Learn why dbt is the best place for analysts to build reliable data products quickly, combining structured workflows with context-aware AI. We will explore how dbt Canvas, dbt Studio, and more give analysts the visibility, control, and flexibility they need to move from exploration to production without relying on engineers. You will also see how AI agents in dbt accelerate development by recommending logic, surfacing relevant models, and helping troubleshoot issues—making self-service both faster and more trusted.

Aura Minerals cut pipeline migration time by 87%, transforming a 45-hour manual process into a 6-hour lift with relatively little manual oversight. In this session, learn how the team used AI tools to accelerate their shift from a complex PySpark environment to a streamlined, modern dbt workflow. You’ll walk away with a clear view of the strategy, the tools they used, and what it looks like to modernize your data stack with AI as a force multiplier.

In this talk, EQT walks through their journey to dbt Fusion, focusing on how they re-architected their data workflows for speed, scalability, and maintainability. Using three real-world projects as case studies, they'll show how State Aware Orchestration reduced runtimes (you don’t want to miss this!), simplified job orchestration, and surfaced a few unexpected pitfalls along the way. They'll wrap up by sharing lessons learned and practical tips for teams planning their own Fusion migration.

At EMC Insurance, inconsistent data definitions across a rigid legacy system led to an estimated $6 million analyst-hours spent on reconciliation instead of delivering insights. We needed a way to standardize metrics fast. By using the dbt semantic layer alongside Analytics8, we created a consistent, queryable layer for metrics like loss ratio, helping teams across the business get on the same page and ensure a single source of truth. This session walks through how we approached the problem, what we built, and what we’d do differently. If you’re trying to clean up inconsistent reporting or move away from fragile legacy logic, this is for you.

Join us for a roundtable discussion where we’ll go deeper into the ideas shared in the Next-gen data development with dbt Fusion engine breakout. Bring your questions, share your take, and connect with peers and presenters. Note attendance in the breakout session is not required.

Get hands-on with dbt Copilot, the AI assistant built into dbt that helps you move faster and write better code. In this workshop, you’ll learn how to use copilot to generate sql, create data tests and documentation, and build semantic models and metrics —all within your existing workflow. What to bring: You must bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and data platform.

Bilt Rewards turned their dbt project into a natural language interface. By connecting their semantic layer and underlying data warehouse to an LLM, business users and data analysts can ask real business questions and get trusted and creative insights. This session shows how they modeled their data for AI, how they kept accuracy intact, and increased data driven conversations across the business.

Easy, fast, and scalable: pick 3. MotherDuck’s managed DuckLake data lakehouse blends the cost efficiency, scale, and openness of a lakehouse with the speed of a warehouse for truly joyful dbt pipelines. We will show you how!

The session details how our lean central data team has achieved significant output by: Deploying the optimal tools (dbt and Lightdash) that supercharge DevEx Democratizing dbt development effectively Leveraging AI driven development Effectively using Kanban prioritization

Delve into the core concepts and applications of data quality with dbt. With a focus on practical implementation, you'll learn to deploy custom data tests, unit testing, and linting to ensure the reliability and accuracy of your data operations. After this course, you will be able to: Recognize scenarios that call for testing data quality Implement efficient data testing methods to ensure reliability (data tests, unit tests) Navigate other quality checks in dbt (linting, CI, compare) Prerequisites for this course include: dbt Fundamentals What to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and data platform. Duration: 2 hours Fee: $200 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes

Get hands-on experience migrating an existing dbt project to Fusion in this interactive workshop. Work alongside dbt experts who will guide you through common migration patterns, troubleshooting techniques, and best practices for optimizing dbt with Fusion. You'll leave this session with practical solutions on how to upgrade a dbt project to Fusion. After this course, you will be able to: Use dbt with Fusion to speed up model compilation, improve development workflows, and get deeper insights into your project’s structure. Prerequisites for this course include: dbt fundamentals What to bring: You will need to bring your own laptop. We will use the dbt VS Code Extension, so please install VS Code ahead of time. Duration : 2 hours Fee : $200 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass. Trainings and certifications are not available for Coalesce Online passes.

At EQT, we use dbt as the backbone for contracts, metadata, and increasingly, semantic models. Many of our users work in Excel, so we built a custom add-in to make governed data and shared metrics directly accessible where exploration happens. This setup also lets us experiment with AI-assisted discovery and text-to-SQL, connecting both raw data and dbt’s semantic layer to live, auditable analysis.

Get ready to accelerate your career trajectory! Join this session designed specifically for dbt practitioners who are serious about their impact. This isn't just about code; it's about making your technical dbt work undeniably indispensable by tying it to quantifiable business value. In this interactive session you will learn: How to talk to your manager about the real ROI of your contributions, fueling your professional growth as a dbt champion How executives think about business outcomes and evaluate software Ways to directly connect the challenging work you do every day to the company's business success How leading dbt customers have already quantified their massive financial impact

Get certified at Coalesce! Choose from two certification exams: The dbt Analytics Engineering Certification Exam is designed to evaluate your ability to: Build, test, and maintain models to make data accessible to others Use dbt to apply engineering principles to analytics infrastructure We recommend that you have at least SQL proficiency and have had 6+ months of experience working in dbt (self-hosted dbt or the dbt platform) before attempting the exam. The dbt Architect Certification Exam assesses your ability to: Design secure, scalable dbt implementations, with a focus on environment orchestration Role-based access control Integrations with other tools Collaborative development workflows aligned with best practices What to expect Your purchase includes sitting for one attempt at one of the two in-person exams at Coalesce You will let the proctor know which certification you are sitting for Please arrive on time, this is a closed-door certification, and attendees will not be let in after the doors are closed What to bring You will need to bring your own laptop to take the exam Duration: 2 Hours Fee: $100 Trainings and certifications are not offered separately and must be purchased with a Coalesce pass Trainings and certifications are not available for Coalesce Online passes If you no-show your certification, you will not be refunded

We transformed our entire stack to turn data into a competitive asset for our team and clients—going from scattered SQL scripts to a governed, scalable, AI-enabled architecture. Learn how we eliminated silos and standardized logic to create a data-forward culture with dbt as our transformation backbone.

AI is reshaping every stage of the analytics process. And at Docusign, that transformation is already underway. The data team is using AI to boost data quality, save engineers time, and deliver insights business users can actually trust. This session takes you end to end, from automated unit tests to governed metrics, showing how Docusign connects AI-driven development with self-serve analytics powered by the dbt Semantic Layer. The result: faster delivery, fewer surprises, and smarter decisions across the org.

Learn how to structure your dbt projects to enable more collaborative development without losing control. This session covers best practices for managing GitHub repos, organizing Snowflake schemas, and enabling safe, governed access to dbt models. Leave with actionable workflows your platform team can implement today to balance speed and oversight.

Discover how Workday built an AI-powered self-service analytics platform that doesn't compromise on governance using Lightdash. We'll discuss concrete strategies for transforming your data organization from a bottleneck into a competitive advantage, backed by real implementation insights.

Siemens Data Cloud runs over 1500 dbt Platform projects across teams and domains. But more projects can mean more silos and less visibility. Because dbt is designed to be project-scoped, getting a birds-eye view isn’t easy. That’s where the dbt Platform Admin API comes in. We’ll show how we used it to extract metadata and build a unified monitoring dashboard. You’ll learn how to track deployments, spot anomalies, and compare project health across your dbt landscape.

Discover how to turn your customer data into actionable insights using Generative AI. In this session, you'll see how Fivetran and dbt make it easy to prepare data from platforms like HubSpot and Zendesk, and how to use that data to power a Gen AI app that answers your business questions in real time.

Learn how dbt is evolving with the next-generation engine powered by Fusion. In this hands-on session, you'll explore how Fusion improves dbt’s performance, enables richer SQL parsing, and sets the stage for future enhancements like better refactoring tools and faster development workflows. What to bring: You must bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt and a data platform.

Join fellow practitioners for intimate roundtable discussions about modern analytics work, led by the analytics team at dbt! We'll explore career evolution, productivity tips, and project best practices. You will also get a sneak peak at how the analysts of dbt are getting value from dbt themselves.

In the last few months, I’ve been working hard to onboard new data and analytics engineers. Along the way, I’ve learned which parts of dbt and dbt Cloud are hard to teach, what confuses people, and where tools or training fall short. I’d like to swap ideas and hear how others are handling this.

Explore the growing dbt and Tableau partnership. Learn how integrations enhance the modern analytics stack, streamline workflows, and provide accurate, actionable insights with strong data governance.

Okta is rebuilding its data platform, moving from disconnected pipelines to a scalable, well-governed foundation with Snowflake and dbt. In this session, you’ll learn how we improved CI/CD, enabled self-service, and are now testing a prototype to make dbt models ready for AI.