◆ Google Looker

Solve common Data Studio problems

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 taskFix the 'Sales by Region' dashboard; it's showing incorrect totals for the APAC region and the…+
Fix the 'Sales by Region' dashboard; it's showing incorrect totals for the APAC region and the sales team needs it for their Monday meeting.
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 fix the 'Sales by Region' dashboard, analyze the data source and calculations for the…+
Before I fix the 'Sales by Region' dashboard, analyze the data source and calculations for the APAC region. Identify the root cause of the incorrect totals and suggest the most efficient way to correct it without impacting other regions or future data integrity.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentI've tried two different fixes for the 'Sales by Region' APAC totals, and they both seem to…+
I've tried two different fixes for the 'Sales by Region' APAC totals, and they both seem to break something else.
I've tried two different fixes for the 'Sales by Region' APAC totals, and they both seem to break something else, like the EMEA totals or the quarterly comparison. The sales VP is pressing hard for this by end of day, and I'm afraid of making it worse. I can't tell if the underlying data is flawed or if the calculation logic itself is fundamentally broken. What's the likely diagnosis here, and what's the best next move to deliver an accurate report without causing new problems?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI constantly get pulled into urgent 'broken dashboard' fixes that disrupt my planned work and…+
I constantly get pulled into urgent 'broken dashboard' fixes that disrupt my planned work.
I constantly get pulled into urgent 'broken dashboard' fixes that disrupt my planned work and prevent me from tackling strategic projects. This makes it hard to show progress on my own goals. What habit should I change to proactively identify and address potential dashboard issues before they become critical emergencies for the business users?
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.