This looks like a straightforward question on the goals of clustering. I think I can handle this - the key is to remember that clustering is an unsupervised technique, so the goal is not to maximize a utility function, but rather to find similarities in the data.
This seems straightforward. I'm pretty confident I can figure out the one method that doesn't need to be overwritten if I just think it through logically.
I'm hesitant about option E; I wonder if integrations would be automatically restored or if we'd have to manually reconnect everything after the rollback.
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