Covering, DataWorks Summit Europe 2017. Brought to you by Hortonworks. Welcome back everyone, live here in Munich, Germany for theCUBE's special presentation of Hortonworks, a Dupes Summit now called DataWorks 2017. I'm John Furrier, my co-host, Dave Vellante. Our next guest is Sean Connolly, Vice President of Corporate Strategy, Chief Strategy Officer. Sean, great to see you again. Thanks for having me, guys. Always a pleasure. Super exciting. Obviously we always pontificating on the status of Hadoop and Hadoop is dead, long live Hadoop, everyone's been demise is greatly over exaggerated. But reality is that no major shifts in the trends other than the fact that the amplification with AI and machine learning has up-leveled the narrative to mainstream around data. Big data has been ridden on Gen 1 on Hadoop, DevOps, Culture, Open Source, started with Hadoop. You guys certainly have been way out in front on all the trends, how you guys have been running all the products. But it's now with IoT and AI as that, the sizzle, the future, self-driving cars, smart cities. You're starting to really see demand for comprehensive solutions that involve data-centric thinking. Okay, so one, two, Open Source continues to dominate. MuleSoft went public. You guys went public years ago. Cloudera filed their S1, a crop of public companies that are Open Source, haven't seen that since Red Hat. Exactly, 99 is when Red Hat went public. Data-centric mega trend with Open Source powering it. You couldn't be happier for the stars lining up. Yeah, well, we definitely placed our bets on that. We went public end of 2014, and it's nice to see that graduating class of town, MuleSoft, Cloudera coming out. That just, I think, helps socialize this movement that Enterprise Open Source, whether it's for on-prem or powering cloud solutions, pushed out to the edge in technologies that are relevant in IoT, that's the wave. I mean, we had a panel earlier today where Daljeet from Centric of British Gas was talking about his, you know, the digitization of energy, right, and virtual power plant notions. He can't achieve that without Open Source powering and fueling that. And the thing about it is just kind of, for me personally, being at my age in this generation of computer industry since I was 19, to see the Open Source go mainstream the way it is, it even gets better every time, but it really is the thousand flower bloom strategy throwing the seeds out there of innovation. I want to ask you, as a strategy question, you guys, from a performance standpoint, you know, I would say kind of got hammered in the public market, Cloudera's valuation privately is 4.1 billion, you guys are close to 700 million, certainly Cloudera's going to get a haircut, looks like, and the public market's based on the multiples from Dave and I's intro, but there's so much value being created. Where is the value for you guys? As you look at the horizon, you're talking about the white spaces that are really developing with use cases that are creating value, the practitioners in the field, creating value, real value for customers. So you covered some of the trends, but I'll translate them into how the customers are deploying. So cloud computing and IoT are somewhat related, right? One is a centralization, the other is decentralization, so it actually calls for a connected data architecture as we refer to it. We were working with a variety of IoT related use cases. You know, Coca-Cola East Japan was spoke at Tokyo Summit about beverage replenishment analytics, getting vending machine analytics from vending machines even on Mount Fuji, right? And optimizing their flow through of inventory and just-in-time delivery. That's an IoT related that run on Azure, it's a cloud related story and it's a big data analytics story that's actually driving better margins for the business and actually better revenues because they're getting the inventory where it needs to be so people can buy it. Those are really interesting use cases that we're seeing being deployed and it's at this convergence of IoT cloud, right? And big data, ultimately that leads to AI but I think that's what we're seeing the rise of. Can you help us understand that sort of value chain? You got the edge, you got the cloud, you need something in between, you're calling a connected data platform. How do you guys participate in that value chain? Yeah, so when we went public, our primary workhorse platform was Hortonworks data platform, right? We have first class cloud services with Azure HD Insight and Hortonworks data cloud for AWS. Curated cloud services pay as you go and Hortonworks data flow, I call is our connective tissue. It's the, it manages all of your data in motion. It's like, it's a data logistics platform. It's like FedEx for data delivery. It goes all the way out to the edge. There's a little component called Minify, Mini-NiFi, which does secure intelligent analytics at the edge and transmission. And so, these smart manufacturing lines, you're gathering the data, you're doing analytics on the manufacturing lines and you're bringing the historical stuff into the data center where you can do historical analytics cross manufacturing lines. Those are the use cases that a connected data- A subset of that data comes back, right? A subset of the data, yep. The key events of that data, it's not, it may not be full. Ten percent? Half, 90 percent? It depends. If you have operational events that you want to store, sometimes you may want to bring full fidelity of that data so you can do, as if you manufactured stuff and when it got deployed and you're seeing issues in the field, like Western digital hard drives. Yeah, failures in the field. They want that data full fidelity of the phone home to do connected data architecture and analytics around that data, right? So you need to, one of the terms I use is in the new world, you need to play it where it lies. If it's out at the edge, you need to play it there. If it makes a stop in the cloud, you need to play it there. If it comes into the data center, you also need to play it there. So a couple years ago, you and I were doing a panel at our big data NYC event and I used the term profitless prosperity. I got like the hairy eyeball from you, I think, but nonetheless, we talked about you guys as a steward of the industry, you have to invest in open source projects and it's expensive. I mean, HDFS itself, YARN, TES, you guys led a lot of those initiatives. With the community. Yeah, with the community. Yeah, but you provided contributions and at least co-leadership, let's say.  So how do we projecting forward, without making forward looking statements, but how does this industry become a cash flow positive industry? Yep. So public company since end of 2014, the markets turned beginning of 2016 towards prior to that high growth with some losses was palatable. Losses were not palatable. That hit us, Splunk, Tableau, most of the IT sector. That's just the nature of the public markets. As more public, open source, data-driven companies will come in, I think it'll better educate the market of the value. So there's only so much I can do to control the stock price. What I can from a business perspective is hit key measures from a path to profitability. So at the end of Q4, 2016, we hit what we call the just that even a break, even which is a stepping stone. On our earnings call at the end of 2016, we ended with 185 million in revenue for the year, only five years into this journey. So that's a tarred revenue growth pace. And we basically stated in Q3 or Q4 of 17, we will hit operating cash flow neutrality, right? So we were operating- You guys also hit 100 million at record pace too, I believe. Yeah, in four years, right? So revenue is one thing, but operating margins, like if you look at our margins on our subscription business, for instance, we've got 84% margin on that. It's a really nice margin business, right? And we can make that better margins, but that's a software margin, right? You know what's ironic? We were talking about Red Hat off camera.  One would think, okay, hey, I could maybe project forth some of these open source companies. Maybe the flip side of this, oh wow, we want it now to your point, the market kind of flipped, but you would think Red Hat is an indicator of how an open source model can work. But it was- Red Hat went public in 1999, right? So- Free bubble.  Oracle's trajectory was different. They didn't, even in inflation adjusted dollars, they didn't hit 100 million in four years. I think it was like seven or eight years or what have you. Salesforce did it in five, right? So these SaaS models and these subscription models and the cloud services, which is an area that's near and dear to my heart. First faster. Right, is you get multiple revenue streams across different products. We're a multi-product cloud service company, right? Not just a single platform. So we were actually teasing this out on our end. That's how you grow the business and that's how Red Hat did it. Well, I want to get your thoughts on this while we're just kind of riffing live here, but because Dave and I were talking on our intro segment about the business model and how there's some camouflage out there, at least from my standpoint. And one of the areas that I was kind of pointing at and trying to poke at and want to get your reaction to is in the classic enterprise, go to market. You have Salesforce expensive, you guys pay, handsome leave for that today, incubate in that market, getting the profitability for it is a good thing. But there's also channels, bars, ISVs and so on. You guys have an open source channel that kind of not as a bar or an ISV. These are entrepreneurs and or businesses themselves, right? So there's got to be a monetization shift there for you guys in the subscription business, certainly. We look at these partners, they're co-developing, they're an open source. So you almost can almost see the dots connecting. It's this new ecosystem, there's always been an ecosystem, but now you have kind of a monetization inherently in a pure open distribution model. It forces you to collaborate, right? And IBM was on stage talking about our system certified on the power system, right? Many may look at IBM as competitive, we view them as a partner. Amazon, right? Some may view them as a competitor with us. They've been a great partner in our state of cloud for AWS. And so it forces you to think about how do you collaborate around deeply engineered systems and value, and we get great revenue streams that are pulled through that they can sell into the market to their ecosystem. So how do you envision monetizing the partners? Just take a random, let's just say Dave and I start this epic idea and we create some connective tissue with your orchestrator called the data platform you have and we start making some serious bang. We make a billion dollars. Do you get paid on that? If it's open source, I mean, we'd be more subscriptions. So I'm trying to see how the tide comes in. Whose boats float on the rising tide of the innovation in these white spaces? Platform thinking is you provide the platform you provide the platform for 10x value that rides atop that platform. That's how the model works. So if you're riding atop the platform, I expect you and that ecosystem to drive at least 10x above and beyond what I would make as a platform provider in that space. That's how it works, right? You need 1,000 flowers to be running on the platform. You know, you saw that with VMware, right? Yup, they hit 10x, and ultimately got to 15 or 16, 17x. Exactly. I think they don't talk about it anymore. I think it's maybe trading the other way. Plus Red Hat, it was somewhere between 15 to 20x, right? Was the value that was created on top of the platform. What about the, I want to ask you about the forking of the Hadoop distros. I mean, there was a time when everybody was announcing Hadoop distros. John Furrier announced Silicon Angle was announcing a Hadoop distro. So we saw consolidation and then you guys announced the ODP, then the ODPI initiative. But there seems to be a bit of a forking in Hadoop distros. Is that a fair statement? Unfair? You know, I think if you look at how the Linux market played out, right?  You're always going to have curated platforms for different purposes, right? We have a strong opinion and a strong focus in the area of IoT, fast analytic data from the edge, and a centralized platform with HDP in the cloud and on-prem. You know, others in the market, CloudR is running sort of a different play where they're curating different, you know, elements and investing in different elements. Neither doesn't make either one bad or good. We just are going after the markets slightly differently. The other point that I'll make there is in 2014, if you look at the Benchart diagrams, there was a lot of overlap. Now if you draw all the areas of focus, there's a lot of white space that we're going after that they aren't going after and they're going after other places and other Hadoop vendors are going after others. So it's, you know, with the market dynamics of IoT, cloud and AI, you're going to see folks change the market options. Is that disparity not a problem for customers though or is it challenging? There has to be a core level of interoperability and that's one of the reasons why we're collaborating with folks in the ODPI, as an example, is there's still, when it comes to some of the core components, there has to be a level of predictability because if you're an ISV riding atop that, you're slowed down by death by infinite certification and choices, so ultimately it has to come down to just a much more sane approach and what you can rely on. When you guys announced ODP, then ODPI, you know the extension, Mike Olson wrote a blog saying it's not necessary, people came out against it and now we're, I don't know, three years in? Three years in, looking back, was he right or not? So I think ODPI, particularly this year, there's more that we can do above and beyond the Hadoop platform. It's expanded to include SQL and other things recently, so there's been some movement in this spec but frankly, I think you talk to John Murtic at ODPI, you talk to SaaS and others, I think we want to be a bit more aggressive in the areas that we go after and try and drive there from a standardization perspective. We had way way on earlier on. There's more we can do and there's more we should do. We had way on with Microsoft at our big data SV event, a couple weeks ago. Talk about the Microsoft relationship with you guys, it seems to be doing very well, comments on that. Yeah, so Microsoft was one of the two companies we chose to partner with early on, right? So, you know, in the 2011, 2012, Microsoft and Teradata were the two, right? Microsoft was how do I democratize and make this technology easy for people? That's manifest itself as Azure Cloud Service, Azure HD Insight. Which has been growing like crazy. Which is globally deployed and we just had another update. It's fundamentally changed our engineering and delivery model. So, this latest release was a cloud first delivery model. So, one of the things that we're proud of is the interactive SQL and the LLAP technology that's in HDP. That went out through Azure HD Insight and it works data cloud first, right? And then, it's certified in HDP 2.6 and on power, right? At the same time. So, it's that cadence of delivery and cloud first delivery model. We couldn't do it without a partnership with Microsoft, right? I mean, I think we've really learned what it takes. If you look at Microsoft at that time, I remember interviewing you on theCUBE. Microsoft, I think, was trading like $26 a share at that time or around like in their low point. Now, the stock is performing really well. Softenatella, very cloud oriented. They're been very open source and friendly. They've been donating a lot to the OCP, to the data centerpiece. Extremely different Microsoft. So, you slipped into that beautiful spot. And I think- Traff it on that growth. I think as one of the stalwarts of enterprise, software providers, I think they've done a really great job of bending the curve towards cloud and still having a mixed portfolio. But in sending a field and sending a channel and selling cloud and growing that revenue stream, that's non-trivial. That's hard. And they know, they know the enterprise sales motions too. So, I want to ask you how that's going overall within Hortonworks. What are some of the conversations that you're involved in with customers today? And I'll see, again, we were sitting on our opening segment on YouTube for them watching that the customers is the forcing function right now. They're really putting the pressure on the suppliers. You're one of them to get tight, reduce friction, lower cost of ownership, get into the cloud, flywheel. What are- And so you see- And I'll throw in another aspect. Some of the more late majority adopters traditionally, over and over right here, by 2025, they want to power down the data center and have more things running in public cloud, if not most everything, right? That's another eight years would have you. So it's still a journey. But this journey to making that an imperative because of the operational, because of the agility, because of the better predictability, the ease of use. That's fundamental. So as you get into the connected tissue, I love that example, with Kubernetes containers, you got developers, a big open source participant, and you got all the stuff that you have. You're going to start to see some coalescing around the cloud native. Yes. How do you guys look at that conversation? I view container platforms, whether they're container services that are running on cloud or what have you, as the new light rail, right? That everything will ride atop, right? And the cloud clearly plays a key role in that. I think that's going to be the de facto way, right? Yeah. And particularly if you go cloud first models, particularly for delivery, it's sort of you need that pot packaging notion and you need the agility of updates that that's going to provide. I think Red Hat, as a partner, has been doing great things on hardening that, making it secure, but there's others in the ecosystem as well as the cloud providers. All three cloud providers actually are investing at the time there. So that's good for your business. It's, it removes friction of deployment. My ride atop that new new rail. Right? It can't get here soon enough, from my perspective. So I want to ask you about the clouds. You're talking about the Microsoft shift. Personally, I think Microsoft realized, holy cow, we can actually make a lot of money if we're selling hardware as services. We can make more money selling the full stack. And it's sort of an epiphany. And so Amazon seems to be doing the same thing you mentioned earlier. You know, Amazon is a great partner, even though a lot of people look at them as a competitor. It seems like Amazon, Azure, et cetera, they're building out their own big data stack. Yes. And offering it as a service. People say that's a threat to you guys. Is it a threat, or is it a tailwind? Is it, hey, we, it is what it is. So this is why I bring up industry-wise, industry-wise, we always have waves of centralization, decentralization, right? They're playing out simultaneously right now with cloud and IoT, right? And the fact of the matter is, is you're going to have multiple clouds, on-prem data and data at the edge. That's the problem I'm looking to facilitate and solve, right? And so I don't view them as competitors. I view them as partners, because we need to collaborate, because there's a value chain of the flow of data. And it's going to, some of it's going to be running through and on those platforms. Yeah, the cloud's not going to solve the edge problem. No. Too expensive. Exactly. Right? Physics. And so, you know, I think, that's where things need to go, right? And I think that's why we talk about this notion of connected data. I don't talk hybrid cloud computing, right? That's for compute. I talk about, how do you connect to your data? How do you know where your data is? And are you getting the right value out of the data by playing it where it lies? I think IoT has been a great, sweet trend for the big data industry, because it really accelerates the value properties for the cloud, too, because now you have a connected network, you can have your KGT2, central and distributed. And there's different dynamics in the U.S. versus Europe, as an example, right? So, U.S. definitely, we're seeing, you know, cloud adoption, you know, that's independent of IoT. Here in Europe, I would argue, the smart mobility initiatives, the smart manufacturing initiatives, and the connected grid initiatives, are bringing cloud in. So, it's IoT and cloud, and that's opening up the cloud opportunity here. Interesting. Sean, prospects for Hortonworks, cashflow positive, Q4, you guys have made a public statement. Any other thoughts you want to share? Just continue to, you know, grow the business, focus on these customer use cases, get them to talk about them at things like DataWorks Summit, and then the more the merrier, the more data-oriented open source driven companies that can graduate in the public markets, I think is awesome. I think it will just help the industry. Operating in the open with full transparency is with the business and the code. And the code. Welcome to the party, baby. Okay, this is theCUBE here at DataWorks 2017 in Munich, Germany. Live coverage, I'm John Furrier with Dave Vellante. Stay with us. More great coverage. Coming up after the short break.


Gosh, sometimes it's really hard not to laugh because you know what's coming. No, so treatment integrity, folks. So here we have the same type of thing as, I don't know, some fidelity words. All right, so treatment fidelity, treatment integrity, basically when we deliver an intervention, we wanna make sure that intervention is delivered the way it is supposed to be delivered. So we need to double check on it, right? So we design an intervention, maybe let's say to increase on task behavior. So what I've asked, but we get a little bit funny around the shop here. So we get off task really easily. So I've asked Brad to slowly shape my behavior with regard to making sure we stay on task. Historically, he's done pretty well. One or two things here and there. But we got, the reinforcers were getting a bit thick. So we needed to reduce the frequency of reinforcement and we needed to reduce the intensity. So he's supposed to be reducing the amount of reinforcers that he delivers. We call it thinning the schedule. But I've been on task for a while now and I suppose I kinda expect a reinforcer but you never know when they're gonna come. And if he's doing this treatment right, this should be a smaller amount of reinforcement than what was done the last time. Great job, Ryan. Oh, yeah, oh! Oh! Oh! These parts were not reinforcing. Those are Christmas hooks and I'm now bleeding. No, wow, there's all sorts of stuff. Another Christmas hook. So if we were talking about treatment fidelity here or treatment integrity, we would have failed. Why? Because he was supposed to be thinning the schedule, not giving me so many reinforcers, which might slow down the rate of videos later because I'm just gonna satiate myself. So treatment integrity, did we do what we were supposed to do with regard to the intervention or not? That's all there is to it.


So lighting is cool but you want to know how to make a night sky, not a problem. Now this is a bit of an older solution but it's also extremely simple. On the right under settings, check show engine content, click the engine folder and then in the search bar type sky and drag it into your scene like so. Now this new sky box should replace the old sky box and then once you've dragged it in, you might have to go to your sky atmosphere and reduce the ray lay in order to actually see the stars. And if you go down under detail, the most important thing here is the sun height. You can drag it back and forth from day to night and the night comes with these awesome beautiful stars. But before we get there in the daytime, the sun's brightness can be controlled here. Cloud speed which really should have been called cloud rotation can be controlled here and how clear the clouds are are determined here. Now here we can control how clear the stars are and that's really it. There are some other cool color settings that you can mess with but as far as just getting a quick, easy, beautiful night sky onto your scene, just replace the sky box with the legacy one. Hope that helps and as always, hope you have a fantastic day and I'll see you around.