Which practice supports governance when distributing Fabric content across multiple workspaces?

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Multiple Choice

Which practice supports governance when distributing Fabric content across multiple workspaces?

Explanation:
Centralized governance policy across workspaces is the best approach because it ensures consistent rules, access controls, data classifications, and auditing wherever content is distributed. When semantic models and reports span multiple workspaces, a single governance policy provides a uniform set of criteria that all spaces must follow, making enforcement, compliance, and lifecycle management much easier. Separating semantic models and reports into different workspaces can create governance gaps or mismatched permissions. Reusing shared semantic models helps with consistency of the models themselves, but it doesn’t by itself enforce governance across all the workspaces where those models and their reports live. Storing everything in one workspace defeats the purpose of distributing content and makes it harder to scale governance as more workspaces are added.

Centralized governance policy across workspaces is the best approach because it ensures consistent rules, access controls, data classifications, and auditing wherever content is distributed. When semantic models and reports span multiple workspaces, a single governance policy provides a uniform set of criteria that all spaces must follow, making enforcement, compliance, and lifecycle management much easier.

Separating semantic models and reports into different workspaces can create governance gaps or mismatched permissions. Reusing shared semantic models helps with consistency of the models themselves, but it doesn’t by itself enforce governance across all the workspaces where those models and their reports live. Storing everything in one workspace defeats the purpose of distributing content and makes it harder to scale governance as more workspaces are added.

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