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.

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.

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.

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.

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.

The demand for skilled Databricks data engineers continues to rise as enterprises accelerate their adoption of the Databricks platform. However, navigating the complex ecosystem of data engineering tools, frameworks and best practices can be overwhelming. This session provides a structured roadmap to becoming an expert Databricks data engineer, offering a clear progression from foundational skills to advanced capabilities. Acadford, a leading training provider, has successfully trained thousands of data engineers on Databricks, equipping them with the skills needed to excel in their careers and obtain professional certifications. Drawing on this experience, we will guide attendees through the most in-demand skills and knowledge areas through a combination of structured learning and practical insights. Key takeaways: Understand the core tech stack in Databricks Explore real-world code examples and live demonstrations Receive an actionable learning path with recommended resources

As insurers increasingly leverage IoT data to personalize policy pricing, reconciling disparate datasets across devices, policies, and insurers becomes mission-critical. In this session, learn how Nationwide transitioned from prototype workflows in Dataiku to a hardened data stack on Databricks, enabling scalable data governance and high-impact analytics. Discover how the team orchestrates data reconciliation across Postgres, Oracle, and Databricks to align customer driving behavior with insurer and policy data—ensuring more accurate, fair discounts for policyholders. With Anomalo’s automated monitoring layered on top, Nationwide ensures data quality at scale while empowering business units to define custom logic for proactive stewardship. We’ll also look ahead to how these foundations are preparing the enterprise for unstructured data and GenAI initiatives.

In today's fast-paced digital landscape, context is everything. Decisions made without understanding the full picture often lead to missed opportunities or suboptimal outcomes. Powering contextualized intelligence is at the heart of MathCo’s proprietary platform — NucliOS, a Databricks-Native Platform leveraging Databricks features across the data lifecycle like Unity Catalog, Delta Lake, MLFlow, and Notebooks. Join this session to discover how NucliOS reimagines the data journey end-to-end: from data discovery and preparation to advanced analysis, dynamic visualization, and scenario modeling, all the way through to operationalizing insights within business workflows. At every step, intelligent agents act in concert, accelerating innovation and delivering speed at scale.

Matei is a legend of open source: he started the Apache Spark project in 2009, co-founded Databricks, and worked on other widely used data and AI software, including MLflow, Delta Lake, and Dolly. His most recent research is about combining large language models (LLMs) with external data sources, such as search systems, and improving their efficiency and result quality. This will be a conversation coverering the latest and greatest of UC, Data Intelligence, AI Governance, and more.

Hear more on the latest in data collaboration, which is paramount to unlocking business success. Delta Sharing is an open-source approach to share and govern data, AI models, dashboards, and notebooks across clouds and platforms - without the costly need for replication. Databricks Clean Rooms provide safe hosting environments for data collaboration across companies, also without the costly duplication of data. And the Databricks Marketplace is the open marketplace for all your data, analytics, and AI needs.

Be first to witness the latest breakthroughs from Databricks and share the success of innovative data and AI companies.

Join this session to hear from two incredible companies, Xylem and Joby Aviation. Xylem shares their successful journey from fragmented legacy systems to a unified Enterprise Data Platform, demonstrating how they integrated complex ERP data across four business segments to achieve breakthrough improvements in parts management and operational efficiency. Following Xylem's story, learn how Joby Aviation leveraged Databricks to automate and accelerate flight test data checks, cutting processing times from over two hours to under thirty minutes. This session highlights how advanced cloud tools empower engineers to quickly build and run custom data checks, improving both speed and safety in flight test operations.

In the rapidly-evolving field of data analytics, (AI/BI) dashboards and Power BI stand out as two formidable approaches, each offering unique strengths and catering to specific use cases. Power BI has earned its reputation for delivering user-friendly, highly customisable visualisations and reports for data analysis. On the other hand, AI/BI dashboards have gained good traction due to their seamless integration with the Databricks platform, making them an attractive option for data practitioners. This session will provide a comparison of these two tools, highlighting their respective features, strengths and potential limitations. Understanding the nuances between these tools is crucial for organizations aiming to make informed decisions about their data analytics strategy. This session will equip participants with the knowledge needed to select the most appropriate tool or combination of tools to meet their data analysis requirements and drive data-informed decision-making processes.

This presentation explores how Databricks' Data Intelligence Platform supports the development and deployment of responsible AI in credit decisioning, ensuring fairness, transparency and regulatory compliance. Key areas include bias and fairness monitoring using Lakehouse Monitoring to track demographic metrics and automated alerts for fairness thresholds. Transparency and explainability are enhanced through the Mosaic AI Agent Framework, SHAP values and LIME for feature importance auditing. Regulatory alignment is achieved via Unity Catalog for data lineage and AIBI dashboards for compliance monitoring. Additionally, LLM reliability and security are ensured through AI guardrails and synthetic datasets to validate model outputs and prevent discriminatory patterns. The platform integrates real-time SME and user feedback via Databricks Apps and AI/BI Genie Space.

Collaboration is redefining efficiency in insurance. This session explores how technologies such as Databricks Delta Sharing, secure data clean rooms, and data marketplaces are empowering insurers to securely share and analyze data across organizational boundaries—without exposing sensitive information. Discover how these solutions streamline operations, enhance risk modeling with real-time data integration, and enable the creation of tailored products through multi-party collaboration. Learn how insurers are leveraging these collaborative data ecosystems to reduce costs, drive innovation, and deliver better customer outcomes, all while maintaining strong privacy and governance standards. Join us to see how embracing collaborative frameworks is helping insurers operate smarter, faster, and more efficiently.