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.

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.

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

Escape the buzz and discover a quiet space to meditate, stretch, and recharge—leaving you centered and refreshed. Please leave your laptops, meetings, and phone calls at the door.