Are you also finding now with how quickly technology and the tools that we've got and AI and everything has come into play, are you finding data governance is being looked at differently and maybe a bit more positively than it used to? Or do you still feel like it's still just as challenging? I'm sure that others would disagree with me, but

I kind of feel like we've hit the limelight because there was always... that time and the human in the loop of making sure it's like there was always something that would make it get over the line.

There was always something that would get you your business outcome because somebody would nudge it that last little bit.

And so if you didn't have every definition, if you didn't have your lineage, if you didn't have all of these rules, and if we didn't know all of that, you know what, we can make it through.

And the slight nuances of the edge cases of percent of things not being right was manageable.

That's kind of not an option if you want accuracy in your AI outcomes.

So the realization is coming is, yeah, I know you always said it was a really good idea to have a definition for everything and have an understanding of that.

How are you managing this has to be perfect narrative and or is everything able to be perfect or do you have to pick and choose the ones that can be? Can you talk us a bit through that? How do you manage that? Yeah, I think