◆ Google Looker

Build one Looker report across multiple Google sources

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 taskBuild a new report that combines sales data from our BigQuery 'transactions' table with…+
Build a new report that combines sales data from our BigQuery 'transactions' table with customer demographics from the Cloud SQL 'crm_data' database. I need to see total sales by customer segment for the last quarter, broken down by region, for the Monday leadership review.
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'm building the 'Product Performance' report for the product team, pulling from our Google…+
I'm building the 'Product Performance' report for the product team, pulling from our Google Analytics 4 and Salesforce data. Make sure it's easy for them to slice the data by product category and launch date, and highlight any products with declining engagement month-over-month. The goal is to spot underperforming products quickly.
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 marketing team needs a consolidated report for their Thursday presentation showing Google…+
The marketing team just asked for a report combining ad spend from Google Ads with website conversions from GA4, but the dates aren't aligning.
The marketing team needs a consolidated report for their Thursday presentation showing Google Ads spend against GA4 conversions, but the date ranges in the two sources don't seem to perfectly overlap, leading to gaps. I'm afraid to tell them I can't get an exact match. Is there a common way to handle these slight date discrepancies when joining disparate Google sources without losing critical data or making assumptions?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternEvery time I build a new report pulling from multiple Google sources like BigQuery, GA4, and…+
I frequently struggle with inconsistent naming conventions and data types when joining data from different Google sources for new reports.
Every time I build a new report pulling from multiple Google sources like BigQuery, GA4, and Cloud SQL, I spend hours cleaning up inconsistent naming conventions and data types. It's a huge time sink and often introduces errors. What habit can I change in my initial data modeling or source preparation to standardize these elements upfront and make future report building more efficient and reliable?
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.