◆ Google Looker

Input data into Looker Studio

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.

3prompts
See the prompt↓All Google Looker tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AImprove — make it easier to acceptBefore I add this new customer feedback data, make sure it cleans up nicely – check for…+
Before I add this new customer feedback data, make sure it cleans up nicely – check for duplicates, inconsistent spellings in product names, and flag any missing sentiment scores.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BDecide — diagnose the stuck momentThe new marketing campaign data just came in, but it's full of blank fields and weird codes…+
The new marketing campaign data just came in, but it's full of blank fields and weird codes.
The new marketing campaign data just came in, but it's full of blank fields and weird codes where I expected product names. I'm afraid if I push this live, the dashboard will show nonsense and Mark from marketing will lose trust in our numbers. I can't tell if this is a data entry error on their side or a formatting issue on mine. What's the fastest way to diagnose this and get a clean dataset ready for the Monday morning review?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CBecome — change the patternI keep spending too much time manually cleaning up data before I can use it in a report.…+
I keep spending too much time manually cleaning up data before I can use it.
I keep spending too much time manually cleaning up data before I can use it in a report. Whether it's sales figures or marketing spend, there's always some formatting issue or missing values. What habit should I change to spend less time on data prep and more on actual analysis, especially when pulling from different sources?
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 Google Looker'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.