Copilot-Focused Model Enhancements
If you've ever worked on a semantic model for any meaningful length of time, you'll know the struggle. You're carefully crafting your model, streamlining it to perfection, then comes the inevitable curveball from above, usually accompanied by an unnerving sense of urgency. Suddenly, you're stuck with questionable fields or calculations that don't fit into your beautifully streamlined vision but must remain nonetheless.
I've faced this more times than I'd like to admit. Marketing insists on keeping an obscure calculation no one fully understands, Finance demands a specific filter condition that clashes with everything else, and Operations have their quirks too. At this point, you're probably wishing you could hide these pesky items from Copilot, even if they're stubbornly stuck in your model.
Thankfully, this is exactly where the simplified AI Data Schema becomes your best friend. It lets you choose which tables and columns Copilot can see, effectively hiding the less-than-ideal aspects of your model from its view. Your stakeholders can keep their bizarrely specific requests satisfied, while Copilot remains blissfully unaware of these clutter-causing fields. Problem solved.
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Verified Answers is another essential tool in your semantic toolkit. There's nothing quite as professionally awkward as discovering that Finance and Marketing have both run their numbers from your so-called "single source of truth" model, only to end up with entirely different results. Your credibility takes a hit faster than you can say "semantic layer."
But Verified Answers let you curate specific responses to common or critical business questions with predefined answers. Think of them as your semantic model's FAQ section, except it’s rigorously vetted and consistent. Instead of Finance and Marketing going rogue with their queries, you provide verified, consistent responses directly in Copilot.
At its core, the role of a data analyst involves deciphering what management really wants, translating vague requests into trustworthy, and repeatable analyses. With Copilot, we're effectively asking AI to handle a chunk of this role by interpreting natural language queries from users. To do that well, Copilot needs as much of your knowledge downloaded into it as possible. You're essentially training your AI partner to interpret requests exactly as you would.
Analysts shouldn't see Copilot as a threat to their jobs, though. Who actually enjoys those endless ad-hoc data requests pinging into their inbox just as they're diving into a complex and intellectually rewarding analysis? I certainly don’t. By training Copilot effectively, you reduce those interruptions, allowing you to focus more of your time on the meaningful and challenging projects you signed up for in the first place.
Set Copilot up for success, and you're setting yourself up for a less stressful working life. Use the simplified AI Schema to shield Copilot from the model's less-than-ideal quirks, and Verified Answers to provide trusted, consistent responses. Your stakeholders get reliable information and you maintain your credibility.