Organizations have hundreds of data sources, some of which are very niche or difficult to access. Incorporating this data into your lakehouse requires significant time and resources, hindering your ability to work on more value-add projects. Enter the Fivetran Connector SDK- a powerful new tool that enables your team to create custom pipelines for niche systems, custom APIs, and sources with specific data filtering requirements, seamlessly integrating with Databricks. During this session, Fivetran will demonstrate how to (1) Leverage the Connector SDK to build scalable connectors, enabling the ingestion of diverse data into Databricks (2) Gain flexibility and control over historical and incremental syncs, delete capture, state management, multithreading data extraction, and custom schemas (3) Utilize practical examples, code snippets, and architectural considerations to overcome data integration challenges and unlock the full potential of your Databricks environment.

Supercharge advanced analytics and AI insights on Databricks with accurate and consistent master data. This session explores how Informatica’s Master Data Management (MDM) integrates with Databricks to provide high-quality, integrated golden record data like customer, supplier, product 360 or reference data to support downstream analytics, Generative AI and Agentic AI. Enterprises can accelerate and de-risk the process of creating a golden record via a no-code/low-code interface, allowing data teams to quickly integrate siloed data and create a complete and consistent record that improves decision-making speed and accuracy.

Learn how visionaries from the world’s leading organizations use Moveworks to give employees a single place to find information, automate tasks, and be more productive. See the Moveworks AI Assistant in action and experience how its reasoning-based architecture allows it to be a one-stop-shop for all employee requests (across IT, HR, finance, sales, and more), how Moveworks empowers developers to easily build new AI agents atop this architecture, and how we give stakeholders tools to implement effective AI governance. Finally, experience how customers and partners alike leverage information in Databricks to supplement their employees' AI journeys.

Unlock the power of your SAP data with SAP Business Data Cloud—a fully managed SaaS solution that unifies and governs all SAP data while seamlessly connecting it with third-party data. As part of SAP Business Data Cloud, SAP Databricks brings together trusted, semantically rich business data with industry-leading capabilities in AI, machine learning, and data engineering. Discover how to access curated SAP data products across critical business processes, enrich and harmonize your data without data copies using Delta Sharing, and leverage the results across your business data fabric. See it all in action with a demonstration.

Unity Catalog (UC) enables governance and security for all data and AI assets within an enterprise’s data lake and is necessary to unlock the full potential of Databricks as a true Data Intelligence Platform. Unfortunately, UC migrations are non-trivial; especially for enterprises that have been using Databricks for more than five years, i.e., 7-Eleven. System Integrators (SIs) offer accelerators, guides, and services to support UC migrations; however, cloud infrastructure changes, anti-patterns within code, and data sprawl can significantly complicate UC migrations. There is no “shortcut” to success when planning and executing a complex UC migration. In this session, we will share how UCX by Databricks Labs, a UC Migration Assistant, allowed 7-Eleven to reorient their UC migration by leveraging assessments and workflows, etc., to assess, characterize, and ultimately plan a tenable approach for their UC migration.

Earlier this year, we finished migration of all dashboards from a traditional BI system to Databricks AI/BI ecosystem, resulting in annual savings of approximately $900,000. We also unlocked the below advantages: Data security, integrity and safety Cost savings Single source of truth Real-time data Genie space We will speak about our journey and how you can migrate your dashboards from traditional BI to AI/BI. Having listed the advantages above, we will also speak of some challenges faced. Migration steps: Analytical scope of dashboard inventory Feature mapping: From traditional BI to AI/BI Building bronze, silver and gold tables Building dashboards Migration shenanigans: Hypercare phase Change management KT documents Demo sessions Deprecation of licenses and dashboards on traditional BI tools We look forward to sharing these lessons learned and insights with you to help you streamline your BI infrastructure and unlock the full potential of Databricks AI/BI.

Struggling to implement traditional machine learning models that deliver real business value? Join us for a hands-on exploration of classical ML techniques powered by Databricks' Mosaic AI platform. This session focuses on time-tested approaches like regression, classification and clustering — showing how these foundational methods can solve real business problems when combined with Databricks' scalable infrastructure and MLOps capabilities. Key takeaways: Building production-ready ML pipelines for common business use cases including customer segmentation, demand forecasting and anomaly detection Optimizing model performance using Databricks' distributed computing capabilities for large-scale datasets Implementing automated feature engineering and selection workflows Establishing robust MLOps practices for model monitoring, retraining and governance Integrating classical ML models with modern data processing techniques

The Databricks Lakehouse for Public Sector is the only enterprise data platform that allows you to leverage all your data, from any source, on any workload to always offer better citizen services/warfighter support/student success with the best outcomes, at the lowest cost, with the greatest investment protection.

Retail Media Networks (RMNs) are transforming how brands engage and connect with consumers throughout the omnichannel. In this session, Databricks and Hightouch will explore how data-driven advertising is reshaping retail promotions and enabling real-time activation of customer insights. Learn how unified data architectures and composable customer stacks are driving hyper-personalized, high-ROI campaigns. Whether you're a retailer monetizing first-party data or a brand optimizing ad spend, this session offers practical strategies and real-world examples to thrive in the evolving RMN landscape.

Databricks Clean Rooms make privacy-safe collaboration possible for data, analytics, and AI — across clouds and platforms. Built on Delta Sharing, Clean Rooms enable organizations to securely share and analyze data together in a governed, isolated environment — without ever exposing raw data. In this session, you’ll learn how to get started with Databricks Clean Rooms and unlock advanced use cases including: Cross-platform collaboration and joint analytics Training machine learning and AI models Enforcing custom privacy policies Analyzing unstructured data Incorporating proprietary libraries in Python and SQL notebooks Auditing clean room activity for compliance Whether you're a data scientist, engineer or data leader, this session will equip you to drive high-value collaboration while maintaining full control over data privacy and governance.

In this session, Joëlle van der Bijl, Chief Data & Analytics Officer at FrieslandCampina, shares the bold journey of replacing legacy data systems with a single, unified data, analytics, and AI platform built on Databricks. Rather than evolving gradually, the company took a leap: transforming its entire data foundation in one go. Today, this data-centric vision is delivering high-value impact: from optimizing milk demand and supply to enabling commercial AI prediction models and scaling responsible AI across the business. Learn how FrieslandCampina is using Databricks to blend tradition with innovation, and unlock a smarter, more sustainable future for dairy.

In this session, we’ll walk through the latest advancements in platform security and compliance on Databricks — from networking updates to encryption, serverless security and new compliance certifications across AWS, Azure and Google Cloud. We’ll also share our roadmap and best practices for how to securely configure workloads on Databricks SQL Serverless, Unity Catalog, Mosaic AI and more — at scale. If you're building on Databricks and want to stay ahead of evolving risk and regulatory demands, this session is your guide.

Databricks continues to redefine how organizations securely and openly collaborate on data. With new innovations like Clean Rooms for multi-party collaboration, Sharing for Lakehouse Federation, cross-platform view sharing and Databricks Apps in the Marketplace, teams can now share and access data more easily, cost-effectively and across platforms — whether or not they’re using Databricks. In this session, we’ll deliver live demos of key capabilities that power this transformation: Delta Sharing: The industry’s only open protocol for seamless cross-platform data sharing Databricks Marketplace: A central hub for discovering and monetizing data and AI assets Clean Rooms: A privacy-preserving solution for secure, multi-party data collaboration Join us to see how these tools enable trusted data sharing, accelerate insights and drive innovation across your ecosystem. Bring your questions and walk away with practical ways to put these capabilities into action today.

Picture the scene — you're exploring a deep, dark cave looking for insights to unearth when, in a burst of smoke, Genie appears and offers you not three but unlimited data wishes. This isn't a folk tale, it's the growing wave of Generative BI that is going to be a part of analytics platforms. Databricks Genie is a tool powered by a SQL-writing LLM that redefines how we interact with data. We'll look at the basics of creating a new Genie room, scoping its data tables and asking questions. We'll help it out with some complex pre-defined questions and ensure it has the best chance of success. We'll give the tool a personality, set some behavioural guidelines and prepare some hidden easter eggs for our users to discover. Generative BI is going to be a fundamental part of the analytics toolset used across businesses. If you're using Databricks, you should be aware of Genie, if you're not, you should be planning your Generative BI Roadmap, and this session will answer your wishes.

Databricks has been innovating the AI landscape, faster than ever before. Hear what's new directly from the Chief AI Scientist at Databricks, Jonathan Frankle, who co-founded MosaicML and now leads the AI research team.

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

Join a live recording of the Over Architected Databricks podcast with Nick and Holly as they take the hottest features for the coming week and try to shoehorn them into one architecture. Audio for this session is delivered in the conference mobile app, you must bring your own headphones to listen.

As data-driven companies scale from small startups to global enterprises, managing secure data access becomes increasingly complex. Traditional access control models fall short at enterprise scale, where dynamic, purpose-driven access is essential. In this talk, we explore how our “Just-in-Time” Purpose-Based Access Control (PBAC) platform addresses the evolving challenges of data privacy and compliance, maintaining least privilege while ensuring productivity. Using features like Unity Catalog, Delta Sharing & Databricks Apps, the platform delivers real-time, context-aware data governance. Leveraging JIT PBAC keeps your data secure, your engineers productive, your legal & security teams happy and your organization future-proof in the ever-evolving compliance landscape.

This session is repeated. Databricks Serverless revolutionizes data engineering and analytics by eliminating the complexities of infrastructure management. This talk will provide an overview of this powerful serverless compute option, highlighting how it enables practitioners to focus solely on building robust data pipelines. We'll explore the core benefits, including automatic scaling, cost optimization and seamless integration with the Databricks ecosystem. Learn how serverless workflows simplify the orchestration of various data tasks, from ingestion to dashboards, ultimately accelerating time-to-insight and boosting productivity. This session is ideal for data engineers, data scientists and analysts looking to leverage the agility and efficiency of serverless computing in their data workflows.

As machine learning (ML) models scale in complexity and impact, organizations must establish a robust MLOps foundation to ensure seamless model deployment, monitoring and retraining. In this session, we’ll share how we leverage Databricks as the backbone of our MLOps ecosystem — handling everything from workflow orchestration to large-scale inference. We’ll walk through our journey of transitioning from fragmented workflows to an integrated, scalable system powered by Databricks Workflows. You’ll learn how we built an automated pipeline that streamlines model development, inference and monitoring while ensuring reliability in production. We’ll also discuss key challenges we faced, lessons learned and best practices for organizations looking to operationalize ML with Databricks.