Companies need a lot of data to build and deploy AI models—and they want it quickly. To meet this demand, platform teams are quickly scaling their Databricks usage, resulting in excess cost driven by inefficiencies and performance anomalies. Capital One has over 4,000 users leveraging Databricks to power advanced analytics and machine learning capabilities at scale. In this talk, we’ll share lessons learned from optimizing our own Databricks usage while balancing lower cost with peak performance. Attendees will learn how to identify top sources of waste, best practices for cluster management, tips for user governance and methods to keep costs in check.

Today’s supply chains demand more than historical insights–they need real-time intelligence. In this actionable session, discover how leading enterprises are unlocking the full potential of their SAP data by integrating it with Databricks and AI. See how CPG companies are transforming supply chain planning by combining SAP ERP data with external signals like weather and transportation data–enabling them to predict disruptions, optimize inventory, and make faster, smarter decisions. Powered by Databricks, this solution delivers true agility and resilience through a unified data architecture. Join us to learn how: You can eliminate SAP data silos and make them ML and AI-ready at scale External data sources amplify SAP use cases like forecasting and scenario planning AI-driven insights accelerate time-to-action across supply chain operations Whether you're just starting your data modernization journey or seeking ROI from SAP analytics, this session will show you what’s possible.

As first-party data becomes increasingly invaluable to organizations, Walmart Data Ventures is dedicated to bringing to life new applications of Walmart’s first-party data to better serve its customers. Through Scintilla, its integrated insights ecosystem, Walmart Data Ventures continues to expand its offerings to deliver insights and analytics that drive collaboration between our merchants, suppliers, and operators.​Scintilla users can now access Walmart data using Cloud Feeds, based on Databricks Delta Sharing technologies. In the past, Walmart used API-based data sharing models, which required users to possess certain skills and technical attributes that weren’t always available. Now, with Cloud Feeds, Scintilla users can more easily access data without a dedicated technical team behind the scenes making it happen. Attendees will gain valuable insights into how Walmart has built its robust data sharing architecture and strategies to design scalable and collaborative data sharing architectures in their own organizations.

Join us to hear about how National Australia Bank (NAB) successfully completed a significant milestone in its data strategy by decommissioning its 26-year-old Teradata environment and migrating to a new strategic data platform called 'Ada'. This transition marks a pivotal shift from legacy systems to a modern, cloud-based data and AI platform powered by Databricks. The migration process, which spanned two years, involved ingesting 16 data sources, transferring 456 use cases, and collaborating with hundreds of users across 12 business units. This strategic move positions NAB to leverage the full potential of cloud-native data analytics, enabling more agile and data-driven decision-making across the organization. The successful migration to Ada represents a significant step forward in NAB's ongoing efforts to modernize its data infrastructure and capitalize on emerging technologies in the rapidly evolving financial services landscape

HP’s 3D Print division empowers manufacturers with telemetry data to optimize operations and streamline maintenance. Using Delta Sharing, Unity Catalog and AI/BI dashboards, HP provides a secure, scalable solution for data sharing and analytics. Delta Sharing D2O enables seamless data access, even for customers not on Databricks. Apigee masks private URLs, and Unity Catalog enhances security by managing data assets. Predictive maintenance with Mosaic AI boosts uptime by identifying issues early and alerting support teams. Custom dashboards and sample code let customers run analytics using any supported client, while Apigee simplifies access by abstracting complexity. Insights from A/BI dashboards help HP refines data strategy, aligning solutions with customer needs despite the complexity of diverse technologies, fragmented systems and customer-specific requirements. This fosters trust, drives innovation,and strengthens HP as a trusted partner for scalable, secure data solutions.

This presentation will explore the transformation of IQVIA's decade-old patient support platform through the implementation of Databricks Data Intelligence Platform. Facing scalability challenges, performance bottlenecks and rising costs, the existing platform required significant redesign to handle growing data volumes and complex analytics. Key issues included static metrics limiting workflow optimization, fragmented data governance and heightened compliance and security demands. By partnering with Customertimes (a Databricks Partner) and adopting Databricks' centralized, scalable analytics solution with enhanced self-service capabilities, IQVIA achieved improved query performance, cost efficiency and robust governance, ensuring operational effectiveness and regulatory compliance in an increasingly complex environment.

Deloitte is observing a growing trend among cybersecurity organizations to develop big data management and analytics solutions beyond traditional Security Information and Event Management (SIEM) systems. Leveraging Databricks to extend these SIEM capabilities, Deloitte can help clients lower the cost of cyber data management while enabling scalable, cloud-native architectures. Deloitte helps clients design and implement cybersecurity data meshes, using Databricks as a foundational data lake platform to unify and govern security data at scale. Additionally, Deloitte extends clients’ cybersecurity capabilities by integrating advanced AI and machine learning solutions on Databricks, driving more proactive and automated cybersecurity solutions. Attendees will gain insight into how Deloitte is utilizing Databricks to manage enterprise cyber risks and deliver performant and innovative analytics and AI insights that traditional security tools and data platforms aren’t able to deliver.

This session will take you on our journey of integrating Databricks as the core serving layer in a large enterprise, demonstrating how you can build a unified data platform that meets diverse business needs. We will walk through the steps for constructing a central serving layer by leveraging Databricks’ SQL Warehouse to efficiently deliver data to analytics tools and downstream applications. To tackle low latency requirements, we’ll show you how to incorporate an interim scalable relational database layer that delivers sub-second performance for hot data scenarios. Additionally, we’ll explore how Delta Sharing enables secure and cost-effective data distribution beyond your organization, eliminating silos and unnecessary duplication for a truly end-to-end centralized solution. This session is perfect for data architects, engineers and decision-makers looking to unlock the full potential of Databricks as a centralized serving hub.

Priorities shift, requirements change, resources fluctuate, and the demands on data teams are only continuing to grow. Join this session, led by Coalesce Sales Engineering Director, Michael Tantrum, to hear about the most efficient way to deliver high quality data to your organization at the speed they need to consume it. Learn how to sidestep the common pitfalls of data development for maximum data team productivity.

Join us for the Tech Industry Forum, formerly known as the Tech Innovators Summit, now part of Databricks Industry Experience. This session will feature keynotes, panels and expert talks led by top customer speakers and Databricks experts. Tech companies are pushing the boundaries of data and AI to accelerate innovation, optimize operations and build collaborative ecosystems. In this session, we’ll explore how unified data platforms empower organizations to scale their impact, democratize analytics across teams and foster openness for building tomorrow’s products. Key topics include: Scaling data platforms to support real-time analytics and AI-driven decision-making Democratizing access to data while maintaining robust governance and security Harnessing openness and portability to enable seamless collaboration with partners and customers After the session, connect with your peers during the exclusive Industry Forum Happy Hour. Reserve your seat today!

Quantum Capital Group (QCG) screens hundreds of deals across the global Sustainable Energy Ecosystem, requiring deep technical due diligence. With over 1.5 billion records sourced from public, premium and proprietary datasets, their challenge was how to efficiently curate, analyze and share this data to drive smarter investment decisions. QCG partnered with Databricks & Tiger Analytics to modernize its data landscape. Using Delta tables, Spark SQL, and Unity Catalog, the team built a golden dataset that powers proprietary evaluation models and automates complex workflows. Data is now seamlessly curated, enriched and distributed — both internally and to external stakeholders — in a secure, governed and scalable way. This session explores how QCG’s investment in data intelligence has turned an overwhelming volume of information into a competitive advantage, transforming deal evaluation into a faster, more strategic process.

At Procore, we're transforming the construction industry through innovative data solutions. This session unveils how we've supercharged our analytics offerings using a unified lakehouse architecture and Delta Sharing, delivering game-changing results for our customers and our business and how data professionals can unlock the full potential of their data assets and drive meaningful business outcomes. Key highlights: Learn how we've implemented seamless, secure sharing of large datasets across various BI tools and programming languages, dramatically accelerating time-to-insights for our customers Discover our approach to sharing dynamically filtered subsets of data across our numerous customers with cross-platform view sharing We'll demonstrate how our architecture has eliminated the need for data replication, fostering a more efficient, collaborative data ecosystem

Migrating legacy workloads to a modern, scalable platform like Databricks can be complex and resource-intensive. Impetus, an Elite Databricks Partner and the Databricks Migration Partner of the Year 2024, simplifies this journey with LeapLogic, an automated solution for data platform modernization and migration services. LeapLogic intelligently discovers, transforms, and optimizes workloads for Databricks, ensuring minimal risk and faster time-to-value. In this session, we’ll showcase real-world success stories of enterprises that have leveraged Impetus’ LeapLogic to modernize their data ecosystems efficiently. Join us to explore how you can accelerate your migration journey, unlock actionable insights, and future-proof your analytics with a seamless transition to Databricks.

Join this 20-minute session to learn how Informatica CDGC integrates with and leverages Unity Catalog metadata to provide end-to-end governance and security across an enterprise data landscape. Topics covered will include: Comprehensive data lineage that provides complete data transformation visibility across multicloud and hybrid environments -Broad data source support to facilitate holistic cataloging and a centralized governance framework Centralized access policy management and data stewardship to enable compliance with regulatory standards Rich data quality to ensure data is cleansed, validated and trusted for analytics and AI

In this session, we will explore the Australian Red Cross Lifeblood's approach to synchronizing an Azure SQL Datavault 2.0 (DV2.0) implementation with Unity Catalog (UC) using Lakeflow Connect. Lifeblood's DV2.0 data warehouse, which includes raw vault (RV) and business vault (BV) tables, as well as information marts defined as views, required a multi-step process to achieve data/business logic sync with UC. This involved using Lakeflow Connect to ingest RV and BV data, followed by a custom process utilizing JDBC to ingest view definitions, and the automated/manual conversion of T-SQL to Databricks SQL views, with Lakehouse Monitoring for validation. In this talk, we will share our journey, the design decisions we made, and how the resulting solution now supports analytics workloads, analysts, and data scientists at Lifeblood.

This session is repeated. Peek behind the curtain to learn how Databricks processes hundreds of petabytes of data across every region and cloud where we operate. Learn how Databricks leverages Data and AI to scale and optimize every aspect of the company. From facilities and legal to sales and marketing and of course product research and development. This session is a high-level tour inside Databricks to see how Data and AI enable us to be a better company. We will go into the architecture of things for how Databricks is used for internal use cases like business analytics and SIEM as well as customer-facing features like system tables and assistant. We will cover how data production of our data flow and how we maintain security and privacy while operating a large multi-cloud, multi-region environment.

Streaming data is hard and costly — that's the default opinion, but it doesn’t have to be.In this session, discover how SEGA simplified complex streaming pipelines and turned them into a competitive edge. SEGA sees over 40,000 events per second. That's no easy task, but enabling personalised gaming experiences for over 50 million gamers drives a huge competitive advantage. If you’re wrestling with streaming challenges, this talk is your next checkpoint.We’ll unpack how Lakeflow Declarative Pipelines helped SEGA, from automated schema evolution and simple data quality management to seamless streaming reliability. Learn how Lakeflow Declarative Pipelines drives value by transforming chaos emeralds into clarity, delivering results for a global gaming powerhouse. We'll step through the architecture, approach and challenges we overcame.Join Craig Porteous, Microsoft MVP from Advancing Analytics, and Felix Baker, Head of Data Services at SEGA Europe, for a fast-paced, hands-on journey into Lakeflow Declarative Pipelines’ unique powers.

Analysts often begin their Databricks journey by running familiar SQL queries in the SQL Editor, but that’s just the start. In this session, I’ll share the roadmap I followed to expand beyond ad-hoc querying into SQL Editor/notebook-driven development to scheduled data pipelines producing interactive dashboards — all powered by Databricks SQL and Unity Catalog. You’ll learn how to organize tables with primary-key/foreign-key relationships along with creating table and column comments to form the semantic model, utilizing DBSQL features like RELY constraints. I’ll also show how parameterized dashboards can be set up to empower self-service analytics and feed into Genie Spaces. Attendees will walk away with best practices for starting out with building a robust BI platform on Databricks, including tips for table design and metadata enrichment. Whether you’re a data analyst or BI developer, this talk will help you unlock powerful, AI-enhanced analytics workflows.

As cybersecurity threats grow in volume and complexity, organizations must efficiently process security telemetry for best-in-class detection and mitigation. Barracuda’s XDR platform is redefining security operations by layering advanced detection methodologies over a broad range of supported technologies. Our vision is to deliver unparalleled protection through automation, machine learning and scalable detection frameworks, ensuring threats are identified and mitigated quickly. To achieve this, we have adopted Databricks as the foundation of our security analytics platform, providing greater control and flexibility while decoupling from traditional SIEM tools. By leveraging Lakeflow Declarative Pipelines, Spark Structured Streaming and detection-as-code CI/CD pipelines, we have built a real-time detection engine that enhances scalability, accuracy and cost efficiency. This session explores how Databricks is shaping the future of XDR through real-time analytics and cloud-native security.

Lely, a Dutch company specializing in dairy farming robotics, helps farmers with advanced solutions for milking, feeding and cleaning. This session explores Lely’s implementation of an Internal Data Marketplace, built around Databricks' Private Exchange Marketplace. The marketplace serves as a central hub for data teams and business users, offering seamless access to data, analytics and dashboards. Powered by Delta Sharing, it enables secure, private listing of data products across business domains, including notebooks, views, models and functions. This session covers the pros and cons of this approach, best practices for setting up a data marketplace and its impact on Lely’s operations. Real-world examples and insights will showcase the potential of integrating data-driven solutions into dairy farming. Join us to discover how data innovation drives the future of dairy farming through Lely’s experience.

We’ll explore how CipherOwl Inc. constructed a near real-time, multi-chain data lakehouse to power anti-money laundering (AML) monitoring at a petabyte scale. We will walk through the end-to-end architecture, which integrates cutting-edge open-source technologies and AI-driven analytics to handle massive on-chain data volumes seamlessly. Off-chain intelligence complements this to meet rigorous AML requirements. At the core of our solution is ChainStorage, an OSS started by Coinbase that provides robust blockchain data ingestion and block-level serving. We enhanced it with Apache Spark™ and Arrow™, coupled for high-throughput processing and efficient data serialization, backed by Delta Lake and Kafka. For the serving layer, we employ StarRocks to deliver lightning-fast SQL analytics over vast datasets. Finally, our system incorporates machine learning and AI agents for continuous data curation and near real-time insights, which are crucial for tackling on-chain AML challenges.

As global energy demands continue to rise, organizations must boost efficiency while staying environmentally responsible. Flogistix uses Sigma and Databricks to build a unified data architecture for real-time, data-driven decisions in vapor recovery systems. With Sigma on the Databricks Data Intelligence Platform, Flogistix gains precise operational insights and identifies optimization opportunities that reduce emissions, streamline workflows, and meet industry regulations. This empowers everyone, from executives to field mechanics, to drive sustainable resource production. Discover how advanced analytics are transforming energy practices for a more responsible future.

Bayada is transforming its data ecosystem by consolidating Matillion+Snowflake and SSIS+SQL Server into a unified Enterprise Data Platform powered by Databricks. Using Databricks' Medallion architecture, this platform enables seamless data integration, advanced analytics and machine learning across critical domains like general ledger, recruitment and activity-based costing. Databricks was selected for its scalability, real-time analytics and ability to handle both structured and unstructured data, positioning Bayada for future growth. The migration aims to reduce data processing times by 35%, improve reporting accuracy and cut reconciliation efforts by 40%. Operational costs are projected to decrease by 20%, while real-time analytics is expected to boost efficiency by 15%. Join this session to learn how Bayada is leveraging Databricks to build a high-performance data platform that accelerates insights, drives efficiency and fosters innovation organization-wide.

Are you struggling to keep up with rapid business changes that demand constant updates to your data pipelines? Is your data engineering team growing rapidly just to manage this complexity? Databricks was not immune to this challenge either. Managing our BI with contributions from hundreds of Product Engineering Teams across the company while maintaining central oversight and quality posed significant hurdles. Join us to learn how we developed a config-driven data pipeline framework using Metric Store and UC Metrics that helped us reduce engineering effort — achieving the work of 100 classical data engineers with just two platform engineers.

This talk explores using advanced data processing and generative AI techniques to revolutionize the retail industry. Using Databricks, we will discuss how cutting-edge technologies enable real-time data analysis and machine learning applications, creating a powerful ecosystem for large-scale, data-driven retail solutions. Attendees will gain insights into architecting scalable data pipelines for retail operations and implementing advanced analytics on streaming customer data. Discover how these integrated technologies drive innovation in retail, enhancing customer experiences, streamlining operations and enabling data-driven decision-making. Learn how retailers can leverage these tools to gain a competitive edge in the rapidly evolving digital marketplace, ultimately driving growth and adaptability in the face of changing consumer behaviors and market dynamics.