The governance platform currently relies on people to gather evidence about a model by hand. Which choice best lets it collect that evidence automatically instead?
Select an answer to reveal the explanation.
Short Explanation
If you wire the governance tooling into the environments where model work happens, the evidence and metrics get collected as the work is done. You don't have to chase people for updates.
Full Explanation
The correct choice is connecting the governance tooling directly to the model development and deployment environments, so evidence and metrics are collected as work happens. Direct connection between governance tooling and the development and deployment environments lets metrics and artifacts be captured automatically as they are produced, rather than depending on someone remembering to report them.
Asking each data scientist to email a status update at the end of every sprint is incorrect because manual status emails are exactly the kind of unreliable, ad hoc evidence collection that integration is meant to replace.
Scheduling a quarterly meeting where teams verbally report on their models is incorrect because a quarterly verbal report is infrequent and unverifiable compared to continuously captured evidence.
Publishing a governance policy document that describes what evidence should exist is incorrect because a policy document states what should be collected but does not itself collect anything.
For the exam, connect 'automatic evidence collection' to integration between governance tooling and the working environments.