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Apply DAX expressions for calculations

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts
See the prompt↓All Microsoft Power BI tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskCalculate the 'Average Order Value' for the sales dashboard by dividing 'Total Sales' by…+
Calculate the 'Average Order Value' for the sales dashboard by dividing 'Total Sales' by 'Number of Orders'. Apply this DAX expression to a new measure, ensuring it correctly aggregates across all filters.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore the executive review, create a new measure for 'Average Order Value' that is robust and…+
Before the executive review, create a new measure for 'Average Order Value' that is robust and accurate. Define the DAX expression, and then test it against different filters and segments to ensure it holds up under various slices of the data.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentMy 'Profit Margin' calculation is showing wildly incorrect values when I filter the dashboard…+
My 'Profit Margin' calculation is showing incorrect values when filtered by region.
My 'Profit Margin' calculation is showing wildly incorrect values when I filter the dashboard by 'Region', but it looks fine at the total level. The finance director is asking for these numbers by end of day. I've checked the base columns, but I'm not sure if it's the DAX or the data model. What's the most likely reason for this discrepancy, and what's the best next step to diagnose the DAX expression's behavior under filter context?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternMy DAX calculations often give me headaches, showing incorrect results or breaking when users…+
My DAX calculations frequently break or show incorrect results under specific filters.
My DAX calculations often give me headaches, showing incorrect results or breaking when users apply specific filters, leading to distrust from the business users. I spend too much time debugging. What habit should I change in how I write or test my DAX expressions to ensure they are robust and accurate across all filter contexts from the beginning?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Microsoft Power BI's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.