 Live from the Fairmont Hotel in San Jose, California, it's theCUBE at Big Data SV 2015. Hello everyone, welcome to day two of Silicon Valley live coverage of theCUBE here, our flagship program, we're about to go out to the events to extract the silimony noise. We are in Big Data Week, Big Data SV is our event, in conjunction with Stratoconference and Hadoop World, the big event going on here. I'm John Furrier, the founder of Silicon Island. I'm with Jeff Kelly, my co-host, chief analyst at Wikibon for Big Data. Jeff, presentation last night, we had a big all day CUBE event yesterday, interviews wall to wall, then we had you releasing your new research to a packed house here at the Fairmont. We streamed that live, we had a great VC panel with Excel partners and Ignition, just an amazing event just to bring out and just extract that signal out of what's really happening. And I think it was really interesting to get the perspectives from your research and then tie that directly into the questions from the crowd and then also the VC, the guys who write the big checks, and the theme is follow the money. So I want to get your take. You presented the research. What did you think? I mean, were you happy with the questions, the feedback? What was it like? Yeah, I thought it was a great turnout, as you said. The crowd was engaged, which is always a good thing when you're giving a presentation. That's important to get feedback. Some really good questions. We heard questions around some more news-focused, topical, timely, I should say, around the open data platform, what that means, some skepticism in the audience about that. A lot of questions around practitioners. What are they really doing out there with Hadoop and Big Data? What are some of the bottlenecks, the challenges they're facing, and of course, questions around the market. We're gonna see some consolidation. We believe that you will. There's a vibrant ecosystem of startups out there in the world of Big Data right now, but like all markets, that's kind of how things start. And it will contract as the big guys play a bigger role in this market, but they're still trying to figure out how they're gonna add value themselves. So a lot happening in this market. It was a great presentation and the panel was fantastic last night. And then of course our party was always fun, where you can get to talk to a lot more people. So yeah, it was a great night and now we've got another full day of theCUBE ahead of us. Yeah, and one of the great things is we always like to bring innovation to the Big Data party. And obviously theCUBE is now in its 50th year. We were at the original Hadoop world and we're gonna introduce our next guest, first guest of the day, who was at our original CUBE, and coined a lot of terms and quite frankly, a lot of the concepts being discussed here. But we're gonna be introducing a lot of new innovation. Certainly we are gonna bring this conversation space into the virtual world. So we go to crowdchat.net and look for some of the live crowdchats going on. Certainly we have a few going on, crowdchat.net slash Stratocomp, which is a back channel for the Stratolinks and share your commentary. If you're at the Stratocomp or interested, just browse that. Big Data Week is our official crowd chat for theCUBE. And there's some spot crowd chats involving we have one going on right now, real data stories, crowdchat.net slash real data stories. Jump in, share the conversation. We're watching that. We'll bring those questions. We'll integrate the crowd into it. Of course, it's all on the record, all recorded. So we love bringing that out. It's a virtual space. Come jump into the virtual CUBEs and those conversations. So we're super excited. Again, follow the money. So when you follow the money, you got to also attract the VCs, which we did last night, Jeff. But more importantly, you got to attract the big guys. What are they doing? You know, they're trimming down. They're laying off people, but they're also hiring. They're getting bulked up for the big battle. Well, yeah, they're laying off on the legacy side of their business and they're trying to bulk up and build up their new approaches to cloud and big data analytics, mobile and social. So it's a transition period for companies like IBM and SAP and others. And but the ones that come out the other side, I think you're going to have an opportunity to really do well in this market. They have got the relationships at the high level in the enterprise. And that's going to help them bring big data to the mainstream. Yeah, but the big guys are not nimble. They're not as fast as they're trying to be. But really, if you want to also follow the innovation, you're going to follow the startup. So our next guest is Abhi, the CEO and founder of Trasada, who was on our first Hadoop World broadcast. I think four years ago, Abhi, welcome back to Cube, friend of the Cube. Saw you last night. Great to see you again. We had an amazing conversation, going back to the original small little table. We were like, are we live? So now it's evolved. Certainly the show's gotten bigger. We've got the crowd chat, got the virtual space and a huge community following. Obviously last night was a great, great party. And it's great to see you there. But give us the update. You got to follow the startups of the ones who are innovating. You're disrupting. And you've done it without any funding. You've got cash flow positive. The VCs are banging on your door. It's an exciting time. And you guys are one of the ones that are emerging out of the pack to be the leaders. And you hustle, brute force, et cetera. So tell us what's up. Well, first of all, it's always good to be here. At this point, I come to these shows for the Cube. You guys are the highlight because there is no better way as borrowing from your words, John, to extract signal from the noise than listening to the Cube. So always a pleasure. It's good to be part of the larger Cube family and the alumni network. And you guys are very kind to me. I'm not that big of a rock star yet. We'll get there one day. I think what both you and Jeff said is absolutely true. We are seeing, and you've heard me say this multiple times, an extremely Darwinian moment in the evolution of technology. I think re-platforming is offensive to use as a word to talk about the potential of this massive change. And like every other massive revolution, whether it's technology, whether it's the first industrial revolution, the dot-com boom, which when you look back, the disruptors in the dot-com boom are all here, alive and kicking, right? I mean, Amazon, Google, they were all the original dot-com players and they're all here. Not many people gave them a chance to be where they are, but Amazon is at all time higher $400 a share. And I think we're seeing something similar in the fact that the big winners, and I don't want to disagree with you, Jeff, but I think the big winners in this race are not just going to be the deployers of data insight, what you call the apps, monetizing the business apps, monetizing data, the Uber's, et cetera, but also a whole slew of enterprise software companies that are helping other large enterprises who are fundamentally data-driven, but not technology companies, innovate with data. And we like to believe we're one of them. I think we were bold in our vision from day one. We've always shared it openly, controversially, and I think in a very honest way on theCUBE, every single time, there's no secret why we are still around, why we are successful. We just announced today morning, 2014 was our first profitable year of operations, which is a huge milestone in any startup's journey in life, and I routinely tell people that the best way to fund your CD's A is by revenues, right? Our customers have funded Trasera CD's A, and we're tremendous success, and while we all fundamentally believe that the value in the technology stack is in the business applications, at this point, I don't even ask where the business applications are. We are one, we are here, and if there's no competition in the market, I think it's a testament to the hard work that Team Trasera has put in to be so early in the space, but also a testament to the fact it's not easy to pull off, and if we have been able to pull it off, I think we are heralding or showing the blueprint for what enterprise software will be in the future, and the blueprint is not clear. It's not known to everybody when you're disruptive. It's very difficult to get people to understand why you're disruptive. CrowdChart is a great example. People may not understand what the potential for that is, but same for Trasera, we had so many people when we started the company say, well, where do you fit in the stack? And we don't fit in the stack, and that was the best sign four years, now that we are four years old, that you are going to be incredibly disruptive in the space. Right, well, you got to be smart about it, because you could have some startups that maybe they don't fit in the stack, if that's not necessarily a good thing, they might have a bad idea, but if you don't fit in the stack and you've got a truly innovative approach that's going to deliver value, that's great. When a VC can't put you in a box, and they say, well, I don't understand, where you fit in this paradigm? How can I invest in you when I don't get it? If you're smart about it and you've got a truly innovative approach that's going to deliver value. That's a great sign. So take a step back for a minute, talk a little bit about your approach. You mentioned your approach is somewhat unique in the industry compared to all those other vendors we're seeing out there on the floor at Strata Hadoop World, which tend to be focused more on a particular tool within that stack, some part of the stack. So we've talked about before on theCUBE, but I think it's worth kind of getting into again and talking a little bit about your fundamental approach and how that differentiates you from some of the other players that we see in this market. Absolutely, I will actually use a term, I think one of you used to talk about the history of Strata, which is our background, Richard and myself, who started the company four years ago, we came from a large bank, we were at Bank of America, and we had lived in a data full enterprise, right? It's a term that I think you use, John. And I think it's very important in this new way where if data is the raw material for the next industrial evolution, something that theCUBE and us, we said together five years ago, it's good to see IBM say the same thing now and President Obama come in and say the same thing, good, huge sign for them to a point, achieve their scientist. But if that philosophy, if that vision is true, we've always said there are three pillars to our success and the same three pillars are critical to our business model. And we put them in the buckets of data, domain and delivery. And I think a lot has been spoken about data, so we won't talk about that a little bit, we'll talk about it a little bit today, not much more. A lot has been spoken about domain. I fundamentally believe that a next generation enterprise software company without domain expertise, not knowledge, but deep, deep domain expertise, the data fullness having lived in a large financial enterprise where data is the business. It's not about moving money back and forth. And how you actually bring domain to solving hitherto manual business processes is critical to build the next generation enterprise. And I think that is why we've been successful. When I look at all the companies that started with us, a lot of them have been on theCUBE and will never come back again. And why they're not here in VR is because we fundamentally understand what needs to be automated. And when data becomes the raw material, you can take the automation a lot higher in the stack. So what used to be a manual activity, a manual task with machine learning becomes automated. And let's remember, there's not enough humans in the world, forget data scientists, and there'll never be enough people in the world to manually extract intelligence from big data. Data is gonna dwarf mankind's capacity to process it. So without automation, you can't monetize the data. And without domain expertise, you can't automate the business process. So I think that's been a critical component. Last, the least spoken about, which I would love to get the two of yours feedback on, is delivery. I think we underestimate the reason why large tech companies are struggling isn't just because that the legacy stack that they have so proudly built the last 20 years is now commoditized, is now free, right? The pivotal announcement with open sourcing the database, open sourcing the real time component of the database, open sourcing the SQL engine, basically proves our huge, huge bet four years ago that every single part of the traditional data stack, storage, database, analytical tools and BI will be free. Pivotal just proved in one swell swoop that that is absolutely true. When that happens, and how do you have the right conversations with a different buyer in a large corporate? When the buyer is no longer the CIO and the chief marketing officer, the chief retail officer, the chief risk officer, how do you train a sales force used to be selling widgets and nodes, and numbers to now go have a educated conversation or using data as a competitive advantage? It's not easy. I think that is, in my opinion, the secret source of Truseta's success. There is no company in the world today who can walk into a bank or a retailer and very soon announce a very interesting healthcare partnerships or a healthcare company to go and have a conversation on how understanding consumer behavior can transform their business. Only Truseta does it well. Avi, we were talking last night and yesterday, certainly on theCUBE, this came up, that this whole big data alliances, the open data platform, if you will, this middleware has always been the battleground in the computer industry. Call it past, call it what you want, but right now there's a lot of stuff going on. And interesting, during the discussion yesterday during Jeff Kelly's presentation, the crowd was interested in the hardware solution. So you're on the app side. So we were discussing, okay, this convergence between born on the cloud or born native app first or data full, like you guys have been successful. And then underneath the DevOps movement has proven that infrastructure code is critical. So I got to ask you, it's coming up on the crowd right now is how do customers keep their systems online at scale? If they're going into an app world from your perspective, you're out going rolling out huge apps, what do they do? How do they scale up and what do you used to do and what is needed in this modern era? So from an app's perspective, looking down the stack, what do you need to run at scale? Great question. Something about our conversation yesterday, John and Jeff crystallized my mind. I actually went back last night, couldn't sleep because I kept thinking about this polarization. What we spoke about for your audience was basically the polarization that the value and the ability to build next generation software will polarize into two ends, the infrastructure software players and the business application players like us. And I actually went back, John, and looked at a presentation that I had done almost six or seven years ago where I made the exact same pitch, basically saying there will be money at the bottom of the stack, infrastructure software. You still need hardware, it is commoditized but you still need to buy hardware. You still need to buy cores, as Frank Catali said yesterday. Every single year we consume more cores. So of course, there is a business to be built on selling commoditized software and hardware, software and products and services. And then there's business to be built on the application side. What crystallized for me last night was the reality that companies like Tresada become massively successful. So we are successful today, become virally successful when the consumption of infrastructure truly becomes as a service. And it's not, let's not get ourselves, virtualization has a long way to go. Hardware as a service doesn't even exist yet as an idea, much less a product. And then the commoditization of infrastructure, platforms and services that can be consumed by applications in a container approach is very, very early. If that fully bakes up, if that fully was to crystallize in the next five or 10 years, the reality is you're talking to somebody at Tresada, the way we have engineered our application development platform, which I think Jeff, you got a sneak peek into when you were down getting our first analyst briefing for us as a company, that application development platform dramatically speeds up in adoption when I can provision securely and in real time an application as the business demands it. And then you truly have a app marketplace like the iOS for enterprise software. I think what I realize, whenever I come to the West Coast, I learn a lot, but I also realize a distinct lack of understanding around what will it take to create an app platform that can instantly provide this user, provide them the application to solve a problem that they think of. And we are far removed from it because we keep investing in building tools. What we're not building is an application data platform where the needs around, I know, provisioning real time applications as you need it are dramatically different. And you saw what we have done with Resilient Analytics Platform 4.1 to make, we are at a point today that if a client buys the Resilient Analytics Platform, we can provision an application to the business user in three weeks and make that even, you know, or truly real time infrastructure catch up. So the containerization, the security, the provision of the services and truly taking every single component of infrastructure and consuming it as a service is the future. So what about old apps? New apps, if you're born native apps, so how do you deal with legacy? You work in a lot of large enterprises, they have old apps. What's going on with that? I mean, how does that work? Is there data fabric? What do you see as that key integration piece with the legacy? I'll be a little harsh on this answer, not that I'm known to be, I'm known to be very nice on your show. But I think the reality is, John, when you look at the evolution of software the last 20 to 30 years, we have gone from, we went from centralized computing, mainframes to distributed computing, which had to happen. Then you look at software and software went from being completely custom built, built to always being bought. And then you look at the next evolution of software, which was, in my opinion, automating dumb processes. So large version of software, CRM, ERP, you take the applications that have been incredibly successful, automated dumb processes, right? CRM reminds you you have a meeting. That's great. Well, I want to remind you that it says that I'm going to meet Jeff Kelly, Jeff is at Wikibon, posted a recent post, criticizing my company's strategy, and I want to be informed in that conversation. Those apps don't exist. The negation of apps are fundamentally intelligent. So there's already two things happen. You either have to figure out a architecture and approach where the last generation of dumb apps, automating simple human processes, can deliver more intelligence. So there's a way in the back end to find actionable customer intelligence and push it out to your sales team, right? Through Salesforce as an example. Or you get completely replaced with the next generation of intelligent applications that are always providing you insight you can monetize. In my opinion, what will end up happening is that the fundamental intelligence engines of the last generation of applications, the old apps will get replaced. The front ends may not, right? The ability for a investment banker going to see IBM, calling on IBM or Apple on his Salesforce beautiful iPad dashboard will still be the same. But what intelligence is pushed through their front end will be replaced by companies like ours. We have a large bank as a customer who is feeding intelligence from our payments intelligence product into their Salesforce dashboard when a banker walks in to have a conversation. He has more intelligent information to have confidence. So I think the front ends will remain. The delivery will remain. The data, the intelligence will change. So we heard yesterday from Tahoe about data refineries and I couldn't help but roll back and think about our data factories conversation from 2010 that you coined that term and was an epic video back from Hadoop 2010. But data factories don't have to be large factories. Give me smaller factories. So that's an issue I want to talk to you about about that world there. But more over the consolidation message that Jeff talked about yesterday and specifically the open data platform. From your perspective, is there pressure from customers to say to the infrastructure providers in the Hadoop ecosystem, guys, get your stuff together and just move forward. Go faster. Is there a go faster message in that? And is that the catalyst for the open data platform or is it just weaker players trying to consolidate together to have a counter to cloud era? So you can argue both sides. I can say, hey, you know, these guys are kind of getting desperate. Maybe they're going to try to come together and try to compete against cloud era. Cloud era is saying, hey, we're winners. We've always been the leader, lead dog, you know, that kind of thing. So what's the approach? I mean, there's a lot of action going on. Bombs are dropping. There's a lot of movement. Is it move faster? Or is it just a defensive position to try to get a number two to cloud era? Definitely the former. I think the reality in the market is move faster. It's definitely move faster. The reality in the market is Hadoop as an ecosystem, from the first time we spoke about it in 2010, and I think you or Dave asked me to define. So what is Hadoop? Explain to us what Hadoop is. I mean, if you have the conversation, I remember moving the code to the data. Till this day, Dave reminds me of that conversation. Miss Dave here, I wish Dave was here too. And the reality is, in four years, Hadoop has come such a long way. You know, Jeff wasn't even part of Wikibon at the time and he is the leading big data analyst at this point in the market. You've come to a stage where Hadoop has become the de facto data operating system for all data analytics in the future, for all kinds of data across all different use cases, across all industries. And if that, if you have achieved that much in four years, which when you look back, it's not that long, it used to look the same. You look exactly the same as four years. It's not that long a time. But the market lacks, and this has been a big issue, in hastening the adoption of it, is a coalition of like-minded players pushing the right enterprise innovation into Hadoop. If the ODP, the Open Data Platform can do that, it's good for all of us. It's good for Cladrera. It's good for the ISVs like us. It's massively important for ISVs like us. I don't believe it's, I think it's gonna be short-sighted on our part, and a little petty to say that weak players have come together and are trying to make Polish a turd. Well, we've seen that. That's what Mike Olson was pointing on his blog post. Other consortiums have been kind of like trying to put a Barney deal together. We love each other, but really they're just trying to get a position. I don't think that's the case here. I do agree with you. I think there's a bigger stakes on the table. That is trillion dollar to him. So I think there's more of a message of hey industry, a lot of things. So I do agree with Pivotal on that. I do want to get your take on my question. I asked Ping Li yesterday, because he was the original founder of Cladrera. I asked him, looking back four years, hits and misses. He kind of didn't want to answer, he didn't want to, but it's like watching grass grow over some of these startups. Yes it is. Some of them are not materializing. So from your perspective, and there's a lot of reasons for that. I think the market certainly exploded in a different direction. So certain theses might not have been in play because of the market growth in general. What is your take on hits and misses? What have we done right in four or five years? And what did we miss that have been either market force or just a misfire? I think what we've, so I'll talk personally for Tresera for a second, then go talk to the market. What Tresera has done well, not looking back, is state true to our vision. We were the first company to come out and say, say that the only way to make money as an enterprise software player in this rapidly evolving, commoditizing, open sourcing market is to build business applications that has not changed. We have not wavered from that vision that statement for a second. And I think it is testament to the fact that today we announced that we close 2014 as our first profitable year of operations. It probably makes us the first pure play Hadoop vendor to be profitable. Huge kudos to the team at Tresera that Jeff, you're the pleasure to meet. It's a lot of hard work that's gone into it. But it was hard. You're a fellow entrepreneur, the both of you are. And it was hard to go to, have these interesting VC conversations when no one understood what you were doing or where you fit. And as I look back now, a little bit more confidence. We're around, we're profitable, we're growing rapidly. But you made bets. You made some certain bets that panned out. Absolutely. Which ones didn't pan out? Can you look back and say, okay, we avoided disaster or we saw that coming to the left turn, right turn? I think there was so much pressure on us in the first two years of Tresera to go figure out a way to fit in the stack. I'm so happy we did not. So that was a huge mistake avoided. I can't tell you how many people came and said, oh well, you know what? Maybe you should become a middle-aged player or maybe you should do BI because BI is sexy and we just funded. It's hot. Yeah, people get excited. And you look back and you go, every three months there's a new BI player who becomes the belly of the ball and you go, well, now you're struggling. So I think that was a big mistake avoid for us. We have always said databases, storage, ETL, analytical tools, NBI should be free. Should be fundamentally free. I have great regard for my friends at HADAP but they're no longer there. I think companies like Squirrel, they announced a new run of funding today but I struggled to see how tool companies can be viable companies. And I know what Pink said yesterday, some platform companies begin as tool companies but you know what? Platform companies are incredibly, incredibly capital intensive to build. Apps are incredibly, incredibly, incredibly capital efficient to build and a great return for shareholders and investors because that is where the future is. So I think a huge mistake avoid it. As for the ecosystem, John, I think something that as I look back, I look at some of the early interviews that we did with you guys with Doug Cutting and Jeff Harbacher to one of my favorite people in the ecosystem. And when you go listen to it, I am disappointed why the open source ecosystem, I know this is tricky, the open source ecosystem hasn't moved quicker in solving some larger enterprise grade issues. I've been surprised with that slowness of approach. I've also been surprised at why, I guess that's one lessons you learn as an entrepreneur. I would have assumed by now that there would have been 100 large Hadoop clusters across a range of industries. They're not. There are still a handful of large in production Hadoop clusters. Hadoop remains in large enterprises, a approved technology, a technology for the future, but still a technology they're testing for success, not building competitive advantage on. I'm surprised with that. I think the last thing I'm surprised about is why does Triseta have no competition? I was talking to you guys last night, when the conversation turns to business applications on Hadoop, only one name figures in the conversation. That has been the case for four years now. At this point, I love it, it emboldens us. We're building the next billion dollar enterprise software company is going to get built on the East Coast. Well, and it's kind of a little different. I was going to say that last night on the panel, but I didn't have time. It's like the winners are usually the ones you don't see coming. That's kind of an axiom in the VC community of the real winners who pick the unicorns. And you guys kind of are different. You're just like, wait a minute, that doesn't fit into a pattern. The ones that come out of the ones who don't have the pattern, I mean, even Google didn't match the pattern. But the market was growing. So a quick question I got to ask you before we break as we're getting the hook here. Yesterday we heard on theCUBE, machine learning is the last competitive moat opportunity, competitive advantage for companies. So, Juan, do you agree, and what do you think the competitive strategy moves are for companies to build sustainable, protected ventures? Meaning once you get some critical mass, it used to be, oh, critical mass, and you're off to the races, then you just build some protection mechanisms. In this new world of openness and scale, what is the competitive advantage? Is it scale, and why do you have no competition? Is it because of certain things? Excellent question. I was taught very early, John, and by my economics professor, that if it takes you $2 to sell a watermelon that you bought for a dollar, you cannot make it up in volume. I think it's a very important lesson to remember. A lot of my friends tell me that Richard and I are building a company the hard way. We are profitable because of the week, nights and weekends spent away from family and couches. There's a lot of fun. I've enjoyed the process. Jeff made an interesting statement and said, building a company should be fun, and if you stop having fun, you shouldn't be in that company anymore. We're having a blast right now. I think that differentiates. We have a culture at Trasada where you fundamentally believe that disruption happens when you understand a business and technology trend so deeply that you know fundamentally how to disrupt it from the inside. That's who we are. There's not a single company in the ecosystem that has a deeper grasp of business problems, business processes and business opportunities and technology and data. I think that's the core of what Trasada is. As to why, why is it that certain trends pick up and certain trends don't? It's certain boldness and vision. You've had it, we've had it, which is you need to have a singular focus that says no matter how hard it becomes to not follow conventional wisdom, to be sidetracked with, and I think it's helped us not being in Silicon Valley. In fact, I think we'll be doing a huge disservice to our country. There are smart people outside the valley, not only in the valley. I know there's a lot of it in the valley. It'll be a service to the nation, to our country and the world if only all the smart people converge in the valley. A big reason why we've been able to stay true to our vision is the noise in the valley doesn't impact Trasada. We come here, head held high, we wear our brand proudly, surprise a lot of people because we have stayed so true to our vision and not wavered from it that we finally have had the strength of spirit to move the market our way. I can't tell you how many customers come to us and tell us. I know you told us three years ago, segment of one, but I finally get it, you know? Or you always said that if you can't monetize big data, you guys have no value to it. I'll answer your question in a second. Machine learning is another fad. It's become sexy to fund machine learning now. We've been doing machine learning since day one. Every time you write code, it's machine learning because that's what code does. I don't think machine learning is the last- Good code, right? Good code, good code. Not like just bad code. And as Hal- Infrastructure as code DevOps should have native machine learning. Absolutely, absolutely. But as Hal-Varian so accurately said, the comparative advantage in the future is data, not code. Machine learning is just another nice, sexy fad for VCs to chase. They should chase it. At the end of the day, when you go talk to a customer, he doesn't ask you, do you use Hadoop? He doesn't ask you how much machine learning you have in there. Doesn't even ask you- That solution is a product feature. Exactly, it is a component to deliver actionable intelligence. Every successful software company that delivers actionable intelligence is doing machine learning in the back end. Artificial intelligence is just another buzzword like everything else. Artificial intelligence applied to solve a marketing problem isn't called AI, it's called marketing intelligence. You're doing it right. I mean customer intelligence down to the persona of one or the segment of one. IBM certainly is going this direction with cognitive, insight engines. Insights is the solution. What's under the cover? What makes up the product and the features a little bit decided. You guys are the blueprint for the future enterprise. Congratulations on your success and you just announced profitability. Again, all with muscle and energy and entrepreneurial spirit, no outside funding. That really is in our view the rock star stat as people who can build companies without outside funding. Certainly when you do need scale me without that rocket fuel will help a good valuation. Well, first of all, thank you John. You're very kind. Wouldn't have been here for every single one of you. I look back for this awesome crew. You guys are, if there is one platform for entrepreneurs to build companies, it's not Silicon Valley, it's called theCUBE. You guys have been so good to us and I would not be here. I represent Team Prasada. We have an unbelievable team. Jeff was asking me, yes, how do you build a good culture? He loves our jackets, by the way. You gotta get him these, these are the cute jackets. But I think we have- Get some better sponsorships going. We'll get some jackets for everybody. We have a team that I am so proud to represent that I would not be here without them. So thank you so much. Well, we love entrepreneurs and last night at the event, I just shared with you, you were part of the company as we had Richie was saying that his, he watched a video of our interview and was inspired to move into the spark direction and his business is exploding. So that's the kind of thing that we love to hear. And again, we don't ask anything for. It's all open source media. We love it. Thanks to your support and everyone out there watching. We love to extract the signal of noise and share that openly with you and the folks out watching. Thanks for watching. This is theCUBE with Obimeta, the founder of Trasada, a successful company and again, setting the standard and a great congratulations to that blueprint for enterprise software in the modern era. Well, this is theCUBE. We'll be right back after this short break.