Empower AI and agents with trusted data and metadata from an end-to-end unified system. Discover how Salesforce Data Cloud, Agentforce, and Databricks work together to fuel automation, AI, and analytics through a unified data strategy—driving real-time intelligence, enabling zero-copy data sharing, and unlocking scalable activation across the enterprise.

The migration to the Databricks Data Intelligence Platform has enabled Techcombank to more efficiently unify data from over 50 systems, improve governance, streamline daily operational analytics pipelines and use advanced analytics tools and AI to create more meaningful and personalized experiences for customers. With Databricks, Techcombank has also introduced key solutions that are reshaping its digital banking services: AI-driven lead management system: Techcombank's internally developed AI program called 'Lead Allocation Curated Engine' (LACE) optimizes lead management and provides relationship managers with enriched insights for smarter lead allocation to drive business growth. AI-powered program for digital banking inclusion of small businesses: An AI-powered GeoSense assists frontline workers with analytics-driven insights about which small businesses and merchants to engage in the bank's digital ecosystem. And more examples, which will be presented.

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.

Modern data science teams face the challenge of navigating complex landscapes of languages, tools and infrastructure. Positron, Posit’s next-generation IDE, offers a powerful environment tailored for data science, seamlessly integrating with Databricks to empower teams working in Python and R. Now integrated within Posit Workbench, Positron enables data scientists to efficiently develop, iterate and analyze data with Databricks — all while maintaining their preferred workflows. In this session, we’ll explore how Python and R users can develop, deploy and scale their data science workflows by combining Posit tools with Databricks. We’ll showcase how Positron simplifies development for both Python and R and how Posit Connect enables seamless deployment of applications, reports and APIs powered by Databricks. Join us to see how Posit + Databricks create a frictionless, scalable and collaborative data science experience — so your teams can focus on insights, not infrastructure.

In a world where data collaboration is essential but trust is scarce, Databricks Clean Rooms delivers a game-changing model: no data shared, all value gained. Discover how data providers can unlock new revenue streams by launching subscription-based analytics and “Built-on-Databricks” services that run on customer data — without exposing raw data or violating compliance. Clean Rooms integrates Unity Catalog’s governance, Delta Sharing’s secure exchange and serverless compute to enable true multi-party collaboration — without moving data. See how privacy-preserving models like fraud detection, clinical analytics and ad measurement become scalable, productizable and monetizable across industries. Walk away with a proven pattern to productize analytics, preserve compliance and turn trustless collaboration into recurring revenue.

Coinbase leverages Databricks to scale ML on blockchain data, turning vast transaction networks into actionable insights. This session explores how Databricks’ scalable infrastructure, powered by Delta Lake, enables real-time processing for ML applications like NFT floor price predictions. We’ll show how GraphFrames helps us analyze billion-node transaction graphs (e.g., Bitcoin) for clustering and fraud detection, uncovering structural patterns in blockchain data. But traditional graph analytics has limits. We’ll go further with Graph Neural Networks (GNNs) using Kumo AI, which learn from the transaction network itself rather than relying on hand-engineered features. By encoding relationships directly into the model, GNNs adapt to new fraud tactics, capturing subtle relationships that evolve over time. Join us to see how Coinbase is advancing blockchain ML with Databricks and deep learning on graphs.

Enterprise customers need a powerful and adaptable data foundation to navigate demands of AI and multi-cloud environments. This session dives into how Google Cloud Storage serves as a unified platform for modern analytics data lakes, together with Databricks. Discover how Google Cloud Storage provides key innovations like performance optimizations for Apache Iceberg, Anywhere Cache as the easiest way to colocate storage and compute, Rapid Storage for ultra low latency object reads and appends, and Storage Intelligence for vital data insights and recommendations. Learn how you can optimize your infrastructure to unlock the full value of your data for AI-driven success.

ClickHouse is a C++ based, column-oriented database built for real-time analytics. While it has its own internal storage format, the rise of open lakehouse architectures has created a growing need for seamless interoperability. In response, we have developed integrations with your favorite lakehouse ecosystem to enhance compatibility, performance and governance. From integrating with Unity Catalog to embedding the Delta Kernel into ClickHouse, this session will explore the key design considerations behind these integrations, their benefits to the community, the lessons learned and future opportunities for improved compatibility and seamless integration.

Most organizations run complex cloud data architectures that silo applications, users and data. Join this interactive hands-on workshop to learn how Databricks SQL allows you to operate a multi-cloud lakehouse architecture that delivers data warehouse performance at data lake economics — with up to 12x better price/performance than traditional cloud data warehouses. Here’s what we’ll cover: How Databricks SQL fits in the Data Intelligence Platform, enabling you to operate a multicloud lakehouse architecture that delivers data warehouse performance at data lake economics How to manage and monitor compute resources, data access and users across your lakehouse infrastructure How to query directly on your data lake using your tools of choice or the built-in SQL editor and visualizations How to use AI to increase productivity when querying, completing code or building dashboards Ask your questions during this hands-on lab, and the Databricks experts will guide you.

Don't miss this session where we demonstrate how the Texas Rangers baseball team is staying one step ahead of the competition by going back to the basics. After implementing a modern data strategy with Databricks and winnng the 2023 World Series the rest of the league quickly followed suit. Now more than ever, data and AI are a central pillar of every baseball team's strategy driving profound insights into player performance and game dynamics. With a 'fundamentals win games' back to the basics focus, join us as we explain our commmitment to world-class data quality, engineering, and MLOPS by taking full advantage of the Databricks Data Intelligence Platform. From system tables to federated querying, find out how the Rangers use every tool at their disposal to stay one step ahead in the hyper competitive world of baseball.

Intuit leverages Databricks Clean Rooms to create a secure, privacy-safe lending marketplace, enabling small business lending partners to perform analytics and deploy ML/AI workflows on sensitive data assets. This session explores the technical foundations of building isolated clean rooms across multiple partners and cloud providers, differentiating Databricks Clean Rooms from market alternatives. We'll demonstrate our automated approach to clean room lifecycle management using APIs, covering creation, collaborator onboarding, data asset sharing, workflow orchestration and activity auditing. The integration with Unity Catalog for managing clean room inputs and outputs will also be discussed. Attendees will gain insights into harnessing collaborative ML/AI potential, support various languages and workloads, and enable complex computations without compromising sensitive information in Clean Rooms.

Transactional systems are a common source of data for analytics, and Change Data Capture (CDC) offers an efficient way to extract only what’s changed. However, ingesting CDC data into an analytics system comes with challenges, such as handling out-of-order events or maintaining global order across multiple streams. These issues often require complex, stateful stream processing logic.This session will explore how Lakeflow Declarative Pipelines simplifies CDC ingestion using the Apply Changes function. With Apply Changes, global ordering across multiple change feeds is handled automatically — there is no need to manually manage state or understand advanced streaming concepts like watermarks. It supports both snapshot-based inputs from cloud storage and continuous change feeds from systems like message buses, reducing complexity for common streaming use cases.

Growth in banking isn’t just about keeping pace—it’s about setting the pace. This session explores how leading banks leverage Databricks’ Data Intelligence Platform to uncover new revenue opportunities, deepen customer relationships, and expand market reach. Hear from industry leaders who have transformed their growth strategies by harnessing the power of advanced analytics and machine learning. Learn how personalized customer experiences, predictive insights and unified data platforms are driving innovation and helping banks scale faster than ever. Key takeaways: Proven strategies for identifying untapped growth opportunities using data-driven approaches Real-world examples of banks creating personalized customer journeys that boost retention and loyalty Tools and techniques to accelerate innovation while maintaining operational efficiency Join us in discovering how data intelligence is redefining growth in banking and thriving throughout uncertainty.

There’s never been a more critical time to ensure data and analytics foundations can deliver the value and efficiency needed to accelerate and scale AI. What are the most difficult challenges that organizations face with data transformation, and what technologies, processes and decisions that overcome these barriers to success? Join this session featuring executives from the Gates Foundation, the nonprofit leading change in communities around the globe, and Avanade, the joint venture between Accenture and Microsoft, in a discussion about impactful data strategy. Learn about the Gates Foundation’s approach to its enterprise data platform to ensure trusted insights at the speed of today’s business. And we’ll share lessons learned from Avanade helping organizations around the globe build with Databricks and seize the AI opportunity.

As enterprises strive to become more data-driven, SAP continues to be central to their operational backbone. However, traditional SAP ecosystems often limit the potential of AI and advanced analytics due to fragmented architectures and legacy tools. In this session, we explore four strategic options for unlocking greater value from SAP data by integrating with Databricks and cloud-native platforms. Whether you're on ECC, S4HANA, or transitioning from BW, learn how to modernize your data landscape, enable real-time insights, and power AI/ML at scale. Discover how SAP Business Data Cloud and SAP Databricks can help you build a unified, future-ready data and analytics ecosystem—without compromising on scalability, flexibility, or cost-efficiency.

The explosion of AI has helped make the enterprise data landscape more important, and complex, than ever before. Join us to learn how Databricks’ and Tableau’s platforms come together to empower users of all kinds to see, understand, and act on your data in a secure, governed, and performant way.

In today’s fast-evolving crypto landscape, organizations require fast, reliable intelligence to manage risk, investigate financial crime, and stay ahead of evolving threats. In this session we will discover how Elliptic built a scalable, high-performance Data Intelligence Platform that delivers real-time, actionable Blockchain insights to their customers. We’ll walk you through some of the key components of the Elliptic Platform, including the Elliptic Entity Graph and our User-Facing Analytics. Our focus will be put on the evolution of our User-Facing Analytics capabilities, and specifically how components from the Databricks ecosystem such as Structured Streaming, Delta Lake, and SQL Warehouse have played a vital role. We’ll also share some of the optimizations we’ve made to our streaming jobs to maximize performance and ensure Data Completeness. Whether you’re looking to enhance your streaming capabilities, expand your knowledge of how crypto analytics works or simply discover novel approaches to data processing at scale, this session will provide concrete strategies and valuable lessons learned.

Moving data between operational systems and analytics platforms is often painful. Traditional pipelines become complex, brittle, and expensive to maintain.Take Kafka and Iceberg: batching on Kafka causes ingestion bottlenecks, while streaming-style writes to Iceberg create too many small Parquet files—cluttering metadata, degrading queries, and increasing maintenance overhead. Frequent updates further strain background table operations, causing retries—even before dealing with schema evolution. But much of this complexity is avoidable. What if Kafka Topics and Iceberg Tables were treated as two sides of the same coin? By establishing a transparent equivalence, we can rethink pipeline design entirely. This session introduces Tableflow—a new approach to bridging streaming and table-based systems. It shifts complexity away from pipelines and into a unified layer, enabling simpler, declarative workflows. We’ll cover schema evolution, compaction, topic-to-table mapping, and how to continuously materialize and optimize thousands of topics as Iceberg tables. Whether modernizing or starting fresh, you’ll leave with practical insights for building resilient, scalable, and future-proof data architectures.

This session explores the strategic migration from Snowflake to Databricks, focusing on the journey of transforming a data lake to leverage Databricks’ advanced capabilities. It outlines the assessment of key architectural differences, performance benchmarks, and cost implications driving the decision. Attendees will gain insights into planning and execution, including data ingestion pipelines, schema conversion and metadata migration. Challenges such as maintaining data quality, optimizing compute resources and minimizing downtime are discussed, alongside solutions implemented to ensure a seamless transition. The session highlights the benefits of unified analytics and enhanced scalability achieved through Databricks, delivering actionable takeaways for similar migrations.

In capital markets, mitigating risk is critical to protecting the firm’s reputation, assets, and clients. This session highlights how firms use technology to enhance risk management, ensure compliance and safeguard operations from emerging threats. Learn how advanced analytics and machine learning models are helping firms detect anomalies, prevent fraud, and manage regulatory complexities with greater precision. Hear from industry leaders who have successfully implemented proactive risk strategies that balance security with operational efficiency. Key Takeaways: Techniques for identifying risks early using AI-powered anomaly detection. Best practices for achieving compliance across complex regulatory environments. Insights into building resilient operations that protect assets without compromising growth potential. Don’t miss this session to discover how data intelligence is transforming risk management in capital markets—helping firms secure their future while driving success!"