Data Sourcing For Metric Trees - Database or Semantic Layer?

We can either build this directly from our database, and this will be essentially, like, a just a tidied up version of what I've just shown you, or we have the option to actually build this model into our semantic layer and create a catalog. The database version is, like, quick and easy as a first draft. Maybe that's an option you want to go with. But long term, it's not accessible or reusable. You know, it's sitting as canvas, in in this form. The benefits of modeling this out into the semantic layer is that it's essential source of truth. It's locked down. You've already gone through the deliberations of, like, how we define these metrics. Like, why not put that additional layer, of of security on top and be like, let's let's put this in a catalog. Others can come and use it, and we're not gonna worry about the calculations that they're using to get to these metrics. The joins are already predefined, and the aggregations are standardized. So taking a step out to actually put this in the catalog can reap a lot of benefits.