The insurance industry is at the crossroads of digital transformation, facing challenges from market competition and customer expectations. While conventional ML applications have historically provided capabilities in this domain, the emergence of Agentic AI frameworks presents a revolutionary opportunity to build truly autonomous insurance applications. We will address issues related to data governance and quality while discussing how to monitor/evaluate fine-tune models. We'll demonstrate the application of the agentic framework in the insurance context and how these autonomous agents can work collaboratively to handle complex insurance workflows — from submission intake and risk evaluation to expedited quote generation. This session demonstrates how to architect intelligent insurance solutions using Databricks Mosaic AI agentic core components including Unity Catalog, Playground, model evaluation/guardrails, privacy filters, AI functions and AI/BI Genie.

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.

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.

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.

Join the Unity Catalog product team for an exclusive deep dive into the latest innovations and upcoming features of Unity Catalog! Explore cutting-edge advancements in access control, discovery, lineage and monitoring — plus get a sneak peek at what’s coming next. Packed with live demos, expert insights and best practices from thousands of customers running Unity Catalog in production, this session is also your chance to engage directly with product experts and get answers to your most pressing questions. Don’t miss this opportunity to stay ahead of the curve and elevate your data governance strategy!

In this session, discover how effective data movement is foundational to successful GenAI implementations. As organizations rush to adopt AI technologies, many struggle with the infrastructure needed to manage the massive influx of unstructured data these systems require. Jim Kutz, Head of Data at Airbyte, draws from 20+ years of experience leading data teams at companies like Grafana, CircleCI, and BlackRock to demonstrate how modern data movement architectures can enable secure, compliant GenAI applications. Learn practical approaches to data sovereignty, metadata management, and privacy controls that transform data governance into an enabler for AI innovation. This session will explore how you can securely leverage your most valuable asset—first-party data—for GenAI applications while maintaining complete control over sensitive information. Walk away with actionable strategies for building an AI-ready data infrastructure that balances innovation with governance requirements.

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.

Accurate charge time estimation is key to vehicle performance and user experience. We developed a scalable ML model that enhances real-time charge predictions in vehicle controls. Traditional rule-based methods struggle with dynamic factors like environment, vehicle state, and charging conditions. Our adaptive ML solution improves accuracy by 10%. We use Unity Catalog for data governance, Delta Tables for storage, and Liquid Clustering for data layout. Job schedulers manage data processing, while AutoML accelerates model selection. MLflow streamlines tracking, versioning, and deployment. A dedicated serving endpoint enables A/B testing and real-time insights. As our data ecosystem grew, scalability became critical. Our flexible ML framework was integrated into vehicle control systems within months. With live accuracy tracking and software-driven blending, we support 50,000+ weekly charge sessions, improving energy management and user experience.

PepsiCo, given its scale, has numerous teams leveraging different tools and engines to access data and perform analytics and AI. To streamline governance across this diverse ecosystem, PepsiCo unifies its data and AI assets under an open and enterprise-grade governance framework with Unity Catalog. In this session, we'll explore real-world examples of how PepsiCo extends Unity Catalog’s governance to all its data and AI assets, enabling secure collaboration even for teams outside Databricks. Learn how PepsiCo architects permissions using service principals and service accounts to authenticate with Unity Catalog, building a multi-engine architecture with seamless and open governance. Attendees will gain practical insights into designing a scalable, flexible data platform that unifies governance across all teams while embracing openness and interoperability.

In regulated industries like finance, agility can't come at the cost of compliance. Morgan Stanley found the answer in combining Dataiku and Databricks to create a governed, collaborative ecosystem for machine learning and predictive analytics. This session explores how the firm accelerated model development and decision-making, reducing time-to-insight by 50% while maintaining full audit readiness. Learn how no-code workflows empowered business users, while scalable infrastructure powered Terabyte-scale ML. Discover best practices for unified data governance, risk automation, and cross-functional collaboration that unlock innovation without compromising security. Ideal for data leaders and ML practitioners in regulated industries looking to harmonize speed, control, and value.

Customer Data Platforms (CDPs) promise better engagement, higher operational efficiency, and revenue growth by centralizing and streamlining access to customer data. However, consolidating sensitive information from a variety of sources creates complex challenges around data governance, security, and privacy. We’ve studied, built, and managed data protection strategies at some of the world’s biggest retailers. We’ll showcase business requirements, common architectural components, and best practices to deploy data protection solutions at scale, protecting billions of sensitive records across regions and countries. Learn how a data vault pattern with granular, policy-based access control and monitoring can improve organizational privacy posture and help meet regulatory requirements (e.g., GDPR, CCPA, e-Privacy). Walk away with a clear framework to deploy such architecture and knowledge of real-world issues, performance optimizations, and design trade-offs

Join us to learn how the UK's Department for Environment, Food & Rural Affairs (DEFRA) transformed data use with Databricks’ Unity Catalog, enabling nationwide projects through secure, scalable analytics. DEFRA safeguards the UK's natural environment. Historical fragmentation of data, talent and tools across siloed platforms and organizations, made it difficult to fully exploit the department’s rich data. DEFRA launched its Data Analytics & Science Hub (DASH), powered by the Databricks Data Intelligence Platform, to unify its data ecosystem. DASH enables hundreds of users to access and share datasets securely. A flagship example demonstrates its power, using Databricks to process aerial photography and satellite data to identify peatlands in need of restoration — a complex task made possible through unified data governance, scalable compute and AI. Attendees will hear about DEFRA’s journey, learn valuable lessons about building a platform crossing organizational boundaries.

American Airlines migrated from Hive Metastore to Unity Catalog using automated processes with Databricks APIs and GitHub Actions. This automation streamlined the migration for many applications within AA, ensuring consistency, efficiency and minimal disruption while enhancing data governance and disaster recovery capabilities.

This talk takes you through the Nationwide Security and Infrastructure data team's journey of migrating from HMS to UC. Discover how HMS federation simplified our transition to UC, allowing for an incremental migration that minimized disruption to data consumers while optimizing our data layout. We’ll share the key technical decisions, challenges faced and lessons learned along the way. The migration process wasn’t without its hurdles, so we’ll walk you through our detailed, step-by-step approach covering planning, execution and validation. We will also showcase the benefits realized, such as improved data governance, more efficient data access and enhanced operational performance. Join us to gain practical insights into executing complex data migrations with a focus on security, flexibility and long-term scalability.

Healthcare and life sciences organizations are exploring AI Agents, driving transformation through intelligent supply chains to helping up-level the patient experience via virtual assistants. This session explores how you can get started with AI Agents, powered by Databricks and robust data governance, and tapping into the full potential of all your data. You’ll learn practical steps for getting started: unifying data with Databricks, ensuring compliance with Unity Catalog, and rapidly deploying AI Agents to drive operational efficiency, improve care, and foster innovation across healthcare and life sciences.

In modern data infrastructure, efficient and scalable data governance is essential for ensuring security, compliance, and accessibility. This session explores how to deploy Unity Catalog OSS on Kubernetes, leveraging its cloud-agnostic nature and efficient resource management. Helm makes Unity Catalog deployment simple and easy by providing a simplified installation process, easy configuration and credentials management.The session will cover why Kubernetes is the ideal platform, provide a technical breakdown of Unity Catalog on Kubernetes, and include a live showcase of its seamless deployment process. By the end, participants will confidently configure and deploy Unity Catalog OSS in their preferred Kubernetes environment and integrate it into their existing infrastructure.

This session will explore Databricks Unity Catalog (UC) implementation by P&G to enhance data governance, reduce data redundancy and improve the developer experience through the enablement of a Lakehouse architecture. The presentation will cover: The distinction between data treated as a product and standard application data, highlighting how UC's structure maximizes the value of data in P&G's data lake. Real-life examples from two years of using Unity Catalog, demonstrating benefits such as improved governance, reduced waste and enhanced data discovery. Challenges related to disaster recovery and external data access, along with our collaboration with Databricks to address these issues. Sharing our experience can provide valuable insights for organizations planning to adopt Unity Catalog on an enterprise scale.

Data is the backbone of modern decision-making, but centralizing it is only the tip of the iceberg. Entitlements, secure sharing and just-in-time availability are critical challenges to any large-scale platform. Join Goldman Sachs as we reveal how our Legend Lakehouse, coupled with Databricks, overcomes these hurdles to deliver high-quality, governed data at scale. By leveraging an open table format (Apache Iceberg) and open catalog format (Unity Catalog), we ensure platform interoperability and vendor neutrality. Databricks Unity Catalog then provides a robust entitlement system that aligns with our data contracts, ensuring consistent access control across producer and consumer workspaces. Finally, Legend functions, integrating with Databricks User Defined Functions (UDF), offer real-time data enrichment and secure transformations without exposing raw datasets. Discover how these components unite to streamline analytics, bolster governance and power innovation.

Payer organizations are rapidly embracing digital transformation, leveraging data and AI to drive operational efficiency, improve member experiences and enhance decision-making. This session explores how advanced analytics, robust data governance and AI-powered insights are enabling payers to streamline claims processing, personalize member engagement, manage pharmacy operations, and optimize care management. Thought leaders will share real-world examples of data-driven innovation, discuss strategies for overcoming interoperability and privacy challenges, and highlight the future potential of AI in reshaping the payer landscape.

Join this deep dive session for practitioners on Unity Catalog, Databricks’ unified data governance solution, to explore its capabilities for managing data and AI assets across workflows. Unity Catalog provides fine-grained access control, automated lineage tracking, quality monitoring and policy enforcement and observability at scale. Whether your focus is data pipelines, analytics or machine learning and generative AI workflows, this session offers actionable insights on leveraging Unity Catalog’s open interoperability across tools and platforms to boost productivity and drive innovation. Learn governance best practices, including catalog configurations, access strategies for collaboration and controls for securing sensitive data. Additionally, discover how to design effective multi-cloud and multi-region deployments to ensure global compliance.

With regulations like LGPD (Brazil's General Data Protection Law) and GDPR, managing sensitive data access is critical. This session demonstrates how to leverage Databricks Unity Catalog system tables and data lineage to dynamically propagate classification tags, empowering organizations to monitor governance and ensure compliance. The presentation covers practical steps, including system table usage, data normalization, ingestion with Lakeflow Declarative Pipelines and classification tag propagation to downstream tables. It also explores permission monitoring with alerts to proactively address governance risks. Designed for advanced audiences, this session offers actionable strategies to strengthen data governance, prevent breaches and avoid regulatory fines while building scalable frameworks for sensitive data management.

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.

T-Mobile’s leadership in 5G innovation and its rapid growth in the fixed wireless business have led to an exponential increase in data, reaching 100s of terabytes daily. This session explores how T-Mobile uses Databricks to manage this data efficiently, focusing on scalable architecture with Delta Lake, auto-scaling clusters, performance optimization through data partitioning and caching and comprehensive data governance with Unity Catalog. Additionally, it covers cost management, collaborative tools and AI-driven productivity tools, highlighting how these strategies empower T-Mobile to innovate, streamline operations and maximize data impact across network optimization, supporting the community, energy management and more.

As enterprises continue their journey to the cloud, data warehouse and data management modernization is essential to optimize analytics and drive business outcomes. Minimizing modernization timelines is important for reducing risk and shortening time to value – and ensuring enterprise data is clean, curated and governed is imperative to enable analytics and AI initiatives. In this session, learn how Informatica's Intelligent Data Management Cloud (IDMC) empowers analytics and AI on Databricks by helping data teams: · Develop no-code/low-code data pipelines that ingest, transform and clean data at enterprise scale · Improve data quality and extend enterprise governance with Informatica Cloud Data Governance and Catalog (CDGC) and Unity Catalog · Accelerate pilot-to-production with Mosaic AI

In this session, we will share NCS’s approach to implementing a Databricks Lakehouse architecture, focusing on key lessons learned and best practices from our recent implementations. By integrating Databricks SQL Warehouse, the DBT Transform framework and our innovative test automation framework, we’ve optimized performance and scalability, while ensuring data quality. We’ll dive into how Unity Catalog enabled robust data governance, empowering business units with self-serve analytical workspaces to create insights while maintaining control. Through the use of solution accelerators, rapid environment deployment and pattern-driven ELT frameworks, we’ve fast-tracked time-to-value and fostered a culture of innovation. Attendees will gain valuable insights into accelerating data transformation, governance and scaling analytics with Databricks.