast, partnered with Engine to build a modern, AI-enabled BI ecosystem that transforms complex, disparate data into actionable insights, driving smarter decision-making across the organization. In this session, learn how Engine, a Built-On Databricks Partner, brought expertise combined with strategic partnerships that enabled Feastables to rapidly stand up a secure, modern data estate to unify complex internal and external data sources into a single, permissioned analytics platform. Feastables unlocked the power of cross-functional collaboration by democratizing data access throughout their enterprise and seamlessly integrating financial, retailer, supply chain, syndicated, merchandising and e-commerce data. Discover how a scalable analytics framework combined with advanced AI models and tools empower teams with Smarter BI across sales, marketing, supply chain, finance and executive leadership to enable real-time decision-making at scale.

AI/BI Genie has transformed self-service analytics for the Databricks Marketing team. This user-friendly conversational AI tool empowers marketers to perform advanced data analysis using natural language — no SQL required. By reducing reliance on data teams, Genie increases productivity and enables faster, data-driven decisions across the organization. But realizing Genie’s full potential takes more than just turning it on. In this session, we’ll share the end-to-end journey of implementing Genie for over 200 marketing users, including lessons learned, best practices and the real business impact of this Databricks-on-Databricks solution. Learn how Genie democratizes data access, enhances insight generation and streamlines decision-making at scale.

Most enterprise data is trapped in unstructured formats — documents, PDFs, scanned images and tables — making it difficult to access, analyze and use. This session shows how to unlock that hidden value by building intelligent document processing workflows on the Databricks Data Intelligence Platform. You’ll learn how to ingest unstructured content using Lakeflow Connect, extract structured data with AI Parse — even from complex tables and scanned documents — and apply analytics or AI to this newly structured data. What you’ll learn: How to build scalable pipelines that transform unstructured documents into structured tables Techniques for automating document workflows with Databricks tools Strategies for maintaining quality and governance with Unity Catalog Real-world examples of AI applications built with intelligent document processing

Ever struggled with getting AI to work effectively for your specific domain needs? Join us to discover how establishing the right data foundation transforms the way you build and deploy specialized AI agents. This session demonstrates how to prepare and structure your information assets to enable more powerful, efficient AI applications. Learn proven approaches for extracting value from both structured and unstructured data, creating knowledge bases that serve as the backbone for domain-specific agents, and implement optimization techniques that balance quality and resource constraints.Key takeaways: Preparing diverse data sources for AI consumption and knowledge extraction Building scalable data foundations that naturally facilitate agent development Optimizing domain-specific agents for performance and cost efficiency Implementing practical governance frameworks for AI systems built on your data

In this presentation, we showcase Reckitt’s journey to develop and implement a state-of-the-art Gen AI platform, designed to transform enterprise operations starting with the marketing function. We will explore the unique technical challenges encountered and the innovative architectural solutions employed to overcome them. Attendees will gain insights into how cutting-edge Gen AI technologies were integrated to meet Reckitt’s specific needs. This session will not only highlight the transformative impacts on Reckitt’s marketing operations but also serve as a blueprint for AI-driven innovation in the Consumer Goods sector, demonstrating a successful model of partnership in technology and business transformation.

T-Mobile’s leadership in 5G innovation and its rapid growth in the fixed wireless business have led to an exponential increase in data, reaching 100s of terabytes daily. This session explores how T-Mobile uses Databricks to manage this data efficiently, focusing on scalable architecture with Delta Lake, auto-scaling clusters, performance optimization through data partitioning and caching and comprehensive data governance with Unity Catalog. Additionally, it covers cost management, collaborative tools and AI-driven productivity tools, highlighting how these strategies empower T-Mobile to innovate, streamline operations and maximize data impact across network optimization, supporting the community, energy management and more.

Curious how to apply resource-intensive generative AI models across massive datasets without breaking the bank? This session reveals efficient batch inference strategies for foundation models on Databricks. Learn how to architect scalable pipelines that process large volumes of data through LLMs, text-to-image models and other generative AI systems while optimizing for throughput, cost and quality. Key takeaways: Implementing efficient batch processing patterns for foundation models using AI functions Optimizing token usage and prompt engineering for high-volume inference Balancing compute resources between CPU preprocessing and GPU inference Techniques for parallel processing and chunking large datasets through generative models Managing model weights and memory requirements across distributed inference tasks You'll discover how to process any scale of data through your generative AI models efficiently.

Two industry veterans have been debating data architecture, tearing apart trends and tinkering with tech for decades and they’re bringing the conversation live — and you’re in control. Got a burning question about lake structures or internal performance? Worried about AI taking over the world? Want straight-talking opinions on the latest hype? Need real-world advice from the people who the experts get advice from? Want to get the juicy behind-the-scenes gossip about any announcements and shockwaves from the Keynotes? This is your chance to have your questions answered! Submit your questions ahead of time or bring them on the day — no topic is off-limits (though there's always a risk of side quests into coffee, sci-fi, or the quirks of English weather). Come for the insights, stay for the chaos.

A successful data strategy requires the right platform and the ability to empower the broader user community by creating simple, scalable and secure patterns that lower the barrier to entry while ensuring robust data practices. Guided by the belief that everyone is a data person, we focus on breaking down silos, democratizing access and enabling distributed teams to contribute through a federated "data-as-a-product" model. We’ll share the impact and lessons learned in creating a single source of truth on Unity Catalog, consolidated from diverse sources and cloud platforms. We’ll discuss how we streamlined governance with Databricks Apps, Workflows and native capabilities, ensuring compliance without hindering innovation. We’ll also cover how we maximize the value of that catalog by leveraging semantics to enable trustworthy, AI-driven self-service in AI/BI dashboards and downstream apps. Come learn how we built a next-gen data ecosystem that empowers everyone to be a data person.

Join us as we dive into how Turnpoint Services, in collaboration with DataNimbus, built an Intelligence Platform on Databricks in just 30 days. We'll explore features like MLflow, LLMs, MLOps, Model Registry, Unity Catalog & Dashboard Alerts that powered AI applications such as Demand Forecasting, Customer 360 & Review Automation. Turnpoint’s transformation enabled data-driven decisions, ops efficiency & a better customer experience. Building a modern data foundation on Databricks optimizes resource allocation & drives engagement. We’ll also introduce innovations in DataNimbus Designer: AI Blocks: modular, prompt-driven smart transformers for text data, built visually & deployed directly within Databricks. These capabilities push the boundaries of what's possible on the Databricks platform. Attendees will gain practical insights, whether you're beginning your AI journey or looking to accelerate it.

How do you transform legacy data into a launchpad for next-gen innovation? GE Vernova is tackling it by rapidly migrating from outdated platforms to Databricks, building one of the world’s largest cloud data implementations. This overhaul wasn’t optional. Scaling AI, cutting technical debt, and slashing license costs demanded a bold, accelerated approach. Led by strategic decisions from the CDO and powered by Genpact’s AI Gigafactory, the migration is tackling 35+ Business and sub domains, 60,000+ data objects, 15,000+ jobs, 3000+ reports from 120+ diverse data sources to deliver a multi-tenant platform with unified governance. The anticipated results? Faster insights, seamless data sharing, and a standardized platform built for AI at scale. This session explores how Genpact and Databricks are fueling GE Vernova’s mission to deliver The Energy to Change the World—and what it takes to get there when speed, scale, and complexity are non-negotiable.

This session unveils Google Cloud's Agent2Agent (A2A) protocol, ushering in a new era of AI interoperability where diverse agents collaborate seamlessly to solve complex enterprise challenges. Join our panel of experts to discover how A2A empowers you to deeply integrate these collaborative AI systems with your existing enterprise data, custom APIs, and critical workflows. Ultimately, learn to build more powerful, versatile, and securely managed agentic ecosystems by combining specialized Google-built agents with your own custom solutions (Vertex AI or no-code). Extend this ecosystem further by serving these agents with Databricks Model Serving and governing them with Unity Catalog for consistent security and management across your enterprise.

As enterprises continue their journey to the cloud, data warehouse and data management modernization is essential to optimize analytics and drive business outcomes. Minimizing modernization timelines is important for reducing risk and shortening time to value – and ensuring enterprise data is clean, curated and governed is imperative to enable analytics and AI initiatives. In this session, learn how Informatica's Intelligent Data Management Cloud (IDMC) empowers analytics and AI on Databricks by helping data teams: · Develop no-code/low-code data pipelines that ingest, transform and clean data at enterprise scale · Improve data quality and extend enterprise governance with Informatica Cloud Data Governance and Catalog (CDGC) and Unity Catalog · Accelerate pilot-to-production with Mosaic AI

Agentic AI has the power to revolutionize mission-critical domains. Yet this journey is not without its challenges – the inevitable barriers, frustrations, and setbacks that mark all progress. This session dives into how Infosys Topaz helps enterprises to strategically implement AI at scale in as little as two months to personalize customer journeys, optimize operations, and unlock new revenue streams. Learn how different enterprises have architected foundation capabilities such as Agentic AI factory to build & accommodate hundreds or even thousands of intelligent agents, setting up data fingerprinting and data harvesting to make enterprise Data ready for AI and ensuring interoperability among diverse AI systems

Join us for this session focused on how leading tech companies are enabling data intelligence across their organizations while maintaining cost efficiency and governance. Hear the successes and the challenges when Databricks empowers thousands of users—from engineers to business teams—by providing scalable tools for AI, BI and analytics. Topics include: Combining AI/BI and Lakehouse Apps to streamline workflows and accelerate insights Implementing systems tables, tagging and governance frameworks for granular control Democratizing data access while optimizing costs for large-scale analytical workloads Hear from customers and Databricks experts, followed by a customer panel featuring industry leaders. Gain insights into how Databricks helps tech innovators scale their platforms while maintaining operational excellence.

How are today’s leading telecom operators transforming customer experience at scale with data and AI? Join us for an inspiring fireside chat with senior leaders from Optus, Plume and AT&T as they share their transformation stories — from the first steps to major milestones and the tangible business impact achieved with Databricks’ Data Intelligence Platform. You’ll hear firsthand how these forward-thinking CSP’s are driving measurable outcomes through unified data, machine learning and AI. Discover the high-impact use cases they’re prioritizing — like proactive care and hyper-personalization — and gain insight into their bold vision for the future of customer experience in telecom. Whether you're just beginning your AI journey or scaling to new heights, this session offers an authentic look at what’s working, what’s next and how data and AI are helping telecoms lead in a competitive landscape.