The implementation of the Databricks AI Factory enabled Seven West Media to transform its business by accelerating the launch of AI-driven use cases, fostering innovation and reducing time to market. By leveraging a unified data and AI platform, the company achieved better ROI through optimized workflows, improved operational efficiency and scalable machine learning models. The AI Factory empowered data teams to experiment faster, unlocking deeper audience insights that enhanced engagement and content personalization. This transformation positioned Seven West Media as a leader in AI-driven media, driving measurable business impact and future-proofing its data strategy.

Every analytics, BI and AI project relies on high-quality data. This is why data engineering, the practice of building reliable data pipelines that ingest and transform data, is consequential to the success of these projects. In this session, we'll show how you can use Lakeflow to accelerate innovation in multiple parts of the organization. We'll review real-world examples of Databricks customers using Lakeflow in different industries such as automotive, healthcare and retail. We'll touch on how the foundational data engineering capabilities Lakeflow provides help power initiatives that improve customer experiences, make real-time decisions and drive business results.

In this presentation, we’ll dive into the power of Liquid Clustering—an innovative, out-of-the-box solution that automatically tunes your data layout to scale effortlessly with your datasets. You’ll get a deep look at how Liquid Clustering works, along with real-world examples of customers leveraging it to unlock blazing-fast query performance on petabyte-scale datasets. We’ll also give you an exciting sneak peek into the roadmap ahead, with upcoming features and enhancements to come.

In this session, we’ll introduce Zerobus Direct Write API, part of Lakeflow Connect, which enables you to push data directly to your lakehouse and simplify ingestion for IOT, clickstreams, telemetry, and more. We’ll start with an overview of the ingestion landscape to date. Then, we'll cover how you can “shift left” with Zerobus, embedding data ingestion into your operational systems to make analytics and AI a core component of the business, rather than an afterthought. The result is a significantly simpler architecture that scales your operations, using this new paradigm to skip unnecessary hops. We'll also highlight one of our early customers, Joby Aviation and how they use Zerobus. Finally, we’ll provide a framework to help you understand when to use Zerobus versus other ingestion offerings—and we’ll wrap up with a live Q&A so that you can hit the ground running with your own use cases.

This session dives into building multi-agent systems on the Mosaic AI Platform, exploring the techniques, architectures and lessons learned from experiences building Greenlight’s real-world agent applications. This presentation is well suited for executives, product managers and engineers alike, breaking down AI Agents into easy-to-understand concepts, while presenting an architecture for building complex systems. We’ll examine the core components of generative AI Agents and different ways to assemble them into agents, including different prompting and reasoning techniques. We’ll cover how the Mosaic AI Platform has enabled our small team to build, deploy and monitor our AI Agents, touching on vector search, feature and model serving endpoints, and the evaluation framework. Finally, we’ll discuss the pros and cons of building a multi-agent system consisting of specialized agents vs. a single large agent for Greenlight’s AI Assistant, and the challenges we encountered.

Imagine performing complex regulatory checks in minutes instead of days. We made this a reality using GenAI on the Databricks Data Intelligence Platform. Join us for a deep dive into our journey from POC to a production-ready AI audit tool. Discover how we automated thousands of legal requirement checks in annual reports with remarkable speed and accuracy. Learn our blueprint for: High-Performance AI: Building a scalable, >90% accurate AI system with an optimized RAG pipeline that auditors praise. Robust Productionization: Achieving secure, governed deployment using Unity Catalog, MLflow, LLM-based evaluation, and MLOps best practices. This session provides actionable insights for deploying impactful, compliant GenAI in the enterprise.

This deep dive covers advanced usage patterns, tips and best practices for maximizing the potential of Lakeflow Declarative Pipelines. Attendees will explore new features, enhanced workflows and cost-optimization strategies through a demo-heavy presentation. The session will also address complex use cases, showcasing how Lakeflow Declarative Pipelines simplifies the management of robust data pipelines while maintaining scalability and efficiency across diverse data engineering challenges.

This session is repeated. This introductory workshop caters to data engineers seeking hands-on experience and data architects looking to deepen their knowledge. The workshop is structured to provide a solid understanding of the following data engineering and streaming concepts: Introduction to Lakeflow and the Data Intelligence Platform Getting started with Lakeflow Declarative Pipelines for declarative data pipelines in SQL using Streaming Tables and Materialized Views Mastering Databricks Workflows with advanced control flow and triggers Understanding serverless compute Data governance and lineage with Unity Catalog Generative AI for Data Engineers: Genie and Databricks Assistant We believe you can only become an expert if you work on real problems and gain hands-on experience. Therefore, we will equip you with your own lab environment in this workshop and guide you through practical exercises like using GitHub, ingesting data from various sources, creating batch and streaming data pipelines, and more.

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.

Building scalable, reliable ETL pipelines is a challenge for organizations managing large, diverse data sources. Theseus, our custom ETL framework, streamlines data ingestion and transformation by fully leveraging Databricks-native capabilities, including Lakeflow Declarative Pipelines, auto loader and event-driven orchestration. By decoupling supplier logic and implementing structured bronze, silver, and gold layers, Theseus ensures high-performance, fault-tolerant data processing with minimal operational overhead. The result? Faster time-to-value, simplified governance and improved data quality — all within a declarative framework that reduces engineering effort. In this session, we’ll explore how Theseus automates complex data workflows, optimizes cost efficiency and enhances scalability, showcasing how Databricks-native tools drive real business outcomes.

In this talk, we will discuss the lessons learned and future vision of transforming two business units to a modern financial data platform at Nasdaq. We'll highlight the transition from disjointed systems to a unified platform using Databricks. Our target audience includes financial engineers, data architects and technical leaders. The agenda covers challenges of legacy systems, reasons for choosing Databricks and key architectural decisions.

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.

HR departments increasingly rely on data to improve workforce planning and experiences. However, managing and getting value from this data can be challenging, especially given the complex technology landscape and the need to ensure data security and compliance. Shell has placed a high priority on safeguarding its people data while empowering its HR department with the tools and access they need to make informed decisions. This session will explore the transformation of Shell's Central Data Platform, starting with their HR use case. You’ll hear about:- The role of automation and data governance, quality, and literacy in Shell’s strategy.- Why they chose Databricks and Immuta for enhanced policy-based access control.- The future for Shell and their vision for a data marketplace to truly embrace a culture of global data sharing.The result? A robust, scalable HR Data Platform that is securely driving a brighter future for Shell and its employees.

Dive into the latest Llama 4 models. See for yourself how to unleash the power of Llama models and achieve next level performance with our curated set of practical tools, techniques and recipes. Join us as we dive into the world of Llama models, exploring their capabilities, developer tools, and exciting use cases. Discover how these innovative models are transforming industries and improving performance in real-world applications.

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.