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.

Over the past three years, Netflix has built a catalog of 100+ mobile and cloud games across TV, mobile and web platforms. With both internal and external studios contributing to this diverse ecosystem, building a robust game analytics platform became crucial for gaining insights into player behavior, optimizing game performance and driving member engagement.In this talk, we’ll share our journey of building Netflix’s Game Analytics platform from the ground up. We’ll highlight key decisions around data strategy, such as whether to develop an in-house solution or adopt an external service. We’ll discuss the challenges of balancing developer autonomy with data integrity and the complexities of managing data contracts for custom game telemetry, with an emphasis on self-service analytics. Attendees will learn how the Games Data team navigated these challenges, the lessons learned and the trade-offs involved in building a multi-tenant data ecosystem that supports diverse stakeholders.

Maximize the performance of your Databricks Platform with innovations on Google Cloud. Discover how Google's Arm-based Axion C4A virtual machines (VMs) deliver breakthrough price-performance and efficiency for Databricks, supercharging Databricks Photon engine. Gain actionable strategies to optimize your Databricks deployments on Google Cloud.

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.

Domo's Databricks integration seamlessly connects business users to both Delta Lake data and AI/ML models, eliminating technical barriers while maximizing performance. Domo's Cloud Amplifier optimizes data processing through pushdown SQL, while the Domo AI Services layer enables anyone to leverage both traditional ML and large language models directly from Domo. During this session, we’ll explore an AI solution around fraud detection to demonstrate the power of leveraging Domo on Databricks.

This presentation outlines the evolution of Databricks and its integration with cloud analytics at Edward Jones. It focuses on the transition from Cloud V1.x to Cloud V2.0, which highlights the challenges faced with initial setup, Unity Catalog implementation and the improvements planned for the future particularly in terms of Data Cataloging, Architecture and Disaster Recovery. Highlights: Cloud Analytics Journey Current Setup (Cloud V1.x) Utilizes Medallion architecture customized to Edward Jones need. Challenges & limitations identified with integration, limited catalogs, Disaster Recovery etc. Cloud V2.0 Enhancements Modifications in storage and compute in Medallion layers Next level integration with enterprise suites Disaster Recovery readiness Future outlook

We’re excited to share with you how SAP Business Data Cloud supports Delta Sharing to share SAP data securely and seamlessly with Databricks—no complex ETL or data duplication required. This enables organizations to securely share SAP data for analytics and AI in Databricks while also supporting bidirectional data sharing back to SAP.In this session, we’ll demonstrate the integration in action, followed by a discussion of how the global beauty group, Natura, will leverage this solution. Whether you’re looking to bring SAP data into Databricks for advanced analytics or build AI models on top of trusted SAP datasets, this session will show you how to get started — securely and efficiently.

In this presentation, we'll show how we achieved a unified development experience for teams working on Mercedes-Benz Data Platforms in AWS and Azure. We will demonstrate how we implemented Azure to AWS and AWS to Azure data product sharing (using Delta Sharing and Cloud Tokens), integration with AWS Glue Iceberg tables through UniForm and automation to drive everything using Azure DevOps Pipelines and DABs. We will also show how to monitor and track cloud egress costs and how we present a consolidated view of all the data products and relevant cost information. The end goal is to show how customers can offer the same user experience to their engineers and not have to worry about which cloud or region the Data Product lives in. Instead, they can enroll in the data product through self-service and have it available to them in minutes, regardless of where it originates.

In this session, you’ll gain actionable insights to modernize your security operations and strengthen cyber resilience. Arctic Wolf will highlight how they eliminated data silos & enhanced their MDR pipeline to investigate suspicious threat actors for customers using Databricks.

A successful data strategy requires the right platform and the ability to empower the broader user community by creating simple, scalable and secure patterns that lower the barrier to entry while ensuring robust data practices. Guided by the belief that everyone is a data person, we focus on breaking down silos, democratizing access and enabling distributed teams to contribute through a federated "data-as-a-product" model. We’ll share the impact and lessons learned in creating a single source of truth on Unity Catalog, consolidated from diverse sources and cloud platforms. We’ll discuss how we streamlined governance with Databricks Apps, Workflows and native capabilities, ensuring compliance without hindering innovation. We’ll also cover how we maximize the value of that catalog by leveraging semantics to enable trustworthy, AI-driven self-service in AI/BI dashboards and downstream apps. Come learn how we built a next-gen data ecosystem that empowers everyone to be a data person.

How do you transform legacy data into a launchpad for next-gen innovation? GE Vernova is tackling it by rapidly migrating from outdated platforms to Databricks, building one of the world’s largest cloud data implementations. This overhaul wasn’t optional. Scaling AI, cutting technical debt, and slashing license costs demanded a bold, accelerated approach. Led by strategic decisions from the CDO and powered by Genpact’s AI Gigafactory, the migration is tackling 35+ Business and sub domains, 60,000+ data objects, 15,000+ jobs, 3000+ reports from 120+ diverse data sources to deliver a multi-tenant platform with unified governance. The anticipated results? Faster insights, seamless data sharing, and a standardized platform built for AI at scale. This session explores how Genpact and Databricks are fueling GE Vernova’s mission to deliver The Energy to Change the World—and what it takes to get there when speed, scale, and complexity are non-negotiable.

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.

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

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.

Building an open data lakehouse? Start with the right blueprint. This session walks through common reference architectures for interoperable lakehouse deployments across AWS, Google Cloud, Azure and tools like Snowflake, BigQuery and Microsoft Fabric. Learn how to design for cross-platform data access, unify governance with Unity Catalog and ensure your stack is future-ready — no matter where your data lives.

This session showcases how both Westinghouse Electric and Alabama Power Company are leveraging cloud-based tools, advanced analytics, and machine learning to transform operational resilience across the energy sector. In the first segment, we'll explore AI's crucial role in enhancing safety, efficiency, and compliance in nuclear operations through technologies like HiVE and Bertha, focusing on the unique reliability and credibility requirements of the regulated nuclear industry. We’ll then highlight how Alabama Power Company has modernized its grid management and storm preparedness by using Databricks to develop SPEAR and RAMP—applications that combine real-time data and predictive analytics to improve reliability, efficiency, and customer service.

Discover how SAP Business Data Cloud and Databricks can transform your business by unifying SAP and non-SAP data for advanced analytics and AI. In this session, we’ll highlight Optimizing Cash Flow with AI with integrated diverse data sources and AI algorithms that enable accurate cash flow forecasting to help businesses identify trends, prevent bottlenecks, and improve liquidity. You’ll also learn about the importance of high-quality, well-governed data as the foundation for reliable AI models and actionable reporting. Key Takeaways: • How to integrate and leverage SAP and external data in Databricks • Using AI for predictive analytics and better decision-making • Building a trusted data foundation to drive business performance Leave this session with actionable strategies to optimize your data, enhance efficiency, and unlock new growth opportunities.

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.

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.

This session will show how we implemented a solution to support high-frequency data ingestion from smart meters. We implemented a robust API endpoint that interfaces directly with IoT devices. This API processes messages in real time from millions of distributed IoT devices and meters across the network. The architecture leverages cloud storage as a landing zone for the raw data, followed by a streaming pipeline built on Lakeflow Declarative Pipelines. This pipeline implements a multi-layer medallion architecture to progressively clean, transform and enrich the data. The pipeline operates continuously to maintain near real-time data freshness in our gold layer tables. These datasets connect directly to Databricks Dashboards, providing stakeholders with immediate insights into their operational metrics. This solution demonstrates how modern data architecture can handle high-volume IoT data streams while maintaining data quality and providing accessible real-time analytics for business users.

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.

Elevate your AI initiatives on Databricks by harnessing the latest advancements in Google Cloud's Gemini models. Learn how to integrate Gemini's built-in reasoning and powerful development tools to build more dynamic and intelligent applications within your existing Databricks platform. We'll explore concrete ideas for agentic AI solutions, showcasing how Gemini can help you unlock new value from your data in Databricks.

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.