Health Catalyst (HCAT) transformed its CI/CD strategy by replacing a rigid, internal deployment tool with Databricks Asset Bundles (DABs), unlocking greater agility and efficiency. This shift streamlined deployments across both customer workspaces and HCAT's core platform, accelerating time to insights and driving continuous innovation. By adopting DABs, HCAT ensures feature parity, standardizes metric stores across clients, and rapidly delivers tailored analytics solutions. Attendees will gain practical insights into modernizing CI/CD pipelines for healthcare analytics, leveraging Databricks to scale data-driven improvements. HCAT's next-generation platform, Health Catalyst Ignite™, integrates healthcare-specific data models, self-service analytics, and domain expertise—powering faster, smarter decision-making.

Barclays Post Trade real-time trade monitoring platform was historically built on a complex set of legacy technologies including Java, Solace, and custom micro-services.This session will demonstrate how the power of Lakeflow Declarative Pipelines' new real-time mode, in conjunction with the foreach_batch_sink, can enable simple, cost-effective streaming pipelines that can load high volumes of data into Databricks new Serverless OLTP database with very low latency.Once in our OLTP database, this can be used to update real-time trading dashboards, securely hosted in Databricks Apps, with the latest stock trades - enabling better, more responsive decision-making and alerting.The session will walk-through the architecture, and demonstrate how simple it is to create and manage the pipelines and apps within the Databricks environment.

AI for enterprises, particularly in the era of GenAI, requires rapid experimentation and the ability to productionize models and agents quickly and at scale. Compliance, resilience and commercial flexibility drive the need to serve models across regions. As cloud providers struggle with rising demand for GPUs in environments, VM shortages have become commonplace, and add to the pressure of general cloud outages. Enterprises that can quickly leverage GPU capacity in other cloud regions will be better equipped to capitalize on the promise of AI, while staying flexible to serve distinct user bases and complying with regulations. In this presentation we will show and discuss how to implement AI deployments across cloud regions, deploying a model across regions and using a load balancer to determine where to best route a user request.

This presentation outlines the evolution of our marketing data strategy, focusing on how we’ve built a strong foundation using the Databricks Lakehouse. We will explore key advancements across data ingestion, strategy, and insights, highlighting the transition from legacy systems to a more scalable and intelligent infrastructure. Through real-world applications, we will showcase how unified Customer 360 insights drive personalization, predictive analytics enhance campaign effectiveness, and GenAI optimizes content creation and marketing execution. Looking ahead, we will demonstrate the next phase of our CDP, the shift toward an end-user-first analytics model powered by AIBI, Genie and Matik, and the growing importance of clean rooms for secure data collaboration. This is just the beginning, and we are poised to unlock even greater capabilities in the future.

Join us as we unveil how we transformed the largest Databricks workspace into the best-in-class lakehouse through Unity Catalog. Discover how we harnessed lineage and unified access management to build ultimate governance automation.

The problem of matching GPS locations to roads and local government areas (LGAs) involves handling large datasets and a number of geospatial operations. In this deep dive, we will outline the challenges of developing scalable solutions for these tasks. We will discuss our multi-step approach, first focusing on the use of H3 indexing to isolate matches with single candidates, then explaining use of different geospatial computational techniques to accurately match points with multiple candidates. From technical perspective, the talk will showcase the use of broadcasting and partitioning techniques, their effect on autoscaling, memory usage and effective data parallelization. This session is for anyone interested in geospatial data, spark performance optimization and the real-world challenges of large-scale data engineering.

In this session, learn about why modern open table formats like Delta and Iceberg are a big deal and how they work with catalogs. Learn about what motivated their creation, how they work, what benefits they can bring to your data and AI platform. Hear about how these formats are becoming increasingly interoperable and what our vision is for their future.

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.

Real-time mode is a new low-latency execution mode for Apache Spark™ Structured Streaming. It can consistently provide p99 latencies less than 300 milliseconds for a broad set of stateless and stateful streaming queries. Our talk focuses on the technical aspects of making this possible in Spark. We’ll dive into the core architecture that enables these dramatic latency improvements, including a concurrent stage scheduler and a non-blocking shuffle. We’ll explore how we maintained Spark’s fault-tolerance guarantees, and we’ll also share specific optimizations we made to our streaming SQL operators. These architectural improvements have already enabled Databricks customers to build workloads with latencies up to 10x lower than before. Early adopters in our Private Preview have successfully implemented real-time enrichment pipelines and feature engineering for machine learning — use cases that were previously impossible at these latencies.

The rise of GenAI has led to a complete reinvention of how we conceptualize Data + AI. In this breakout, we will recontextualize the rise of GenAI in traditional ML paradigms, and hopefully unite the pre- and post-LLM eras. We will demonstrate when and where GenAI may prove more effective than traditional ML algorithms, and highlight problems for which the wheel is unnecessarily being reinvented with GenAI. This session will also highlight how MLflow provides a unified means of benchmarking traditional ML against GenAI, and lay out a vision for bridging the divide between Traditional ML and GenAI practitioners.

In this session we will explore the revolutionary advancements in nuclear AI capabilities with HiVE and Bertha on Databricks architecture. HiVE, developed by Westinghouse, leverages over a century of proprietary data to deliver unparalleled AI capabilities. At its core is Bertha, a generative AI model designed to tackle the unique challenges of the nuclear industry. This session will delve into the technical architecture of HiVE and Bertha, showcasing how Databricks' scalable environment enhances their performance. We will discuss the secure data infrastructure supporting HiVE, ensuring data integrity and compliance. Real-world applications and use cases will demonstrate the impact of HiVE and Bertha on improving efficiency, innovation and safety in nuclear operations. Discover how the fusion of HiVE and Bertha with Databricks architecture is transforming the nuclear AI landscape and driving the future of nuclear technology.

While Spark offers powerful processing capabilities for massive data volumes, cost-efficiency challenges are always bothering users operating at large scales. At Pinterest, where we run millions of Spark jobs monthly, maintaining infra cost efficiency is crucial to support our rapid business growth. To tackle this challenge, we have developed several strategies that have saved us tens of millions of dollars across numerous job instances. We will share our analytical methodology for identifying performance bottlenecks, and the technical solutions to overcome various challenges. Our approach includes extracting insights from billions of collected metrics, leveraging remote shuffle services to address shuffle slowness and improve memory utilization and reduce costs while hosting hundreds of millions of pods. The presentation aims to trigger more discussions about cost efficiency topics of Apache Spark in the community and help the community to tackle the common challenge.

Discover how Databricks serverless compute revolutionizes data workflows by eliminating infrastructure management, enabling rapid scaling and optimizing costs for Notebooks, Jobs and Lakeflow Declarative Pipelines. This session will delve into the serverless architecture, highlighting its ability to dynamically allocate resources, reduce idle costs and simplify development cycles. Learn about recent advancements, including cost savings and practical strategies for migration and optimization. Tailored for Data Engineers and Architects, this talk will also explore use cases, features, limitations and future roadmap, empowering you to make informed infrastructure decisions while unlocking the full potential of Databricks’ serverless capabilities.

At Data and AI in 2022, Databricks pioneered the term to shift left in how AI workloads would enable less data science driven people to create their own apps. In 2025, we take a look at how Experian is doing on that journey. This session highlights Databricks services that assist with the shift left paradigm for Generative AI, including how AI/BI Genie helps with Generative analytics, and how Agent Studio helps with synthetic generation of test cases to validate model performance.

Understanding customer engagement and retention isn’t optional—it’s mission-critical. Join us for a live demo to see how you can build a scalable, governed customer health scoring model by transforming raw signals into actionable insights. Discover how Coalesce’s low-code development platform works seamlessly with Databricks’ lakehouse architecture to unify and operationalize customer data at scale. With built-in governance, automation, and metadata intelligence, you’ll deliver trusted scores that support proactive decision-making across the business. Why Attend? Accelerate time-to-insight with automated, low-code transformations Build repeatable, enterprise-grade scoring models with full data lineage Ensure governance, transparency, and compliance at every step

Learn how Chevron transitioned their central finance and procurement analytics into the cloud using Databricks and ThoughtSpot’s Agentic Analytics Platform. Explore how Chevron leverages ThoughtSpot to unlock actionable insights, enhance their semantic layer with user-driven understanding, and ultimately drive more impactful strategies for customer engagement and business growth. In this session, Chevron explains the dos, don’ts, and best practices of migrating from outdated legacy business intelligence to real time, AI-powered insights.

Learn how Databricks and Confluent are simplifying the path from real-time data to governed, analytics- and AI-ready tables. This session will cover how Confluent Tableflow automatically materializes Kafka topics into Delta tables and registers them with Unity Catalog — eliminating the need for custom streaming pipelines. We’ll walk through how this integration helps data engineers reduce ingestion complexity, enforce data governance and make real-time data immediately usable for analytics and AI.

DSv2, Spark's next-generation Catalog API, is gaining traction among data source developers. It shifts complexity to Apache Spark™, improves connector reliability and unlocks new functionality such as catalog federation, MERGE operations, storage-partitioned joins, aggregate pushdown, stored procedures and more. This session covers the design of DSv2, current strengths and gaps and its evolving roadmap. It's intended for Spark users and developers working with data sources, whether custom-built or off-the-shelf.

Curious to know how Adidas is transforming customer experience and business impact with agentic workflows, powered by Databricks? By leveraging cutting-edge tools like MosaicML’s deployment capabilities, Mosaic AI Gateway, and MLflow, Adidas built a scalable GenAI agentic infrastructure that delivers actionable insights from growing 2 million product reviews annually. With remarkable results: 60% latency reduction (15.5 seconds to 6 seconds) 91.67% cost savings (transitioning to more efficient LLMs) 98.5% token efficiency, reducing input tokens from 200k to just 3k 20% increase in productivity (faster time to insight) Empowering over 500 decision-makers across 150+ countries, this infrastructure is set to optimize products and services for Adidas’ 500 million members by 2025 while supporting dozens of upcoming AI-driven solutions. Join us to explore how Adidas turned agentic workflows infra into a strategic advantage using Databricks and learn how you can do the same!

In today’s data-driven landscape, business users expect seamless, interactive analytics without having to switch between different environments. This presentation explores our web application that unifies a Power BI dashboard with Databricks Genie, allowing users to query and visualize insights from the same dataset within a single, cohesive interface. We will compare two integration strategies: one that leverages a traditional webpage enhanced by an Azure bot to incorporate Genie’s capabilities, and another that utilizes Databricks Apps to deliver a smoother, native experience. We use the Genie API to build this solution. Attendees will learn the architecture behind these solutions, key design considerations and challenges encountered during implementation. Join us to see live demos of both approaches, and discover best practices for delivering an all-in-one, interactive analytics experience.

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.

Overflow Available First come, first serve. No reservation required. Where: Moscone South, Level 3, Room 302 Join the 60-minute kickoff session at the Financial Services Forum to explore how data and AI transform finance. Featuring keynotes from top innovators in banking, capital markets, and insurance and exciting announcements from Databricks, this event offers invaluable insights. What to expect: Business imperatives: Learn how institutions drive growth, reduce risk and boost efficiency with data intelligence Transformative vision: See how Databricks enhances fraud prevention, automates processes and personalizes experiences Cutting-edge insights: Discover the latest trends in data-driven finance Customer success stories: Hear how global leaders leverage data and AI for a competitive edge Connect with C-suite executives and industry pioneers shaping financial services. Leave with actionable strategies to drive growth, ensure compliance and transform your organization through intelligence-driven decisions!

Come hear from some of the biggest names in games about how Data and AI is helping them shape their future, build better games and create player-centric experiences. In this session you’ll hear, first, what Databricks is hearing from Games studios globally as their key priorities. We then shift to customers sharing their stories and perspectives. Dennis Ceccarelli from 2K Games sharing how his passion for building immersive, player-first experiences, has helped him shape the future of sports entertainment in the interactive space. You’ll leave invigorated on the impact Data and AI can have on games, and our global players and have new ideas on ways you can further your impact.

Join us for an engaging 60-minute Healthcare and Life Sciences Industry Forum at the year’s premier Databricks event! You’ll hear directly from Databricks experts and industry leaders about how unifying data, governing AI models and empowering teams with data intelligence can drive meaningful change across the healthcare and life sciences continuum. Discover how data and AI are transforming the industry — helping streamline healthcare operations, personalize patient care and accelerate breakthroughs in research and development. Don’t miss this opportunity to learn about the future of data-driven healthcare.

Join us for an inspiring forum showcasing how manufacturers and transportation leaders are turning today's challenges into tomorrow's opportunities. From automotive giants revolutionizing product development with generative AI to logistics providers optimizing routes for both cost and sustainability, discover how industry pioneers are reshaping the future of industrial operations. Highlighting this session is an exciting collaboration between Heathrow Airport and Virgin Atlantic, demonstrating how partnership and innovation are transforming the air travel experience. Learn how these leaders and other companies are using Databricks to tackle their most pressing challenges — from smart factory transformations to autonomous systems development — proving that the path to profitability and sustainability runs through intelligent operations.