 Okay, so John Friedrich with Meta Integration, John. Thank you. So I have precisely one slide, and it is only five minutes. They always say spend about five minutes per slide. There it is. Fairly simple picture, right? Now, we called it the big picture, and I say we because Christian Burma was going to be here, but unfortunately is going to be a little late. So it's just me, and but we called it the big picture, which of course could mean a lot of different things. I mean, if for example, you're in some kind of conference about, I don't know, string theory, I guess the big picture would look a little different than it does here. Actually, even within this community here, what is the big picture of course varies a lot. Now this is the big picture mostly from what we see as a company Meta Integration. If you know us at all, we deal with being able to exchange information, especially what people deal with in enterprise architecture, in master data management, et cetera. In other words, what we always refer to as metadata. And so what we talk about is being able to move it around. Now, why do we do it? Well, so all our partners can actually start to look at this big picture and start answering some things. One of the things to recognize here is because of the development, even going back, because of the development of relational databases and then all the stuff that came out of it from business intelligence, standardized ETL, all these wonderful technologies have allowed us now to get a good picture of the entire data flow architecture here, horizontally across at the bottom of this picture. A very good picture of it. In fact, we connect into just about every one of the technologies that is in the exhibit hall, one way or another, so that people can do that. They can take it and bring it together. And in fact, many of those partners have solutions to do that that we then feed. So it works out really well. The idea being that you can actually access all those different technologies, business, intelligence, data warehouse designs, of course data integration, ETL, ELT, that sort of thing. ODIs, any SAPBW, all that kind of stuff that would be in the enterprise, being able to capture metadata out of there and be able to therefore answer where do those business reports come from? And if I make a data entry over here, where does it appear? And if you can answer those questions, it's huge. You're answering things that the business user wants. And as we know, that's where the money is. Business users will define that. You can also answer a lot of wonderful information management questions. For example, if I'm going to make a change to a system, where will it impact, et cetera. Okay, we know all these things, but keep in mind, as I said, what has created that opportunity has been, in part, standardization and in part, the fact that very powerful tools exist out there that we can then take advantage of the fact that they have a standard way of doing it, at least within that environment of the tool. So what we've done, obviously, is put that all together into one nice picture. You have a nice end-to-end lineage picture. But the other thing that needs to be recognized that is equally maybe even more important, depending on which community you look at, this community probably even more important, is what we refer to as semantic lineage, but this vertical component. The idea is that there are, in fact, relationships that can be, and in fact, lineage impact, et cetera, type questions that can be asked vertically. And of course, actually, even from data flow issues, for example, change of something, what does it do to what is in your enterprise vocabulary? Okay, here's your terms. Then, what terms are those mapped down to in these reports that you wouldn't have seen data flow for? These are all huge, huge possibilities in terms of being able to answer, as I said, fundamental questions like, where's data coming from? Where does it go to? And therefore, how do I manage what is sitting out there? Again, five minutes, and I think I'm there? 30 seconds. 30 seconds, oh, I was looking at that one. So I'm pretty close to the end. Basically, what I'm trying to get across is a recognition that we're spending a lot of time, in a lot of ways, we have mastered, in a lot of ways, the data flow, lineage impact analysis problem. And we're just now beginning to really understand how to tie in the semantic lineage side to that. That's gonna be a big, huge push. I think you'll see a lot of the companies out there putting it together either through metadata management solutions, enterprise architecture, all that kind of stuff. Thank you. Thank you. Thank you.