There are 2 main use cases when it comes to collaborating with model consumers. These are outlined below:
Model exposure
High level end-to-end data flow
Model exposure
In this example, a customer has created a canvas that shows all of the available Amazon data.
If someone else wants to know which data exists on a certain topic, they can come to this canvas and explore what is available.
It's also really easy to swap queries between different databases - for example, too see how model contents change in production vs. development environments.
High level end-to-end data flow
In a canvas you can easily to explain how data is flowing through systems. This helps improve trust with data when you can display things visually.
It allows engineers to no longer work in a silo, and collaborate with other engineers and stakeholders.
Stakeholders can be involved in the process, helping them understand model structure.
The lag between request & delivery is removed, because models can be built alongside others.
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For more technical information about how the dbt integration works, see our docs.