◆ Google Looker

Configure Looker caching

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 taskSet the cache retention for the 'Daily Sales Summary' dashboard to 1 hour. Make sure this…+
Set the cache retention for the 'Daily Sales Summary' dashboard to 1 hour. Make sure this applies to all users accessing it.
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 acceptThe 'Daily Sales Summary' dashboard is getting hit hard by users refreshing it constantly,…+
The 'Daily Sales Summary' dashboard is getting hit hard by users refreshing it constantly, slowing down our database. Analyze the typical usage patterns and data freshness requirements for this dashboard, then recommend an optimal caching strategy to reduce database load without compromising data accuracy for the business users.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentOur database team just flagged the 'Daily Sales Summary' dashboard as a top contributor to…+
Our database team just flagged the 'Daily Sales Summary' dashboard as a top contributor to database load, especially during peak morning hours.
Our database team just flagged the 'Daily Sales Summary' dashboard as a top contributor to database load, especially during peak morning hours. I'm worried about hitting our database capacity limits, but the sales team needs fresh data daily. I don't know if a short cache time will make the data too stale for them. What's the balance, and what's the best next step to reduce database strain without impacting the sales team's daily operations?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI often find myself reacting to database load alerts caused by popular dashboards that weren't…+
I often find myself reacting to database load alerts caused by popular dashboards that weren't properly cached from the start.
I often find myself reacting to database load alerts caused by popular dashboards that weren't properly cached from the start. This wastes time and puts pressure on the database team. What habit should I change in my dashboard development workflow to proactively consider and implement appropriate caching strategies for new dashboards before they go live to a wide audience?
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.