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.

This session will provide an in-depth overview of how PepsiCo, a global leader in food and beverage, transformed its outdated data platform into a modern, unified and centralized data and AI-enabled platform using the Databricks SQL serverless environment.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.

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.

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.

Feastables, founded by YouTube sensation MrBeast, partnered with Engine to build a modern, AI-enabled BI ecosystem that transforms complex, disparate data into actionable insights, driving smarter decision-making across the organization. In this session, learn how Engine, a Built-On Databricks Partner, brought expertise combined with strategic partnerships that enabled Feastables to rapidly stand up a secure, modern data estate to unify complex internal and external data sources into a single, permissioned analytics platform. Feastables unlocked the power of cross-functional collaboration by democratizing data access throughout their enterprise and seamlessly integrating financial, retailer, supply chain, syndicated, merchandising and e-commerce data. Discover how a scalable analytics framework combined with advanced AI models and tools empower teams with Smarter BI across sales, marketing, supply chain, finance and executive leadership to enable real-time decision-making at scale.

AI/BI Genie has transformed self-service analytics for the Databricks Marketing team. This user-friendly conversational AI tool empowers marketers to perform advanced data analysis using natural language — no SQL required. By reducing reliance on data teams, Genie increases productivity and enables faster, data-driven decisions across the organization. But realizing Genie’s full potential takes more than just turning it on. In this session, we’ll share the end-to-end journey of implementing Genie for over 200 marketing users, including lessons learned, best practices and the real business impact of this Databricks-on-Databricks solution. Learn how Genie democratizes data access, enhances insight generation and streamlines decision-making at scale.

Most enterprise data is trapped in unstructured formats — documents, PDFs, scanned images and tables — making it difficult to access, analyze and use. This session shows how to unlock that hidden value by building intelligent document processing workflows on the Databricks Data Intelligence Platform. You’ll learn how to ingest unstructured content using Lakeflow Connect, extract structured data with AI Parse — even from complex tables and scanned documents — and apply analytics or AI to this newly structured data. What you’ll learn: How to build scalable pipelines that transform unstructured documents into structured tables Techniques for automating document workflows with Databricks tools Strategies for maintaining quality and governance with Unity Catalog Real-world examples of AI applications built with intelligent document processing

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.

Join us for this session focused on how leading tech companies are enabling data intelligence across their organizations while maintaining cost efficiency and governance. Hear the successes and the challenges when Databricks empowers thousands of users—from engineers to business teams—by providing scalable tools for AI, BI and analytics. Topics include: Combining AI/BI and Lakehouse Apps to streamline workflows and accelerate insights Implementing systems tables, tagging and governance frameworks for granular control Democratizing data access while optimizing costs for large-scale analytical workloads Hear from customers and Databricks experts, followed by a customer panel featuring industry leaders. Gain insights into how Databricks helps tech innovators scale their platforms while maintaining operational excellence.

Deliver trusted, high-performance insights by incorporating Unity Catalog metric views and business semantics into your AI/BI workflows. This session dives into the architecture and best practices for defining reusable metrics, implementing governance and enhancing query performance in AI/BI Dashboards and Genie. Learn how to manage business semantics effectively to ensure data consistency while empowering business users with governed, self-service analytics. Ideal for teams looking to streamline analytics at scale, this session provides practical strategies for driving data accuracy and governance.

Want to learn how to build your own custom data intelligence applications directly in Databricks? In this workshop, we’ll guide you through a hands-on tutorial for building a Streamlit web app that leverages many of the key products at Databricks as building blocks. You’ll integrate a live DB SQL warehouse, use Genie to ask questions in natural language, and embed AI/BI dashboards for interactive visualizations. In addition, we’ll discuss key concepts and best practices for building production-ready apps, including logging and observability, scalability, different authorization models, and deployment. By the end, you'll have a working AI app—and the skills to build more.

Explore how Databricks AI/BI Genie revolutionizes retail analytics, empowering business users to become self-reliant data explorers. This session highlights no-code AI apps that create a conversational interface for retail data analysis. Genie spaces harness NLP and generative AI to convert business questions into actionable insights, bypassing complex SQL queries. We'll showcase retail teams effortlessly analyzing sales trends, inventory and customer behavior through Genie's intuitive interface. Witness real-world examples of AI/BI Genie's adaptive learning, enhancing accuracy and relevance over time. Learn how this technology democratizes data access while maintaining governance via Unity Catalog integration. Discover Retail Genie's impact on decision-making, accelerating insights and cultivating a data-driven retail culture. Join us to see the future of accessible, intelligent retail analytics in action.

Assortment and space analytics optimizes product selection and shelf allocation to boost sales, improve inventory management and enhance customer experience. However, challenges like evolving demand, data accuracy and operational alignment hinder success. Older approaches struggled due to siloed tools, slow performance and poor governance. Databricks unified platform resolved these issues, enabling seamless data integration, high-performance analytics and governed sharing. The innovative AI/BI Genie interface empowered self-service analytics, driving non-technical user adoption. This solution helped Walmart cut time to value by 90% and saved $5.6M annually in FTE hours leading to increased productivity. Looking ahead, AI agents will let store managers and merchants execute decisions via conversational interfaces, streamlining operations and enhancing accessibility. This transformation positions retailers to thrive in a competitive, customer-centric market.

Earlier this year, we finished migration of all dashboards from a traditional BI system to Databricks AI/BI ecosystem, resulting in annual savings of approximately $900,000. We also unlocked the below advantages: Data security, integrity and safety Cost savings Single source of truth Real-time data Genie space We will speak about our journey and how you can migrate your dashboards from traditional BI to AI/BI. Having listed the advantages above, we will also speak of some challenges faced. Migration steps: Analytical scope of dashboard inventory Feature mapping: From traditional BI to AI/BI Building bronze, silver and gold tables Building dashboards Migration shenanigans: Hypercare phase Change management KT documents Demo sessions Deprecation of licenses and dashboards on traditional BI tools We look forward to sharing these lessons learned and insights with you to help you streamline your BI infrastructure and unlock the full potential of Databricks AI/BI.

Picture the scene — you're exploring a deep, dark cave looking for insights to unearth when, in a burst of smoke, Genie appears and offers you not three but unlimited data wishes. This isn't a folk tale, it's the growing wave of Generative BI that is going to be a part of analytics platforms. Databricks Genie is a tool powered by a SQL-writing LLM that redefines how we interact with data. We'll look at the basics of creating a new Genie room, scoping its data tables and asking questions. We'll help it out with some complex pre-defined questions and ensure it has the best chance of success. We'll give the tool a personality, set some behavioural guidelines and prepare some hidden easter eggs for our users to discover. Generative BI is going to be a fundamental part of the analytics toolset used across businesses. If you're using Databricks, you should be aware of Genie, if you're not, you should be planning your Generative BI Roadmap, and this session will answer your wishes.

In this session, we'll explore how Rooms To Go enhances organizational collaboration by integrating AI/BI Genie with Microsoft Teams. Genie enables warehouse employees and members of the sales team to interact with data using natural language, simplifying data exploration and analysis. By connecting Genie to Microsoft Teams, we bring real-time data insights directly to a user’s phone. We'll provide a comprehensive overview on setting up this integration as well as a demo of how the team uses it daily. Attendees will gain practical knowledge to implement this integration, empowering their teams to access and interact with data seamlessly within Microsoft Teams.

Crisp streamlines a brand’s data ingestion across 60+ retail sources, to build a foundation of sales and inventory intelligence on Databricks. Data is normalized and analysis-ready, and integrates seamlessly with AI tools - such as Databricks’ Genie and Blueprints. This session will provide an overview of the Crisp retail data platform and how our semantic layer, normalized and harmonized data sets can help drive powerful insights for supply chain, BI/Analytics, and data science teams.

Managing metrics across teams can feel like everyone’s speaking a different language, which often leads to loss of trust in numbers. Based on a real-world use case, we’ll show you how to establish a governed source of truth for metrics that works at scale and builds a solid foundation for AI integration. You’ll explore how Bolt.eu’s data team governs consistent metrics for different data users and leverages Euno’s automations to navigate the overlap between Looker and dbt. We’ll cover best practices for deciding where your metrics belong and how to optimize engineering and maintenance workflows across Databricks, dbt and Looker. For curious analytics engineers, we’ll dive into thinking in dimensions & measures vs. tables & columns and determining when pre-aggregations make sense. The goal is to help you contribute to a self-serve experience with consistent metric definitions, so business teams and AI agents can access the right data at the right time without endless back-and-forth.

You already see the value of the lakehouse. But are you truly maximizing its potential across all workloads, from BI to AI? In this session, Onehouse unveils how our open lakehouse architecture unifies your entire stack, enabling true interoperability across formats, catalogs, and engines. From lightning-fast ingestion at scale to cost-efficient processing and multi-catalog sync, Onehouse helps you go beyond trade-offs. Discover how Apache XTable (Incubating) enables cross-table-format compatibility, how OpenEngines puts your data in front of the best engine for the job, and how OneSync keeps data consistent across Snowflake, Athena, Redshift, BigQuery, and more. Meanwhile, our purpose-built lakehouse runtime slashes ingest and ETL costs. Whether you’re delivering BI, scaling AI, or building the next big thing, you need a lakehouse that’s open and powerful. Onehouse opens everything—so your data can power anything.

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.

Transform your AI/BI Genie into a text-to-SQL powerhouse using the Genie Conversation APIs. This session explores how Genie functions as an intelligent agent, translating natural language queries into SQL to accelerate insights and enhance self-service analytics. You'll learn practical techniques for configuring agents, optimizing queries and handling errors — ensuring Genie delivers accurate, relevant responses in real time. A must-attend for teams looking to level up their AI/BI capabilities and deliver smarter analytics experiences.

At Data and AI in 2022, Databricks pioneered the term to shift left in how AI workloads would enable less data science driven people to create their own apps. In 2025, we take a look at how Experian is doing on that journey. This session highlights Databricks services that assist with the shift left paradigm for Generative AI, including how AI/BI Genie helps with Generative analytics, and how Agent Studio helps with synthetic generation of test cases to validate model performance.

Learn how Chevron transitioned their central finance and procurement analytics into the cloud using Databricks and ThoughtSpot’s Agentic Analytics Platform. Explore how Chevron leverages ThoughtSpot to unlock actionable insights, enhance their semantic layer with user-driven understanding, and ultimately drive more impactful strategies for customer engagement and business growth. In this session, Chevron explains the dos, don’ts, and best practices of migrating from outdated legacy business intelligence to real time, AI-powered insights.

In today’s data-driven landscape, business users expect seamless, interactive analytics without having to switch between different environments. This presentation explores our web application that unifies a Power BI dashboard with Databricks Genie, allowing users to query and visualize insights from the same dataset within a single, cohesive interface. We will compare two integration strategies: one that leverages a traditional webpage enhanced by an Azure bot to incorporate Genie’s capabilities, and another that utilizes Databricks Apps to deliver a smoother, native experience. We use the Genie API to build this solution. Attendees will learn the architecture behind these solutions, key design considerations and challenges encountered during implementation. Join us to see live demos of both approaches, and discover best practices for delivering an all-in-one, interactive analytics experience.

This session is repeated. Get the most out of your AI/BI Dashboards by scaling them across your entire organization. This session covers best practices for automating report distribution, embedding dashboards in external applications, and ensuring secure access across all surfaces. You'll walk away with practical strategies for delivering insights to the right people at the right time—empowering decision-makers at every level with the data they need to drive impactful outcomes.