 The use cases that we're seeing most kind of represent kind of the vast majority of customers are folks that are using what I would really call big data, sensor data, web data, log data, where they're data that they've really not analyzed before and that is, you know, really, really big. And they bring it into a service and allow them to kind of analyze and see trends, information they haven't actually used before. Specifically gaming. We have five or six gaming customers are using this for behavioral analysis. We have a number of customers using this for digital marketing, kind of looking at cross brand analysis. Other folks are using this for kind of a number of different things, looking at website trends and analysis again at a micro level. So kind of gives you a sense. So Rich, you said three things, cloud, big data and analytics. Yep. I wonder if we could unpack those. It's SaaS based service, right? It's absolutely. Sign up for the service and we not only provide the kind of database infrastructure, the platform of service that we talked about last year, but we also provide some of the integration capabilities. So if you're using big data, you're using web data or log data or sensor data, we actually have an agent technology that we can embed in those systems and load information in it at frankly very, very high rates. We have one customer that's actually loading 10 billion rows of information a day into our service. Okay. And then your big data piece, you talked about the column store, the stone breaker mojo. So that's the sort of data, the storage subsystem, right? Yeah. It's a data store. Yeah. Within a cloud infrastructure. So we're talking about a cloud based database, the securities inside the database, right? Absolutely. And you know, like anything, we run on Amazon. So we use Amazon as a platform with our own database. But the fact of the matter is we leverage all of their security services, take advantage of that. And many of the applications we're looking for aren't and doing today are ones where information is being aggregated at a high level. So security is not as big a concern as if you were looking at HIPAA data, for instance. Right. Okay. But so you're not, you know, partnering in Amazon in the sense that they're offering your service, you're utilizing the AWS infrastructure. You guys architected that, which is not trivial. Everybody thinks you can swipe the credit card and now you're on your way. It's exactly right. You really have to think about how to architect it, how to deal with security, how to deal with scale. You've got to deal with all the compatibility issues, the API issues. It's exactly right. Make sure it performs properly. I mean, there's a lot of work there that goes into that. And you bring up a really good point. One of the things that I think is an advantage in the way we look at it is we also provide a console environment for a particular user so that they can look at their instance that's running in the service and know exactly what's going on. What jobs are running, what jobs aren't running, what the performance looks like. If they have long running queries, why they're having long running queries, we give them a ton of information. And then, you know, we're at the Tableau conference. They can also, even though it's a service, connect to their local Tableau, you know, instance and be able to either leverage Tableau in the cloud or traditional Tableau. Okay. And then your analytics piece. Maybe you just touched upon that, but are you talking about an analytics, full-blown analytics platform? Are we talking about a platform to build analytics apps or a combination? Yeah. Most of what we're being used for, if you think about it, is we're a solution right now for the kinds of apps that we're looking at. So we'll build our dashboards and for those particular areas. For instance, we've done that for gaming. We've done it for digital media. We'll do that for some other areas as we move forward. Now, where are you guys based? We're based in California, in Mountain View, right in the middle of Silicon Valley. So it's a nice place to be. And what's head count? Head count today is almost 30 folks. So we're real small, real agile, growing like a weed. So what are some of the markets you're in, your customers are in, I should say? Do you see any, Dom, you mentioned gaming. What are some of the early adopters of your technology and your platform as a service approach? You know, most of our customers, interesting, I think because we're cloud-based, our line of business kinds of folks or medium-sized businesses that look at the cost profile of a service and say, this is something I can now do. You know, I can have my kind of little data warehouse for myself that nobody else, you know, I don't have to worry about all these other things of assembling all the components and all the people that are required to manage it. I can do it kind of myself. And that's what's enabled a number of our customers kind of in the medium line of business, you know, whether it be marketing or a particular area of a business. We have another kind of group that's emerging looking at sensor data on telemetrics basically on cars, which is also a real kind of interesting market because there's all kinds of sensors in cars these days, being able to collect those in real time and understand exactly what's going on from that automobile and how it's being driven and relationship to everyone else in that community is pretty interesting. It allows manufacturers to do a number of different things in terms of fine-tuning performance and fine-tuning usability, et cetera. So, you know, considering the business that you're in and the approach you're taking, I think I know to some degree the answer to this question, but I'd like to get you to expand a little bit on how you see this big data world evolving in terms of on-premise versus cloud. You mentioned you've got a lot of departmental customers. Do you see cloud becoming the dominant deployment model for big data in the enterprise? We've done some coverage at events like Strata and other places. We've talked to Cloud Air, for instance, kind of the market leader, kind of one of the first Hadoop companies. You know, most of their deployments are behind the firewall. Do you see that moving in the direction of the cloud? And is it going to be for all organizations or do you think, you know, the really large organizations that can still hire allegiance of administrators and developers are still going to do it behind the firewall? There's people that are going to build on-premise things for a long time. But I think we're at the beginning of a big trend. Forgetting about big data for a minute. The ability to basically have computing services outsourced to someone else just is the right thing to do over time. Why should companies be spending so much money just focusing and, you know, resources on getting their infrastructure in place to actually support the business? The more, the higher percentage of people can be supporting the business, the better that company is going to be. And Cloud's going to enable that. And so we're at the front end of that. I think for big data, if you tie Cloud to big data, you know, there's an issue with people don't know all of what they don't know about big data. So if you can give them a solution that's low friction, that they can get up and running really quickly, it's going to start to expand, I think, the market. Right now we're in love with social and we're in love with web data. And there's, you know, there's great applications and we're creating great value in those markets. But there's all kinds of things ahead of us. You know, we're just starting to talk about sensor data and we're just talking about all of the different areas where we could put sensors. And I think that market's going to explode. You know, instrumenting applications, instrumenting all kinds of things. That's starting and that gives, doing it in a cloud-based environment, gives you a cost profile and a time-to-value equation that makes it really exciting and I think going to be a big vacuum in the market or in a sucking sound in the marketplace, so to speak. So yeah, really the idea of, you know, you as a business, you as a company, focus on your core business and let us focus on some of the hard work in the database side and the data side of the business and let you focus on the front-end really. Yeah, and if you have a system that can allow you, as I said earlier, to start looking at value fairly quickly, then you can start to figure out how to actually tune those systems and how to get value back to that business much quicker. You know, if you can do that in three or four days to three or four weeks, that's a completely different equation than what we've been operating on over the last 15 years. Now you guys just closed your Series A, the $5 million Series A this summer, right? Yes. So how much have you raised the date, almost $8 million? No, seven, little over seven. The company was growing real rapidly, but as we talked about, a lot of people don't know who treasured it is, so we decided to raise a Series A to really bring on some more resources to expand sales and marketing, pretty classic model. So you used most of the money for promotion? We're going to as it goes forward and we just closed that. That's been closed, I think, three or four or five weeks, so it's relatively new. So ink is drying on that? Yeah, I haven't spent it all yet. Yeah, give me a couple months. Excellent. All right, Rich, well listen, thanks for stopping in, the Cube, a little drive by, really appreciate that. Good luck with the company and its continued growth. All right, keep it right there, everybody. Jeff Kelly and I will be back. This is the Cube. We're live from the Tableau Customer Conference in the heart of DC. Well, sort of, we're actually in Maryland, but we're here at the nation's capital. We saw it last night, we'll be right back after this.