Multi-statement transactions bring the atomicity and reliability of traditional databases to modern data warehousing on the lakehouse. In this session, we’ll explore real-world patterns enabled by multi-statement transactions — including multi-table updates, deduplication pipelines and audit logging — and show how Databricks ensures atomicity and consistency across complex workflows. We’ll also dive into demos and share tips to getting started and migrations with this feature in Databricks SQL.

AI agent systems hold immense promise for automating complex tasks and driving intelligent decision‑making, but only when they are engineered to be both resilient and transparent. In this session we will explore how Dataiku’s LLM Mesh pairs with Databricks Mosaic AI to streamline the entire lifecycle: ingesting and preparing data in the Lakehouse, prompt engineering LLMs hosted on Mosaic AI Model Serving Endpoints, visually orchestrating multi‑step chains, and monitoring them in real time. We’ll walk through a live demo of a Dataiku flow that connects to a Databricks hosted model, adds automated validation, lineage, and human‑in‑the‑loop review, then exposes the agent via Dataiku's Agent Connect interface. You’ll leave with actionable patterns for setting guardrails, logging decisions, and surfacing explanations—so your organization can deploy trustworthy domain‑specific agents faster & safer.

XP is one of the largest financial institutions in Brazil– and they didn’t reach that scale by moving slowly. After getting inspired at Data + AI Summit in 2024, they sprang into action to overhaul their advertising strategy using their first-party data in Databricks. Just a year later, they’ve achieved remarkable success: they’ve unlocked $66 million in incremental revenue from advertising, with the same budget as before. In this session, XP will share the tactical steps they took to bring a first-party data and AI strategy to customer acquisition– including how they built predictive models for customer quality and connected Databricks to their ecosystem through Hightouch’s Composable CDP. If you’re supporting an advertising team or are looking for real strategies to take home from this conference that can transform your business: this session is for you.

Think Databricks is just for data and models? Think again. In this session, you’ll see how to build and scale a full-stack AI app capable of handling thousands of queries per second entirely on Databricks. No extra cloud platforms, no patchwork infrastructure. Just one unified platform with native hosting, LLM integration, secure access, and built-in CI/CD. Learn how Databricks Apps, along with services like Model Serving, Jobs, and Gateways, streamline your architecture, eliminate boilerplate, and accelerate development, from prototype to production.

In an era where insights-driven decision-making is paramount, the insurance industry stands at the cusp of a major technological revolution. This session will delve into how Agentic AI — AI agents act autonomously to achieve critical goals — can be leveraged to transform insurance operation (underwriting, claims, services), enhance customer experiences and drive strategic growth.

The Databricks ecosystem has 5,000+ partners, who help enable you to leverage Databricks to unify all your data and AI workloads for more meaningful insights. Hear from some of the leading cloud, technology, and consulting partners.

SAP is the world's 3rd-largest publicly traded software company by revenue, and recently launched the joint SAP Databricks "Business Data Cloud". See how it all works from a practitioner's perspective, including reference architecture, demo, and example customers. See firsthand how the powerful suite of SAP applications benefits from a joint Databricks solution - with data being more easily governed, discovered, shared, and used for AI/ML..

FunPlus's journey to building a cost-effective and efficient data platform with Databricks: exploring how FunPlus leveraged Databricks to tackle key challenges, enhance data engineering and ML efficiency, and showcasing best practices and their impact on game development and operations.

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.

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.

This session will explore Databricks Unity Catalog (UC) implementation by P&G to enhance data governance, reduce data redundancy and improve the developer experience through the enablement of a Lakehouse architecture. The presentation will cover: The distinction between data treated as a product and standard application data, highlighting how UC's structure maximizes the value of data in P&G's data lake. Real-life examples from two years of using Unity Catalog, demonstrating benefits such as improved governance, reduced waste and enhanced data discovery. Challenges related to disaster recovery and external data access, along with our collaboration with Databricks to address these issues. Sharing our experience can provide valuable insights for organizations planning to adopt Unity Catalog on an enterprise scale.

This session will explore how Adobe uses a sophisticated data security architecture built on the Databricks Data Intelligence Platform, along with the Open Cybersecurity Schema Framework (OCSF), to enable scalable, real-time threat detection across more than 10 PB of security data. We’ll compare different approaches to OCSF implementation and demonstrate how Adobe processes massive security datasets efficiently — reducing query times by 18%, maintaining 99.4% SLA compliance, and supporting 286 security users across 17 teams with over 4,500 daily queries. By using Databricks' Platform for serverless compute, scalable architecture, and LLM-powered recommendations, Adobe has significantly improved processing speed and efficiency, resulting in substantial cost savings. We’ll also highlight how OCSF enables advanced cross-tool analytics and automation, streamlining investigations. Finally, we’ll introduce Databricks’ new open-source OCSF toolkit for scalable security data normalization and invite the community to contribute.

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.

In this session you'll learn how to onboard to Databricks in a way that ensures you can effectively measure and manage ROI of using Databricks down the line. We will show you how to set-up workspaces and compute, decide on a tagging strategy and how to utilize policies to enforce best practices and make future you a happy camper.

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.

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.

This hands-on lab guides participants through the complete customer data analytics journey on Databricks, leveraging leading partner solutions - Fivetran, dbt Cloud, and Sigma. Attendees will learn how to:- Seamlessly connect to Fivetran, dbt Cloud, and Sigma using Databricks Partner Connect- Ingest data using Fivetran, transform and model data with dbt Cloud, and create interactive dashboards in Sigma, all on top of the Databricks Data Intelligence Platform- Empower teams to make faster, data-driven decisions by streamlining the entire analytics workflow using an integrated, scalable, and user-friendly platform

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.

Data is the backbone of modern decision-making, but centralizing it is only the tip of the iceberg. Entitlements, secure sharing and just-in-time availability are critical challenges to any large-scale platform. Join Goldman Sachs as we reveal how our Legend Lakehouse, coupled with Databricks, overcomes these hurdles to deliver high-quality, governed data at scale. By leveraging an open table format (Apache Iceberg) and open catalog format (Unity Catalog), we ensure platform interoperability and vendor neutrality. Databricks Unity Catalog then provides a robust entitlement system that aligns with our data contracts, ensuring consistent access control across producer and consumer workspaces. Finally, Legend functions, integrating with Databricks User Defined Functions (UDF), offer real-time data enrichment and secure transformations without exposing raw datasets. Discover how these components unite to streamline analytics, bolster governance and power innovation.

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.

Databricks Financial Service customers in the GenAI space have a common use case of ingestion and processing of unstructured documents — PDF/images — then performing downstream GenAI tasks such as entity extraction and RAG based knowledge Q&A. The pain points for the customers for these types of use cases are: The quality of the PDF/image documents varies since many older physical documents were scanned into electronic form The complexity of the PDF/image documents varies and many contain tables — images with embedding information — which require slower Tesseract OCR They would like to streamline postprocess for downstream workloads In this talk we will present an optimized structured streaming workflow for complex PDF ingestion. The key techniques include Apache Spark™ optimization, multi-threading, PDF object extraction, skew handling and auto retry logics

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!