◆ Google Looker

Implement data governance with Looker

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 taskApply the 'confidential' tag to all fields in the 'Employee Compensation' model. Restrict…+
Apply the 'confidential' tag to all fields in the 'Employee Compensation' model. Restrict access to this model to only members of the 'HR Leadership' user group, and ensure no one outside that group can even see its existence.
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 acceptI need to implement data governance for our customer data. Before I roll out the new 'Customer…+
I need to implement data governance for our customer data. Before I roll out the new 'Customer Profile' model, help me identify potential privacy risks and ensure compliance with GDPR. Flag any fields that contain personally identifiable information (PII) and suggest anonymization strategies where appropriate.
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 legal team just asked for a full audit trail on the 'Customer Consent' field used in our…+
The legal team just asked about the lineage of the 'Customer Consent' field in our marketing reports.
The legal team just asked for a full audit trail on the 'Customer Consent' field used in our marketing dashboards. I'm worried I can't quickly show them exactly where it originates and how it's transformed, which could delay our new campaign. What's the most likely gap in our current data governance setup, and what's the immediate next step to get them the information they need?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternDifferent departments often use slightly different definitions for metrics like 'new customer'…+
I frequently find different teams using slightly different definitions for key business metrics.
Different departments often use slightly different definitions for metrics like 'new customer' or 'churn rate', leading to inconsistent reporting and endless debates. This erodes trust in our data and wastes time. What habit should I change to proactively standardize these definitions and ensure everyone is speaking the same data language?
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.