We've looked at this. We've discussed this. This could be, you know, lots of people in a cross functional meter departmental meeting. We can look into it even further in situ. Right? So this is all based on a catalog. So if I were to click on my chart, I have the ability to explore this cell. And this is because it's been built on, my predefined model on my catalog. So here I can see This means that you can now slice and dice this chart in any dimension, any time frame, any anything you wish just to dig into what's going on because all powered by, the logicalness of the semantic layer, which means you can just take any metric dimension and split this chart out. Yeah. Absolutely. So I'm doing this in, in a new single cell view. I'm not I'm not in a canvas. I can't pan around. But I am able to, yeah, do what I like with it, and it's not gonna affect the underlying, report. So I, I've just split my geography, and I can see, okay. There's, like, UK is predominantly driving this. I could also look at that as a table if I wanted, see the underlying data. Let's stick with the visual. And if I wanted to save this, I could save it as a canvas. So let me just save it back there. I've just changed this visual. That's okay. And then what that's gonna do is push this into canvas, where I can do further work on it. So, if I get back to where it was, so it might be now that maybe I am a local user. Maybe I've just discovered this. I've explored my own, and I want someone else to go and, like, dig deeper, I could tag them to come to have a look. We have a lot of success with, I'd say, low code users that then have the ability to identify issues or trends and tag others that maybe want to look further into the SQL, like do or bring in additional data that's not in your model. So, you can build a fairly simple catalog, and it still can open up, to a lot more. I think I saw Ollie darting around in this canvas. Yeah. I'm I'm into this canvas now because you've you've obviously you've taken out you've seen a metric which looks strange. You've exploded it, explored it a bit, and then you've said, I wanna save this to a new canvas, which is now gonna be more of a kind of working environment to problem solve what's going on. And I've joined you in here, and I'm now bringing in other metrics and exploring the data myself. I've actually brought in something here about expansion to see if the, you know, what the geographies which are driving churn. I need to say geographies which drive the expansion. So let me just run that query here, and you can see actually that the expansion's coming for a lot from the UK, which isn't really where we're getting our our our drop as much. Actually, that's not true. The UK is dropping too. So it's not that we're changing a geography split here. We've got churn and expansion happening in the same region, so that's not necessarily the answer we're looking for. But at least we're digging into the numbers together. We're cloud we're working in a real time and collaborative environment. And maybe to finish this off, I'm now gonna make bring in a template, which is just a kind of a a slide in this case, a slide presentation, and I can then drop in that chart to say, expansion, region isn't a cause of journal, whatever we've come to realize. So I can tell the story that the metric tree points to and help us get to a decision point, a presentable outcome, all built off that semantic layer. So all the metrics we're looking at, all running off the same rules, all have the same definitions. So our exploration and our metric tree are all working together through one exploratory workflow.