FedEx, a global leader in transportation and logistics, faced a common challenge in the era of big data: how to democratize data and foster data-driven decision making with thousands of data practitioners at FedEx wanting to build models, get real-time insights, explore enterprise data, and build enterprise-grade solutions to run the business. This breakout session will highlight how FedEx overcame challenges in data governance and security using Unity Catalog, ensuring that sensitive information remains protected while still allowing appropriate access across the organization. We'll share their approach to building intuitive self-service interfaces, including the use of natural-language processing to enable non-technical users to query data effortlessly. The tangible outcomes of this initiative are numerous, but chiefly: increased data literacy across the company, faster time-to-insight for business decisions, and significant cost-savings through improved operational efficiency.

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.

Modern data workloads span multiple sources — data lakes, databases, apps like Salesforce and services like cloud functions. But as teams scale, secure data access and governance across shared compute becomes critical. In this session, learn how to confidently integrate external data and services into your workloads using Spark and Unity Catalog on Databricks. We'll explore compute options like serverless, clusters, workflows and SQL warehouses, and show how Unity Catalog’s Lakeguard enforces fine-grained governance — even when concurrently sharing compute by multiple users. Walk away ready to choose the right compute model for your team’s needs — without sacrificing security or efficiency.

Global Data at Scale: Powering Front Office Transformation with DatabricksJoin KPMG for an engaging session on how we transformed our data platform and built a cutting-edge Global Data Store (GDS)—a game-changing data hub for our Front Office Transformation (FOT). Discover how we seamlessly unified data from various member firms, turning it into a dynamic engine for and enabled our business to leverage our Front Office ecosystem to enable smarter analytics and decision-making. Learn about our unique approach that rapidly integrates diverse datasets into the GDS and our hub-and-spoke model, connecting member firms’ data lakes, enabling secure, high-speed collaboration via Delta Sharing. Hear how we are leveraging Unity Catalog to help ensure data governance, compliance, and straight forward data lineage. We’ll share strategies for risk management, security (fine-grained access, encryption), and scaling a cloud-based data ecosystem.

Learn how to build sophisticated systems that enable natural language interactions with both your structured databases and unstructured document collections. This session explores advanced techniques for creating unified and governed AI systems that can seamlessly interpret questions, retrieve relevant information and generate accurate answers across your entire data ecosystem. Key takeaways include: Strategies for combining vector search over unstructured documents with retrieval from structured databases Techniques for optimizing unstructured data processing through effective parsing, metadata enrichment and intelligent chunking Methods for integrating different retrieval mechanisms while ensuring consistent data governance and security Practical approaches for evaluating and improving KBQA system quality through automated and human feedback

Morgan Stanley, a highly regulated financial institution, needs to meet stringent security and regulatory requirements around data storage and processing. Traditionally, this has necessitated maintaining control over data and compute within their own accounts with the associated management overhead. In this session, we will cover how Morgan Stanley has partnered with Databricks on a fully-managed compute and storage solution that allows them to meet their regulatory obligations with significantly reduced effort. This innovative approach enables rapid onboarding of new projects onto the platform, improving operational efficiency while maintaining the highest levels of security and compliance.

Lakeflow Connect streamlines the ingestion of incremental data from popular databases like SQL Server and PostgreSQL. In this session, we’ll review best practices for networking, security, minimizing database load, monitoring and more — tailored to common industry scenarios. Join us to gain practical insights into Lakeflow Connect's functionality so that you’re ready to build your own pipelines. Whether you're looking to optimize data ingestion or enhance your database integrations, this session will provide you with a deep understanding of how Lakeflow Connect works with databases.

AWS Marketplace is revolutionizing how enterprises worldwide discover, procure, and manage their software solutions. With access to over 5,000+ verified sellers offering software, data, and professional services - including industry leaders like Databricks - organizations can streamline procurement through flexible pricing models and simplified terms. The platform seamlessly integrates with AWS services while providing consolidated billing, centralized governance, and streamlined vendor management. Through innovations like Buy with AWS, customers can purchase directly from Partner websites, making software acquisition more efficient than ever. Join us to learn how AWS Marketplace is driving value for both customers and Partners, helping organizations accelerate their digital transformation while maintaining security and compliance.

Join us as we explore the well-architected framework for modern data lakehouse architecture, where AWS's comprehensive data, AI, and infrastructure capabilities align with Databricks' unified platform approach. Building upon core principles of Operational Excellence, Security, Reliability, Performance, and Cost Optimization, we'll demonstrate how Data and AI Governance alongside Interoperability and Usability enable organizations to build robust, scalable platforms. Learn how Ripple modernized its data infrastructure by migrating from a legacy Hadoop system to a scalable, real-time analytics platform using Databricks on AWS. This session covers the challenges of high operational costs, latency, and peak-time bottlenecks—and how Ripple achieved 80% cost savings and 55% performance improvements with Photon, Graviton, Delta Lake, and Structured Streaming.

Modern companies are managing more data than ever before, and the need to derive value from that data is becoming more urgent with AI. But AI adoption is often limited due to data security challenges, and adding to this complexity is the need to remain compliant with evolving regulation. At Capital One, we’ve deployed tokenization to further secure our data without compromising performance. In this talk, we’ll discuss lessons learned from our tokenization journey and show how companies can tokenize the data in their Databricks environment.

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.

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.

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.

The Delta Lake architecture promises to provide a single, highly functional, and high-scale copy of data that can be leveraged by a variety of tools to satisfy a broad range of use cases. To date, most use cases have focused on interactive data warehousing, ETL, model training, and streaming. Real-time access is generally delegated to costly and sometimes difficult-to-scale NoSQL, indexed storage, and domain-specific specialty solutions, which provide limited functionality compared to Spark on Delta Lake. In this session, we will explore the Delta data-skipping and optimization model and discuss how Capital One leveraged it along with Databricks photon and Spark Connect to implement a real-time web application backend. We’ll share how we built a highly-functional and performant security information and event management user experience (SIEM UX) that is cost effective.

As online gaming evolves, so do cheating methods that exploit client-server vulnerabilities. Traditional anti-cheat, such as kernel-level drivers and runtime detections, has long been the primary defense. However, advanced cheats like Direct Memory Access (DMA) exploits and AI-powered Computer Vision (CV) hacks increasingly render client-side detection ineffective. This presentation examines the escalating arms race between cheat creators and developers, highlighting client-side limitations. With CV cheats mimicking human behavior, anti-cheat must shift toward server-side, data-driven detection. By leveraging AI, machine learning, and behavioral analytics to analyze player patterns, input anomalies, and decision inconsistencies, future solutions can move beyond static detection to adaptive security models, ensuring fair play at scale. The session will also include real-life examples from Riot Games’ anti-cheat efforts, specifically insights and case studies from the development and operation of Riot Vanguard, to illustrate how these strategies are applied in practice.

Securing Databricks using Databricks as SIEM showcases our approach on how we leverage Databricks product capabilities to prevent and mitigate security risks for Databricks. It demonstrates how Databricks can serve as a powerful Security Information and Event Management (SIEM) platform, offering advanced capabilities for data collection and threat detection. This session explores data collection from diverse data sources and real-time threat detection.

Delta Sharing enables cross-domain sharing of data assets for collaboration. A practical concern providers and recipients face in doing so is the need to manually configure network and storage firewalls. This is particularly challenging for large-scale providers and recipients with strict compliance requirements. In this talk, we will describe our solution to fully eliminate these complexities. This enhances user experience, scalability and security, facilitating seamless data collaboration across diverse environments and cloud platforms.

Despite the proliferation of cloud data warehousing, BI tools, and AI, spreadsheets are still the most ubiquitous data tool. Business teams in finance, operations, sales, and marketing often need to analyze data in the cloud data warehouse but don't know SQL and don't want to learn BI tools. AI tools offer a new paradigm but still haven't broadly replaced the spreadsheet. With new AI tools and legacy BI tools providing business teams access to data inside Databricks, security and governance are put at risk. In this session, Row Zero CEO, Breck Fresen, will share examples and strategies data teams are using to support secure spreadsheet analysis at Fortune 500 companies and the future of spreadsheets in the world of AI. Breck is a former Principal Engineer from AWS S3 and was part of the team that wrote the S3 file system. He is an expert in storage, data infrastructure, cloud computing, and spreadsheets.

As organizations increasingly adopt Databricks as a unified platform for analytics and AI, ensuring robust data governance becomes critical for compliance, security, and operational efficiency. This presentation will explore the end-to-end framework for governing the Databricks cloud, covering key use cases, foundational governance principles, and scalable automation strategies. We will discuss best practices for metadata, data access, catalog, classification, quality, and lineage, while leveraging automation to streamline enforcement. Attendees will gain insights into best practices and real-world approaches to building a governed data cloud that balances innovation with control.

Join cybersecurity leaders from SAP, Anvilogic, Capital One, Wiz, and Databricks to explore how modern data intelligence is transforming security operations. Discover how SAP adopted a modular, AI-powered detection engineering lifecycle using Anvilogic on Databricks. Learn how Capital One built a detection and correlation engine leveraging Delta Lake, Apache Spark Streaming, and Databricks to process millions of cybersecurity events per second. Finally, see how Wiz and Databricks’ partnership enhances cloud security with seamless threat visibility. Through expert insights and live demos, gain strategies to build scalable, efficient cybersecurity powered by data and AI.

Join the 60-minute kickoff session at the Public Sector Forum for an opportunity to to accelerate innovation into your enterprise through governance, compliance and GenAI. Featuring keynotes from data-driven agency leaders and providing a future-looking journey from Databricks, this event offers invaluable insights. Understand the outcomes of Data and AI powering transformation across common areas of government and beyond: Improving constituent experience Reducing cost and enhancing services Identifying fraud, waste and abuse Achieving scale and security You will not want to miss this exclusive opportunity to own your data and eliminate government silos. Discover the Data + AI Company with deep compliance experience and widespread adoption.

Westat, a leader in data-driven research for 60 years+, has implemented a centralized Databricks platform to support hundreds of research projects for government, foundations, and private clients. This initiative modernizes Westat’s technical infrastructure while maintaining rigorous statistical standards and streamlining data science. The platform enables isolated project environments with strict data boundaries, centralized oversight, and regulatory compliance. It allows project-specific customization of compute and analytics, and delivers scalable computing for complex analyses. Key features include config-driven Infrastructure as Code (IaC) with Terragrunt, custom tagging and AWS cost integration for ROI tracking, budget policies with alerts for proactive cost management, and a centralized dashboard with row-level security for self-service cost analytics. This unified approach provides full financial visibility and governance while empowering data teams to deliver value. Audio for this session is delivered in the conference mobile app, you must bring your own headphones to listen.

Learn how GenAI is being applied to financial services teams using Claude, an acknowledged leader in large language models. Integrated with the scale and security of the Databricks Data Intelligence Platform, we will share how Claude is enabling financial services organizations to streamline operations, maximize productivity for investment and compliance teams and in some cases turn traditional cost-centers into revenue drivers.

The Global Water Security Center translates environmental science into actionable insights for the U.S. Department of Defense. Prior to incorporating Databricks, responding to these requests required querying approximately five hundred thousand raster files representing over five hundred billion points. By leveraging lakehouse architecture, Databricks Auto Loader, Spark Streaming, Databricks Spatial SQL, H3 geospatial indexing and Databricks Liquid Clustering, we were able to drastically reduce our “time to analysis” from multiple business days to a matter of seconds. Now, our data scientists execute queries on pre-computed tables in Databricks, resulting in a “time to analysis” that is 99% faster, giving our teams more time for deeper analysis of the data. Additionally, we’ve incorporated Databricks Workflows, Databricks Asset Bundles, Git and Git Actions to support CI/CD across workspaces. We completed this work in close partnership with Databricks.