Want to learn how to build your own custom data intelligence applications directly in Databricks? In this workshop, we’ll guide you through a hands-on tutorial for building a Streamlit web app that leverages many of the key products at Databricks as building blocks. You’ll integrate a live DB SQL warehouse, use Genie to ask questions in natural language, and embed AI/BI dashboards for interactive visualizations. In addition, we’ll discuss key concepts and best practices for building production-ready apps, including logging and observability, scalability, different authorization models, and deployment. By the end, you'll have a working AI app—and the skills to build more.

The convergence of cloud, data and AI is revolutionizing the pharmaceutical industry, creating a powerful ecosystem that drives innovation at scale across the entire value chain. At Gilead, teams harness these technologies on a unified cloud, data, & AI platform, accelerating business processes in pre-clinical and clinical stage, enabling smarter manufacturing and commercial processes, and deliver AI initiatives by reusing data products. Gilead will discuss how they have leveraged AWS, Databricks, and Data Mesh to manage vast amounts of heterogeneous data. Also, showcase use cases of traditional AI/ML, and Generative AI, and a Marketplace approach to drive adoption of AI Agents, demonstrating how this cloud-based, AI-powered platform is transforming the entire value chain. Gilead will also discuss how they are exploring the future of pharmaceutical innovation through Agentic AI, where the synergy of cloud, data and AI is unlocking new possibilities for a healthier world. In the second part, Muddu Sudhakar, Founder and Investor, will discuss how organizations can build and buy solutions for AI, Agents with Data Platforms. AWS and Databricks provide industry-leading platforms to build Agentic AI solutions. We will also cover Agentic AI Platform, Agent orchestration, Agent Interoperability, Agent Guardrails and Agentic workflows. This discussion also covers challenges in deploying and managing Agentic AI platforms. Enterprises need impactful AI initiatives & Agents to realize the promise and vision of AI and drive significant ROI.

Today’s organizations need faster, more reliable insights — but metric sprawl and inconsistent KPIs make that difficult. In this session, you’ll learn how Unity Catalog Metrics helps unify business semantics across your organization. Define your KPIs once, apply enterprise-grade governance with fine-grained access controls, auditing and lineage, and use them across any Databricks tool — from AI/BI Dashboards and Genie to notebooks and Lakeflow. You’ll learn how to eliminate metric chaos by centrally defining and governing metrics with Unity Catalog. You’ll walk away with strategies to boost trust through built-in governance and empower every team — regardless of technical skill — to work from the same certified metrics.

Take a front-row seat for a comprehensive, high-level introduction to Mosaic AI through the lens of Data Intelligence. In this session, we’ll spotlight the Databricks Platform’s newest features and announcements, showcase how Mosaic AI transforms raw enterprise data into actionable insights and share real-world examples of success. Whether you’re beginning your AI journey or scaling your existing efforts, this talk will provide you with the foundational knowledge and inspiration to fully leverage Mosaic AI for Data Intelligence and next-generation GenAI solutions.

Your data and AI use-cases are multiplying. At the same time, there is increased focus and scrutiny to meet sophisticated security and regulatory requirements. IQVIA utilizes serverless use-cases across data engineering, data analytics, and ML and AI, to empower their customers to make informed decisions, support their R&D processes and improve patient outcomes. By leveraging native controls on the platform, serverless enables them to streamline their use cases while maintaining a strong security posture, top performance and optimized costs. This session will go over IQVIA’s journey to serverless, how they met their security and regulatory requirements, and the latest and upcoming enhancements to the Databricks Platform.

As cheat developers evolve, so must detection techniques. This session will explore our methodologies, challenges and future directions, demonstrating how machine learning is transforming anti-cheat strategies and preserving competitive integrity in online gaming and how Databricks is enabling us to do so. As online gaming grows, maintaining fair play is an ongoing challenge. Call of Duty, a highly competitive first-person action game, faces aimbot usage—cheats that enable near-perfect accuracy, undermining fair play. Additionally, traditional detection methods are increasingly becoming less effective against advanced cheats that mimic human behavior. Machine learning presents a scalable and adaptive solution to this. We developed a data pipeline that collects features such as angle velocity, acceleration, etc. to train a deep neural network and deployed it. We are processing 30 million rows of data per hour for this detection on Databricks Platform.

Ready to streamline your ML lifecycle? Join us to explore MLflow 3.0 on Databricks, where we'll show you how to manage everything from experimentation to production with less effort and better results. See how this powerful platform provides comprehensive tracking, evaluation, and deployment capabilities for traditional ML models and cutting-edge generative AI applications. Key takeaways: Track experiments automatically to compare model performance Monitor models throughout their lifecycle across environments Manage deployments with robust versioning and governance Implement proven MLOps workflows across development stages Build and deploy generative AI applications at scale Whether you're an MLOps novice or veteran, you'll walk away with practical techniques to accelerate your ML development and deployment.

Learn how Data Profiling, Data Quality Monitoring, and Data Classification come together to provide end-to-end visibility into the health of your data and AI pipelines.

Discover how two industry leaders are delivering measurable business value through practical AI implementations. Lippert Components demonstrates their success in transforming customer support through GenAI, enhancing efficiency and reducing agent turnover across their million-call operation. Hypertherm shares how their innovative three-pronged automation approach revolutionized order processing, achieving 52% automation rates and handling 100,000 orders without human intervention in 2024, while freeing up valuable resources for strategic roles. These real-world applications showcase how AI solutions can drive operational excellence across customer service and supply chain domains.

At Second Dinner, delivering fast, personalized gameplay experiences is key to player engagement. In this session, Justin Wu shares how the team implemented real-time feature serving using Databricks to power responsive, data-driven game mechanics at scale. He’ll dive into the architecture, technical decisions, and trade-offs behind their solution—highlighting how they balance performance, scalability, and cost. Whether you're building live features or rethinking your game data stack, this session offers practical insights to accelerate your journey.

Unlock Genie's full potential with best practices for curating, deploying and monitoring Genie spaces at scale. This session offers a deep dive into the latest enhancements and provides practical guidance on designing high-quality spaces, streamlining deployment workflows and implementing robust monitoring to ensure accuracy and performance in production. Ideal for teams aiming to scale conversational analytics, you’ll leave with actionable strategies to keep your Genie spaces efficient, reliable and aligned with business outcomes.

Customer data is an organization's most valuable asset. It is also the hardest to govern and use in a dynamic business environment. Consumers can revoke their consent in an instant, regulations continue to grow, and internal data policies change. Most troubling is when cross-functional teams question whether, when, and how they can use customer data. How does an organization—let alone a data governance team and its stakeholders—manage this data and policy fragmentation, while enabling data use? Join product leaders from OneTrust as they explore new data governance practices and technologies for delivering AI-ready data. We’ll demo an integration that orchestrates data policy enforcement through Unity Data Catalog and the OneTrust Data Use Governance solution. Understand how this new offering in addition with OneTrust’s solutions for Consent & Preferences and AI Governance align your data governance & compliance initiatives for AI innovation.

Windsurf has taken the developer and vibe coding ecosystem by a storm since its launch in November 2024. Wave after wave of features like Tab, MCP support, browser Preview, web search, Deploys, etc. might all seem random, but there’s a method to the madness. We are building Windsurf to be the ultimate collaborative agent, one in which the human and the AI operate as if with the same brain. Windsurf will be everywhere the developer does work, understanding the entire SDLC, and providing value along the way. In this talk, you’ll learn how Windsurf drives its strategy and builds on the frontier for its users and customers.

Curious about the cutting-edge technology that's revolutionizing AI model performance? Join us for an in-depth exploration of TAO and discover how this innovative approach is transforming the capabilities of modern AI systems. This research-focused session peels back the layers of theoretical foundations, implementation challenges, and breakthrough applications that make TAO one of the most promising advancements in AI development. Key takeaways: Understanding the fundamental principles behind TAO and how it differs from conventional optimization techniques Examining the quantifiable improvements in model accuracy, efficiency, and generalization capabilities Exploring real-world case studies where TAO has solved previously intractable AI challenges Analyzing current research directions and future potential for further enhancements Whether you're a research scientist, AI engineer, or technical leader, this session will equip you with valuable insights into how TAO can be leveraged to push your AI models beyond current limitations.

Join us to discover how leading tech companies accelerate growth using open ecosystems and built-on solutions to foster collaboration, accelerate innovation and create scalable data products. This session will explore how organizations use Databricks to securely share data, integrate with partners and enable teams to build impactful applications powered by AI and analytics. Topics include: Using Delta Sharing for secure, real-time data collaboration across teams and partners Embedding analytics and creating marketplaces to extend product capabilities Building with open standards and governance frameworks to ensure compliance without sacrificing agility Hear real-world examples of how open ecosystems empower organizations to widen the aperture on collaboration, driving better business outcomes. Walk away with insights into how open data sharing and built-on solutions can help your teams innovate faster at scale.

Join us for an interactive breakout session designed to explore scalable, real-world solutions powered by Partners with Databricks. In this high-energy session, you'll hear from three of our leading partners — Accenture, Capgemini and Wipro — as they each deliver rapid-fire, 5-minute demos of their most impactful, production-grade solutions built for the telecom industry. From network intelligence to customer experience to AI-driven automation, these solutions are already driving tangible outcomes at scale. After the demos, you’ll have the unique opportunity to engage directly with each partner in a “speed dating” style format. Dive deep into the solutions, ask your questions and explore how these approaches can be tailored to your organization’s needs. Whether you're solving for churn, fraud, network ops or enterprise AI use cases, this session is your chance to connect, collaborate and walk away with practical ideas you can take back to your teams.

Ready to take your AI/BI dashboards to the next level? This session dives into the latest capabilities in Databricks AI/BI Dashboards and how to maximize impact across your organization. Learn how data authors can tailor visualizations for different audiences, optimize performance and seamlessly integrate with Genie for a unified analytics experience. We’ll also share practical tips on how business users and data teams can better collaborate — ensuring insights are accessible, actionable and aligned to business goals.

Join this session for a concise tour of Apache Spark™ 4.0’s most notable enhancements: SQL features: ANSI by default, scripting, SQL pipe syntax, SQL UDF, session variable, view schema evolution, etc. Data type: VARIANT type, string collation Python features: Python data source, plotting API, etc. Streaming improvements: State store data source, state store checkpoint v2, arbitrary state v2, etc. Spark Connect improvements: More API coverage, thin client, unified Scala interface, etc. Infrastructure: Better error message, structured logging, new Java/Scala version support, etc. Whether you’re a seasoned Spark user or new to the ecosystem, this talk will prepare you to leverage Spark 4.0’s latest innovations for modern data and AI pipelines.

Explore how AI is transforming business intelligence and data analytics across the Databricks platform. This session offers a comprehensive overview of AI-assisted capabilities, from generating dashboards and visualizations to integrating Genie on dashboards for conversational analytics. Whether you’re a data engineer, analyst or BI developer, this session will equip you to leverage AI with BI for better, smarter decisions.

Retail and CPG companies face growing pressure to better forecast demand, optimize pricing and manage inventory — yet traditional approaches take months to deploy and often require extensive engineering support. In this session, we will showcase Workcloud Modeling Studio, a low-code/no-code ML platform designed for data scientists working in retail and CPG. Learn how this tool improves forecasting accuracy and accelerates time-to-value from months to hours. We will walk through a real-world use case of demand forecasting for a retailer using Zebra's Modeling Studio. This talk will demonstrate how to build, train and deploy an ML forecasting pipeline — without reinventing the wheel.