A tricky case would be SLA reporting in a support platform. You can calculate resolution time from timestamps, but enterprise tickets may have paused SLA clocks while waiting on the customer, and different support tiers may have different targets. A computed column can be perfectly valid and still flag the wrong tickets if those rules aren't reflected in the metric. I'd want to test the calculation against edge cases before letting users group and chart the results for operational decisions.
Good example, Sina. For an official SLA report, I would want the pause rules and support-tier targets defined and tested centrally, then expose those measures in the report. Asking each user to recreate that logic in a computed column makes it too easy to get different answers. AI-generated computations are useful for exploring data, but operational decisions need agreed definitions and edge-case tests.
Sina Rezaei
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A tricky case would be SLA reporting in a support platform. You can calculate resolution time from timestamps, but enterprise tickets may have paused SLA clocks while waiting on the customer, and different support tiers may have different targets. A computed column can be perfectly valid and still flag the wrong tickets if those rules aren't reflected in the metric. I'd want to test the calculation against edge cases before letting users group and chart the results for operational decisions.