r/Looker

I'm a Business intelligence analyst and converted all our company tableau dashboards into lookml dashboard. However, the issue is IT is saying all my dashboards are consuming too many TCPU.

We have like 10 dashboard with some holding less than 10 tiles and some holding more than 20 tiles.

Currently, we are trying to move our database from Teradata into GCP but IT is slow.

Users complain that when they add a filter, it takes too long to update. I am unable to use materialized views or PDT because GCP is not yet set up.

Does any have a workaround for this?

Also, how to set lookml dashboards to run once a day instead of running the query everytime someone opens the file?

Hey all, hoping to get some advice from people who have dealt with this.

We use BigQuery + dbt + Looker. Looker is good for LookML + BI, but I’m starting to wonder whether it makes sense for it to be the place where all of our semantic logic lives.

We want people to be able to self-serve data through dashboards, but also through ChatGPT, internal tools, and whatever other interfaces we end up using. Ideally, someone asking the same question gets the same answer regardless of where they ask it, with the same metrics, joins, filters, definitions, and time logic behind it.

The bit I’m struggling with is that conversational analytics needs more than just a semantic model. It also needs business context, guidance on how to explore safely, known gotchas, and some way of showing where an answer came from.

At the moment, that stuff can end up spread across dbt, Looker, MCP config, prompts/skills, and whatever chat tool we are using. I don’t really want to maintain different versions of the same context for every tool.

I’ve been looking at Cube as a more headless option, where the semantic layer sits behind APIs and different tools consume it. But then I worry about what we would use for business-facing dashboards and how much extra platform work we would be taking on.

I’m also looking at Lightdash because we use dbt Core. It seems closer to what we want, but I’m still trying to work out whether it is mainly a BI tool with a semantic layer, or whether people are successfully using it as a shared layer across other clients too.

I’m not looking to rip out Looker tomorrow. I’m mostly trying to work out whether this is the right direction before going too far down the rabbit hole.

Has anyone been through something similar? What did you choose, and what would you do differently?