Are data teams ready for AI? Prophecy’s exclusive survey, “The Impact of GenAI on Data Teams”, gives the clearest picture yet of GenAI’s potential in data management, and what’s standing in the way. The top two obstacles? Poor governance and slow access to high-quality data. The message is clear: Modernizing your data platform with Databricks is essential. But it’s only the beginning. To unlock the power of AI and analytics, organizations must deliver governed, self-service access to clean, trusted data. Traditional data prep tools introduce risks around security, quality, and cost. It’s no wonder data leaders cited data transformation as the area where GenAI will make the biggest impact. To deliver what’s needed teams need a shift to governed self-service. Data analysts and scientists move fast while staying within IT’s guardrails. Join us to learn more details from the survey and how leading organizations are ahead of the curve, using GenAI to reshape how data gets done.

GenAI systems are evolving beyond basic information retrieval and question answering, becoming sophisticated agents capable of managing multi-turn dialogues and executing complex, multi-step tasks autonomously. However, reliably evaluating and systematically improving their performance remains challenging. In this session, we'll explore methods for assessing the behavior of LLM-driven agentic systems, highlighting techniques and showcasing actionable insights to identify performance bottlenecks and to creating better-aligned, more reliable agentic AI systems.

Join us to see how the powerful combination of ThoughtSpot's agentic analytics platform and the Databricks Data Intelligence Platform is changing the game for data-driven organizations. We'll demonstrate how DataSpot breaks down technical barriers to insight. You'll learn how to get trusted, real-time answers thanks to the seamless integration between ThoughtSpot's semantic layer and Databricks Unity Catalog. This session is for anyone looking to leverage data more effectively, whether you're a business leader seeking AI-driven insights, a data scientist building models in Python, or a product owner creating intelligent applications.

The ability for different AI systems to collaborate is more critical than ever. From traditional ML development to fine-tuning GenAI models, Databricks delivers the stability, cost-optimization and productivity Expedia Group (EG) needs. Learn how to unlock the full potential of AI interoperability with Databricks. AI acceleration: Discover how Databricks acts as a central hub, helping to scale AI model training and prediction generation to deliver high-quality insights for customers. Cross-platform synergy: Learn how EG seamlessly integrated Databricks' powerful features into its ecosystem, streamlining workflows and accelerating time to market. Scalable deployment: Understand how Databricks stability and reliability increased efficiency in prototyping and running scalable production workloads. Join Shiyi Pickrell to understand the future of AI interoperability, how it’s generating business value and driving the next generation of travel AI-powered experiences.

In an era of skyrocketing content volumes, companies are sitting on huge libraries — of video, images and audio — just waiting to be leveraged to power targeted advertising and recommendations, as well as reinforce brand safety. Coactive AI will show how fast and accurate AI-driven metadata enrichment, combined with Databricks Unity Catalog and lakehouse, is accelerating and optimizing media workflows. Learn how leading brands are using content metadata to: Unlock new revenue through contextual advertising Drive personalization at scale Enhance brand safety with detailed, scene-level analysis Build unified taxonomies that fuel cross-functional insights Transform content from a static asset into a dynamic engine for growth, engagement and compliance.

Discover how to build and deploy AI-powered applications natively on the Databricks Data Intelligence Platform. This session introduces best practices and a standard reference architecture for developing production-ready apps using popular frameworks like Dash, Shiny, Gradio, Streamlit and Flask. Learn how to leverage agents for orchestration and explore primary use cases supported by Databricks Apps, including data visualization, AI applications, self-service analytics and data quality monitoring. With serverless deployment and built-in governance through Unity Catalog, Databricks Apps enables seamless integration with your data and AI models, allowing you to focus on delivering impactful solutions without the complexities of infrastructure management. Whether you're a data engineer or an app developer, this session will equip you with the knowledge to create secure, scalable and efficient applications within a Databricks environment.

Join Robin Sutara, Field CDO for Databricks, as she discusses creating a robust data strategy for organizational change in an ecosystem that is under constant transformation. Attendees will learn best practices from Databricks customers for successful data strategy, including business alignment, people and culture, democratization, governance, and measurement as vital strategic aspects. Understanding these elements will help you drive more data and AI transformation success within your organization.

Lakeflow Jobs is the production-ready fully managed orchestrator for the entire Lakehouse with 99.95% uptime. Join us for a dive into how you can orchestrate your enterprise data operations, from triggering your jobs only when your data is ready to advanced control flow with conditionals, looping and job modularity — with demos! Attendees will gain practical insights into optimizing their data operations by orchestrating with Lakeflow Jobs: New task types: Publish AI/BI Dashboards, push to Power BI or ingest with Lakeflow Connect Advanced execution control: Reference SQL Task outputs, run partial DAGs and perform targeted backfills Repair runs: Re-run failed pipelines with surgical precision using task-level repair Control flow upgrades: Native for-each loops and conditional logic make DAGs more dynamic + expressive Smarter triggers: Kick off jobs based on file arrival or Delta table changes, enabling responsive workflows Code-first approach to pipeline orchestration

Delta Sharing is revolutionizing how enterprises share live data and AI assets securely, openly and at scale. As the industry’s first open data-sharing protocol, it empowers organizations to collaborate seamlessly across platforms and with any partner, whether inside or outside the Databricks ecosystem. In this deep-dive session, you’ll learn best practices and real-world use cases that show how Delta Sharing helps accelerate collaboration and fuel AI-driven innovation. We’ll also unveil the latest advancements, including: Managed network configurations for easier, secure setup OIDC identity federation for trusted, open sharing Expanded asset types including dynamic views, materialized views, federated tables, read clones and more Whether you’re a data engineer, architect, or data leader, you’ll leave with practical strategies to future-proof your data-sharing architecture. Don’t miss the live demos, expert guidance and an exclusive look at what’s next in data collaboration.

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.

Join industry leaders from Dow and Michelin as they reveal how data intelligence is revolutionizing sustainable manufacturing without compromising profitability. Dow demonstrates how their implementation of Databricks' Data Intelligence Platform has transformed their ability to track and reduce carbon footprints while driving operational efficiencies, resulting in significant cost savings through optimized maintenance and reduced downtime. Michelin follows with their ambitious strategy to achieve 3% energy consumption reduction by 2026, leveraging Databricks to turn this environmental challenge into operational excellence. Together, these manufacturing giants showcase how modern data architecture and AI are creating a new paradigm where sustainability and profitability go hand-in-hand.

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.

This session will provide an in-depth overview of how PepsiCo, a global leader in food and beverage, transformed its outdated data platform into a modern, unified and centralized data and AI-enabled platform using the Databricks SQL serverless environment. Through three distinct implementations that transpired at PepsiCo in 2024, we will demonstrate how the PepsiCo Data Analytics & AI Group unlocked pivotal capabilities that facilitated the delivery of diverse data-driven insights to the business, reduced operational expenses and enhanced overall performance through the newly implemented platform.

Today, executives are focused on managing regulatory scrutiny and emerging threats. Banks worldwide are leveraging the Databricks Data Intelligence Platform to enhance fraud prevention, ensure compliance and protect sensitive data while improving operational efficiency.This session will highlight how leading banks are implementing AI-driven risk management to identify vulnerabilities, streamline governance and enhance resilience. By utilizing unified data platforms, these institutions can effectively tackle threats and foster trust without hindering growth.Key takeaways: Fraud detection: Best practices for using machine learning to combat fraud Regulatory compliance: Insights on navigating complex regulations Secure operations: Strategies for scalable operations that protect assets and support growth Join us to see how data intelligence is reshaping the banking industry and enabling success in uncertain times!

In the age of agentic AI, competitive advantage lies not only in AI models, but in the quality of the data agents reason on and the agility of the tools that feed them. To fully realize the ROI of agentic AI, organizations need a platform that enables high-quality data pipelines and provides scalable, enterprise-grade tools. In this session, discover how a unified platform for integration, data management, MCP server management, API management, and agent orchestration can help you to bring cohesion and control to how data and agents are used across your organization.

Think you know everything AI/BI can do? Think again. This session explores the art of the possible with Databricks AI/BI Dashboards and Genie, going beyond traditional analytics to unleash the full power of the lakehouse. From incorporating AI into dashboards to handling large-scale data with ease to delivering insights seamlessly to end users — we’ll showcase creative approaches that unlock insights and real business outcomes. Perfect for adventurous data professionals looking to push limits and think outside the box.

Eli Lilly and Company, a leading bio-pharma company, is revolutionizing manufacturing with next-gen fully digital sites. Lilly and Tredence have partnered to establish a Databricks-powered Global Manufacturing Data Fabric (GMDF), laying the groundwork for transformative data products used by various personas at sites and globally. By integrating data from various manufacturing systems into a unified data model, GMDF has delivered actionable insights across several use cases such as batch release by exception, predictive maintenance, anomaly detection, process optimization and more. Our serverless architecture leverages Databricks Auto Loader for real-time data streaming, PySpark for automation and Unity Catalog for governance, ensuring seamless data processing and optimization. This platform is the foundation for data driven processes, self-service analytics, AI and more. This session will provide details on the data architecture and strategy and share a few use cases delivered.

At Capital One, data-driven decision making is paramount to our success. This session explores how a focused proof of concept (POC) accelerated a shift in our data pipeline management strategy, resulting in operational improvements and expanded analytical capabilities. We'll cover the business challenges that motivated POC initiation, including data latency, cost savings and scalability limitations, and real-world results. We'll also dive into an examination of the before-and-after architecture with highlights for key technological levers. This session offers insights for data engineering and machine learning practitioners seeking to optimize their data pipelines for improved performance, scalability and business value.

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.

Maximize the value of your company’s marketing efforts with Data Intelligence for Marketing. Databricks provides seamless, out-of-the-box integration with your ecosystem, empowering every marketer with self-serve insights. And with AI-driven CDP, you get a complete view of customers and campaigns.

Databricks SQL is the fastest-growing data warehouse on the market, with over 10k organizations thanks to its price performance and AI innovations. See the best practices and common architectural challenges of migrating your legacy DW, including reference architectures. Learn how to easily migrate per the recently acquired the Lakebridge migration tool, and through our partners.

Stuck on a treadmill of endless report building requests? Wondering how you can ship reliable AI products to internal users and even customers? Omni is a BI and embedded analytics platform on Databricks that lets users answer their own data questions – sometimes with a little AI help. No magic, no miracles – just smart tooling that cuts through the noise and leverages well-known concepts (semantic layer, anyone?) to improve accuracy and delight users. This talk is your blueprint for getting reliable AI use cases into production and reaching the promised land of contagious self-service.

Nondeterministic AI models, like large language models (LLMs), offer immense creative potential but require new approaches to testing and scalability. Drawing from her experience running New York Times-featured Generative AI comedy shows, Erin uncovers how traditional benchmarks may fall short and how embracing unpredictability can lead to innovative, laugh-inducing results. This talk will explore methods like multi-tiered feedback loops, chaos testing and exploratory user testing, where AI outputs are evaluated not by rigid accuracy standards but by their adaptability and resonance across different contexts — from comedy generation to functional applications. Erin will emphasize the importance of establishing a root source of truth — a reliable dataset or core principle — to manage consistency while embracing creativity. Whether you’re looking to generate a few laughs of your own or explore creative uses of Generative AI, this talk will inspire and delight enthusiasts of all levels.

Nestlé USA, a division of the world’s largest food and beverage company, Nestlé S.A., has embarked on a transformative journey to unlock GenAI capabilities on their data platform. Deloitte, Databricks, and Nestlé have collaborated on a data platform modernization program to address gaps associated with Nestlé’s existing data platform. This joint effort introduces new possibilities and capabilities, ranging from development of advanced machine learning models, implementing Unity Catalog, and adopting Lakehouse Federation, all while adhering to confidentiality protocols. With help from Deloitte and Databricks, Nestlé USA is now able to meet its advanced enterprise analytics and AI needs with the Databricks Data Intelligence Platform.

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.