◆ Microsoft Power BI

Convert JSON list records to tables

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

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskTake this JSON list of customer orders and convert it into a clean table in the finance…+
Take this JSON list of customer orders and convert it into a clean table in the finance dashboard, ready for the Q3 revenue report.
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 I bring this JSON sales data into the new regional dashboard, make sure it's easy to…+
Before I bring this JSON sales data into the new regional dashboard, make sure it's easy to merge with existing customer records and that any missing fields are flagged clearly. I don't want to spend all day cleaning this up.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe new marketing JSON data isn't matching our customer IDs, and finance needs this reconciled…+
The new JSON data feed from the marketing campaign isn't aligning with our existing customer IDs, and the finance team needs a unified view by end of day Friday.
The new marketing JSON data isn't matching our customer IDs, and finance needs this reconciled by Friday for their campaign ROI. I'm afraid of double-counting or misattributing sales. I can't tell if the IDs are just different formats or if there's a deeper mismatch. What's the likely diagnosis for this ID misalignment, and what's the best next move to get this data merged accurately and quickly?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm spending too much time every month manually cleaning and reshaping JSON data from various…+
I keep losing hours every month manually cleaning and reshaping JSON data from different sources before it's usable in our reports.
I'm spending too much time every month manually cleaning and reshaping JSON data from various sources before I can even start analysis. It's eating into my strategic work. What habit should I change to automate or streamline this initial JSON ingestion and transformation process, so I'm not always behind before I even begin?
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.