It makes sense for people when they hear it, but what does it actually mean in practice? And maybe can you tell us a little bit about what separates a truly trusted foundation from one that simply has governance controls in place?

Yeah, sure.

So to me, a trusted data foundation is one that can answer four questions for us, right? So the first is, is this data good, right? So good means a fit for the purpose to which it's intended.

So for instance, good for our finance team is 100% accurate 100% of the time.

good for our marketing team if it's coming down to something like running a marketing campaign where we're emailing all of the people that, you know, stopped by our booth at a trade show.

If we transpose some characters at an email address, it doesn't really matter if we have the email address wrong, we'll still run with that marketing campaign.

So really understanding whether or not the data is good enough for the use case and the requirements of when it comes to things like, you know, quality and freshness and so on are set by use case, right? So the second question that we need to be able to answer is, what does the data mean? So if I take something like revenue, what does revenue mean? So to a salesperson, it's a component of the calculation of how they get paid commission.

Can you talk a little bit more about why the Data Foundation, the Trusted Data Foundation, helps with that part of moving from experimentation into production?