>> Narrator: From Berlin, Germany, it's theCUBE! Covering Dataworks Summit Europe 2018. Brought to you by Hortonworks. >> Well, hello. Welcome to theCUBE. I'm James Kobielus. I'm lead analyst at Wikibon for big data analytics. Wikibon, of course, is the analyst team inside of SiliconANGLE Media. One of our core offerings is theCUBE and I'm here with Joe Morrissey. Joe is the VP for International at Hortonworks and Hortonworks is the host of Dataworks Summit. We happen to be at Dataworks Summit 2018 in Berlin! Berlin, Germany. And so, Joe, it's great to have you. >> Great to be here! >> We had a number of conversations today with Scott Gnau and others from Hortonworks and also from your customer and partners. Now, you're International, you're VP for International. We've had a partner of yours from South Africa on theCUBE today. We've had a customer of yours from Uruguay. So there's been a fair amount of international presence. We had Munich Re from Munich, Germany. Clearly Hortonworks is, you've been in business as a company for seven years now, I think it is, and you've established quite a presence worldwide, I'm looking at your financials in terms of your customer acquisition, it just keeps going up and up so you're clearly doing a great job of bringing the business in throughout the world. Now, you've told me before the camera went live that you focus on both Europe and Asia PACS, so I'd like to open it up to you, Joe. Tell us how Hortonworks is doing worldwide and the kinds of opportunities you're selling into. >> Absolutely. 2017 was a record year for us. We grew revenues by over 40% globally. I joined to lead the internationalization of the business and you know, not a lot of people know that Hortonworks is actually one of the fastest growing software companies in history. We were the fastest to get to $100 million. Also, now the fastest to get to $200 million but the majority of that revenue contribution was coming from the United States. When I joined, it was about 15% of international contribution. By the end of 2017, we'd grown that to 31%, so that's a significant improvement in contribution overall from our international customer base even though the company was growing globally at a very fast rate. >> And that's also not only fast by any stretch of the imagination in terms of growth, some have said," Oh well, maybe Hortonworks, "just like Cloudera, maybe they're going to plateau off "because the bloom is off the rose of Hadoop." But really, Hadoop is just getting going as a market segment or as a platform but you guys have diversified well beyond that. So give us a sense for going forward. What are your customers? What kind of projects are you positioning and selling Hortonworks solutions into now? Is it a different, well you've only been there 18 months, but is it shifting towards more things to do with streaming, NiFi and so forth? Does it shift into more data science related projects? Coz this is worldwide. >> Yeah. That's a great question. This company was founded on the premise that data volumes and diversity of data is continuing to explode and we believe that it was necessary for us to come and bring enterprise-grade security and management and governance to the core Hadoop platform to make it really ready for the enterprise, and that's what the first evolution of our journey was really all about. A number of years ago, we acquired a company called Onyara, and the logic behind that acquisition was we believe companies now wanted to go out to the point of origin, of creation of data, and manage data throughout its entire life cycle and derive pre-event as well as post-event analytical insight into their data. So what we've seen as our customers are moving beyond just unifying data in the data lake and deriving post-transaction inside of their data. They're now going all the way out to the edge. They're deriving insight from their data in real time all the way from the point of creation and getting pre-transaction insight into data as well so-- >> Pre-transaction data, can you define what you mean by pre-transaction data. >> Well, I think if you look at it, it's really the difference between data in motion and data at rest, right? >> Oh, yes. >> A specific example would be if a customer walks into the store and they've interacted in the store maybe on social before they come in or in some other fashion, before they've actually made the purchase. >> Engagement data, interaction data, yes. >> Engagement, exactly. Exactly. Right. So that's one example, but that also extends out to use cases in IoT as well, so data in motion and streaming data, as you mentioned earlier since become a very, very significant use case that we're seeing a lot of adoption for. Data science, I think companies are really coming to the realization that that's an essential role in the organization. If we really believe that data is the most important asset, that it's the crucial asset in the new economy, then data scientist becomes a really essential role for any company. >> How do your Asian customers' requirements differ, or do they differ from your European cause European customers clearly already have their backs against the wall. We have five weeks until GDPR goes into effect. Do many of your Asian customer, I'm sure a fair number sell into Europe, are they putting a full court, I was going to say in the U.S., a full court press on complying with GDPR, or do they have equivalent privacy mandates in various countries in Asia or a bit of both? >> I think that one of the primary drivers I see in Asia is that a lot of companies there don't have the years of legacy architecture that European companies need to contend with. In some cases, that means that they can move towards next generation data-orientated architectures much quicker than European companies have. They don't have layers of legacy tech that they need to sunset. A great example of that is Reliance. Reliance is the largest company in India, they've got a subsidiary called GO, which is the fastest growing telco in the world. They've implemented our technology to build a next-generation OSS system to improve their service delivery on their network. >> Operational support system. >> Exactly. They were able to do that from the ground up because they formed their telco division around being a data-only company and giving away voice for free. So they can in some extent, move quicker and innovate a little faster in that regards. I do see much more emphasis on regulatory compliance in Europe than I see in Asia. I do think that GDPR amongst other regulations is a big driver of that. The other factor though I think that's influencing that is Cloud and Cloud strategy in general. What we've found is that, customers are drawn to the Cloud for a number of reasons. The economics sometimes can be attractive, the ability to be able to leverage the Cloud vendors' skills in terms of implementing complex technology is attractive, but most importantly, the elasticity and scalability that the Cloud provides us, hugely important. Now, the key concern for customers as they move to the Cloud though, is how do they leverage that as a platform in the context of an overall data strategy, right? And when you think about what a data strategy is all about, it all comes down to understanding what your data assets are and ensuring that you can leverage them for a competitive advantage but do so in a regulatory compliant manner, whether that's data in motion or data at rest. Whether it's on-prem or in the Cloud or in data across multiple Clouds. That's very much a top of mind concern for European companies. >> For your customers around the globe, specifically of course, your area of Europe and Asia, what percentage of your customers that are deploying Hortonworks into a purely public Cloud environment like HDInsight and Microsoft Azure or HDP inside of AWS, in a public Cloud versus in a private on-premises deployment versus in a hybrid public-private multi Cloud. Is it mostly on-prem? >> Most of our business is still on-prem to be very candid. I think almost all of our customers are looking at migrating, some more close to the Cloud. Even those that had intended to have a Cloud for a strategy have now realized that not all workloads belong in the Cloud. Some are actually more economically viable to be on-prem, and some just won't ever be able to move to the Cloud because of regulation. In addition to that, most of our customers are telling us that they actually want Cloud optionality. They don't want to be locked in to a single vendor, so we very much view the future as hybrid Cloud, as multi Cloud, and we hear our customers telling us that rather than just have a Cloud strategy, they need a data strategy. They need a strategy to be able to manage data no matter where it lives, on which tier, to ensure that they are regulatory compliant with that data. But then to be able to understand that they can secure, govern, and manage those data assets at any tier. >> What percentage of your deals involve a partner? Like IBM is a major partner. Do you do a fair amount of co-marketing and joint sales and joint deals with IBM and other partners or are they mostly Hortonworks-led? >> No, partners are absolutely critical to our success in the international sphere. Our partner revenue contribution across EMEA in the past year grew, every region grew by over 150% in terms of channel contribution. Our total channel business was 28% of our total, right? That's a very significant contribution. The growth rate is very high. IBM are a big part of that, as are many other partners. We've got, the very significant reseller channel, we've got IHV and ISV partners that are critical to our success also. Where we're seeing the most impact with with IBM is where we go to some of these markets where we haven't had a presence previously, and they've got deep and long-standing relationships and that helps us accelerate time to value with our customers. >> Yeah, it's been a very good and solid partnership going back several years. Well, Joe, this is great, we have to wrap it up, we're at the end of our time slot. This has been Joe Morrissey who is the VP for International at Hortonworks. We're on theCUBE here at Dataworks Summit 2018 in Berlin, and want to thank you all for watching this segment and tune in tomorrow, we'll have a full slate of further discussions with Hortonworks, with IBM and others tomorrow on theCUBE. Have a good one. (upbeat music)

(upbeat techno) >> Announcer: Live, from Las Vegas, it's theCUBE. Covering NetApp Insight 2017. Brought to you by, NetApp. >> Hello, everyone, welcome back to our Cube coverage, exclusive coverage here at the NetApp Insight 2017. This is theCUBE, I'm John Furrier, the co-host, co-founder of the SiliconANGLE Keith Townsend CTO advisor here in Las Vegas, Nevada at the Mandalay Bay, our next guest is Jennifer Meyer, senior director cloud product marketing, and Ingo Fuchs who's the senior manager cloud product marketing. You guys are doing a lot of the heavy lifting on the front lines for NetApp on the cloud, welcome to theCUBE, good to see you. >> Thank you so much for having us. >> Okay, so, we've been covering it, but now it's pretty clear there's a cloud play, there is a cloud play for Netapp, you guys are showing product, lot of products in the keynotes, both in the data center in the next generation but the cloud's the big part of the story, it's certainly we hear resonating with customers, and all the guests that have come up on the A teams, and your partner channels, all are like this is really, really great thing. >> Yeah, I think -- >> Part of the plan? >> Absolutely part of the plan, I mean if you caught any of the latest messaging which, you know, Jean and the team have worked really hard on, it's all about us being the data authority and the hybrid cloud, right, and so, if you think about, let's unpack hybrid cloud, there's only about 1% of the population of the planet that's not adopting cloud in some way, and we believe that after the last 25 years of our history in data management and our leadership with things like ONTAP that we are well-equipped to help people get there, how they want to get there and with what, right. >> And you have an install base too, so you've been selling boxes, everyone knows you for selling, that's an old term but I'm showing my age, (Jennifer laughs) hardware, but hardware's not going away either, Amazon makes their own stuff too, so you got to still store stuff, so storage will be there, servers will be there, hyperconverging, all that's happening under the hood, but the software's where the value is, certainly, you know, we have expression at SiliconANGLE, software's eating the world as Mark Andreesen said, but data's eating software, Anthony, your general manager came on and said, you know, data is trumping applications, used to be applications had data, now data has applications. >> Right. >> So that flips things, upside-down, and you guys got to go build that market out for your customers. How do your customers at NetApp, and prospective customers, new customers, NetNew, engage with NetApp and what's the positioning, what's the value? >> Yeah, there are a lot of different ways to do it. So if you're an existing NetApp customer today, a really really easy way to get into the cloud, so we have one of our product called ONTAP Cloud, it's our storage operating system, the number one operating system in the world, running inside Azure and AWS hyperscalers so you use all the same tools, all the same mechanisms that you would use on premises, but you're now running in the cloud, so that makes it really easy to lift and shift applications that are using NFS or CIFS or iSCSI protocols, straight into the cloud, because you have the same storage operating system that you have on premises, you have datafication, you have snapshot, you have cloning, you have all of the advantages of data management infrastructure that has been developed over the last 25 years. >> So some of the push-back that I've seen is that, yeah, you have the tooling, but isn't the cloud all about the new? Can you actually build new apps with on, using ONTAP and Microsoft Azure NFS, can you talk to us a little bit about the story, about not just bringing your legacy tools, quote unquote, but also, the new capabilities that developers will find as a result of the cloud offerings. >> Yeah, absolutely, I think in my opinion the most exciting announcement this week, and others may argue differently -- >> You're a little biased. >> You're a little bit, yeah. >> I'm a little bit biased, because you know, >> We'll take it with a grain of salt. >> It's my baby so I do care about it, is that we, that Microsoft announced, and that we announced that we are the technology provider for Microsoft launching an Enterprise-class NFS service natively in Azure. Now, if you think about that, if it runs natively in Azure, it sits right next to the infrastructure that is processing HDInsight, that's running SQL server, Microsoft announced that they are having SQL running on Linux, so suddenly having an Enterprise cloud very very fast, high performance, managed by NetApp NFS service running natively in Azure opens up the opportunities to do IoT, run your Enterprise databases against this infrastructure and really opening up the door for customers to do more. And because you're using tools like HDInsight, you can run analytics, you can now expand into AI, into machine learning, all of that is now open to people that are cloud-native, and cloud natives don't want to go back and learn how to manage a storage infrastructure, that's not a good use of their time, so something like the NFS service in Azure, you don't have to learn how to do storage, all you do is go to the portal, you provision it, you click on it, it's running, it's done. >> I think that's a really important point, because everybody just hears it's a new native or first-party service in Azure, which frankly is industry-first. I mean, nobody, especially from the storage provider standpoint is doing that today, but I think the ability to get all those Enterprise-class services without it feeling like a prostate exam is probably a first for everybody. (men laughing) >> Probably you get, you get put under for that these days, but I mean, my point is, the multi-cloud thing's interesting to me, and I think you guys have hit on something with the Cloud Orchestrator product we saw on stage, the demo, is that multi-cloud, customers don't want to be locked in. >> That's right. >> That's the number one thing we hear in theCUBE, and the suppliers, whoa, we don't lock in, now open-source has been growing, that's great, but you know, the new lock-in as we still call it, is functionality, are you helping customers scale up and scale out at the same time, so the question for you is, how far along is that cloud orchestrator, and is that the guiding principle of the cloud group to seamlessly, first of all the cloud orchestrator allows you to move data around just by clicking buttons, so it takes away all the under-the-covers work that's needed. >> That's right. >> 'Cause each cloud has its own architecture. >> That's right. >> How they do things. So, that's a value quotient I think will be a home run. >> It is, and a big priority for NetApp and specifically in our cloud business unit and our cloud marketing is to make sure that people feel like they have the freedom to choose where they want to go and how, right, and so think about it like a compass, a compass still needs you to pick the destination, and it tells you the best way to get there. That's really sort of what we're trying to do and the orchestrator is just a very flexible way to help people do it, even at the API level. >> Alright, so for all the naysayers out there that are, oh NetApp, they're just cloud washing, they're not really in the cloud game, what does this mean, how do you put that to rest, 'cause I know you've been involved in Amazon for some time, now with the Microsoft deal pretty significant, what do you say to the naysayers or customers that might learn for the first time wow, good story there, or there's a path to the cloud. >> You know, we joked one time we should have an entire marketing campaign that said, oh, I didn't know NetApp did that, because there are so many things, even me, being fairly new to NetApp that I didn't even know we were doing, let alone how long we were doing them for, so it might shock some people to know that we've been doing the ONTAP cloud product for four years, I mean four years, and that product frankly was born out of our own need to abstract the software and test it on our own for TestApp, right, >> Well Jean's in town so she's a good marketer so she should do a good job of changing the marketing angle, but the tell sign to me at events is on keynotes, right, this is to me the relevance barometer, I think Amazon has really nailed this, they have so many announcements they can't even keep track of them, they actually, there's just a tsunami, and that is an indicator of success, and that's to me the competitive advantage, keep on introducing new products. You guys had how many products introduced on stage today, I mean, it was just not enough time. >> A lot, the payload was huge. >> There's a huge -- >> It's a really good sign of momentum and what's to come, yeah. >> Great sign, great sign. And I think what's going to, I'm sorry, we're so excited we can't even help ourselves. (men laughing) I think what's going to be interesting and a challenge for marketing moving forward is how do you put a net around it when you want to announce it, because when you look at continuous innovation and delivery, we're going to be doing something every few days, right, once a month, once every two weeks, so -- >> Well you guys have a good install base, and I always said you can't go out of business if you have money in the bank and if you have customers, thousands of customers do you guys have, not losing that core, building on the core, so how are you guys, from a product marketing standpoint, you got to package to the core, you got to have your core base, but now you have new constituencies, new personas in your base, now, developing, you have analytics, you have chief data officers, you have the guy who's going to be thinking about governance now and GP, GS, >> GDPR. >> G, D, >> G, D, P, R, >> G, E, P, R. Gettin' late in the day. (Jennifer laughing) But it's a global skill, you guys now have a new territory to take down, what's the plan? >> You take that one. >> Yeah, I think it's a really interesting one. Let me give you a specific example, and then we can broaden the story a little bit, but we recognize that one of the problems that our customers have is packing up their SAS environments. So that they have come from on-premises environments, where they were maybe using our storage, maybe not, moved into the cloud, and now, like one of our customers was talking recently about, he has hundreds of SAS providers, and he doesn't really know what data they have, so he's concerned about data protection, he's concerned about losing that data, obviously hacking attacks and similar things. >> Yeah. >> So we actually started a program around a product that we call Cloud Control, and Cloud Control for Office 365 is a first iteration of that that we launched just a few months ago, and it takes the Office 365 data and protects it and retains that data so that if something happens, somebody hacks, somebody corrupts your files, your CEO deletes emails and three months later you want it back, that data is there and it's protected and it's secure, so that's a native cloud service, you don't buy any equipment from us, your earlier comment about moving boxes, so the cloud for us is a great vehicle to get to these new buyers, and the interest that we're getting back is tremendous, but you're absolutely right that we need to find different ways and we are finding different ways to get to these buyers, to get to these personas that are out there. >> Well, not having a hardware-specific thing is certainly a great way, cloud, I mean. >> Exactly. >> Absolutely. >> you got a lot of data back in the recovery, there's no walls in the cloud, so the on-premises paradigm changes it a lot. >> Yeah, and this time we're talking SAS to SAS, right? >> That's great, so ecosystem partners, one of the big successes is partnerships. What's the strategy on partners, I mean cloud-native foundation, cloud CNCF cloud native compute foundations has grown, who's in there are you guys getting involved in that, what's your position, what's the strategy for partnering. >> Yeah, so as you would expect, you know, cloud is different enough that one framework doesn't match the things that we've been doing for those 25 years that we've been so successful in this business, so what we've tried to do in this new cloud first partner program that we've launched several months ago is really target our cloud native partners, these guys that couldn't care less about on-prem, they don't even know how to spell the word storage, and see how do we help service them with some of these great data services that we're bringing to bear, really, and these guys have no previous NetApp history with us. And we've got, you know, a couple dozen partners that have already signed up on our behalf, and we'll continue that momentum, but we're certainly excited to give them a new level of treatment that NetApp hasn't done before. >> So I would love to hear feedback from the lower-level from the ecosystem. NetApp I think, which is I think is a good thing, is very opinionated when it comes to its approach to cloud. This isn't oh, bring any old object store to the, it's you know what if you adopt ONTAP, if you adapt NetApp, data-driven vision, the data fabric, if you adopt that, then you enable a new level of cloud mobility. So if you, as you've brought that nest to the ecosystem, what's been the response, I mean a lot of these guys are pretty opinionated themselves. >> I was going to say you've already talked to Anthony and he's pretty opinionated. >> Yes (laughing). >> Yeah, no I think it's well-received, right, I mean, who doesn't want the ability to have some freedom to move around and choose their partners as we go, and I think one thing that Ingo was alluding to earlier is the fact that we're pretty heterogeneous in our data services, you don't have to have NetApp to be able to benefit from Cloud Control, or Cloud Sync, or OnCommand Insight, which is one of our sort of business insight tools for infrastructure and cloud-cost monitoring. So, it's nice to be able to give them a more sort of open message, but still have a pretty strong opinion on where people need to go and why. >> So let's talk about Cloud Control a little bit more, is Cloud Control an API, or is that just a, is that only control plane? >> It's a service, so it's a native cloud service, you can buy it on the marketplace, you can do free trials, you don't buy any hardware anywhere, it will grab the data through official APIs out of Office 365 and store it in a choice of locations, so we can host the storage for you, or you can store it in AWS, you can store it in Azure, or you can store it on-premises and storage with AppScale, which is our object store, so you know, for some customers it's important for compliance reasons to have an off-site on-premises copy, other customers would prefer to use Azure, use AWS, depends on what kind of licensing agreement, or massive purchase agreements they might have, so we give our customers that flexibility, but that is an example for native cloud service. We have another one that's called Cloud Sync, which is a data migration tool, you can go from CIFS, NFS, or S3, to CIFS, NFS, or S3. To, and it transforms the data, so you can go from an NFS source and move it natively into an S3 object in the cloud. It's another example for a native cloud service, it's not a license, it's not something that you buy and install on-premises. >> So that brings a question about data mobility today, I know cloud orchestrator is something that's coming in the future, but as far as data mobility, can I do something as simple as, say, or as complex, depending on your perspective, say I have two AWS regions, I'm front-ending this with ONTAP and I'm using ONTAP as a filer, and I want to replicate storage from one AWS region to another one, can I do that with object in the back-end and then use ONTAP to present that as files on both coasts, for example? >> Yeah, it depends a little bit on your application, the database that you're using, but say you're using ONTAP cloud, you can replicate between regions using cross-region replication, that's easy. But what's different is we have HA, so what you can do with ONTAP cloud is that you can do a fail-over from one availability zone to another availability zone, and that's all managed within the software. So if you're thinking about moving Enterprise application, mission-critical applications running production inside the cloud, you definitely do want to have HA, we did, we tackled this a little bit different for the NFS Azure service 'cause we were running and operating the infrastructure that is underneath the Azure portal so we have the reliability built into our product because it's running on our equipment. So we have complete control over that. >> Guys, final question, I know we got to go but I want to get your thoughts on management software, because the management game is changing the cloud too, as the trend of having the same code bases running on-prem or on the cloud, or applications working across multiple clouds brings up the role of the folks that are being shifted to high-value activities. One of them is, you know, managing dashboards automating some of the system management, application management, OnCommand has been around for a long, long time, NetApp has a history of good management tooling. How does that translate to the products in the cloud? >> It does, and I want to pull back to talk a little bit about OnCommand Insight 'cause we kind of overlook it because it's been around for a little while and it's more traditionally thought of as an SRM tool, but really, some of the capabilities that we've talked about even as early as today, was the fact that now we're extending sort of those infrastructure analytics and those business insights so you can identify resources that are wasted or places where you're out of capacity and you're bottlenecking, now into the cloud for things like cost-monitoring. So, imagine you're a CIO and you have people going around your back swiping credit cards to find whatever tools they want to use in the SAS universe to get their jobs done, only you have no idea where they're spending your money. Now you'll have the ability to look at almost a unified bill and see which departments are charging what money, and charge back those departments to keep them accountable in your budget. >> John: We call that the toolshed problem. >> Toolshed >> All these tools. >> They're everywhere. >> They're everywhere, don't be a tool, get out, get that toolshed, there's too many things in a tool, you get too many tools >> We have a lot of tools. Yeah, so we're happy to have things like that that help to give people a little bit more empowerment to first identify what's going on and how to fix it. >> The problem is though, in tools, they buy a tool, sometimes it turns into something else, like you buy a hammer and it turns into a lawnmower, but that's not what it's designed for. >> That's right. >> You can't mow your lawn with a hammer. >> You can't. >> So a final question before we break is product marketing focus. What's your to-do items, you guys got your list, I know you're making decisions on there with the product teams on how to take it to market, what's the to-do list for you guys. >> I'll give my answer and then I'll let you close, but it's messaging, messaging, messaging, right? I think in marketing we traditionally get sick of our own message before sometimes our audiences have heard it, and certainly we don't want to let Jean down, because she's done such a phenomenal job of getting the ship steered in a singular direction, so you're going to see a lot of big bold messages from us, a lot of us not being apologetic about some of the great IP that we've got and some of the things that we're doing, so we want to be sort of out there, reiterating that we're helping people harness the power of the hybrid cloud, and that we are the data authority on the hybrid cloud. >> And they say position it and they will come. That's absolutely right, anything you'd like to add? >> You know, so I spend a lot of time both with our internal product team and with our partners like Microsoft for example, it's really exciting the last few weeks, and the great thing for me is that we have more and more partners coming to us, wanting to leverage our products and working with us and understanding how they can participate in the data fabric vision, how can they be part of this network of partners and solutions and services that we're building, and that has been really, really exciting, cloud is real, and we're making it work. >> We're a little excited. >> Cloud is real, we look forward to following up, I'll have to get you guys into the studio in Palo Alto, a lot to talk about, lot more certainly, Kubernetes containers, we're getting a huge renaissance in application development that's going to create a lot of value, you guys are at the center of it. That's the keyword, the center of the action, here in Las Vegas with NetApp Insight 2017, we'll be right back with more live coverage afterwards I'm John Furrier, Keith Townsend, we'll be right back. (upbeat techno)

>> Announcer: Live from Midtown Manhattan it's theCUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> OK, welcome back everyone we're here in New York City it's theCUBE's exclusive coverage of Big Data NYC, in conjunction with Strata Data going on right around the corner. It's out third day talking to all the influencers, CEO's, entrepreneurs, people making it happen in the Big Data world. I'm John Furrier co-host of theCUBE, with my co-host here Jim Kobielus who is the Lead Analyst at Wikibon Big Data. Nenshad Bardoliwalla. >> Bar-do-li-walla. >> Bardo. >> Nenshad Bardoliwalla. >> That guy. >> Okay, done. Of Paxata, Co-Founder & Chief Product Officer it's a tongue twister, third day, being from Jersey, it's hard with our accent, but thanks for being patient with me. >> Happy to be here. >> Pranav Rastogi, Product Manager, Microsoft Azure. Guys, welcome back to theCUBE, good to see you. I apologize for that, third day blues here. So Paxata, we had your partner on Prakash. >> Prakash. >> Prakash. Really a success story, you guys have done really well launching theCUBE fun to watch you guys from launching to the success. Obviously your relationship with Microsoft super important. Talk about the relationship because I think this is really people can start connecting the dots. >> Sure, maybe I'll start and I'LL be happy to get Pranav's point of view as well. Obviously Microsoft is one of the leading brands in the world and there are many aspects of the way that Microsoft has thought about their product development journey that have really been critical to the way that we have thought about Paxata as well. If you look at the number one tool that's used by analysts the world over it's Microsoft Excel. Right, there isn't even anything that's a close second. And if you look at the the evolution of what Microsoft has done in many layers of the stack, whether it's the end user computing paradigm that Excel provides to the world. Whether it's all of their recent innovation in both hybrid cloud technologies as well as the big data technologies that Pranav is part of managing. We just see a very strong synergy between trying to combine the usage by business consumers of being able to take advantage of these big data technologies in a hybrid cloud environment. So there's a very natural resonance between the 2 companies. We're very privileged to have Microsoft Ventures as an investor in Paxata and so the opportunity for us to work with one of the great brands of all time in our industry was really a privilege for us. Yeah, and that's the corporate sides so that wasn't actually part of it. So it's a different part of Microsoft which is great. You have also business opportunity with them. >> Nenshad : We do. >> Obviously data science problem that we're seeing is that they need to get the data faster. All that prep work, seems to be the big issue. >> It does and maybe we can get Pranav's point of view from the Microsoft angle. >> Yeah so to sort of continue what Nenshad was saying, you know the data prep in general is sort of a key core competence which is problematic for lots of users, especially around the knowledge that you need to have in terms of the different tools you can use. Folks who are very proficient will do ETL or data preparation like scenarios using one of the computing engines like Hive or Spark. That's good, but there's this big audience out there who like Excel-like interface, which is easy to use a very visually rich graphical interface where you can drag and drop and can click through. And the idea behind all of this is how quickly can I get insights from my data faster. Because in a big data space, it's volume, variety and velocity. So data is coming at a very fast rate. It's changing it's growing. And if you spend lot of time just doing data prep you're losing the value of data, or the value of data would change over time. So what we're trying to do would sort of enabling Paxata or HDInsight is enabling these users to use Paxata, get insights from data faster by solving key problems of doing data prep. >> So data democracy is a term that we've been kicking around, you guys have been talking about as well. What is actually mean, because we've been teasing out first two days here at theCUBE and BigData NYC is. It's clear the community aspect of data is growing, almost on a similar path as you're seeing with open source software. That genie's out the bottle. Open source software, tier one, it won, it's only growing exponentially. That same paradigm is moving into the data world where the collaboration is super important, in this data democracy, what is that actually mean and how does that relate to you guys? >> So the perspective we have is that first something that one of our customers said, that is there is no democracy without certain degrees of governance. We all live in a in a democracy. And yet we still have rules that we have to abide by. There are still policies that society needs to follow in order for us to be successful citizens. So when when a lot of folks hear the term democracy they really think of the wild wild west, you know. And a lot of the analytic work in the enterprise does have that flavor to it, right, people download stuff to their desktop, they do a little bit of massaging of the data. They email that to their friend, their friend then makes some changes and next thing you know we have what what some folks affectionately call spread mart hell. But if you really want to democratize the technology you have to wrap not only the user experience, like Pranav described, into something that's consumable by a very large number of folks in the enterprise. You have to wrap that with the governance and collaboration capabilities so that multiple people can work off the same data set. That you can apply the permissions so that people, who is allowed to share with each other and under what circumstances are they allowed to share. Under what circumstances are you allowed to promote data from one environment to another? It may be okay for someone like me to work in a sandbox but I cannot push that to a database or HDFS or Azure BLOB storage unless I actually have the right permissions to do so. So I think what you're seeing is that, in general, technology is becoming a, always goes on this trend, towards democratization. Whether it's the phone, whether it's the television, whether it's the personal computer and the same thing is happening with data technologies and certainly companies like. >> Well, Pranav, we're talking about this when you were on theCUBE yesterday. And I want to get your thoughts on this. The old way to solve the governance problem was to put data in silos. That was easy, I'll just put it in a silo and take care of it and access control was different. But now the value of the data is about cross-pollinating and make it freely available, horizontally scalable, so that it can be used. But the same time and you need to have a new governance paradigm. So, you've got to democratize the data by making it available, addressable and use for apps. The same time there's also the concerns on how do you make sure it doesn't get in the wrong hands and so on and so forth. >> Yeah and which is also very sort of common regarding open source projects in the cloud is a how do you ensure that the user authorized to access this open source project or run it has the right credentials is authorized and stuff. So, the benefit that you sort of get in the cloud is there's a centralized authentication system. There's Azure Active Directory, so you know most enterprise would have Active Directory users. Who are then authorized to either access maybe this cluster, or maybe this workload and they can run this job and that sort of further that goes down to the data layer as well. Where we have active policies which then describe what user can access what files and what folders. So if you think about the entrance scenario there is authentication and authorization happening and for the entire system when what user can access what data. And part of what Paxata brings in the picture is like how do you visualize this governance flow as data is coming from various sources, how do you make sure that the person who has access to data does have access data, and the one who doesn't cannot access data. >> Is that the problem with data prep is just that piece of it? What is the big problem with data prep, I mean, that seems to be, everyone keeps coming back to the same problem. What is causing all this data prep. >> People not buying Paxata it's very simple. >> That's a good one. Check out Paxata they're going to solve your problems go. But seriously, there seems to be the same hole people keep digging themselves into. They gather their stuff then next thing they're in the in the same hole they got to prepare all this stuff. >> I think the previous paradigms for doing data preparation tie exactly to the data democracy themes that we're talking about here. If you only have a very silo'd group of people in the organization with very deep technical skills but don't have the business context for what they're actually trying to accomplish, you have this impedance mismatch in the organization between the people who know what they want and the people who have the tools to do it. So what we've tried to do, and again you know taking a page out of the way that Microsoft has approached solving these problems you know both in the past in the present. Is to say look we can actually take the tools that once were only in the hands of the, you know, shamans who know how to utter the right incantations and instead move that into the the common folk who actually. >> The users. >> The users themselves who know what they want to do with the data. Who understand what those data elements mean. So if you were to ask the Paxata point of view, why have we had these data prep problems? Because we've separated the people who had the tools from the people who knew what they wanted to do with it. >> So it sounds to me, correct me if this is the wrong term, that what you offer in your partnership is it basically a broad curational environment for knowledge workers. You know, to sift and sort and annotating shared data with the lineage of the data preserved in essentially a system of record that can follow the data throughout its natural life. Is that a fair characterization? >> Pranav: I would think so yeah. >> You mention, Pranav, the whole issue of how one visualizes or should visualize this entire chain of custody, as it were, for the data, is there is there any special visualization paradigm that you guys offer? Now Microsoft, you've made a fairly significant investment in graph technology throughout your portfolio. I was at Build back in May and Sacha and the others just went to town on all things to do with Microsoft Graph, will that technology be somehow at some point, now or in the future, be reflected in this overall capability that you've established here with your partner here Paxata? >> I am not sure. So far, I think what you've talked about is some Graph capabilities introduced from the Microsoft Graph that's sort of one extreme. The other side of Graph exists today as a developer you can do some Graph based queries. So you can go to Cosmos DB which had a Gremlin API. For Graph based query, so I don't know how. >> I'll get right to the question. What's the Paxata benefits of with HDInsight? How does that, just quickly, explain for the audience. What is that solution, what are the benefits? >> So the the solution is you get a one click install of installing Paxata HDInsight and the benefit is as a benefit for a user persona who's not, sort of, used to big data or Hadoop they can use a very familiar GUI-based experience to get their insights from data faster without having any knowledge of how Spark works or Hadoop works. >> And what does the Microsoft relationship bring to the table for Paxata? >> So I think it's a couple of things. One is Azure is clearly growing at an extremely fast pace. And a lot of the enterprise customers that we work with are moving many of their workloads to Azure and and these cloud based environments. Especially for us, the unique value proposition of a partner who truly understands the hybrid nature of the world. The idea that everything is going to move to the cloud or everything is going to stay on premise is too simplistic. Microsoft understood that from day one. That data would be in it and all of those different places. And they've provided enabling technologies for vendors like us. >> I'll just say it to maybe you're too coy to say it, but the bottom line is you have an Excel-like interface. They have Office 365 they're user's going to instantly love that interface because it's an easy to use interface an Excel-like it's not Excel interface per se. >> Similar. >> Metaphor, graphical user interface. >> Yes it is. >> It's clean and it's targeted at the analyst role or user. >> That's right. >> That's going to resonate in their install base. >> And combined with a lot of these new capabilities that Microsoft is rolling out from a big data perspective. So HDInsight has a very rich portfolio of runtime engines and capabilities. They're introducing new data storage layers whether it's ADLS or Azure BLOB storage, so it's really a nice way of us working together to extract and unlock a lot of the value that Microsoft. >> So, here's the tough question for you, open source projects I see Microsoft, comments were hell froze because LINUX is now part of their DNA, which was a comment I saw at the even this week in Orlando, but they're really getting behind open source. From open compute, it's just clearly new DNA's. They're they're into it. How are you guys working together in open source and what's the impact to developers because now that's only one cloud, there's other clouds out there so data's going to be an important part of it. So open source, together, you guys working together on that and what's the role for the data? >> From an open source perspective, Microsoft plays a big role in embracing open source technologies and making sure that it runs reliably in the cloud. And part of that value prop that we provide in sort of Azure HDInsight is being sure that you can run these open source big data workloads reliably in the cloud. So you can run open source like Apache, Spark, Hive, Storm, Kafka, R Server. And the hard part about running open source technology in the cloud is how do you fine tune it, and how do you configure it, how do you run it reliably. And that's what sort of what we bring in from a cloud perspective. And we also contribute back to the community based on sort of what learned by running these workloads in the cloud. And we believe you know in the broader ecosystem customers will sort of have a mixture of these combinations and their solution They'll be using some of the Microsoft solutions some open source solutions some solutions from ecosystem that's how we see our customer solution sort of being built today. >> What's the big advantage you guys have at Paxata? What's the key differentiator for why someone should work with you guys? Is it the automation? What's the key secret sauce to you guys? >> I think it's a couple of dimensions. One is I think we have come the closest in the industry to getting a user experience that matches the Excel target user. A lot of folks are attempting to do the same but the feedback we consistently get is that when the Excel user uses our solution they just, they get it. >> Was there a design criteria, was that from the beginning how you were going to do this? >> From day one. >> So you engineer everything to make it as simple as like Excel. >> We want people to use our system they shouldn't be coding, they shouldn't be writing scripts. They just need to be able. >> Good Excel you just do good macros though. >> That's right. >> So simple things like that right. >> But the second is being able to interact with the data at scale. There are a lot of solutions out there that make the mistake in our opinion of sampling very tiny amounts of data and then asking you to draw inferences and then publish that to batch jobs. Our whole approach is to smash the batch paradigm and actually bring as much into the interactive world as possible. So end users can actually point and click on 100 million rows of data, instead of the million that you would get in Excel, and get an instantaneous response. Verses designing a job in a batch paradigm and then pushing it through the the batch. >> So it's interactive data profiling over vast corpuses of data in the cloud. >> Nenshad: Correct. >> Nenshad Bardoliwalla thanks for coming on theCUBE appreciate it, congratulations on Paxata and Microsoft Azure, great to have you. Good job on everything you do with Azure. I want to give you guys props, with seeing the growth in the market and the investment's been going well, congratulations. Thanks for sharing, keep coverage here in BigData NYC more coming after this short break.

>> Announcer: Live from Midtown Manhattan, it's theCUBE, covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay, welcome back, everyone. Live in Manhattan, this is theCUBE's coverage of our fifth year doing Big Data, NYC; eighth year covering Hadoop World, which is now evolved into Strata Data which is right around the corner. We're doing that in conjunction with that event. This is, again, where we have the thought leaders, we have the experts, we have the entrepreneurs and CEOs come in, of course. The who's who in tech. And my next two guests, is Jagane Sundar, CUBE alumni, who was on yesterday. CTO of WANdisco, one of the hottest companies, most valuable companies in the space for their unique IP, and not a lot of people know what they're doing. So congratulations on that. But you're here with one of your partners, a company I've heard of, called Microsoft, also doing extremely well with Azure Cloud. We've got Pranav Rastogi, who's the program manager of Microsoft Cloud Azure. You guys have an event going on as well at Microsoft Ignite which has been creating a lot of buzz this year again. As usual, they have a good show, but this year the Cloud certainly has taken front and center. Welcome to theCUBE, and good to see you again. >> Thank you. >> Thank you. >> Alright, so talk about the partnership. You guys, Jagane deals with all the Cloud guys. You're here with Microsoft. What's going on with Microsoft? Obviously they've been, if you look at the stock price. From 20-something to a complete changeover of the leadership of Satya Nadella. The company has mobilized. The Cloud has got traction, putting a dent in the universe. Certainly, Amazon feels a little bit of pain there. But, in general, a lot more work to do. What are you guys doing together? Share the relationship. >> So, we just announced a product that's a one-click deployment in the Microsoft Azure Cloud, off WANdisco's Fusion Replication technology. So, if you got some data assets, Hadoop or Cloud object stores on-premise and you want to create a hybrid or a Cloud environment with Azure and Picture, ours is the only way of doing Active/Active. >> Active/Active. And there is some stuff out there that's looking like Active/Active. DataPlane by Hortonworks. But it's fully not Active/Active. We talked a little bit about that yesterday. >> Jagane: Yes. >> Microsoft, you guys, what's interesting about these guys besides the Active/Active? It's a unique thing. It's an ingredient for you guys. >> Yes, the interesting thing for us is, the biggest problem that we think customers have for big data perspective is, if you look at the landscape of the ecosystem in terms of open source projects that are available it's very hard to a: figure out How do I use this software?, b: How do I install it? And, so what we have done is created an experience in Azure HDInsight where you can discover these applications, within the context of your cluster and you can install these applications by one-click install. Which installs the application, configures it, and then you're good to go. We think that this is going to sort of increase the productivity of users trying to get sense out of big data. The key challenges we think customers have today is setting up some sort of hybrid environment between how do you connect your on premise data to move it to the Cloud, and there are different use cases that you can have you can move parts of the data and you can do experiment easily in the Cloud. So what we've done is, we've enabled WANdisco as an application on our HDInsight application platform, where customers can install it using a single-click deploy connected with the data that's sitting on-prem, use the Active/Active feature to have both these environments running simultaneously and they're in sync. >> So one benefits the one-click thing, that's on your side, right? You guys are enabling that. So, okay, I get that. That's totally cool. We'll get to that in a second. I want to kind of drill down on that. But, what's the benefit to the customers, that you guys are having? So, I'm a customer, I one-click, I want some WANdisco Active/Active. Why am I doing it? What does the Cloud change? How does your Cloud change from that experience? >> One example that you can think about is going to change is in an on-premise environment you have a cluster running, but you're kind of limited on what you can do with the cluster, because you've already setup the number of nodes and the workloads your running is fairly finite, but what's happening in reality and today is, lots of users, especially in the machine learning space, and AI space, and the analytic space are using a lot of open source libraries and technologies and they're using it on top of Hadoop, and they're using it on top of Spark. However, in experimenting with these technologies is hard on-prem because it's a locked environment. So we believe, with the Cloud, especially with it offering WANdisco and HDInsight, once you move the data you can start spinning up clusters, you can start installing more open source libraries, experiment, and you can shut down the clusters when you're done. So it's going to increase your efficiency, it's going to allow you to experiment faster, and it's going to reduce for cost as well, because you don't have to have the cluster running all the time and once you are done with your experimentation, then you can decide which way do you want to go. So, it's going to remove the-- >> Jagane, what's your experience with Azure? A lot of people have been, some people have been critical, and rightfully so. You guys are moving as fast you can. You can only go as fast you can, but the success of the Cloud has been phenomenal. You guys have done a great job with the Cloud. Got to give you props on that. Your customers are benefiting, or Microsoft's customers are benefiting. How's the relationship? Are you getting more customers through these guys? Are you bringing customers from on-prem to Cloud? How's the customer flow going? >> Almost all of our customers who have on-prem instances of Hadoop are considering Cloud in one form or the other. Different Clouds have different strengths, as they've found-- >> Interviewer: And different technologies. >> Indeed. And Azure's strengths appear to be the HDInsight piece of it and as Pranam just mentioned, the cool thing is, you can replicate into the Cloud, start up a 50 node Spark cluster today to run a query, that may return results to you really fast. Now, remember this is data that you can write to both in the Cloud and on-premise. It's kept consistent by our technology, or tomorrow you may find that somebody tells you, Hive with the new Tez enhancements is faster, sure, spin up a hundred node Hive cluster in the Cloud, HDInsight supports that really well. You're getting consistent data and your queries will respond much faster than your on-premise. >> We've had Oliver Chu on, before with Hortonworks obviously they're partnering there. HDInsight's been getting a lot of traction lately. Where's that going? We've seen some good buzz on that. Good people talking about it. What's the latest update on your end? >> HDInsight is doing really good. The customers love the ease of creating a cluster using just a few clicks and the benefits that customers get, clusters are optimized for certain scenarios. So if you're doing data science, you can create a Spark cluster, install open source libraries. We have Microsoft R Server running on Spark, which is a unique offering to Microsoft, which lots of customers have appreciated. You also have streaming scenarios that you can do using open source technologies, like we have Apache Kafka running on a stack, which is becoming very popular from an ingestion perspective. Folks have been-- >> Has the Kupernetes craze come down to your group yet? Has it trickled down? It seems to be going crazy. You hired an amazing person from Google, Brendan Burns, we've interviewed before. He's part of the original Kubernetes spec he now works for Microsoft. What's the buzz on the Kubernetes container world there? >> In general, Microsoft Azure has seen great benefits out of it. We are seeing lots of traction in that space. From my role in particular, I focus more on the HDInsight big data space, which is kind of outside of what we do with Kubernetes' work. >> And your relationship is going strong with WANdisco? >> Pranav: Yes. >> Right. >> We just launched this offering just about yesterday is what we announced and we're looking forward to getting customers on to the stack. >> That's awesome. What's your take on the industry right now? Obviously, the partnerships are becoming clearer as people can see there's (mumbles). You're starting to see the notion of infrastructure and services are changing. More and more people want services and then you got the classic infrastructure which looks like it's going to be hybrid. That's pretty clear, we see that. Services versus infrastructure, how should customers think about how they architect their environments? So they can take advantage of the Active/Active and also have a robust, clean, not a lot of re-skilling going on, but more of a good organization from a personnel standpoint, but yet get to a hybrid architecture? >> So, it depends, the Cloud gives you lots of options to meet the customers where they are. Different customers have different kinds of requirements. Customers who have specialized, some of their applications will probably want to go more of an infrastructure route, but customers also love to have some of the past benefits where, you know, I have a service running where I don't have to worry about the infrastructure, how dispatching happen, how does OS updates happen, how does maintenance happen. They want to sort of rely on the Microsoft Azure Cloud provider to take care of it. So that they can focus on their application specific logic, or business specific logic, or analytical workloads, and worry about optimizing those parts of the application because that is their core-- >> It's been great.I want to get your thoughts real quick. Share some color. What's going on inside Microsoft? Obviously, open source has become a really big part of the culture, even just at Ignite. More Linux news is coming. You guys have been involved in Linux. Obviously, open source with Azure, ton of stuff, I know is built in the Microsoft Cloud on open source. You're contributing now as to Kubernetes, as I mentioned earlier. Seems to be a good cultural shift at Microsoft. What's the vibe on the open source internally at Microsoft? Can you share, just some anecdotal insight into what's the vibe like inside, around open source? >> The vibe has increased quite a lot around open source. You rightly mentioned, just recently we've announced a SQL server on Linux as well, at the Ignite conference. You can also deploy a SQL server on a docker container, which is quite revolutionary if you think about how forward we have come. Open source is so pervasive it's almost used in a lot of these projects. Microsoft employees are contributing back to open source projects in terms of, bug fixes, feature requests, or documentation updates. It's a very, very active community and by and large I think customers are benefiting a lot, because there are so many folks working together on open source projects and making them successful and especially around the Azure stack, we also ensure that you can run these open source workloads lively in the Cloud. From an enterprise perspective, you get the best of both worlds. You get the latest innovations happening in open source, plus the reliability of the managed platform that Azure provides at an enterprise scale. >> So again, obviously Microsoft partnership is huge, all the Clouds as well. Where do you want to take the relationship with Microsoft? What happens next? You guys are just going to continue to do business, you're like expecting the one-click's nice, I have some questions on that. What happens next? >> So, I see our partnership becoming deeper. We see the value that HDInsight brings to the ecosystem and all of that value is captured by the data. At the end of the day, if you have stale data, if you have data that you can't rely on the applications are useless. So we see ourselves getting more and more deeply embedded in the system. We see of ourselves as an essential part of the data strategy for Azure. >> Yeah, we see continuous integration as a development concept, continuous analytics as a term, that's being kicked around. We were talking yesterday about, here in theCUBE, real time, I want some data real time and IT goes back, "Here it is, it's real time!" No, but the data's three weeks old. I mean, real time (laughs) is a word that doesn't mean I got to see it really fast, low latency response. Well, that's not the data I want. I meant the data in real time, not you giving me a real time query. So again, this brings up a mind shift in terms of the new way to do business in the Cloud and hybrid. It's changing the game. As customers scratch their heads and try to figure out how to make their organizations more DevOps oriented, what do you guys see for advice for those managers, who are really getting behind it, really want to make change, who kind of have to herd the cats a little bit, and maybe break out security and put it in it's own group? Or you come and say, okay IT guys we're going to change into our operating model, even on-prem, we'll use some burst in to the Cloud, Azure's got 365 on there, lot of coolness developing. What's the advice for the mindset of the change agents out there that are going to do the transformation? >> My advice would be, if you've done the same thing by hand over two times, it's time you automated it, but-- >> Interviewer: Two times?! >> Two times. >> No three rule? Three strikes you're out? >> You're saying two, contrarian. >> That's a careful statement. Because, if you try automating something that you've never actually tried by hand, that's a disaster as well. A couple times, so you know how it's supposed to work. >> Interviewer: Get a good groove on it. >> Right, then you optimize, you automate, and then you turn the knobs. So, you try a hundred node cluster, maybe that's going to be faster. Maybe after a certain point, you don't get any improvements, so you know how to-- >> So take some baby steps, and one easy way to do it is to automate something that you've done. >> Jagane: Yes, exactly. >> That's almost risk-free, relatively speaking. Thoughts, advice to change agents out there. This is your industry hat on. You can take your Microsoft hat off. >> Baby steps. So you start small, you get familiar with the environment and your toolsets are provided so that you get a consistent experience on what you were doing on-prem and sort of in a hybrid space. And the whole idea is as you get more comfortable the benefits of the Cloud far outweigh any sort of cultural changes that need to happen-- >> Guys, thanks for coming on theCUBE, really appreciate it. Thoughts on the Big Data NYC this week? What do you think? >> I think it's a conference that has a lot of Cloud hanging over it and people are scratching their heads. Including vendors, customers, everybody scratching their head, but there is a lot of Cloud in this conference, although this is not a Cloud conference. >> Yeah, they're trying to make it an AI conference. A lot of AI watching certainly we're seeing that everywhere. But again, nothing wrong hyping up AI. It's good for society. It really is cool, but still, that's talking about baby steps, AI is still not there. It seems like, AI from when I got my CS degree in the 80's, not a lot innovation, well machine learning is getting better, but, a lot more way to go on AI. Don't you think? >> Yes, you know a few of the announcements we've made in this week is all about making it easier for developers to get started with AI and machine learning and our whole hope is with these investments that we've done and Azure machine learning improvements and the companion app and the workbench, allows you to get started very easily with AI and machine learning models and you can apply and build these models, do a CICD process and deploy these models and be more effective in the space. >> Yeah and also the tooling market has kind of gotten out of control. We were just joking the other day, that there's this tool shed mindset where everything is in the tool shed and people bought a hammer and turned it into a lawnmower. So it's like, you got to be careful which tools you have. Think about a platform. Think holistically, but if you take the baby steps and implement it, certainly it's there. My personal opinion, I think the Cloud is the equalizer. Cloud can bring compute power that changes what a tool was built for. Even, go back six years, the tools that were out there even six years ago are completely changed by the impact of unlimited, potentially unlimited capacity horsepower. So, okay that resets a little bit. You agree? >> I do. I totally agree. >> Who wins, who loses on the reset? >> The Cloud is an equalizer, but there is a mindset shift that goes with that those who can adapt to the mindset shift, will win. Those who can not and are still clinging to their old practices will have a hard time. >> Yeah, it's exciting. If you're still reinventing Hadoop from 2011 then, probably not good shape right now. >> Jagane: Not a good place to be. >> Using Hadoop is great for Bash, but you can't make that be a lawnmower. That's my opinion. Okay, thanks for coming on. I appreciate it (laughs) You're smiling, you got something that you, no? >> Pranav: (laughs) Thank you so much for that comment. >> Yeah, tool sheds are out there, be careful. Guys do your job. Congratulations on your partnership, appreciate it. This is theCUBE, live in New York. More after this short break. We'll be right back.

>> Narrator: From the Silicon Angle Media Office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> Hi, I'm Stu Miniman and we're here at the east coast studio for Silicon Angle Media. Happy to welcome back to the program, a many time guest, Chris Selland, who is now the Vice President of strategic growth with Unifi Software. Great to see you Chris. >> Thanks so much Stu, great to see you too. >> Alright, so Chris, we'd had you in your previous role many times. >> Chris: Yes >> I think not only is the first time we've had you on since you made the switch, but also first time we've had somebody from Unifi Software on. So, why don't you give us a little bit of background of Unifi and what brought you to this opportunity. >> Sure, absolutely happy to sort of open up the relationship with Unifi Software. I'm sure it's going to be a long and good one. But I joined the company about six months ago at this point. So I joined earlier this year. I actually had worked with Unifi for a bit as partners. Where when I was previously at the Vertica business inside of HP/HP, as you know for a number of years prior to that, where we did all the work together. I also knew the founders of Unifi, who were actually at Greenplum, which was a direct Vertica competitor. Greenplum is acquired by EMC. Vertica was acquired by HP. We were sort of friendly respected competitors. And so I have known the founders for a long time. But it was partly the people, but it was really the sort of the idea, the product. I was actually reading the report that Peter Burris or the piece that Peter Burris just did on I guess wikibon.com about distributed data. And it played so into our value proposition. We just see it's where things are going. I think it's where things are going right now. And I think the market's bearing that out. >> The piece you reference, it was actually, it's a Wikibon research meeting, we run those weekly. Internally, we're actually going to be doing them soon we will be broadcasting video. Cause, of course, we do a lot of video. But we pull the whole team together, and it was one, George Gilbert actually led this for us, talking about what architectures do I need to build, when I start doing distributed data. With my background really more in kind of the cloud and infrastructure world. We see it's a hybrid, and many times a multi-cloud world. And, therefore, one of the things we look at that's critical is wait, if I've got things in multiple places. I've got my SAS over here, I've got multiple public clouds I'm using, and I've got my data center. How do I get my arms around all the pieces? And of course data is critical to that. >> Right, exactly, and the fact that more and more people need data to do their jobs these days. Working with data is no longer just the area where data scientists, I mean organizations are certainly investing in data scientists, but there's a shortage, but at the same time, marketing people, finance people, operations people, supply chain folks. They need data to do their jobs. And as you said where it is, it's distributed, it's in legacy systems, it's in the data center, it's in warehouses, it's in SAS applications, it's in the cloud, it's on premise, It's all over the place, so, yep. >> Chris, I've talked to so many companies that are, everybody seems to be nibbling at a piece of this. We go to the Amazon show and there's this just ginormous ecosystem that everybody's picking at. Can you drill in a little bit for what problems do you solve there. I have talked to people. Everything from just trying to get the licensing in place, trying to empower the business unit to do things, trying to do government compliance of course. So where's Unifi's point in this. >> Well, having come out of essentially the data warehousing market. And now of course this has been going on, of course with all the investments in HDFS, Hadoop infrastructure, and open source infrastructure. There's been this fundamental thinking that, well the answer's if I get all of the data in one place then I can analyze it. Well that just doesn't work. >> Right. >> Because it's just not feasible. So I think really and its really when you step back it's one of these like ah-ha that makes total sense, right. What we do is we basically catalog the data in place. So you can use your legacy data that's on the main frame. Let's say I'm a marketing person. I'm trying to do an analysis of selling trends, marketing trends, marketing effectiveness. And I want to use some order data that's on the main frame, I want some click stream data that's sitting in HDFS, I want some customer data in the CRM system, or maybe it's in Sales Force, or Mercado. I need some data out of Workday. I want to use some external data. I want to use, say, weather data to look at seasonal analysis. I want to do neighborhooding. So, how do I do that? You know I may be sitting there with Qlik or Tableau or Looker or one of these modern B.I. products or visualization products, but at the same time where's the data. So our value proposition it starts with we catalog the data and we show where the data is. Okay, you've got these data sources, this is what they are, we describe them. And then there's a whole collaboration element to the platform that lets people as they're using the data say, well yes that's order data, but that's old data. So it's good if you use it up to 2007, but the more current data's over here. Do things like that. And then we also then help the person use it. And again I almost said IT, but it's not real data scientists, it's not just them. It's really about democratizing the use. Because business people don't know how to do inner and outer joins and things like that or what a schema is. They just know, I'm trying do a better job of analyzing sales trends. I got all these different data sources, but then once I found them, once I've decided what I want to use, how do I use them? So we answer that question too. >> Yea, Chris reminds me a lot of some the early value propositions we heard when kind of Hadoop and the whole big data wave came. It was how do I get as a smaller company, or even if I'm a bigger company, do it faster, do it for less money than the things it use to be. Okay, its going to be millions of dollars and it's going to take me 18 months to roll out. Is it right to say this is kind of an extension of that big data wave or what's different and what's the same? >> Absolutely, we use a lot of that stuff. I mean we basically use, and we've got flexibility in what we can use, but for most of our customers we use HDFS to store the data. We use Hive as the most typical data form, you have flexibility around there. We use MapReduce, or Spark to do transformation of the data. So we use all of those open source components, and as the product is being used, as the platform is being used and as multiple users, cause it's designed to be an enterprise platform, are using it, the data does eventually migrate into the data lake, but we don't require you to sort of get it there as a prerequisite. As I said, this is one of the things that we really talk about a lot. We catalog the data where it is, in place, so you don't have to move it to use it, you don't have to move it to see it. But at the same time if you want to move it you can. The fundamental idea I got to move it all first, I got to put it all in one place first, it never works. We've come into so many projects where organizations have tried to do that and they just can't, it's too complex these days. >> Alright, Chris, what are some of the organizational dynamics you're seeing from your customers. You mention data scientist, the business users. Who is identifying, whose driving this issues, whose got the budget to try to fix some of these challenges. >> Well, it tends to be our best implementations are driven really, almost all of them these days, are driven by used cases. So they're driven by business needs. Some of the big ones. I've sort of talked about customers already, but like customer 360 views. For instance, there's a very large credit union client of ours, that they have all of their data, that is organized by accounts, but they can't really look at Stu Miniman as my customer. How do I look at Stu's value to us as a customer? I can look at his mortgage account, I can look at his savings account, I can look at his checking account, I can look at his debit card, but I can't just see Stu. I want to like organize my data, that way. That type of customer 360 or marketing analysis I talked about is a great use case. Another one that we've been seeing a lot of is compliance. Where just having a better handle on what data is where it is. This is where some of the governance aspects of what we do also comes into play. Even though we're very much about solving business problems. There's a very strong data governance. Because when you are doing things like data compliance. We're working, for instance, with MoneyGram, is a customer of ours. Who this day and age in particular, when there's money flows across the borders, there's often times regulators want to know, wait that money that went from here to there, tell me where it came from, tell me where it went, tell me the lineage. And they need to be able to respond to those inquiries very very quickly. Now the reality is that data sits in all sorts of different places, both inside and outside of the organization. Being able to organize that and give the ability to respond more quickly and effectively is a big competitive advantage. Both helps with avoiding regulatory fines, but also helps with customers responsiveness. And then you've got things GDPR, the General Data Protection Regulation, I believe it is, which is being driven by the EU. Where its sort of like the next Y2K. Anybody in data, if they are not paying attention to it, they need to be pretty quick. At least if they're a big enough company they're doing business in Europe. Because if you are doing business with European companies or European customers, this is going to be a requirement as of May next year. There's a whole 'nother set of how data's kept, how data's stored, what customers can control over data. Things like 'Right to Be Forgotten'. This need to comply with regulatory... As data's gotten more important, as you might imagine, the regulators have gotten more interested in what organizations are doing with data. Having a framework with that, organizes and helps you be more compliant with those regulations is absolutely critical. >> Yeah, my understanding of GDPR, if you don't comply, there's hefty fines. >> Chris: Major Fines. >> Major Fines. That are going to hit you. Does Unifi solve that? Is there other re-architecture, redesign that customers need to do to be able to be compliant? [speaking at The same Time] >> No, no that's the whole idea again where being able to leave the data where it is, but know what it is and know where it is and if and when I need to use it and where it came from and where it's going and where it went. All of those things, so we provide the platform that enables the customers to use it or the partners to build the solutions for their customers. >> Curious, customers, their adoption of public cloud, how does that play into what you are doing? They deploy more SAS environments. We were having a conversation off camera today talking about the consolidation that's happening in the software world. What does those dynamics mean for your customers? >> Well public cloud is obviously booming and growing and any organization has some public cloud infrastructure at this point, just about any organization. There's some very heavily regulated areas. Actually health care's probably a good example. Where there's very little public cloud. But even there we're working with... we're part of the Microsoft Accelerator Program. Work very closely with the Azure team, for instance. And they're working in some health care environments, where you have to be things like HIPAA compliant, so there is a lot of caution around that. But none the less, the move to public cloud is certainly happening. I think I was just reading some stats the other day. I can't remember if they're Wikibon or other stats. It's still only about 5% of IT spending. And the reality is organizations of any size have plenty of on-prem data. And of course with all the use of SAS solutions, with Salesforce, Workday, Mercado, all of these different SAS applications, it's also in somebody else's data center, much of our data as well. So it's absolutely a hybrid environment. That's why the report that you guys put out on distributed data, really it spoke so much to what out value proposition is. And that's why you know I'm really glad to be here to talk to you about it. >> Great, Chris tell us a little bit, the company itself, how many employees you have, what metrics can you share about the number of customers, revenue, things like that. >> Sure, no, we've got about, I believe about 65 people at the company right now. I joined like I said earlier this year, late February, early March. At that point we we were like 40 people, so we've been growing very quickly. I can't get in too specifically to like our revenue, but basically we're well in the triple digit growth phase. We're still a small company, but we're growing quickly. Our number of customers it's up in the triple digits as well. So expanding very rapidly. And again we're a platform company, so we serve a variety of industries. Some of the big ones are health care, financial services. But even more in the industries it tends to be driven by these used cases I talked about as well. And we're building out our partnerships also, so that's a big part of what I do also. >> Can you share anything about funding where you are? >> Oh yeah, funding, you asked about that, sorry. Yes, we raised our B round of funding, which closed in March of this year. So we [mumbles], a company called Pelion Venture Partners, who you may know, Canaan Partners, and then most recently Scale Venture Partners are investors. So the companies raised a little over $32 million dollars so far. >> Partnerships, you mentioned Microsoft already. Any other key partnerships you want to call out? >> We're doing a lot of work. We have a very broad partner network, which we're building up, but some of the ones that we are sort of leaning in the most with, Microsoft is certainly one. We're doing a lot of work guys at Cloudera as well. We also work with Hortonworks, we also work with MapR. We're really working almost across the board in the BI space. We have spent a lot of time with the folks at Looker. Who was also a partner I was working with very closely during my Vertica days. We're working with Qlik, we're working with Tableau. We're really working with actually just about everybody in sort of BI and visualization. I don't think people like the term BI anymore. The desktop visualization space. And then on public cloud, also Google, Amazon, so really all the kind of major players. I would say that they're the ones that we worked with the most closely to date. As I mentioned earlier we're part of the Microsoft Accelerator Program, so we're certainly very involved in the Microsoft ecosystem. I actually just wrote a blog post, which I don't believe has been published yet, about some of the, what we call the full stack solutions we have been rolling out with Microsoft for a few customers. Where we're sitting on Azure, we're using HDInsight, which is essentially Microsoft's Hadoop cloud Hadoop distribution, visualized empower BI. So we've really got to lot of deep integration with Microsoft, but we've got a broad network as well. And then I should also mention service providers. We're building out our service provider partnerships also. >> Yeah, Chris I'm surprised we haven't talked about kind of AI yet at all, machine learning. It feels like everybody that was doing big data, now has kind pivoted in maybe a little bit early in the buzz word phase. What's your take on that? You've been apart of this for a while. Is big data just old now and we have a new thing, or how do you put those together? >> Well I think what we do maps very well until, at least my personal view of what's going on with AI/ML, is that it's really part of the fabric of what our product does. I talked before about once you sort of found the data you want to use, how do I use it? Well there's a lot of ML built into that. Where essentially, I see these different datasets, I want to use them... We do what's called one click functions. Which basically... What happens is these one click functions get smarter as more and more people use the product and use the data. So that if I've got some table over here and then I've got some SAS data source over there and one user of the product... or we might see field names that we, we grab the metadata, even though we don't require moving the data, we grab the metadata, we look at the metadata and then we'll sort of tell the user, we suggest that you join this data source with that data source and see what it looks like. And if they say: ah that worked, then we say oh okay that's part of sort of the whole ML infrastructure. Then we are more likely to advise the next few folks with the one click function that, hey if you trying to do a analysis of sales trends, well you might want to use this source and that source and you might want to join them together this way. So it's a combination of sort of AI and ML built into the fabric of what we do, and then also the community aspect of more and more people using it. But that's, going back to your original question, That's what I think that... There was quote, I'll misquote it, so I'm not going to directly say it, but it was just.. I think it might have John Ferrier, who was recently was talking about ML and just sort of saying you know eventually we're not going to talk about ML anymore than we talk about phone business or something. It's just going to become sort of integrated into the fabric of how organizations do business and how organizations do things. So we very much got it built in. You could certainly call us an AI/ML company if you want, its actually definitely part of our slide deck. But at the same time its something that will just sort of become a part of doing business over time. But it really, it depends on large data sets. As we all know, this is why it's so cheap to get Amazon Echoes and such these days. Because it's really beneficial, because the more data... There's value in that data, there was just another piece, I actually shared it on Linkedin today as a matter of fact, about, talking about Amazon and Whole Foods and saying: why are they getting such a valuation premium? They're getting such a valuation premium, because they're smart about using data, but one of the reasons they're smart about using the data is cause they have the data. So the more data you collect, the more data you use, the smarter the systems get, the more useful the solutions become. >> Absolutely, last year when Amazon reinvented, John Ferrier interviewed Andy Jassy and I had posited that the customer flywheel, is going to be replaced by that data flywheel. And enhanced to make things spin even further. >> That's exactly right and once you get that flywheel going it becomes a bigger and bigger competitive advantage, by the way that's also why the regulators are getting interested these days too, right? There's sort of, that flywheel going back the other way, but from our perspective... I mean first of all it just makes economic sense, right? These things could conceivably get out of control, that's at least what the regulators think, if you're not careful at least there's some oversight and I would say that, yes probably some oversight is a good idea, so you've got kind of flywheels pushing in both directions. But one way or another organizations need to get much smarter and much more precise and prescriptive about how they use data. And that's really what we're trying to help with. >> Okay, Chris want to give you the final word, Unify Software, you're working on kind of the strategic road pieces. What should we look for from you in your segment through the rest of 2017? >> Well, I think, I've always been a big believer, I've probably cited 'Crossing the Chasm' like so many times on theCUBE, during my prior HP 10 year and such but you know, I'm a big believer and we should be talking about customers, we should be talking about used cases. It's not about alphabet soup technology or data lakes, it's about the solutions and it's about how organizations are moving themselves forward with data. Going back to that Amazon example, so I think from us, yes we just released 2.O, we've got a very active blog, come by unifisoftware.com, visit it. But it's also going to be around what our customers are doing and that's really what we're going to try to promote. I mean if you remember this was also something, that for all the years I've worked with you guys I've been very much... You always have to make sure that the customer has agreed to be cited, it's nice when you can name them and reference them and we're working on our customer references, because that's what I think is the most powerful in this day and age, because again, going back to my, what I said before about, this is going throughout organizations now. People don't necessarily care about the technology infrastructure, but they care about what's being done with it. And so, being able to tell those customer stories, I think that's what you're going to probably see and hear the most from us. But we'll talk about our product as much as you let us as well. >> Great thing, it reminds me of when Wikibon was founded it was really about IT practice, users being able to share with their peers. Now when the software economy today, when they're doing things in software often that can be leveraged by their peers and that flywheel that they're doing, just like when Salesforce first rolled out, they make one change and then everybody else has that option. We're starting to see that more and more as we deploy as SAS and as cloud, it's not the shrink wrap software anymore. >> I think to that point, you know, I was at a conference earlier this year and it was an IT conference, but I was really sort of floored, because when you ask what we're talking about, what the enlightened IT folks and there is more and more enlightened IT folks we're talking about these days, it's the same thing. Right, it's how our business is succeeding, by being better at leveraging data. And I think the opportunities for people in IT... But they really have to think outside of the box, it's not about Hadoop and Sqoop and Sequel and Java anymore it's really about business solutions, but if you can start to think that way, I think there's tremendous opportunities and we're just scratching the surface. >> Absolutely, we found that really some of the proof points of what digital transformation really is for the companies. Alright Chris Selland, always a pleasure to catch up with you. Thanks so much for joining us and thank you for watching theCUBE. >> Chris: Thanks too. (techno music)

>> Announcer: Coverage DataWorks Summit Europe 2017 brought to you by Hortonworks. >> Welcome back everyone. Live here in Munich, Germany for theCUBE'S special presentation of Hortonworks Hadoop Summit now called DataWorks 2017. I'm John Furrier, my co-host Dave Vellante, our next guest is Shaun Connolly, Vice President of Corporate Strategy, Chief Strategy Officer. Shaun 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, but runs in demise is greatly over-exaggerated, but reality is is that no major shifts in the trends other than the fact that the amplification with AI and machine learning has upleveled the narrative to mainstream around data, big data has been written on on gen one on Hadoop, DevOps, culture, open-source. Starting with Hadoop you guys certainly have been way out in front of all the trends. How you guys have been rolling out the products. But it's now with IoT and AI as that sizzle, the future self driving cars, smart cities, you're starting to really see demand for comprehensive solutions that involve data-centric thinking. Okay, said one. Two, open-source continues to dominate MuleSoft went public, you guys went public years ago, Cloudera filed their S-1. 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, big megatrend 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 in 2014 and it's nice to see that graduating class of Taal and MuleSoft, Cloudera coming out. That just I think helps socializes movement that enterprise open-source, whether it's for on-prem or powering cloud solutions pushed out to the edge, and technologies that are relevant in IoT. That's the wave. We had a panel earlier today where Dahl Jeppe from Centric of British Gas, was talking about his ... The digitization of energy and virtual power plant notions. He can't achieve that without open-source powering and fueling that. >> And the thing about it is is just kind of ... For me personally being my age in this generation of computer industry since I was 19, to see the open-source go mainstream the way it is, is even gets better every time, but it really is the thousandth 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, 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. The public market is based on the multiples from Dave and I's intro, but there's so much value being created. Where's the value for you guys as you look at the horizon? You're talking about 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 em into how the customers are deploying. Cloud computing and IoT are somewhat related. One is a centralization, the other is decentralization, so it actually calls for a connected data architecture as we refer to it. We're working with a variety of IoT-related use cases. Coca-Cola, East Japan spoke at Tokyo Summit about beverage replenishment analytics. Getting vending machine analytics from vending machines even on Mount Fuji. And optimizing their flow-through of inventory in just-in-time delivery. That's an IoT-related to 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 cuz 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 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've got the edge, you got the cloud, you need something in-between, you're calling it connected data platform. How do you guys participate in that value chain? >> When we went public our primary workhorse platform was Hortonworks Data Platform. We had first class cloud services with Azure HDInsight and Hortonworks Data Cloud for AWS, curated cloud services pay-as-you-go, and Hortonworks DataFlow, I call as our connective tissue, it manages all of your data motion, 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 and ify, which does secure intelligent analytics at the edge and transmission. These smart manufacturing lines, you're gathering the data, you're doing analytics on the manufacturing lines, and then you're bringing the historical stuff into the data center where you can do historical analytics across manufacturing lines. Those are the use cases that are connect the data archives-- >> Dave: A subset of that data comes back, right? >> A subset of the data, yep. The key events of that data it may not be full of-- >> 10%, half, 90%? >> 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 you manufacture stuff and when it got deployed and you're seeing issues in the field, like Western Digital Hard Drives, that failure's in the field, they want that data full fidelity to connect the data architecture and analytics around that data. 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 the hairy eyeball from you, 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, Tez, you guys lead a lot of those initiatives. >> Shaun: With the community, yeah, but we-- >> With the community yeah, but you provided contributions and co-leadership let's say. You're there at the front of the pack. How do we project it forward without making forward-looking statements, but how does this industry become a cashflow positive industry? >> Public companies since end of 2014, the markets turned beginning at 2016 towards, prior to that high growth with some losses was palatable, losses were not palatable. That his 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 will better educate the market of the value. 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. The end of Q4 2016, we hit what we call the just-to-even or breakeven, 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 hard revenue growth pace and we basically stated in Q3 or Q4 of 17, we will hit operating cashflow neutrality. So we are operating business-- >> John: But you guys also hit a 100 million at record pace too, I believe. >> Yeah, in four years. 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. We can make that better margins, but that's a software margin. >> You know what's ironic, we were talking about Red Hat off camera. Here's Red Hat kicking butt, really hitting all cylinders, three billion dollars in bookings, one would think, okay hey I can 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 that Red Hat is an indicator of how an open-source model can work. >> By the way Red Hat went public in 99, so it was a different trajectory, like you know I charted their trajectory out. Oracle's trajectory was different. They didn't even in inflation adjusted dollars they didn't hit a 100 million in four years, I think it was seven or eight years or what have you. Salesforce did it in five. So these SaaS models and these subscription models and the cloud services, which is an area that's near and dear to my heart. >> John: Goes faster. >> You get multiple revenue streams across different products. We're a multi-products cloud service company. Not just a single platform. >> So we were actually teasing this out on our-- >> And 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 ripping live here 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. One of the main 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 sales force expansive, you guys pay handsomely for that today. Incubating that market, getting the profitability for it is a good thing, but there's also channels, VARs, ISVs, and so on. You guys have an open-source channel that kind of not as a VAR or an ISV, these are entrepreneurs and or businesses themselves. There's got to be a monetization shift there for you guys in the subscription business certainly. When you look at these partners, they're co-developing, they're in open-source, you can almost see the dots connecting. Is this new ecosystem, there's always been an ecosystem, but now that you have kind of a monetization inherently in a pure open distribution model. >> It forces you to collaborate. IBM was on stage talking about our system certified on the Power Systems. Many may look at IBM as competitive, we view them as a partner. Amazon, some may view them as a competitor with us, they've been a great partner in our for AWS. 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 ecosystems. >> How do you vision monetizing the partners? 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 would we be more subscriptions? 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. >> So you expect some contributions? >> That's how it works. You need a thousand flowers to be running on the platform. >> You saw that with VMware. They hit 10x and ultimately got to 15 or 16, 17x. >> Shaun: Exactly. >> I think they don't talk about it anymore. I think it's probably trading the other way. >> You know my days at JBoss Red Hat it was somewhere between 15 to 20x. That was the value that was created on top of the platforms. >> 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 SiliconANGLE was announcing 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? >> I think if you look at how the Linux market played out. You have clearly Red Hat, you had Conicho Ubuntu, you had SUSE. You're always going to have curated platforms for different purposes. 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. Others in the market Cloudera is running sort of a different play where they're curating different elements and investing in different elements. Doesn't make either one bad or good, we are just going after the markets slightly differently. The other point I'll make there is in 2014 if you looked at the then chart diagrams, there was a lot of overlap. Now if you draw 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 new vendors are going after others. With the market dynamics of IoT, cloud and AI, you're going to see folks chase the market opportunities. >> Is that dispersity not a problem for customers now 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. 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, 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 to what you can rely on. >> When you guys announced ODP, then ODPI, the extension, Mike Olson wrote a blog saying it's not necessary, people came out against it. Now we're three years in looking back. Was he right or not? >> I think ODPI take away this year, there's more than 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 on this spec, but frankly you talk to John Mertic at ODPI, you talk to SAS 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 Wei Wang on earlier-- >> Shaun: There's more we can do and there's more we should do. >> We had Wei 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. >> Microsoft was one of the two companies we chose to partner with early on, so and 2011, 2012 Microsoft and Teradata were the two. Microsoft was how do I democratize and make this technology easy for people. That's manifest itself as Azure Cloud Service, Azure HDInsight-- >> Which is growing like crazy. >> Which is globally deployed and we just had another update. It's fundamentally changed our engineering and delivering model. 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 HDInsight what works data cloud first. Then it certified in HDP 2.6 and it went power at the same time. It's that cadence of delivery and cloud first delivery model. We couldn't do it without a partnership with Microsoft. I think we've really learned what it takes-- >> If you look at Microsoft at that time. I remember interviewing you on theCUBE. Microsoft was trading something like $26 a share at that time, around their low point. Now the stock is performing really well. Stockinnetel very cloud oriented-- >> Shaun: They're very open-source. >> They're very open-source and friendly they've been donating a lot to the OCP, to the data center piece. Extremely different Microsoft, so you slipped into that beautiful spot, reacted 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 nontrivial, that's hard. >> They know the enterprise sales motions too. I want to ask you how that's going over all within Hortonworks. What are some of the conversations that you're involved in with customers today? Again we were saying in our opening segment, it's on YouTube if you're not watching, but the customers is the forcing function right now. They're really putting the pressure one the suppliers, you're one of them, to get tight, reduce friction, lower costs of ownership, get into the cloud, flywheel. And so you see a lot-- >> 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 the public cloud, if not most everything. That's another eight years or what 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 better predictability, ease of use. That's fundamental. >> As you get into the connected tissue, I love that example, with Kubernetes containers, you've got developers, a big open-source participant and you got all the stuff you have, you just start to see some coalescing around the cloud native. How do you guys look at that conversation? >> I view container platforms, whether they're container services that are running one on cloud or what have you, as the new lightweight rail that everything will ride atop. The cloud currently plays a key role in that, I think that's going to be the defacto way. In particularly if you go cloud first models, particularly for delivery. You need that 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. There's others in the ecosystem as well as the cloud providers. All three cloud providers actually are investing in it. >> John: So it's good for your business? >> It removes friction of deployment ... And I ride atop that new rail. It can't get here soon enough from my perspective. >> So I want to ask about clouds. You were talking about the Microsoft shift, personally I think Microsoft realized holy cow, we could actaully make a lot of money if we're selling hardware services. We can make more money if we're selling the full stack. It was 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 etc., they're building out their own big data stack 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 it is what it is? >> This is why I bring up industry-wide we always have waves of centralization, decentralization. They're playing out simultaneously right now with cloud and IoT. The fact of the matter is that you're going to have multiple clouds on-prem data and data at the edge. That's the problem I am looking to facilitate and solve. 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 the data and some of it's going to be running through and on those platforms. >> The cloud's not going to solve the edge problem. Too expensive. It's just physics. >> So I think that's where things need to go. I think that's why we talk about this notion of connected data. I don't talk hybrid cloud computing, 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. It really accelerates the value proposition of the cloud too because now you have a connected network, you can have your cake and eat it too. Central and distributed. >> There's different dynamics in the US versus Europe, as an example. US definitely we're seeing a cloud adoption 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. So on a prospects for Hortonworks cashflow positive Q4 you guys have made a public statement, any other thoughts you want to share. >> Just continue to 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-- >> Shaun: On the business and the code. (laughter) >> Welcome to the party baby. 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 after this short break. (upbeat music)

>> Narrator: Live from San Jose, California it's theCUBE covering Big Data Silicon Valley 2017. >> Welcome back everyone. We're here live in Silicon Valley. This is theCUBE's coverage of Big Data Silicon Valley. Our event in conjunction with O'Reilly Strata Hadoop, of course we have our Big Data NYC event and we have our special popup event in New York and Silicon Valley. This is our Silicon Valley version. I'm John Furrier, with my co-host Jeff Frick and our next guest is Scott Gnau, CTO of Hortonworks. Great to have you on, good to see you again. >> Scott: Thanks for having me. >> You guys have an event coming up in Munich, so I know that there's a slew of new announcements coming up with Hortonworks in April, next month in Munich for your EU event and you're going to be holding a little bit of that back, but some interesting news this morning. We had Wei Wang yesterday with Microsoft Azure team HDInsight's. That's flowering nicely, a good bet there, but the question has always been at least from people in the industry and we've been questioning you guys on, hey, where's your cloud strategy? Because as a disture you guys have been very successful with your always open approach. Microsoft as your guy was basically like, that's why we go with Hortonworks because of pure open source, committed to that from day one, never wavered. The question is cloud first, AI, machine learning this is a sweet spot for IoT. You're starting to see the collision between cloud and data, and in the intersection of that is deep learning, IoT, a lot of amazing new stuff going to be really popping out of this. Your thoughts and your cloud strategy. >> Obviously we see cloud as an enabler for these use cases. In many instances the use cases can be femoral. They might not be tied immediately to an ROI, so you're going to go to the capital committee and all this kind of stuff, versus let me go prove some value very quickly. It's one of the key enablers core ingredients and when we say cloud first, we really mean it. It's something where the solutions work together. At the same time, cloud becomes important. Our cloud strategy and I think we've talked about this in many different venues is really twofold. One is we want to give a common experience to our customers across whatever footprint they chose, whether it be they roll their own, they do it on print, they do it in public cloud and they have choice of different public cloud vendors. We want to give them a similar experience, a good experience that is enterprise great, platform level experience, so not point solution kind of one function and then get rid of it, but really being able to extend the platform. What I mean by that of course, is being able to have common security, common governance, common operational management. Being able to have a blueprint of the footprint so that there's compatibility of applications that get written. And those applications can move as they decide to change their mind about where their platform hosting the data, so our goal really is to give them a great and common experience across all of those footprints number one. Then number two, to offer a lot of choices across all of those domains as well, whether it be, hey I want to do infrastructure as a service and I know what I want on one end of the spectrum to I'm not sure exactly what I want, but I want to spin up a data science cluster really quickly. Boom, here's a platform as a service offer that runs and is available very easy to consume, comes preconfigured and kind of everywhere in between. >> By the way yesterday Wei was pointing out 99.99 SLAs on some of the stuff coming out. >> Are amazing and obviously in the platform as a service space, you also get the benefit of other cloud services that can plug in that wouldn't necessarily be something you'd expect to be typical of a core Hadoop platform. Getting the SLAs, getting the disaster recovery, getting all of the things that cloud providers can provide behind the scenes is some additional upside obviously as well in those deployment options. Having that common look and feel, making it easy, making it frictionless, are all of the core components of our strategy and we saw a lot of success with that in coming out of year end last year. We see rapid customer adoption. We see rapid customer success and frankly I see that I would say that 99.9% of customers that I talk to are hybrid where they have a foot in nonprem and they have a foot in cloud and they may have a foot in multiple clouds. I think that's indicative of what's going on in the world. Think about the gravity of data. Data movement is expensive. Analytics and multi-core chipsets give us the ability to process and crunch numbers at unprecedented rates, but movement of data is actually kind of hard. There's latency, it can be expensive. A lot of data in the future, IoT data, machine data is going to be created and live its entire lifecycle in the cloud, so the notion of being able to support hybrid with a common look and feel, I think very strategically positions us to help our customers be successful when they start actually dealing with data that lives its entire lifecycle outside the four walls of the data center. >> You guys really did a good job I thought on having that clean positioning of data at rest, but also you had the data in motion, which I think ahead of its time you guys really nailed that and you also had the IoT edge in mind, we've talked I think two years ago and this was really not on everyone's radar, but you guys saw that, so you've made some good bets on the HDInsight and we talked about that yesterday with Wei on here and Microsoft. So edge analytics and data in motion a very key right now, because that batch streaming world's coming together and IoTs flooding it with all this kind of data. We've seen the success in the clouds where analytics have been super successful with powering by the clouds. I got to ask you with Microsoft as your preferred cloud provider, what's the current status for customers who have data in motion, specifically IoT too. It's the common question we're getting, not necessarily the Microsoft question, but okay I've got edge coming in strong-- >> Scott: Mm-hmm >> and I'm going to run certainly hybrid in a multi cloud world, but I want to put the cloud stuff for most of the analytics and how do I deal with the edge? >> Wow, there's a lot there (laughs) >> John: You got 10 seconds, go! (laughs) You have Microsoft as your premier cloud and you have an Amazon relationship with a marketplace and what not. You've got a great relationship with Microsoft. >> Yeah. I think it boils down to a bigger macro thing and hopefully I'll peel into some specifics. I think number one, we as an industry kind of short change ourselves talking about Hadoop, Hadoop, Hadoop, Hadoop, Hadoop. I think it's bigger than Hadoop, not different than but certainly than, right, and this is where we started with the whole connected platforms indicating of traditional Hadoop comes from traditional thinking of data at rest. So I've got some data, I've stored it and I want to run some analytics and I want to be able to scale it and all that kinds of stuff. Really good stuff, but only part of the issue. The other part of the issue is data that's moving, data that's being created outside of the four walls of the data center. Data that's coming from devices. How do I manage and move and handle all of that? Of course there have been different hype cycles on streaming and streaming analytics and data flow and all those things. What we wanted to do is take a very protracted look at the problem set of the future. We said look it's really about the entire lifecycle of data from inception to demise of the data or data being delayed, delete it, which very infrequently happens these days. >> Or cold storage-- >> Cold storage, whatever. You know it's created at the edge, it moves through, it moves in different places, its landed, its analyzed, there are models built. But as models get deployed back out to the edge, that entire problem set is a problem set that I think we, certainly we at Hortonworks are looking to address with the solutions. That actually is accelerated by the notion of multiple cloud footprints because when you think about a customer that may have multiple cloud footprints and trying to tie the data together, it creates a unique opportunity, I think there's a reversal in the way people need to think about the future of compute. Where having been around for a little bit of time, it's always been let me bring all the data together to the applications and have the applications run and then I'll send answers back. That is impossible in this new world order, whether it be the cloud or the fog or any of the things in between or the data center, data are going to be distributed and data movement will become the expensive thing, so it will be very important to be able to have applications that are deployable across a grid, and applications move to the data instead of data moving to the application. And or at least to have a choice and be able to be selective so that I believe that ultimately scalability five years from now, ten years from now, it's not going to be about how many exabytes I have in my cloud instance, that will be part of it, it will be about how many edge devices can I have computing and analyzing simultaneously and coordinating with each other this information to optimize customer experience, to optimize the way an autonomous car drives or anywhere in between. >> It's totally radical, but it's also innovative. You mentioned the cost of moving data will be the issue. >> Scott: Yeah. >> So that's going to change the architecture of the edge. What are you seeing with customers, cuz we're seeing a lot of people taking a protracted view like you were talking about and looking at the architectures, specifically around okay. There's some pressure, but there's no real gun to the head yet, but there's certainly pressure to do architectural thinking around edge and some of the things you mentioned. Patterns, things you can share, anecdotal stories, customer references. >> You know the common thing is that customers go, "Yep, that's going to be interesting. "It's not hitting me right now, "but I know it's going to be important. "How can I ease into it and kind of without the suspenders "how can I prove this is going to work and all that." We've seen a lot of certainly interest in that. What's interesting is we're able to apply some of that futuristic IoT technology in Hortonworks data flow that includes NiFi and MiNiFi out to the edge to traditional problems like, let me get the data from the branches into the central office and have that roundtrip communication to a banker who's talking to a customer and has the benefit of all the analytics at home, but I can guarantee that roundtrip of data and analytics. Things that we thought were solid before, can be solved very easily and efficiently with this technology, which is then also extensible even out further to the edge. In many instances, I've been surprised by customer adoption with them saying, "Yeah, I get that, but gee this helps me "solve a problem that I've had for the last 20 years "and it's very easy and it sets me up "on the right architectural course, "for when I start to add in those edge devices, "I know exactly how I'm going to go do it." It's been actually a really good conversation that's very pragmatic with immediate ROI, but again positioning people for the future that they know is coming. Doing that, by the way, we're also able to prove the security. Think about security is a big issue that everyone's talking about, cyber security and everything. That's typically security about my data center where I've got this huge fence around it and it's very controlled. Think about edge devices are now outside that fence, so security and privacy and provenance become really, really interesting in that world. It's been gratifying to be able to go prove that technology today and again put people on that architectural course that positions them to be able to go out further to the edge as their business demands it. >> That's such great validation when they come back to you with a different solution based on what you just proposed. >> Scott: Yep. >> That means they really start to understand, they really start to see-- >> Scott: Yep. >> How it can provide value to them. >> Absolutely, absolutely. That is all happening and again like I said this I think the notion of the bigger problem set, where it's not just storing data and analyzing data, but how do I have portable applications and portable applications that move further and further out to the edge is going to be the differentiation. The future successful deployments out there because those deployments and folks are able to adopt that kind of technology will have a time to market advantage, they'll have a latency advantage in terms of interaction with a customer, not waiting for that roundtrip of really being able to push out customized, tailored interactions, whether it be again if it's driving your car and stopping on time, which is kind of important, to getting a coupon when you're walking past a store and anywhere in between. >> It's good you guys have certainly been well positioned for being flexible, being an open source has been a great advantage. I got to ask you the final question for the folks watching, I'm sure you guys answer this either to investors or whatnot and customers. A lot's changed in the past five years and a lot's happening right now. You just illustrated it out, the scenario with the edge is very robust, dynamic, changing, but yet value opportunity for businesses. What's the biggest thing that's changing right now in the Hortonworks view of the world that's notable that you thinks worth highlighting to people watching that are your customers, investors, or people in the industry. >> I think you brought up a good point, the whole notion of open and the whole groundswell around open source, open community development as a new paradigm for delivering software. I talked a little bit about a new paradigm of the gravity of data and sensors and this new problem set that we've got to go solve, that's kind of one piece of this storm. The other piece of the storm is the adoption and the wave of open, open community collaboration of developers versus integrated silo stacks of software. That's manifesting itself in two places and obviously I think we're an example of helping to create that. Open collaboration means quicker time to market and more innovation and accelerated innovation in an increasingly complex world. That's one requirement slash advantage of being in the open world. I think the other thing that's happening is the generation of workforce. When I think about when I got my first job, I typed a resume with a typewriter. I'm dating myself. >> White out. >> Scott: Yeah, with white out. (laughter) >> I wasn't a good typer. >> Resumes today is basically name and get GitHub address. Here's my body of work and it's out there for everybody to see, and that's the mentality-- >> And they have their cute videos up there as well, of course. >> Scott: Well yeah, I'm sure. (laughter) >> So it's kind of like that shift to this is now the new paradigm for software delivery. >> This is important. You've got theCUBE interview, but I mean you're seeing it-- >> Is that the open source? >> In the entertainment. No, we're seeing people put huge interviews on their LinkedIn, so this notion of collaboration in the software engineering mindset. You go back to when we grew up in software engineering, now it went to open source, now it's GitHub is essentially a social network for your body of work. You're starting to see the software development open source concepts, they apply to data engineering, data science is still early days. Media media creation what not so, I think that's a really key point in the data science tools are still in their infancy. >> I think open, and by the way I'm not here to suggest that everything will be open, but I think a majority and-- >> Collaborative the majority of the problem that we're solving will be collaborative, it will be ecosystem driven and where there's an extremely large market open will be the most efficient way to address it. And certainly no one's arguing that data and big data is not a large market. >> Yep. You guys are all on the cloud now, you got the Microsoft, any other updates that you think worth sharing with folks. >> You've got to come back and see us in Munich then. >> Alright. We'll be there, theCUBE will be there in Munich in April. We have the Hortonworks coverage going on in Data Works, the conference is now called Data Works in Munich. This is theCUBE here with Scott Gnau, the CTO of Hortonworks. Breaking it down I'm John Furrier with Jeff Frick. More coverage from Big Data SV in conjunction with Strata Hadoop after the short break. (upbeat music)

(upbeat electronic music) >> Male Voiceover: Live from New York, it's the Cube, covering big data New York City 2016. Brought to you by headline sponsors Sisco, IBM, Nvidia, and our ecosystem sponsors. Now, here are your hosts. Dave Vellante and Peter Burress. >> We're back in the Big Apple. This is the Cube, the worldwide leader in live tech coverage, we're here at Big Data NYC, Big Data week is part of strata plus dupe world. Shaun Connolly is here as the vice president of strategy at Horton Works, long time friend and Cube alum, great to see you again. >> Thanks for having me, were back at the same venue last year, always a pleasure. >> Yeah, it's good, we're growing, I guess the event's growing, we haven't been over there yet, but some of our guys have, but what's it like over there? >> You know, it feels the same, some of the different use cases, I think last year was streaming, we're hearing more machine learning and things like that as far as use cases, so similar vibe. >> Yeah, so things are evolving, right? How's Hortonworks evolving? >> We're continuing to report our quarterly earnings as the only publicly traded company in this space, things from a business perspective are doing well. Our connected data platforms strategy which we unveiled at the beginning of this year, which is written data in motion and data at rest and enabling these new gen transformational applications continues to play out. The data in motion piece is sort of decoupled and unrelated to a hadou platform, it's really about acquiring and handling the FedEx for data delivery type notions, data logistics, secure transmission. That's based on the Apache Ni-Fi tech that was originally built sort of at the NSA over the past eight years, so. Really a nice robust piece of technology that we've pushed out to the edge in our latest release so you can really skin these down into a secure site to site transmission. A lot of sophisticated capabilities there, so we're seeing a lot of uptake in that sort of architectural vision, the products are maturing, both on prem and in the cloud, things are pretty exciting. >> Well this cloud thing seems pretty real. (Shaun laughing) You can get a lot of traction, right? Everybody kind of knew it was coming, but what are you seeing? >> Yeah so it was, I guess I started the journey back in 2009, when I was at Springsource in Paul Moretz was CEO of Vmware, and that was pre sort of cloud at that time. We were talking about this notion of platform as a service, and things like that. And that resonated really well with folks back then, but their main ask was how do you solve the data problem, how do actually get the data to the apps that need it. Fast forward to 2016, I think it's been a lot of open source innovation, you know a lot of commercial innovation, the rise of cloud for providing a fast path to value, booting up these used cases, it's a fascinating transition to watch. Many of our customers are, people use the word hybrid. What that means to me is they'll have data center workloads, or multi data center workloads, but they also have cloud workloads, sometimes even multi cloud workloads, and that inherent nature of the beast is why I use sort of the term of connected data architecture, is y%ou need an architecture that inherently is built to span that fact. And that's just increasing, that's just the world we live in today. >> But the fact is because there speed of light issues, there's data fidelity issues. >> Shaun: Yup. >> There's other types of things, how are you starting to see those practical and very physical realities start to impact the whole concept of design as it pertains to data, as it pertains to analytics, as it pertains to the infrastructure associated with the two? >> Yup, so at Hoop Summit that we had last June, there were really some really good sessions that were there. Folks like Comcast, Ford, Schlumberger talked about this connected data architecture reality, right. If you look at like, I like to use the connected car ecosystem as a good example, cause there were insurance providers and others that were sort of speaking on behalf of that, where you have the cars and other data that's inherently born up there, and there's a slug of use cases that are around edge analytics, streaming analytics, time series analytics, and we're seeing that, and I think the cloud lends itself really well for those types of use cases. But we also see manufacturing line data for the cars, where you want to get a 360 degree view of operational issues, and dovetail that with manufacturing line elements, and that's inherently what we've seen is, what your classic sort of on prem data wake, in quotes has been used for so you can get that 360 degree operational intelligence type of analytics to come out of that, right? So that type of use case, whether you apply it to oil and gas and having the sensors on the oil rigs, in the Schlumberger example, that pattern is repeating itself across different industries. British Gas, in Europe talks about how they're fundamentally changing the nature of the relationship with their customer because of the smart meters, and their connectivity in the homes and they can deliver a better value there. So that's inherently connected data realm, there's cloud use cases, and in the data center use cases. So I see these use cases, you know, they'll be use case specific in applications that are sprinkled across that fabric, if you will. And that's really what we're seeing. >> At our panel last year here in this venue, we would talk about a lot of things, one was the market, the sort of ebbs and flows you just mentioned, you guys are the only public player, Talon's joining that crew. >> Shaun: Yeah. Excellent. >> You've seen some. >> Shaun: We need more. >> We need more, we've seen some MNA, Plat 4 taken out, I don't know if that was, I don't know the specifics of that deal. Might have been an acu hire, might not, I don't know. And Data Mere did a raise, so you're seeing these rip currents, in all directions. What are you seeing in the marketplace, lot of funding early on, lot of players, lot of innovation, and now it's like, okay, the music at some point's going to stop, but. >> Yeah. >> What's your take? >> So in our last call, and I think we repeated it on our prior earnings call, you know, our focus and then we put out there in our earnings, in our Q3 earnings will sort of reiterate where we stand is, we basically said Q4 is when we look to go adjust to even or break even. >> Right. >> And then 2017 we'll go from there. We reiterated that guidance, we had a little over 62 million in billings for the quarter, so the business is pretty robust and growing, it's a. We're only five years into this, I mean we're just five years old, so it's a very fast pace of billings growth, right? That's almost a 250 million run rate, right? For exiting that quarter. You know, annual run rate. So we see a lot of the use cases really continuing to move on. I think what I and what our customers ask us is, they're on a digital transformation journey, and they want the industry to start talking about those types of business value drivers, right? So I think we should expect to see a transition from the piece parts animals in the zoo and what's the right open source piece of technology, and more why should you care, right? As a business, how is this transforming what you do? How does this open up new lines of business? We started seeing that at Hadoop Summit when I think about two dozen customers were sharing, very rich stories, right? So that's where things are. But I think running a company is, you have to run it with a certain sense of rigor and that was one of the reasons why we chose to go public, right? >> So, we by the way, we totally agree that customers want to stop talking about digital business in platitudes and start actually identifying specifically what is it about it that's new and different, and find ways of doing it. >> Shaun: Sure. >> Coming back to the issue, however, of how you go about making some of those transformations relevant. There is clearly a knowledge gap about what digital business is, what it isn't, certainly. But there's also a fair amount of skills that have yet to be developed, that are required for a lot of the use cases that companies are pursuing. Not just in terms of implementing the technology appropriately, but actually constructing and conceptualizing the use cases. >> Shaun: Sure. >> So that suggests that there's two paths forward. There's a path forward where we can do a better job of diffusing knowledge through people, and there's a path for where we can do a better job of building software that's easier to use. >> Shaun: Mm hmm. >> And there's both. How do you see this playing out over the course of the next few years? >> Yep, and I think in any new area as technology's emerging, like one of the things I use is Apache Software Foundation. Literally every other week there's a new data related Apache project that lands, so it's. It can be really confusing, but it's exhilarating from the fact of I participate in that, and I try and figure out what ones we can harness in a consumable platform, whether it's one prem or a cloud or what have you. What use cases can it light up? So I think you have both of those vectors, and it really depends on, I like to use the classic software adoption curve, you have a lot of the left side of the chasm folks, where a lot of this new stuff is going to be sharper edges, and they're always going to be trailblazers, right? But we are also seeing a lot of some of these advanced analytics. Some of these new solutions are automating the pipeline, so you can actually let the infrastructure and these engines do more of the thinking for you, so you get your model's output. Even to the point where you run multi model simulation in parallel, and out pops the best fit. That's where things will head, right? I think it's just a matter of the technology maturing, making sure we address things like security, metadata management, governance, and those illities that the enterprise expects, and then really forcing ourselves to simplify and automate as much as possible, right. And that was one of the reasons on that last one why in October 2011 we basically chose Teradata and Microsoft as key partners. Teradata because in 2011, clearly, right? >> Peter: Teradata. >> They're Teradata, right? Microsoft because it simplifies technologies and brings them to billions of users, right? And so we need to do both, you need to harden it, right? For the most rigorous large enterprises, but you need to simplify it for the meat of the market adopters, right? The early majority and late majority. You have to do both. >> Shaun, you're sitting across from a CEO, and you have to say these are the three things you need to do to enact this digital transformation. >> Shaun: Yup. >> What are the three things you're telling him? >> So, I think they need as a business to identify how do they want to leverage data as capital, and what pockets of value do they want to go chase, number one. Number two, how is their business being impacted by the fact that you have the rise of IOT and inherently increasing connected society and infrastructure. How is that impacting them? And number three is, how do they evolve what they're used to doing, right? You have to align it, exactly. >> Because that's really many respects of, I like to say there's a difference between invention and innovation. Invention is the engineering act, innovation's a social act, it's adopting those new practices >> Shaun: Exactly. >> That actually allow you to enact the invention and generate revenue. >> Exactly. Now in our space, I think we have a very compelling renovate value prop which is a cost savings where you can drive cost out, but the innovate use cases are the ones. Like if all you're going to do is renovate, then you will fail, you will stall, right? Because it's not a balance of cost savings. It's about how do you actually transform your business. And in the case of like the British Gas example, I used that as how they engaged that end consumer is fundamentally changing. So that's the question I put back in those conversations is how do you want to evolve your business and how do you leverage data as capital? Because the beauty of data as capital is you can actually generate multiple lines of interest off of a single data set, cause you can derive different insights off of that, so it's not like a dollar, right? And single compound, it's multiple compound annual interest rate on that. But they have to chase the right use cases. >> Although, we've also learned from great design that if you do the right thing better, you get rid of a lot waste and so coming back to your point, doing the right thing better often leads to cost savings. >> Yes. Exactly. One inherently can drive the other, but if you're just driving it then >> Peter: Just doing cost. >> You're not going to transform your buisiness. >> Peter: You're just going to continue to do the same or wrong things worse. >> Shaun: Exactly. >> Or wrong things cheaper. >> And that's difficult for enterprises. Because there's a certain way to do data management inherently inside in a highly structured manner, but I do think the rise of like IOT, I don't see as a market, I see it as infinite slices of prosciutto, right? (laughter) It's a very thinly sliced set of market opportunities, right? But it's forcing people to think about different use cases and how that might impact their business. >> We see those set of capabilities. >> Yup. >> Which leads to the prosciutto. >> Exactly. >> So you, and come up with a really nice sandwich. (laughter) >> It's my Italian. >> Let's keep going. >> I'm loving it. >> I'm getting a little hungry. >> You have always made a big deal out of your partnerships not being barney deals but being deep integration relationships. So you mentioned two here, Teradata and Microsoft. As the cloud becomes more prevalent, as things evolve and machine learning becomes the hot buzzword, et cetera. How have you evolved those relationships specifically in terms of the integration work that you've done? Have you kept up that engineering ethos, or? >> And that was the thing. With Microsoft, we clearly spent a lot of sweat equity on the Azure HDInsight service, but if you look at that ecosystem, they have Azure machine learning, right? They have a whole raft of services, right, that you can apply to the data when it's in the cloud, right? So how that piece integrates with the broader ecosystem of services is a lot of engineering work as well. I've always said, there's work to be done in our green box, but the other half of the work is how it plumbs into the rest. And so if you look at the AWS ecosystem, how do you optimize for S3 as a storage tier, and ephemeral workloads where HDFS is maybe a caching mechanism but it's not your primary storage, right? It brings up really interesting integration modes and how you actually bring your value out into really interesting use cases, right? So I think it's opened up a lot of areas where we can drive a lot more integration, drive the open source tech in a way that's relevant for those use cases. >> Alright, we got to go but, summit in Tokyo, is it next month? >> Yes, end of October. >> End of October. >> It's our first time, so primarily summits have been US and Europe. We had Melbourne end of August, and we have Tokyo end of October. I'll be, they're bringing the right hander out of retirement, so I'll be onstage in Tokyo. (laughing) I've usually been behind the scenes. >> Throwing the slurve? (laughter) >> Yeah, exactly. So I'm looking forward to it, it'll be exciting. >> Alright, good, and then 17, you're going to start again in the spring. >> Shaun: Yup. >> You're in Munich. >> Shaun: Yup. Munich. >> You were in Dublin last year, you're moving to Munich this year. >> Shaun: Exactly. >> Hopefully the Cube will be back, in Munich, alright? >> We love you guys, you guys do a good job. >> Let's make it happen, do good stuff in Europe, so thanks again for coming out. >> Shaun: Thanks for having me. >> Always a pleasure. Alright, keep it right there, we'll be back right after this short break. This is the Cube, we're live from New York City. ( upbeat electronic music)