Scaling trusted self-service for dbt stakeholders

Scale dbt beyond the build team by enabling stakeholders to find, understand, and confidently reuse trusted data products—without requiring everyone to become a developer. This course covers what “trusted self-service” looks like in practice: documentation that answers stakeholder questions, ownership and support workflows, and trust signals that reduce back-and-forth and increase adoption.

After this lab, you will be able to:

• Define the components of trusted self-service (people, process, and platform signals)
• Implement stakeholder-friendly documentation patterns (definitions, intended use, grain, caveats)
• Establish ownership and support workflows for questions, requests, and change management
• Design a scalable stakeholder access model that expands governed consumption while protecting developer workflows

Prerequisites:

• Basic familiarity with dbt concepts (models, sources, tests, docs)

What to bring: You must bring your own laptop to complete the hands-on exercises. We will provide any required sandbox environments for dbt and the data platform.

Duration: 2 hours