dbt Mesh allowed for monolithic dbt projects to be broken down into more consumable and governed smaller projects. Now, learn how cross-platform mesh will allow you to take this one step further with development across data platforms using Iceberg tables. After this course you will be able to: Identify ideal use cases dbt Mesh Configure cross-project references between data platforms Navigate dbt Catalog Prerequisites for this course include: dbt Fundamentals, specifically data models and building model dependencies dbt Model governance Various data platforms 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.

Self-serve analytics promises speed. But without clear guidance, it often leads to hidden obstacles like cluttered dashboards, runaway costs, and a loss of trust in the data. Add AI to the mix, and those faults become fractures. In this session, we'll unpack why self-serve efforts stall, with lessons from real-world teams at Shopify and Tableau. We’ll also explore how BetterHelp uses dbt alongside Euno’s lineage and usage insights to declutter, cut compute costs, and determine which data assets and reports teams (and AI agents) can trust.

This course will focus on leveraging the semantic layer to build and consume metrics from dbt. We will start with an initial dbt project and leverage dbt Copilot to create the necessary logic to power your semantic layer. After defining and building these assets, we will configure partner tools to utilize single source of truth reporting: driving collaboration across data consumers in your team. Prerequisites: The prerequisites for this course include: dbt Fundamentals, specifically data modeling and model configurations 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 a data platform.

Join dbt experts Dustin Dorsey and Dakota Kelley from phData as they share real-world lessons from implementing dbt at some of the world’s largest enterprises. In this “tales from the field” talk, they’ll share real stories that highlight the most common challenges companies face and how they’ve helped teams solve them. Whether you’re just starting your dbt journey or looking to mature your organization, come hear from the experts and learn how to avoid the costly mistakes others have made.

Learn how the Wikimedia Foundation implemented an on-prem, open source data lake to fund Wikipedia and the future of open knowledge. We'll discuss data architecture including challenges integrating open source tools, learnings from our implementation, how we achieved a 10x decrease in query run times, and more.

Join us for a roundtable discussion where we’ll go deeper into the ideas shared in the Shaping the future of self-service with the dbt MCP server and Semantic Layer breakout. Bring your questions, share your take, and connect with peers and presenters. Note attendance in the breakout session is not required.

See how AI is shaping developer tools for the next generation. AWS Kiro provides a powerful general purpose IDE great for a wide variety of programming languages and tasks. Pairing Kiro with the dbt MCP Server makes this even more powerful by providing access to dbt specific functionality, context and agents. In addition to this, interact with an external agent deployed in Amazon Bedrock AgentCore.

Teams across industries spend countless hours every week, month, and quarter creating data-driven slide decks and documents for leadership reviews, business updates, and client reporting—even though the data lives in their BI tools. This “last mile” of data reporting remains highly manual, repetitive, and a drain on strategic bandwidth. In this session, we’ll share how leading companies are automating this process with Rollstack: Sony Music’s The Orchard streamlines leadership business reviews and scales reporting across its network of labels, enabling its lean Analytics team to focus on insights instead of slide production. CarGurus empowers its Customer Success teams to scale client QBR reporting, ensuring consistent, reliable outputs while saving hours of manual work. Join us to see how these organizations are transforming reporting workflows and giving their teams more time to focus on decisions that move the business forward—instead of being stuck as PowerPoint jockeys.

AI isn’t just a lab experiment at J.Crew. It’s already driving results. This session unpacks how a few early wins with AI are being scaled across the company. You'll learn how to spot issues early on and change approaches when necessary to ensure AI is useful across your organization, and what it takes to turn pilot projects into repeatable systems, including the training, tools, and metrics that matter. If you’re trying to apply AI beyond your data team to your business users, this could serve as your playbook.

Jerrie and Faith have developed a framework for thoughtful, effective data testing and QA. In this peer exchange, attendees will battle-test the framework by sharing where it fits across industries. Attendees will walk away with their own testing framework to try in their day jobs.

The dbt language is growing to support new workflows across both dbt Core and the dbt Fusion engine. In this session, we’ll walk through the latest updates to dbt—from sample mode to iceberg catalogs to UDFs—showing how they work across different engines. You’ll also learn how to track the roadmap, contribute to development, and stay connected to the future of dbt.

Learn how a small team at Dexcom used dbt to unify hundreds of global manufacturing data tables into 30 analytics-ready models—delivering sub-15-minute freshness and complex processing at scale. The result: faster, smarter manufacturing decisions that support the timely delivery of technology that has transformed how people manage diabetes and track their glucose.

Merging two large organizations with different tools, teams, and data practices is never simple. At Virgin Media O2, we used dbt to help bring consistency to that complexity, building a hybrid data mesh that supported self-serve analytics across domains. In this session, we’ll share how we gave teams clearer ownership, put governance in place using dbt, and set up secure data sharing through GCP’s Analytics Hub. If you’re working in a federated or fast-changing environment, this session offers practical lessons for making self-serve work at scale.

CHG Healthcare migrated 2000+ legacy MySQL jobs to dbt Cloud and Snowflake in record time. We'll share how Datafold used their AI-powered Migration Agent to migrate and refactor convoluted legacy code into dbt Cloud and Snowflake with full automatic validation, dramatically accelerating our modernization.

Let's get meshy! Learn how to evolve your organization's dbt project(s) to more effectively manage distributed data at scale by adopting data mesh as a grounding philosophy. This is your roadmap of "socio" strategies & "technical" dbt features to implement following the four principles of data mesh.

Discover how dbt Catalog brings structure and clarity to your data ecosystem by turning metadata into a powerful asset. In this session, we’ll dive into how the dbt Catalog helps data teams and their stakeholders explore, trust, and act on data faster—by connecting lineage, documentation, and usage in one place. Learn what’s available today, what’s coming next, and how dbt Catalog fits into the broader vision for metadata in the AI era.

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.

Step into a dynamic, interactive session where you'll experience the data transformation journey from multiple angles: Data Engineer, Manager, Analytics VP, and Chief Data Officer. This immersive tabletop exercise isn’t your typical panel or demo—it’s a high-empathy, scenario-driven experience designed to build cross-role understanding and alignment across the modern data stack. Each scene drops you into a real-world challenge—whether it's data trust issues, managing cost pressures, or preparing for an AI initiative—and forces a go/no-go decision with your peers. You’ll explore how your choices impact others across the org, from the technical trenches to the boardroom. Whether you're a practitioner, leader, or executive, this session will help you see data not just as pipelines and dashboards, but as a 360-degree opportunity to drive business change. Walk away with a clear picture of the capabilities your team needs (without naming products) and a roadmap for building champions across your org.

You’re sold on dbt, but your org isn’t quite there yet. Whether you’re introducing dbt from scratch or trying to scale it responsibly, this talk is for data practitioners navigating buy-in, timing, and tooling choices. We’ll cover how to choose the right entry point, which features to start with (and which to save for later), and how to align your rollout with your organization’s readiness. You’ll leave with a practical framework for introducing dbt in a way that sticks.

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

dbt Canvas makes it simple for every data practitioner to contribute to a dbt project. Learn the foundational concepts of developing in Canvas, dbt's new visual editor, and the best practices of editing and creating dbt models. After this course, you will be able to: Create new dbt models and edit existing models in dbt Canvas Understand the different operators in Canvas Evaluate the underlying SQL produced by Canvas Prerequisites for this course include: Basic SQL understanding 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

Building stakeholder trust through data is crucial for organizations. At Roche, we used dbt to create a transparent, robust data transformation process that helped gain confidence and increase dashboard adoption.This talk will show how the dbt helped Roche build a data platform trusted by business stakeholders.

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