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dbt Mesh FAQs

dbt Mesh is a new architecture enabled by dbt Cloud. It allows you to better manage complexity by deploying multiple interconnected dbt projects instead of a single large, monolithic project. It’s designed to accelerate development, without compromising governance.

Overview of Mesh

 What are the main benefits of implementing dbt Mesh?
 What are model contracts?
 What are model versions?
 What are model access modifiers?
 What are model groups?
 What are some potential challenges when using dbt Mesh?
 How does this relate to the concept of data mesh?

How dbt Mesh works

 Can dbt Mesh handle cyclic dependencies between projects?
 Is it possible for multiple projects to directly reference a shared source?
 What if a model I've already built on from another project later becomes protected?
 If I run `dbt build --select +model`, will this trigger a run of upstream models in other projects?
 If each project/domain has its own data warehouse, is it still possible to build models across them?
 Can I run tests that involve tables from multiple different projects?
 Which team's data schema would dbt Mesh create?
 Is it possible to apply model contracts to source data?
 Can contracts be partially enforced?
 Can I have multiple owners in a group?
 Can contracts be assigned individual owners?
 Can I make a model “public” only for specific team(s) to use?
 Is it possible to orchestrate job runs across multiple different projects?
 Integrations available between the dbt Cloud Discovery API and other tools for cross-project lineage?
 How does data restatement work in dbt Mesh, particularly when fixing a data set bug?
 How does dbt handle job run logs and can it feed them to standard monitoring tools, reports, etc.?
 Can dbt Mesh reference models in other accounts within the same data platform?

Permissions and access

 How do user access permissions work in dbt Mesh?
 How do all the different types of “access” interact?
 Is it possible to request access permissions from other teams within dbt Cloud?
 As a central data team member, can I still maintain visibility on the entire organizational DAG?
 How can I limit my developers from accessing sensitive production data when referencing from other projects?
 Does dbt Mesh work if projects are 'duplicated' (dev project <> prod project)?

Compatibility with other features

 How does the dbt Semantic Layer relate to and work with dbt Mesh?
 How does dbt Explorer relate to and work with dbt Mesh?
 How does the dbt Cloud CLI relate to and work with dbt Mesh?


 Does dbt Mesh require me to be on a specific version of dbt?
 Is there a way to leverage dbt Mesh capabilities in dbt Core?
 Does dbt Mesh require a specific dbt Cloud plan?

Tips on implementing dbt Mesh

 Is there a recommended migration or implementation process?
 Are there tools available to help me migrate to a dbt Mesh?
 My team isn’t structured to require multiple projects today. What aspects of dbt Mesh are relevant to me?