>> Live from San Diego California, it's theCUBE. Covering KubeCon and CloudNativeCon. Brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Welcome back. We're at the end of three days of wall-to-wall coverage here at KubeCon CloudNativeCon 2019 in San Diego. I am Stu Miniman and my co-host for this week has been John Troyer, and we figured no better way to cap our coverage than bring on a CUBE alumni who has likely educated more people about containers and Kubernetes, you know, may be second only to the CNCF. So, Nigel Poulton now the head of content at msb.com. Nigel, pleasure to see you and thanks for coming back on the program. >> Honestly gents, the pleasure is all mine, as always. >> All right, so Nigel, first of all I'd love to get your just gestalt of the week. You know, take away, what's the energy. You know, how is was this community doing. >> Yeah, so it's the end of the week and my brain is a mixture of fried and about to explode, okay. Which i think is a good thing. That's what you want at the end of a conference, right. But I think if we can dial it back to the first day at that opening keynote, something that really grabbed me at the time and has been sort of a theme for me throughout the conference, is when they asked, can you raise your hand if this is your first KubeCon, and it's a room of 8,000 people, and I don't have the data at hand right, but I'm sat there, I've got my brother on this side, it's his first ever KubeCon, and he kind of goes like this, and then he realizes that nearly everybody around us has got their hands up, so he's kind of like, whoa yeah, I feel like I'm on the in the in-crowd now. And I think from the people that I've spoken to it seems to be that the community is maturing, the conference or the event itself is maturing, and that starts to bring in kind of a different crowd, and a new crowd. People that are not necessarily building Kubernetes or building projects in the Kubernetes ecosystem, but looking to bring it into their organizations to run their own applications. >> Yeah, no absolutely. You know, the rough number I heard was somewhere two-thirds to three-quarters of that room were new. >> Nigel: I can believe that. >> 12,000 here in attendance, right. There were 8,000 here last year. >> Nigel: Yeah. >> You think about the, you know, somebody, oh I sent somebody this year, I sent somebody different the next year, and all the new people. So, you know, Nigel, luckily that keeps you busy, because there is something I've said for a long, long, time is there is always a need for that introductory and then how do I get started and how do I get into here, and luckily the the ecosystem and all the projects and everything, somebody could pick that up in five or 10 minutes if they'd just put their mind to it, right. >> So I say this a lot of the time, that I feel like we live in the Golden Age of being able to take hold of your own career and learn a technology and make the best of what's available for you. Now we don't live in the day where we used, you know, to learn something new you would have to buy infrastructure. I mean even to learn Windows back in the day, or NetWare or Linux you'd need a couple of dusty old PCs in the corner of your office or your bedroom or something, and it was hard. Whereas now with cloud, with video training, with all the hands-on labs and stuff that are out there, with all of the sessions that you get at events like this, if you're interested in pushing your career forward, not only have you not got an excuse not to do it anymore, but the opportunities are just amazing, right. I feel like we live in such an, I feel like we're living in a exciting time for tech. >> Well Nigel, you do books, said you've done training courses, you have your platform of like a lab platform, msb.com. And one of the challenges in this space is that it is moving so fast, right. Yes, you have, anything's at your fingertips, but. >> Nigel: Yeah. >> Kubernetes changes every every quarter. Here at the show, both scale of people's deployments, but also scale of the probably number of projects, and everything has a different name. >> Nigel: Yeah. >> So, how are you, what should people be looking for? How are you changing your curriculum? What are you what are you adding to it, what are you replicating? >> Yeah, so that's super interesting. I think, right, as well, so it's a Golden Age for learning right, but if you're in the technology industry in the sort of areas that we are, right, if you don't love it and if you're not passionate about it, I almost feel like you're in the wrong industry, because you need that passion, and that sort of it's my hobby as well as my job, just to keep up. Like I feel like I spend an unhealthy amount of time in the Cloud Native ecosystem and just trying to keep track of everything that's going on. And all that time that I spend in, I still feel like I'm playing catch-up all the time. So I think you have to adjust your mentality. Like if you thought that you could learn something, a technology or whatever, and be comfortable for five years in your role, then you really need to adjust that. Like just an example, right. So I write, I offer a book as well, and I would love nothing better than to write that book, stick it on a shelf on Amazon and what-have-you and let it be valid for five years. I would love that because it's hard work, but I can't so like I do a six monthly update, but that applies to way more than that. So for your career, you know, if you want to, it sounds cheesy, if you want to rock it in your career, you have got to keep yourself up to date. And it's a race, but I do think that the kind of things were doing with tech now, they're fun things, right. >> Yeah, a little scary, because while we're at this show I hope you kept up with all the Amazon announcements, the Google announcements. >> Nigel: Yeah. >> And everything going, because it is it is non-stop. >> Nigel: It is. >> Out there. Nigel, we last had you on theCUBE two years ago at this show, and at every show for a bunch of shows it seemed like there was a project or a category du jour. >> Nigel: Yeah. >> I don't know that I quite got that this year. There were some really cool things at edge computing. There was the observability, something we spent a bunch of time talking on. But we'd love to just kind of throw it out there as to what you're seeing in the ecosystem, the landscape, some of the areas that are interesting. >> Nigel: Yeah. >> Important, and what's growing, what's not. >> Okay, so if I can take the event first off, right, so KubeCon itself. Loads of new people, okay, and when I talk to them I'm getting three answers from them. Like number one, they're like, some people like, I just love it, you know, which is great, and I've loved it and it's an amazing event. Other people are like kind of over awed by it, the size. So I don't know, maybe we should send them to re:Invent and then come back here and then they'll be like, oh yeah, it's not so bad. But the second thing is that some of the sessions are going over the first timers heads. So I'm hoping, and I'm sure it will, that going forward in Amsterdam and Boston next year that we'll start to be able to pitch parts of the conference to that new user base. So that was kind of a theme from speaking to people at the event from me. But a couple of things from the ecosystem, like we talked about service mesh, right, two years ago, and it felt like it was a bit of a buzzword, but everyone was talking about it and it was a real theme, and I don't get that at this conference, but what I do feel from the community in general is that uptake and adoption is actually starting to happen now, and thanks a lot to, well look, Linkerd pretty easy these days, STO is making great strides to being easier to deploy, but I also think that the cloud providers, those hosted cloud providers, really stepping up to the plate, like they did with hosted Kubernetes, you know when it was hard to get Kubernetes for your environment. We're seeing a similar thing with the service mesh. You can spin something up in GKE, Kubernetes cluster, click the box, and I'll have a service mesh, thank you very much. >> Well, it's funny. I think back to Austin, when I talk to the average customer in the show floor and said, "What are you doing?" they were rolling their own. Picking all of the pieces and doing it. When I talk to the average customer here, is, I'm using managed services. >> Nigel: Yeah. >> Seems to have matured a lot. Of course, some of the manage public cloud services were brand new or a couple months there. Is that's a general direction you see things going? >> So, yes, but I almost wonder if it will be like cloud in general, right, where there was a big move to the cloud. And I understand why people will want to do hosted Kubernetes and things, 'cause it's easy and you know it gets you. I'm careful that when I use the term production grade, because I know it means different things to different people, but you get something that we can at least loosely turn production grade. >> Yeah, and actually just to be clear, we had a lot of discussions about on-premises, so I guess it's more the managed service rather than the, I'm going to roll all the pieces myself. >> Yeah, but I wonder will we start, and because of price and maybe the ability to tweak the cluster towards your needs and things, whether we might see people taking their first steps on a managed service or a hosted Kubernetes, and then as they scale up then they start to say, well, tell you what we'll start rolling our own, because we're better at doing this now, and then run like, you know, you still have your hosted stuff, but you have some stuff on premises as well, and then we move towards something that's a bit more hybrid. I don't know, but I just wonder if that will become a trend. >> Well Nigel, I mean it's been a busy week. You started off with workshops. I don't know, what did you miss? What's the first, when you go home, back to England, are you going to, and you pop open your browser and start looking at all the session videos and stuff, I don't know, what didn't you get a chance to do here this week? >> So I was kind of, for me it's been the busiest KubeCon I've had and it's robbed me of a lot of sessions, right, and when I remember when I looked at the catalog at the beginning it was like, you know it's one of those conferences where almost every slot there's three things that I want to go to, which is a sign of a good conference. I'm quite interested at the moment in K3s. I actually haven't touched it for a long time, but outside of KubeCon I have had a lot of people talk to me about that, so I will go home and I will hunt down, right, what are the K3s sessions to try and get myself back up to speed, 'cause I know there are other projects that are similar right, but I find it quite fascinating in that it's one of those projects where it started out with like this goal of we'll be for the edge, right, or for IOT or something, and the community are like, we really like it, and actually I want to use it for loads of other things. You have no idea whether it will go on to be like a roaring success, but it. I don't know, so often you have it where a project isn't planned to be something. >> Announcer: Good afternoon attendees. Breakout sessions will begin in 10 minutes. >> But it naturally in the community. >> Announcer: Session locations are listed. >> Take it on and say. >> Announcer: On the noted schedule. >> We're going to do something with it. >> Announcer: On digital signage throughout the venue. >> That wasn't originally planned, yeah. So I'll be looking up K3s as my first thing when I go home, but it is the first thing on a long list, right. >> All right. Nigel, tell us a little bit about, you know, latest things you're doing, msb.com. I know you had your book signing for your book here, had huge lines here. >> Yeah. >> Great to see. So, tell us about what you're doing overall. >> Thank you, yeah. So, I've got a couple of books and I've got a bunch of video training courses out there, and I'm super fortunate that I've reached a lot of people, but a real common theme when I talk to people are like, look, I love your book, I love your video courses, whatever, how do I take that next step, and the answer was always, look, get your hands on as much as possible, okay. And I would send people to like Minikube and to play with Docker or play with Kubernetes and various other solutions, but none of them really seem to be like, a real something that looked and smelled and tasted like production. So I'm working with a start-up at the moment, msb.com, where we have curated learning content. Everybody gets their own fully functioning private free node Kubernetes cluster. Ingress will work, internet-facing load balancers will all work on it, and the idea is that instead of having like a single node development environment on your laptop, which is fine, but you know, you can't really play with scheduling and things like that, then msb.com takes that sort of learning journey to the next level because it's it's a real working cluster, plus we've got this amazing visual dashboard so that when you're deploying stuff and scaling and rolling updates you see it all happening in the browser. And for me as an educator, right, it's sometimes hard for people to connect the dots when you're reading a book or, and I spend hours on like PowerPoint animations and stuff, whereas now in this browser to augment like reading a book, and to augment taking a training video, you can go and get your hands on and have this amazing sort of rich visual experience that really helps you like, sort of, oh I get it now, yeah. >> All right, so Nigel, final question I have for you. I've known you back when we were just a couple of infrastructure guys. You've done phenomenal things. >> Nigel: The glory days. >> With kind of the wave of containers, you're a Docker captain. You know, really well known in the Kubernetes. When you reflect back on something, on kind of this journey we've been on, you look at 12,000 people here, you know Docker has some recent news here, so give us a reflection back on that this journey the whole industry's on. >> Yeah, so I had breakfast with a guy this morning who I wrote my first ever public blog with. He had a blog site and he loaned me some space on his blog site 'cause I didn't even know how to build a blog at the time, and it was a storage blog, yeah, we're talking about EMC and HDS and all that kind of stuff, and I'm having breakfast with him, 14 I think years later in San Diego at KubeCon. And I think, and I don't know if this really answers your question, but I feel like that Kubernetes is almost so, if ubiquitous is the right word or it's so pervasive, and it's so all-encompassing almost, that it is bringing almost the entire community. I don't want to get too carried away with saying this, right, but it is bringing people from all different areas to like a common platform for want of a better term, right. I mean we were infrastructure guys, yourself as well John, and here we are at an event that as a community and as a technology I think it's just, it's changing the world, but it's also bringing things almost under one hood. So I would say anybody, like whatever you're doing, do all roads lead to Kubernetes at the moment, I don't know. >> Yeah, well we know software can actually be a unifying factor. Best term I've heard is Kubernetes is looking to be that universal back plain. >> Nigel: Yeah. >> and therefore, both you know, southbound to the infrastructure, northbound to the application. Nigel Poulton congratulations on the progress. Definitely, everybody makes sure to check out his training online, and thank you for helping us to wrap up our three days of coverage here. For John Troyer, I am Stu Miniman. TheCUBE will be at KubeCon 2020 in both Amsterdam and Boston. we will be at lots of other shows. Be sure to check out thecube.net. Please reach out if you have any questions. We are looking for more people to help support our growing coverage in the cloud native space, so thank you so much for the community, thank you to all of our guests, thank you to the CNCF and our sponsors that make this coverage possible, and thank you to you our audience for watching theCUBE. (upbeat music)

>> From the Silicon Angle Media office in Boston Massachusetts, it's theCUBE. Now here's your host, Dave Vellante. (upbeat music) >> Hello everybody, this is Dave Vallante with Stu Miniman and we're going to take a look back at ten years of theCUBE at VMworld and look forward to see what's coming next. So, as I say, this is theCUBE's 10th year at VMworld, that's VMworld, of course 2019. And Stu, if you think about the VMware of 2010, when we first started, it's a dramatically different VMware today. Let's look back at 2010. Paul Maritz was running VMware, he set forth the vision of the software mainframe last decade, well, what does that mean, software mainframe? Highly integrated hardware and software that can run any workload, any application. That is the gauntlet that Tucci and Maritz laid down. A lot of people were skeptical. Fast forward 10 years, they've actually achieved that, I mean, essentially, it is the standard operating system, if you will, in the data center, but there's a lot more to the story. But you remember, at the time, Stu, it was a very complex environment. When something went wrong, you needed guys with lab coats to come in a figure out, you know, what was going on, the I/O blender problem, storage was a real bottleneck. So let's talk about that. >> Yeah, Dave, so much. First of all, hard to believe, 10 years, you know, think back to 2010, it was my first time being at VMworld, even though I started working with VMware back in 2002 when it was like, you know, 100, 150 person company. Remember when vMotion first launched. But that first show that we went to, Dave, was in San Francisco, and most people didn't know theCUBE, heck, we were still figuring out exactly what theCUBE will be, and we brought in a bunch of our friends that were doing the CloudCamps in Silicon Valley, and we were talking about cloud. And there was this gap that we saw between, as you said, the challenges we were solving with VMware, which was fixing infrastructure, storage and networking had been broken, and how were we going to make sure that that worked in a virtual environment even better? But there were the early thought leaders that were talking about that future of cloud computing, which, today in 2019, looks like we had a good prediction. And, of course, where VMware is today, we're talking all about cloud. So, so many different eras and pieces and research that we did, you know, hundreds and hundreds of interviews that we've done at that show, it's definitely been one of our flagship shows and one of our favorite for guests and ecosystems and so much that we got to dig into at that event. >> So Tod Nielsen, who was the President and probably COO at the time, talked about the ecosystem. For every dollar spent on a VMware license, $15 was spent on the ecosystem. VMware was a very, even though they were owned by EMC, they were very, sort of, neutral to the ecosystem. You had what we called the storage cartel. It was certainly EMC, you know, but NetApp was right there, IBM, HP, you know, Dell had purchased EqualLogic, HDS was kind of there as well. These companies were the first to get the APIs, you remember, the VASA VAAI. So, we pushed VMware at the time, saying, "Look, you guys got a storage problem." And they said, "Well, we don't have a lot of resources, "we're going to let the ecosystem solve the problem, "here's an API, you guys figure it out." Which they largely did, but it took a long time. The other big thing you had in that 2010 timeframe was storage consolidation. You had the bidding war between Dell and HP, which, ultimately, HP, under Donatelli's leadership, won that bidding war and acquired 3PAR >> Bought 3PAR >> for 2.4, 2.5 billion, it forced Dell to buy Compellent. Subsequently, Isilon was acquired, Data Domain was acquired by EMC. So you had this consolidation of the early 2000s storage startups and then, still, storage was a major problem back then. But the big sea change was, two things happened in 2012. Pat Gelsinger took over as CEO, and VMware acquired Nicira, beat Cisco to the punch. Why did that change everything? >> Yeah, Dave, we talked a lot about storage, and how, you know, the ecosystem was changing this. Nicira, we knew it was a big deal. When I, you know, I talked to my friends that were deep in networking and I talked with Nicira and was majorly impressed with what they were doing. But this heterogeneous, and what now is the multi-cloud environment, networking needs to play a critical role. You see, you know, Cisco has clearly targeted that environment and Nicira had some really smart people and some really fundamental technology underneath that would allow networking to go just beyond the virtual machine where it was before, the vSwitch. So, you know, that expansion, and actually, it took a little while for, you know, the Nicira acquisition to run into NSX and that product to gain maturity, and to gain adoption, but as Pat Gelsinger has said more recently, it is one of the key drivers for VMware, getting them beyond just the hypervisor itself. So, so much is happening, I mean, Dave, I look at the swings as, you know, you said, VMware didn't have enough resources, they were going to let the ecosystem do it. In the early days, it was, I chose a server provider, and, oh yeah, VMware kind of plays in it. So VMware really grew how much control and how much power they had in buying decisions, and we're going through more of that change now, as to, as they're partnering we're going to talk about AWS and Microsoft and Google as those pieces. And Pat driving that ship. The analogy we gave is, could Pat do for VMware what Intel had done for a long time, which is, you have a big ecosystem, and you slowly start eating away at some of that other functionality without alienating that ecosystem. And to Pat's credit, it's actually something that he's done quite well. There's been some ebbs and flows, there's pushback in the community. Those that remember things like the "vTax," when they rolled that out. You know, there's certain features that the rolled into the hypervisor that have had parts of the ecosystem gripe a little bit, but for the most part, VMware is still playing well with the ecosystem, even though, after the Dell acquisition of EMC, you know, we'll talk about this some more, that relationship between Dell and VMware is tighter than it ever was in the EMC days. >> So that led to the Software-Defined Data Center, which was the big, sort of, vision. VMware wanted to do to storage and networking what it had done to compute. And this started to set up the tension between with VMware and Cisco, which, you know, lives on today. The other big mega trend, of course, was flash storage, which was coming into play. In many ways, that whole API gymnastics was a Band-Aid. But the other big piece if it is Pat Gelsinger was much more willing to integrate, you know, some of the EMC technologies, and now Dell technologies, into the VMware sort of stack. >> Right, so Dave, you talked about all of those APIs, Vvols was a huge multi-year initiative that VMware worked on and all of the big storage players were talking about how that would allow them to deeply integrate and make it virtualization-aware storage your so tense we come out on their own and try to do that. But if you look at it, VVols was also what enabled VMware to do vSAN, and that is a little bit of how they can try to erode in some of the storage piece, because vSAN today has the most customers in the hyperconverged infrastructure space, and is keeping to grow, but they still have those storage partnerships. It didn't eliminate it, but it definitely adds some tension. >> Well it is important, because under EMC's ownership it was sort of a let 1,000 flowers bloom sort of strategy, and today you see Jeff Clarke coming in and consolidating the portfolios, saying, "Look, let's let VMware go hard with vSAN." So you're seeing a different type of governance structure, we'll talk about that. 2013 was a big year. That's the year they brought in Sanjay Poonen, they did the AirWatch acquisition, they took on what the industry called VDI, what VMware called EUC, End-User Computing. Citrix was the dominant player in that space, VMware was fumbling, frankly. Sanjay Poonen came in, the AirWatch acquisition, now, VMware is a leader in that space, so that was big. The other big thing in 2013 was, you know, the famous comment by Carl Eschenbach about, you know, if we lose to the book seller, we'll all lose. VMware came out with it's cloud strategy, vCloud Air. I was there with the Wall Street analyst that day listening to Pat explain that and we were talking afterwards to a number of the Wall Street analysts saying, "This really doesn't make a lot of sense." And then they sort of retreated on that, saying that it was going to be an accelerant, and it just was basically a failed cloud strategy. >> And Dave, that 2013 is also when they spun out Cloud Foundry and founded Pivital. So, you know, this is where they took some of the pieces from EMC, the Greenplum, and they took some of the pieces from VMware, Spring and the Cloud Foundation, and put those together. As we speak right now, there was just an SEC Filing that VMware might suck them back in. Where I look at that, back in 2013, there was a huge gap between what VMware was doing on the infrastructure side and what Cloud Foundry was doing on the application modernization standpoint, they had bought the Pivotal Labs piece to help people understand new programming models and everything along those lines. Today, in 2019, if you look at where VMware is going, the changes happening in containerization, the changes happening from the application down, they need to come together. The Achilles heel that I have seen from VMware for a long time is that VMware doesn't have enough a tie to or help build the applications. Microsoft owns the applications, Oracle owns the applications. You know, there are all the ISVs that own the applications, and Pivotal, if they bring that back into VMware it can help, but it made sense at the time to kind of spin that out because it wasn't synergies between them. >> It was what I called at the time a bunch of misfit toys. And so it was largely David Goulden's engineering of what they called The Federation. And now you're seeing some more engineering, financial engineering, of having VMware essentially buy another, you know, Dell Silver Lake asset, which, you know, drove the stock price up 77% in a day that the Dow dropped 800 points. So I guess that works, kind of funny money. The other big trend sort of in that mid-part of this decade, hyperconverged, you know, really hit. Nutanix, who was at one point a strong partner of both VMware and Dell, was sort of hitting its groove swing. Fast forward to 2019, different situation, Nutanix really doesn't have a presence there. You know, people are looking at going beyond hyperconverged. So there's sort of the VMware ecosystem, sort of friendly posture has changed, they point fingers at each other. VMware says, "Well, it's Nutanix's fault." Nutanix will say it's VMware's fault. >> Right, so Dave, I pointed out, the Achilles heel for VMware might be that they don't have the closest tie to the application, but their greatest strength is, really, they are really the data center operating system, if you will. When we wrote out our research on Server SAN was before vSAN had gotten launched. It was where Nutanix, Scale Computing, SimpliVity, you know, Pivot3, and a few others were early in that space, but we stated in our research, if Microsoft and VMware get serious about that space, they can dominate. And we've seen, VMware came in strong, they do work with their partnerships. Of course, Dell, with the VxRail is their largest solution, but all of the other server providers, you know, have offerings and can put those together. And Microsoft, just last year, they kind of rebranded some of the Azure Stack as HCI and they're going strong in that space. So, absolutely, you know, strong presence in the data center platform, and that's what they're extending into their hybrid and multi-cloud offering, the VMware Cloud Solutions. >> So I want to get to some of the trends today, but just real quick, let's go through some of this. So 2015 was the big announcement in the fall where Dell was acquiring EMC, so we entered, really, the Dell era of VMware ownership in 2016. And the other piece that happened, really 2016 in the fall, but it went GA 2017, was the announcement AWS and VMware as the preferred partnership. Yes, AWS had a partnership with IBM, they've subsequently >> VMware had a partnership >> Yeah, sorry, VMware has a partnership with IBM for their cloud, subsequently VMware has done deals with Google and Microsoft, so there's, we now have entered the multi-cloud hybrid world. VMware capitulated on cloud, smart move, cleaned up its cloud strategy, cleaned that AirWatch mess. AWS also capitulated on hybrid. It's a term that they would never use, they don't use it necessarily a lot today, but they recognize that On Prem is a viable portion of the marketplace. And so now we've entered this new era of cloud, hybrid cloud, containers is the other big trend. People said, "Containers are going to really hurt VMware." You know, the jury's still out on that, VMware sort of pushes back on that. >> And Dave, just to put a point on that, you know, everybody, including us, spent a lot of time looking at this VMware Cloud on AWS partnership, and what does it mean, especially, to the parent, you know, Dell? How do they make that environment? And you've pointed out, Dave, that while VMware gets in those environments and gives themselves a very strong cloud strategy, AWS is the key partner, but of course, as you said, Microsoft Azure, Google Cloud, and all the server providers, we have a number of them including CenturyLink and Rackspace that they're partnering with, but we have to wait a little while before Amazon, when they announced their outpost solutions, VMware is a critical software piece, and you've got two flavors of the hardware. You can run the full AWS Stack, just like what they're running in their data center, but the alternative, of course, is VMware software running on Dell hardware. And we think that if VMware hadn't come in with a strong position with Amazon and their 600,000 customers, we're not sure that Amazon would have said, "Oh yeah, hey, you can run that same software stack "that you're running, but run some different hardware." So that's a good place for Dell to get in the environment, it helps kind of close out that story of VMware, Dell, and AWS and how the pieces fit together. >> Yeah, well so, by the way, earlier this week I privately mentioned to a Dell executive that one of the things I thought they should do was fold Pivotal into VMware. By the way, I think they should go further. I think they should look at RSA and Dell Boomi and SecureWorks, make VMware the mothership of software, and then really tie in Dell's hardware to VMware. That seems to me, Stu, the direction that they're going to try to gain an advantage on the balance of the ecosystem. I think VMware now is in a position of strength with, what, 5 or 600,000 customers. It feels like it's less ecosystem friendly than it used to be. >> Yeah, Dave, there's no doubt about it. HPE and IBM, who were two of the main companies that helped with VMware's ascendancy, do a lot of other things beyond VMware. Of course, IBM bought Red Hat, it is a key counterbalance to what VMware is doing in the multi-cloud. And Dave, to your point, absolutely, if you look at Dell's cloud strategy, they're number one offering is VMware, VMware cloud on Dell. Dell as the project dimension piece. All of these pieces do line up. I'll say, some of those pieces, absolutely, I would say, make sense to kind of pull in and shell together. I know one of the reasons they keep the security pieces at arm's length is just, you know, when something goes wrong in the security space, and it's not of the question of if, it's a question of when, they do have that arm's length to be able to keep that out and be able to remediate a little bit when something happens. >> So let's look at some of the things that we're following today. I think one of the big ones is, how will containers effect customer spending on VMware? We know people are concerned about the vTax. We also know that they're concerned about lock-in. And so, containers are this major force. Can VMware make containers a tailwind, or is it a headwind for them? >> So you look at all the acquisitions that they've made lately, Dave, CloudHealth is, from a management standpoint, in the public cloud. Heptio and Bitnami, targeting that cloud native space. Pair that with Cloud Foundry and you see, VMware and Pivotal together trying to go all-in on Kubernetes. So those 600,000 customers, VMware wants to be the group that educates you on containerization, Kubernetes, you know, how to build these new environments. For, you know, a lot of customers, it's attractive for them to just stay. "I have a relationship, "I have an enterprise licensing agreement, "I'm going to stay along with that." The question I would have is, if I want to do something in a modern way, is VMware really the best partner to choose from? Do they have the cost structure? A lot of these environments set up, you know, it's open source base, or I can work with my public cloud providers there, so why would I partner with VMware? Sure, they have a lot of smart people and they have expertise and we have a relationship, but what differentiates VMware, and is it worth paying for that licensing that they have, or will I look at alternatives? But as VMware grows their hybrid and multi-cloud deployments they absolutely are on the short list of, you know, strategic partners for most customers. >> The other big thing that we're watching is multi-cloud. I have said over and over that multi-cloud has largely been a symptom of multi-vendor. It's not necessarily, to date anyway, been a strategy of customers. Having said that, issues around security, governance, compliance have forced organizations and boards to say, "You know what, we need IT more involved, "let's make multi-cloud part of our strategy, "not only for governance and compliance "and making sure it adheres to the corporate edicts, "but also to put the right workload on the right cloud." So having some kind of strategy there is important. Who are the players there? Obviously VMware, I would say, right now, is the favorite because it's coming from a position of strength in the data center. Microsoft with it's software state, Cisco coming at it from a standpoint of network strength. Google, with Anthos, that announcement earlier this year, and, of course, Red Hat with IBM. Who's the company that I didn't mention in that list? >> Well, of course, you can't talk about cloud, Dave, without talking about AWS. So, as you stated before, they don't really want to talk about hybrid, hey, come on, multi-cloud, why would you do this? But any customer that has a multi-cloud environment, they've got AWS. And the VMware-AWS partnership is really interesting to watch. It will be, you know, where will Amazon grow in this environment as they find their customers are using multiple solutions? Amazon has lots of offerings to allow you leverage Kubernetes, but, for the most part, the messaging is still, "We are the best place for you, "if you do everything on us, "you're going to get better pricing "and all of these environments." But as you've said, Dave, we never get down to that homogeneous, you know, one vendor solution. It tends to be, you know, IT has always been this heterogeneous mess and you have different groups that purchase different things for different reasons, and we have not seen, yet, public cloud solving that for a lot of customers. If anything we often have many more silos in the clouds than we had in the data center before. >> Okay. Another big story that we're following, big trend, is the battle for networking. NSX, the software networking component, and then Cisco, who's got a combination of, obviously, hardware and software with ACI. You know, Stu, I got to say, Cisco a very impressive company. You know, 60+% market share, being able to hold that share for a long time. I've seen a lot of companies try to go up against Cisco. You know, the industry's littered with failures. It feels, however, like NSX is a disruptive force that's very hard for Cisco to deal with in a number of dimensions. We talked about multi-cloud, but networking in general. Cisco's still a major player, still, you know, owns the hardware infrastructure, obviously layering in its own software-defined strategy. But that seems to be a source of tension between the two companies. What's the customer perspective? >> Yeah, so first of all, Dave, Cisco, from a hardware perspective, is still going strong. There are some big competitors. Arista has been doing quite well into getting in, especially, a high performance, high speed environments, you know, Jayshree Ullal and that team, you know, very impressive public company that's doing quite well. >> Service providers that do really well there. >> Absolutely, but, absolutely, software is eating the world and it is impacting networking. Even when you look at Cisco's overall strategy, it is in the future. Cisco is not a networking company, they are a software company. The whole DevNet, you know, group that they have there is helping customers modernize, what we were talking about with Pivotal. Cisco is going there and helping customers create those new environments. But from a customer standpoint, they want simplicity. If my VMware is a big piece of my environment, I've probably started using NSX, NSX-T, some of these environments. As I go to my service providers, as I go to multi-cloud, that NSX piece inside my VMware cloud foundation starts to grow. I remember, Dave, a few years back, you know, Pat Gelsinger got up on a stage and was like, "This is the biggest collection of network administrators that we've ever seen!" And everybody's looking around and they're like, "Where? "We're virtualization people. "Oh, wait, just because we've got vNICs and vSwitches "and things like that." It still is a gap between kind of a hardcore networking people and the software state. But just like we see on storage, Dave, it's not like vSAN, despite it's thousands and thousands of customers, it is not the dominant player in storage. It's a big player, it's a great revenue stream, and it is expanding VMware beyond their core vSphere solutions. >> Back to Cisco real quickly. One of the things I'm very impressed with Cisco is the way in which they've developed infrastructures. Code with the DevNet group, how CCIEs are learning Python, and that's a very powerful sort of trend to watch. The other thing we're watching is VMware-AWS. How will it affect spending, you know, near-term, mid-term, long-term? Clearly it's been a momentum, you know, tailwind, for VMware today, but the questions remains, long-term, where will customers place their bets? Where will the spending be? We know that cloud is growing dramatically faster than On Prem, but it appears, at least in the near- to mid-term, for one, two, maybe three more cycles, maybe indefinitely, that the VMware-AWS relationship has been a real positive for VMware. >> Yeah, Dave, I think you stated it really well. When I talked to customers, they were a bit frozen a couple of years ago. "Ah, I know I need to do more in cloud, "but I have this environment, what do I do? "Do I stay with VMware, do I have to make a big change." And what VMware did, is they really opened things up and said, "Look, no, you can embrace cloud, and we're there for you. "We will be there to help be that bridge to the future, "if you will, so take your VMware environment, "do VMware cloud in lots of places, "and we will enable that." What we know today, the stat that we hear all the time, the old 80/20 we used to talk about was 80% keeping the lights on, now the 80% we hear about is, there's only 20% of workloads that are in public cloud today. It doesn't mean that that other 80% is going to flip overnight, but if you look over the next five to ten years, it could be a flip from 80/20 to 20/80. And as that shift happens, how much of that estate will stay under VMware licenses? Because the day after AWS made the announcement of VMware cloud on AWS, they offered some migration services. So if you just want to go on natively on the public cloud, you can do that. And Microsoft, Google, everybody has migration services, so use VMware for what I need to, but I might go more native cloud for some of those other environments. So we know it is going to continue to be a mix. Multi-cloud is what customers are doing today, and multi- and hybrid-cloud is what customers will be doing five years from now. >> The other big question we're watching is Outposts. Will VMware and Outposts get a larger share of wallet as a result of that partnership at the expense of other vendors? And so, remains to be seen, Outposts grabbed a lot of attention, that whole notion of same control plane, same hardware, same software, same data plane On Prem as in the Data Center, kind of like Oracle's same-same approach, but it's seemingly a logical one. Others are responding. Your thoughts on whether or not these two companies will dominate or the industry will respond or an equilibrium. >> Right, so first of all, right, that full same-same full stack has been something we've been talking about now, feels like for 10 years, Dave, with Oracle, IBM had a strategy on that, and you see that, but one of the things with VMware has strong strength. What they have over two decades of experiences on is making sure that I can have a software stack that can actually live in heterogeneous environments. So in the future, if we talk about if Kubernetes allows me to live in a multi-cloud environment, VMware might be able to give me some flexibility so that I can move from one hardware stack to another as I move from data centers to service providers to public clouds. So, absolutely, you know, one to watch. And VMware is smart. Amazon might be their number one partner, but they're lining up everywhere. When you see Sanjay Poonen up on stage with Thomas Kurian at Google Cloud talking about how Anthos in your data center very much requires VMware. You see Sachi Nodella up on stage talking about these kind of VMware partnerships. VMware is going to make sure that they live in all of these environments, just like they lived on all of the servers in the data center in the past. >> The other last two pieces that I want to touch on, and they're related is, as a result of Dell's ownership of VMware, are customers going to spend more with Dell? And it's clear that Dell is architecting a very tight relationship. You can see, first of all, Michael Dell putting Jeff Clarke in charge of everything Dell was brilliant, because, in a way, you know, Pat was kind of elevated as this superstar. And Michael Dell is the founder, and he's the leader of the company. So basically what he's created is this team of rivals. Now, you know, Jeff and Pat, they've worked together for decades, but very interesting. We saw them up on stage together, you know, last year, well I guess at Dell Technologies World, it was kind of awkward, but so, I love it. I love that tension of, It's very clear to me that Dell wants to integrate more tightly with VMware. It's the clear strategy, and they don't really care at this point if it's at the expense of the ecosystem. Let the ecosystem figure it out themselves. So that's one thing we're watching. Related to that is long-term, are customers going to spend more of their VMware dollars in the public cloud? Come back to Dell for a second. To me, AWS is by far the number one competitor of Dell, you know, that shift to the cloud. Clearly they've got other competitors, you know, NetApp, Huawei, you know, on and on and on, but AWS is the big one. How will cloud spending effect both Dell and AWS long-term? The numbers right now suggest that cloud's going to keep growing, $35, $40 billion run-rate company growing at 40% a year, whereas On Prem stuff's growing, you know, at best, single digits. So that trend really does favor the cloud guys. I talked to a Gartner analyst who tracks all this stuff. I said, "Can AWS continue to grow? It's so big." He said, "There's no reason, they can't stop. "The market's enormous." I tend to agree, what are your thoughts? >> Yeah, first of all, on the AWS, absolutely, I agree, Dave. They are still, if you look at the overall IT spend, AWS is still a small piece. They have, that lever that they have and the influence they have on the marketplace greatly outweighs the, you know, $30, $31 billion that they're at today, and absolutely they can keep growing. The one point, I think, what we've seen, the best success that Dell is having, it is the Dell and VMware really coming together, product development, go to market, the field is tightly, tightly, tightly alligned. The VxRail was the first real big push, and if they can do the same thing with the vCloud foundation, you know, VMware cloud on Dell hardware, that could be a real tailwind for Dell to try to grow faster as an infrastructure company, to grow more like the software companies or even the cloud companies will. Because we know, when we've run the numbers, Dave, private cloud is going to get a lot of dollars, even as public cloud continues its growth. >> I think the answer comes down to a couple things. Because right now we know that 80% of the spend and stall base is On Prem, 20% in the cloud. We're entering now the cloud 2.0, which introduces hybrid-cloud, On Prem, you know, connecting to clouds, multi-cloud, Kubernetes. So what it comes down to, to me Stu, is to what degree can Dell, VMware, and the ecosystem create that cloud experience in a hybrid world, number one? And number two, how will they be able to compete from a cost-structure standpoint? Dell's cost-structure is better than anybody else's in the On Prem world. I would argue that AWS's cost-structure is better, you know, relative to Dell, but remains to be seen. But really those two things, the cloud experience and the cost-structure, can they hold on, and how long can they hold on to that 80%? >> All right, so Dave here's the question I have for you. What are we talking about when we're talking about Dell plus VMware and even add in Pivotal? It's primarily hardware plus software. Who's the biggest in that multi-cloud space? It's IBM plus Red Hat, which you've stated emphatically, "This is a services play, and IBM has, you know, "just got, you know, services in their DNA, "and that could help supercharge where Red Hat's going "and the modernization." So is that a danger for Dell? If they bring in Pivotal, do they need to really ramp up that services? How do they do that? >> Yeah, I don't think it's a zero sum game, but I also don't think there's, it's five winners. I think that the leader, VMware right now would be my favorite, I think it's going to do very well. I think Red Hat has got, you know, a lot of good market momentum, I think they've got a captive install base, you know, with IBM and its large outsourcing business, and I think they can do pretty well, and I think number three could do okay. I think the other guys struggle. But it's so early, right now, in the hybrid-cloud world and the multi-cloud world, that if I were any one of those five I'd be going hard after it. We know Google's got the dollars, we know Microsoft has the software state, so I can see Microsoft actually doing quite well in that business, and could emerge as the, maybe they're not a long-shot right now, but they could be a, you know, three to one, four to one leader that comes out as the favorite. So, all right, we got to go. Stu, thanks very much for your insights. And thank you for watching and listening. We will be at VMworld 2019. Three days of coverage on theCUBE. Thanks for watching everybody, we'll see you next time. (upbeat music)

>> Announcer: Live, from Orlando, Florida, it's TheCUBE, covering PentahoWorld 2017. Brought to you by Hitachi Vantara. >> Welcome back to sunny Orlando everybody. This is TheCUBE, the leader in live tech coverage. My name is Dave Vellante and this is PentahoWorld, #PWorld17. Don DeLoach here, he's the co-chair of the midwest IoT council. Thanks so much for coming on TheCUBE. >> Good to be here. >> So you've just written a new book. I got it right in my hot off the presses in my hands. The Future of IoT, leveraging the shift to a data-centric world. Can you see that okay? Alright, great, how's that, you got that? Well congratulations on getting the book done. >> Thanks. >> It's like, the closest a male can come to having a baby, I guess. But, so, it's fantastic. Let's start with sort of the premise of the book. What, why'd you write it? >> Sure, I'll give you the short version, 'cause that in and of itself could go on forever. I'm a data guy by background. And for the last five or six years, I've really been passionate about IoT. And the two converged with a focus on data, but it was kind of ahead of where most people in IoT were, because they were mostly focused on sensor technology and communications, and to a limited extent, the workflow. So I kind of developed this thesis around where I thought the market was going to go. And I would have this conversation over and over and over, but it wasn't really sticking and so I decided maybe I should write a book to talk about it and it took me forever to write the book 'cause fundamentally I didn't know what I was doing. Fortunately, I was able to eventually bring on a couple of co-authors and collectively we were able to get the book written and we published it in May of this year. >> And give us the premise, how would you summarize? >> So the central thesis of the book is that the market is going to shift from a focus on IoT enabled products like a smart refrigerator or a low-fat fryer or a turbine in a factory or a power plant or whatever. It's going to shift from the IoT enabled products to the IoT enabled enterprise. If you look at the Harvard Business Review article that Jim Heppelmann and Michael Porter did in 2014, they talked about the progression from products to smart products to smart, connected products, to product systems, to system of systems. We've largely been focused on smart, connected products, or as I would call IoT enabled products. And most of the technology vendors have focused their efforts on helping the lighting vendor or the refrigerator vendor or whatever IoT enable their product. But when that moves to mass adoption of IoT, if you're the CIO or the CEO of SeaLand or Disney or Walmart or whatever, you're not going to want to be a company that has 100,000 IoT enabled products. You're going to want to be an IoT enabled company. And the difference is really all around data primacy and how that data is treated. So, right now, most of the data goes from the IoT enabled product to the product provider. And they tell you what data you can get. But that, if you look at the progression, it's almost mathematically impossible that that is sustainable because company, organizations are going to want to take my, like let's just say we're talking about a fast food restaurant. They're going to want to take the data from the low-fat fryer and the data from the refrigerator or the shake machine or the lighting system or whatever, and they're going to want to look at it in the context of the other data. And they're going to also want to combine it with their point-of-sale or crew scheduling, or inventory and then if they're smart, they'll start to even pull in external data, like pedestrian traffic or street traffic or microweather or whatever, and they'll create a much richer signature. And then, it comes down to governance, where I want to create this enriched data set, and then propagate it to the right constituent in the right time in the right way. So you still give the product provider back the data that they want, and there's nothing that precludes you from doing that. And you give the low-fat fryer provider the data that they want, but you give your regional and corporate offices a different view of the same data, and you give the FDA or your supply chain partner, it's still the same atomic data, but what you're doing is you're separating the creation of the data from the consumption of the data, and that's where you gain maximum leverage, and that's really the thesis of the book. >> It's data, great summary by the way, so it's data in context, and the context of the low-fat fryer is going to be different than the workflow within that retail operation. >> Yeah, that's right and again, this is where, the product providers have initially kind of pushed back because they feel like they have stickiness and loyalty that's bred out of that link. But, first of all, that's going to change. So if you're Walmart or a major concern and you say, "I'm going to do a lighting RFP," and there's 10 vendors that say, "Hey, we want to compete for this," and six of 'em will allow Walmart to control the data, and four say, "No, we have to control the data," their list just went to six. They're just not going to put up with that. >> Dave: Period, the end, absolutely. >> That's right. So if the product providers are smart, they're going to get ahead of this and say, "Look, I get where the market's going. "We're going to need to give you control of the data, "but I'm going to ask for a contract that says "I'm going to get the data I'm already getting, "'cause I need to get that, and you want me to get that. "But number two, I'm going to recognize that "they can give, Walmart can give me my data back, "but enrich it and contextualize it "so I get better data back." So everybody can win, but it's all about the right architecture. >> Well and the product guys going to have the Trojan horse strategy of getting in when nobody was really looking. >> Don: That's right. >> And okay, so they've got there. Do you envision, Don, a point at which the Walmart might say, "No, that's our data "and you don't get it." >> Um, not really- >> or is there going to be a quid pro quo? >> and here's why. The argument that the product providers have made all along is, almost in a condescending way sometimes, although not intentionally condescending, it's been, look, we're selling you this low-fat fryer for your fast food restaurant. And you say you want the data, but you know, we had a team of people who are experts in this. Leave that to us, we'll analyze the data and we'll give you back what you need. Now, there's some truth to the fact that they should know their products better than anybody, and if I'm the fast food chain, I want them to get that data so that they can continually analyze and help me do my job better. They just don't have to get that data at my expense. There are ways to cooperatively work this, but again, it comes back to just the right architecture. So what we call the first receiver is in essence, setting up an abstraction close to the point of the ingestion of all this data. Upon which it's cleansed, enriched, and then propagated again to the right constituent in the right time in the right way. And by the way, I would add, with the right security considerations, and with the right data privacy considerations, 'cause like, if you look around the market now, things like GEP are in Europe and what we've seen in the US just in the wake of the elections and everything around how data is treated, privacy concerns are going to be huge. So if you don't know how to treat the data in the context of how it needs to be leveraged, you're going to lose that leverage of the data. >> Well, plus the widget guys are going to say "Look, we have to do predictive maintenance "on those devices and you want us to do that." You know, they say follow the money. Let's follow the data. So, what's the data flow look like in your mind? You got these edge devices. >> Yep, physical or virtual. Doesn't have to be a physical edge. Although, in a lot of cases, there are good reasons why you'd want a physical edge, but there's nothing technologically that says you have to have a physical edge. >> Elaborate on that, would you? What do you mean by virtual? >> Sure, so let's say I have a server inside a retail outfit. And it's collecting all of my IoT data and consolidating it and persisting it into a data store and then propagating it to a variety of constituents. That would be creating the first receiver in the physical edge. There's nothing that says that that edge device can't grab that data, but then persist it in a distributed Amazon cloud instance, or a Rackspace instance or whatever. It doesn't actually need to be persisted physically on the edge, but there's no reason it can't either. >> Okay, now I understand that now. So the guys at Wikibon, which is a sort of sister company to TheCUBE, have envisioned this three tiered data model where you've got the devices at the edge where real-time activity's going on, real-time analytics, and then you've got this sort of aggregation point, I guess call it a gateway. And then you've got, and that's as I say, aggregation of all these edge devices. And then you've got the cloud where the heavy modeling is done. It could be your private cloud or your public cloud. So does that three tier model make sense to you? >> Yeah, so what you're describing as the first tier is actually the sensor layer. The gateway layer that you're describing, in the book would be characterized as the first receiver. It's basically an edge tier that is augmented to persist and enrich the data and then apply the proper governance to it. But what I would argue is, in reality, I mean, your reference architecture is spot-on. But if you actually take that one step further, it's actually an n-tier architecture. Because there's no reason why the data doesn't go from the ten franchise stores, to the regional headquarters, to the country headquarters, to the corporate headquarters, and every step along the way, including the edge, you're going to see certain types of analytics and computational work done. I'll put a plug for my friends at Hitachi Lumada in on this, you know, there's like 700 horizontal IoT platforms out there. There aren't going to be 700 winners. There's going to be probably eight to 10, and that's only because the different specific verticals will provide for more winners than it would be if it was just one like a search engine. But, the winners are going to have to have an extensible architecture that is, will ultimately allow enterprises to do the very things I'm talking about doing. And so there are a number out there, but one of the things, and Rob Tiffany, who's the CTO of Lumada, I think has a really good handle on his team on an architecture that is really plausible for accomplishing this as the market migrates into the future. >> And that architecture's got to be very flexible, not just elastic, but sometimes we use the word plastic, plasticity, being able to go in any direction. >> Well, sure, up to and including the use of digital twins and avatars and the logic that goes along with that and the ability to spin something up and spin something down gives you that flexibility that you as an enterprise, especially the larger the enterprise, the more important that becomes, need. >> How much of the data, Don, at that edge do you think will be persisted, two part question? It's not all going to be persisted, is it? Isn't that too expensive? Is it necessary to persist all of that data? >> Well, no. So this is where, you'll hear the notion of data exhaust. What that really means is, let's just say I'm instrumenting every room in this hotel and each room has six different sensors in it and I'm taking a reading once a second. The ratio of inconsequential to consequential data is probably going to be over 99 to one. So it doesn't really make sense to persist that data and it sure as hell doesn't make sense to take that data and push it into a cloud where I spend more to reduce the value of the payload. That's just dumb. But what will happen is that, there are two things, one, I think people will see the value in locally persisting the data that has value, the consequential data, and doing that in a way that's stored at least for some period of time so you can run the type of edge analytics that might benefit from having that persisted store. The other thing that I think will happen, and this is, I don't talk much, I talk a little bit about it in the book, but there's this whole notion where when we get to the volumes of data that we really talk about where IoT will go by like 2025, it's going to push the physical limitations of how we can accommodate that. So people will begin to use techniques like developing statistical metadata models that are a highly accurate metadata representation of the entirety of the data set, but probably in about one percent of the space that's queryable and suitable for machine learning where it's going to enable you to do what you just physically couldn't do before. So that's a little bit into the future, but there are people doing some fabulous work on that right now and that'll creep into the overall lexicon over time. >> Is that a lightweight digital twin that gives you substantially the same insight? >> It could augment the digital twin in ways that allow you to stand up digital twins where you might not be able to before. The thing that, the example that most people would know about are, like in the Apache ecosystem, there are toolsets like SnappyData that are basically doing approximation, but they're doing it via sampling. And that is a step in that direction, but what you're looking for is very high value approximation that doesn't lose the outlier. So like in IoT, one of the things you normally are looking for is where am I going to pick up on anomalous behavior? Well if I'm using a sample set, and I'm only taking 15%, I by definition am going to lose a lot of that anomalous behavior. So it has to be a holistic representation of the data, but what happens is that that data is transformed into statistics that can be queryable as if it was the atomic data set, but what you're getting is a very high value approximation in a fraction of the space and time and resources. >> Ok, but that's not sampling. >> No, it's statistical metadata. There are, there's a, my last company had developed a thing that we called approximate query, and it was based on that exact set of patents around the formation of a statistical metadata model. It just so happens it's absolutely suited for where IoT is going. It's kind of, IoT isn't really there yet. People are still trying to figure out the edge in its most basic forms, but the sheer weight of the data and the progression of the market is going to force people to be innovative in how they look at some of these things. Just like, if you look at things like privacy, right now, people think in terms of anonymization. And that's, basically, I'm going to de-link data contextually where I'm going to effectively lose the linkages to the context in order to conform with data privacy. But there are techniques, like if you look at GDCAR, their techniques, within certain safe harbors, that allow you to pseudonymize the data where you can actually relink it under certain conditions. And there are some smart people out there solving these problems. That's where the market's going to go, it's just going to get there over time. And what I would also add to this equation is, at the end of the day, right now, the concepts that are in the book about the first receiver and the create, the abstraction of the creation of the data from the consumption of the data, look, it's a pretty basic thing, but it's the type of shift that is going to be required for enterprises to truly leverage the data. The things about statistical metadata and pseudonymization, pseudonymization will come before the statistical metadata. But the market forces are going to drive more and more into those areas, but you got to walk before you run. Right now, most people still have silos, which is interesting, because when you think about the whole notion of the internet of things, it infers that it's this exploitation of understanding the state of physical assets in a very broad based environment. And yet, the funny thing is, most IoT devices are silos that emulate M2M, sort of peer to peer networks just using the internet as a communication vehicle. But that'll change. >> Right, and that's really again, back to the premise of the book. We're going from these individual products, where all the data is locked into the product silo, to this digital fabric, that is an enterprise context, not a product context. >> That's right and if you go to the toolsets that Pentaho offers, the analytic toolsets. Let's just say, now that I've got this rich data set, assuming I'm following basic architectural principles so that I can leverage the maximum amount of data, that now gives me the ability to use these type of toolsets to do far better operational analytics to know what's going on, far better forensic analysis and investigative analytics to mine through the date and do root cause analysis, far better predictive analytics and prescriptive analytics to figure out what will go on, and ultimately feed the machine learning algorithms ultimately to get to in essence, the living organism, the adaptive systems that are continuously changing and adapting to circumstances. That's kind of the Holy Grail. >> You mentioned Hitachi Vantara before. I'm curious what your thoughts are on the Hitachi, you know, two years ago, we saw the acquisition, said, okay, now what? And you know, on paper it sounded good, and now it starts to come together, it starts to make more sense. You know, storage is going to the cloud. HDS says, alright, well we got this Hitachi relationship. But what do you make of that? How do you assess it, and where do you see it going? >> First of all, I actually think the moves that they've done are good. And I would not say that if I didn't think it. I'd just find a politically correct way not to say that. But I do think it's good. So they created the Hitachi Insight Group about a year and a half ago, and now that's been folded into Hitachin Vantara, alongside HDS and Pentaho and I think that it's a fairly logical set of elements coming together. I think they're going down the right path. In full disclosure, I worked for Hitachi Data Systems from '91 til '94, so it's not like I'm a recent employee of them, it's 25 years ago, but my experience with Hitachi corporate and the way they approach things has been unlike a lot of really super large companies, who may be super large, but may not be the best engineers, or may not always get everything done so well, Hitachi's a really formidable organization. And I think what they're doing with Pentaho and HDS and the Insight Group and specifically Lumada, is well thought out and I'm optimistic about where they're going. And by the way, they won't be the only winner in the equation. There's going to be eight or nine different key players, but they'll, I would not short them whatsoever. I have high hopes for them. >> The TAM is enormous. Normally, Hitachi eventually gets to where it wants to go. It's a very thoughtful company. I've been watching them for 30 years. But to a lot of people, the Pentaho and the Insight's play make a lot of sense, and then HDS, you used to work for HDS, lot of infrastructure still, lot of hardware, but a relationship with Hitachi Limited, that is quite strong, where do you see that fit, that third piece of the stool? >> So, this is where there's a few companies that have unique advantages, with Hitachi being one of them. Because if you think about IoT, IoT is the intersection of information technology and operational technology. So it's one thing to say, "I know how to build a database." or "I can build machine learning algorithms," or whatever. It's another thing to say, "I know how to build trains "or CAT scans or smart city lighting systems." And the domain expertise married with the technology delivers a set of capabilities that you can't match without that domain expertise. And, I mean, if you even just reduce it down to artificial intelligence and machine learning, you get an expert ML or AI guy, and they're only as good as the limits of their domain expertise. So that's why, and again, that's why I go back to the comparison to search engines, where there's going to be like, there's Google and maybe Yahoo. There's probably going to be more platform winners because the vertical expertise is going to be very, very important, but there's not going to be 700 of 'em. But Hitachi has an advantage that they bring to the table, 'cause they have very deep roots in energy, in medical equipment, in transportation. All of that will manifest itself in what they're doing in a big way, I think. >> Okay, so, but a lot of the things that you described, and help me understand this, are Hitachi Limited. Now of course, Hitachi Data Systems started as, National Advance Systems was a distribution arm for Hitachi IT products. >> Don: Right, good for you, not many people remember. >> I'm old. So, like I said, I had a 30 year history with this company. Do you foresee that that, and by the way, interestingly, was often criticized back when you were working for HDS, it was like, it's still a distribution hub, but in the last decade, HDS has become much more of a contributor to the innovation and the product strategy and so forth. Having said that, it seems to me advantageous if some of those things you discussed, the trains, the medical equipment, can start flowing back through HDS. I'm not sure if that's explicitly the plan. I didn't necessarily hear that, but it sort of has to, right? >> Well, I'm not privy to those discussions, so it would be conjecture on my part. >> Let's opine, but right, doesn't that make sense? >> Don: It makes perfect sense. >> Because, I mean HDS for years was just this storage silo. And then storage became a very uninteresting business, and credit to Hitachi for pivoting. But it seems to me that they could really, and they probably have a, I had Brian Householder on earlier I wish I had explored this more with him. But it just seems, the question for them is, okay, how are you going to tap those really diverse businesses. I mean, it's a business like a GE or a Siemens. I mean, it's very broad based. >> Well, again, conjecture on my part, but one way I would do it would be to start using Lumada in the various operations, the domain-specific operations right now with Hitachi. Whether they plan to do that or not, I'm not sure of. I've heard that they probably will. >> That's a data play, obviously, right? >> Well it's a platform play. And it's enabling technology that should augment what's already going on in the various elements of Hitachi. Again, I'm, this is conjecture on my part. But you asked, let's just go with this. I would say that makes a lot of sense. I'd be surprised if they don't do that. And I think in the process of doing that, you start to crosspollinate that expertise that gives you a unique advantage. It goes back to if you have unique advantages, you can choose to exploit them or not. Very few companies have the set of unique advantages that somebody like Hitachi has in terms of their engineering and massive reach into so many, you know, Hitachi, GE, Siemens, these are companies that have big reach to the extent that they exploit them or not. One of the things about Hitachi that's different than almost anybody though is they have all this domain expertise, but they've been in the technology-specific business for a long time as well, making computers. And so, they actually already have the internal expertise to crosspollinate, but you know, whether they do it or not, time will tell. >> Well, but it's interesting to watch the big whales, the horses in the track, if you will. Certainly GE has made a lot of noise, like, okay, we're a software company. And now you're seeing, wow, that's not so easy, and then again, I'm sanguine about GE. I think eventually they'll get there. And then you see IBM's got their sort of IoT division. They're bringing in people. Another company with a lot of IT expertise. Not a lot of OT expertise. And then you see Hitachi, who's actually got both. Siemens I don't know as well, but presumably, they're more OT than IT and so you would think that if you had to evaluate the companies' positions, that Hitachi's in a unique position. Certainly have a lot of software. We'll see if they can leverage that in the data play, obviously Pentaho is a key piece of that. >> One would assume, yeah for sure. No, I mean, I again, I think, I'm very optimistic about their future. I think very highly of the people I know inside that I think are playing a role here. You know, it's not like there aren't people at GE that I think highly of, but listen, you know, San Ramon was something that was spun up recently. Hitachi's been doing this for years and years and years. You know, so different players have different capabilities, but Hitachi seems to have sort of a holistic set of capabilities that they can bring together and to date, I've been very impressed with how they've been going about it. And especially with the architecture that they're bringing to bear with Lumada. >> Okay, the book is The Future of IoT, leveraging the shift to a data-centric world. Don DeLoach, and you had a co-author here as well. >> I had two co-authors. One is Wael Elrifai from Pentaho, Hitachi Vantara and the other is Emil Berthelsen, a Gartner analyst who was with Machina Research and then Gartner acquired them and Emil has stayed on with them. Both of them great guys and we wouldn't have this book if it weren't for the three of us together. I never would have pulled this off on my own, so it's a collective work. >> Don DeLoach, great having you on TheCUBE. Thanks very much for coming on. Alright, keep it right there buddy. We'll be back. This is PentahoWorld 2017, and this is TheCUBE. Be right back.

>> Announcer: Live from San Jose, California, it's theCUBE. Covering Big Data Silicon Valley 2017. >> Okay, welcome back everyone. Here live in Silicon Valley this is theCUBE. I'm John Furrier, covering our Big Data SV event, #BigDataSV. Our companion event to Big Data NYC, all in conjunction Strata Hadoop, the Big Data World comes together, and great to have guests come by. Donna Prlich, who's the senior VP of products and solutions at Pentaho, a Hitachi company who we've been following before Hitachi had acquired you guys. But you guys are unique in the sense that you're a company within Hitachi left alone after the acquisition. You're now running all the products. Congratulations, welcome back, great to see you. >> Yeah, thank you, good to be back. It's been a little while, but I think you've had some of our other friends on here, as well. >> Yep, and we'll be at Pentaho World, you have Orlando, I think is October. >> Yeah, October, so I'm excited about that, too, so. >> I'm sure the agenda is not yet baked for that because it's early in the year. But what's going on with Hitachi? Give us the update, because you're now, your purview into the product roadmap. The Big Data World, you guys have been very, very successful taking this approach to big data. It's been different and unique to others. >> [Donna} Yep. What's the update? >> Yeah, so, very exciting, actually. So, we've seen, especially at the show that the Big Data World, we all know that it's here. It's monetizable, it's where we, actually, where we shifted five years ago, and it's been a lot of what Pentaho's success has been based on. We're excited because the Hitachi acquisition, as you mentioned, sets us up for the next bit thing, which is IOT. And I've been hearing non-stop about machine learning, but that's the other component of it that's exciting for us. So, yeah, Hitachi, we're-- >> You guys doing a lot of machine learning, a lot of machine learning? >> So we, announced our own kind of own orchestration capabilities that really target how do you, it's less about building models, and how do you enable the data scientists and data preparers to leverage the actual kind of intellectual properties that companies have in those models they've built to transform their business. So we have our own, and then the other exciting piece on the Hitachi side is, on the products, we're now at the point where we're running as Pentaho, but we have access to these amazing labs, which there's about 25 to 50 depending on where you are, whether you're here or in Japan. And those data scientists are working on really interesting things on the R & D side, when you apply those to the kind of use cases we're solving for, that's just like a kid in a candy store with technology, so that's a great-- >> Yeah, you had a built-in customer there. But before I get into Pentaho focusing on what's unique, really happening within you guys with the product, especially with machine learning and AI, as it starts to really get some great momentum. But I want to get your take on what you see happening in the marketplace. Because you've seen the early days and as it's now, hitting a whole another step function as we approach machine learning and AI. Autonomous vehicles, sensors, everything's coming. How are enterprises in these new businesses, whether they're people supporting smart cities or a smart home or automotive, autonomous vehicles. What's the trends you are seeing that are really hitting the pavement here. >> Yeah, I think what we're seeing is, and it's been kind of Pentaho's focus for a long time now, which is it's always about the data. You know, what's the data challenge? Some of the amounts of data which everybody talks about from IOT, and then what's interesting is, it's not about kind of the concepts around AI that have been around forever, but when you start to apply some of those AI concepts to a data pipeline, for instance. We always talk about that 6data pipeline. The reason it's important is because you're really bringing together the data and the analytics. You can't separate those two things, and that's been kind of not only a Pentaho-specific, sort of bent that I've had for years, but a personal one, as well. That, hey, when you start separating it, it makes it really hard to get to any kind of value. So I think what we're doing, and what we're going to be seeing going forward, is applying AI to some of the things that, in a way, will close the gaps between the process and the people, and the data and the analytics that have been around for years. And we see those gaps closing with some of the tools that are emerging around preparing data. But really, when you start to bring some of that machine learning into that picture, and you start applying math to preparing data, that's where it gets really interesting. And I think we'll see some of that automation start to happen. >> So I got to ask you, what is unique about Pentaho? Take a minute to share with the audience some of the unique things that you guys are doing that's different in this sea of people trying to figure out big data. You guys are doing well, an6d you wrote a blog post that I referenced earlier yesterday, around these gaps. How, what's unique about Pentaho and what are you guys doing with examples that you could share? >> Yeah, so I think the big thing about Pentaho that's unique is that it's solving that analytics workflow from the data side. Always from the data. We've always believed that those two things go together. When you build a platform that's really flexible, it's based on open source technology, and you go into a world where a customer says, "I not only want to manage and have a data lake available," for instance, "I want to be able to have that thing extend over the years to support different groups of users. I don't want to deliver it to a tool, I want to deliver it to an application, I want to embed analytics." That's where having a complete end-to-end platform that can orchestrate the data and the analytics across the board is really unique. And what's happened is, it's like, the time has come. Where all we're hearing is, hey, I used to think it was throw some data over and, "here you go, here's the tools." The tools are really easy, so that's great. Now we have all kinds of people that can do analytics, but who's minding the data? With that end-to-end platform, we've always been able to solve for that. And when you move in the open source piece, that just makes it much easier when things like Spark emerge, right. Spark's amazing, right? But we know there's other things on the horizon. Flink, Beam, how are you going to deal with that without being kind of open source, so this is-- >> You guys made a good bet there, and your blog post got my attention because of the title. It wasn't click bait either, it was actually a great article, and I just shared it on Twitter. The Holy Grail of analytics is the value between data and insight. And this is interesting, it's about the data, it's in bold, data, data, data. Data's the hardest part. I get that. But I got to ask you, with cloud computing, you can see the trends of commoditization. You're renting stuff, and you got tools like Kinesis, Redshift on Amazon, and Azure's got tools, so you don't really own that, but the data, you own, right? >> Yeah, that's your intellectual property, right? >> But that's the heart of your piece here, isn't it, the Holy Grail. >> Yes, it is. >> What is that Holy Grail? >> Yeah, that Holy Grail is when you can bring those two things together. The analytics and the data, and you've got some governance, you've got the control. But you're allowing the access that lets the business derive value. For instance, we just had a customer, I think Eric might have mentioned it, but they're a really interesting customer. They're one of the largest community colleges in the country, Ivy Tech, and they won an award, actually, for their data excellence. But what's interesting about them is, they said we're going to create a data democracy. We want data to be available because we know that we see students dropping out, we can't be efficient, people can't get the data that they need, we have old school reporting. So they took Pentaho, and they really transformed the way they think about running their organization and their community colleges. Now they're adding predictive to that. So they've got this data democracy, but now they're looking at things like, "Okay we an see where certain classes are over capacity, but what if we could predict, next year, not only which classes are over capacity, what's the tendency of a particular student to drop out?" "What could we do to intervene?" That's where the kind of cool machine learning starts to apply. Well, Pentaho is what enables that data democracy across the board. I think that's where, when I look at it from a customer perspective, it's really kind of, it's only going to get more interesting. >> And with RFID and smart phones, you could have attendance tracking, too. You know, who's not showing up. >> Yeah absolutely. And you bring Hitachi into the picture, and you think about, for instance, from an IOT perspective, you might be capturing data from devices, and you've got a digital twin, right? And then you bring that data in with data that might be in a data lake, and you can set a threshold, and say, "Okay, not only do we want to be able to know where that student is," or whatever, "we want to trigger something back to that device," and say, "hey, here's a workshop for you to login to right away, so that you don't end up not passing a class." Or whatever it is, it's a simplistic model, but you can imagine where that starts to really become transformative. >> So I asked Eric a question yest6erday. It was from Dave Valante, who's in Boston, stuck in the snowstorm, but he was watching, and I'll ask you and see how it matches. He wrote it differently on Crouch, it was public, but this is in my chat, "HDS is known for main frames, historically, and storage, but Hitachi is an industrial giant. How is Pentaho leveraging the Hitachi monster?" >> Yes, that's a great way to put it. >> Or Godzilla, because it's Japan. >> We were just comparing notes. We were like, "Well, is it an $88 billion company or $90 billion. According to the yen today, it's 88. We usually say 90, but close enough, right? But yeah, it's a huge company. They're in every industry. Make all kinds of things. Pretty much, they've got the OT of the world under their belt. How we're leveraging it is number one, what that brings to the table, in terms of the transformations from a software perspective and data that we can bring to the table and the expertise. The other piece is, we've got a huge opportunity, via the Hitachi channel, which is what's seeing for us the growth that we've had over the last couple of years. It's been really significant since we were acquired. And then the next piece is how do we become part of that bigger Hitachi IOT strategy. And what's been starting to happen there is, as I mentioned before, you can kind of probably put the math together without giving anything away. But you think about capturing, being able to capture device data, being able to bring it into the digital twin, all of that. And then you think about, "Okay, and what if I added Pentaho to the mix?" That's pretty exciting. You bring those things together, and then you add a whole bunch of expertise and machine learning and you're like, okay. You could start to do, you could start to see where the IOT piece of it is where we're really going to-- >> IOT is a forcing function, would you agree? >> Yes, absolutely. >> It's really forcing IT to go, "Whoa, this is coming down fast." And AI and machine learning, and cloud, is just forcing everyone. >> Yeah, exactly. And when we came into the big data market, whatever it was, five years ago, in the early market it's always hard to kind of get in there. But one of the things that we were able to do, when it was sort of, people were still just talking about BI would say, "Have you heard about this stuff called big data, it's going to be hard." You are going to have to take advantage of this. And the same thing is happening with IOT. So the fact that we can be in these environments where customers are starting to see the value of the machine generated data, that's going to be-- >> And it's transformative for the business, like the community college example. >> Totally transformative, yeah. The other one was, I think Eric might have mentioned, the IMS, where all the sudden you're transforming the insurance industry. There's always looking at charts of, "I'm a 17-year-old kid," "Okay, you're rate should be this because you're a 17-year-old boy." And now they're starting to track the driving, and say, "Well, actually, maybe not, maybe you get a discount." >> Time for the self-driving car. >> Transforming, yeah. >> Well, Donna, I appreciate it. Give us a quick tease here, on Pentaho World coming in October. I know it's super early, but you have a roadmap on the product side, so you can see a little bit around the corner. >> Donna: Yeah. >> What is coming down the pike for Pentaho? What are the things that you guys are beavering away at inside the product group? >> Yeah, I think you're going to see some really cool innovations we're doing. I won't, on the Spark side, but with execution engines, in general, we're going to have some really interesting kind of innovative stuff coming. More on the machine learning coming out, and if you think about, if data is, you know what, is the hard part, just think about applying machine learning to the data, and I think you can think of some really cool things, we're going to come up with. >> We're going to need algorithms for the algorithms, machine learning for the machine learning, and, of course, humans to be smarter. Donna, thanks so much for sharing here inside theCUBE, appreciate it. >> Thank you. >> Pentaho, check them out. Going to be at Pentaho World in October, as well, in theCUBE, and hopefully we can get some more deep dives on, with their analyst group, for what's going on with the engines of innovation there. More CUBE coverage live from Silicon Valley for Big Data SV, in conjunction with Strata Hadoop, I'm John Furrier. Be right back with more after this short break. (techno music)

>> Announcer: Live from Santa Fe, California, it's the Cube covering Big Data Silicon Valley 2017. >> Welcome, back, everyone. We're here live in Silicon Valley in San Jose for Big Data SV in conjunct with stratAHEAD Hadoop part two. Three days of coverage here in Silicon Valley and Big Data. It's our eighth year covering Hadoop and the Hadoop ecosystem. Now expanding beyond just Hadoop into AI, machine learning, IoT, cloud computing with all this compute is really making it happen. I'm John Furrier with my co-host George Gilbert. Our next guest is Arik Pelkey who is the senior director of product marketing at Pentaho that we've covered many times and covered their event at Pentaho world. Thanks for joining us. >> Thank you for having me. >> So, in following you guys I'll see Pentaho was once an independent company bought by Hitachi, but still an independent group within Hitachi. >> That's right, very much so. >> Okay so you guys some news. Let's just jump into the news. You guys announced some of the machine learning. >> Exactly, yeah. So, Arik Pelkey, Pentaho. We are a data integration and analytics software company. You mentioned you've been doing this for eight years. We have been at Big Data for the past eight years as well. In fact, we're one of the first vendors to support Hadoop back in the day, so we've been along for the journey ever since then. What we're announcing today is really exciting. It's a set of machine learning orchestration capabilities, which allows data scientists, data engineers, and data analysts to really streamline their data science processes. Everything from ingesting new data sources through data preparation, feature engineering which is where a lot of data scientists spend their time through tuning their models which can still be programmed in R, in Weka, in Python, and any other kind of data science tool of choice. What we do is we help them deploy those models inside of Pentaho as a step inside of Pentaho, and then we help them update those models as time goes on. So, really what this is doing is it's streamlining. It's making them more productive so that they can focus their time on things like model building rather than data preparation and feature engineering. >> You know, it's interesting. The market is really active right now around machine learning and even just last week at Google Next, which is their cloud event, they had made the acquisition of Kaggle, which is kind of an open data science. You mentioned the three categories: data engineer, data science, data analyst. Almost on a progression, super geek to business facing, and there's different approaches. One of the comments from the CEO of Kaggle on the acquisition when we wrote up at Sylvan Angle was, and I found this fascinating, I want to get your commentary and reaction to is, he says the data science tools are as early as generations ago, meaning that all the advances and open source and tooling and software development is far along, but now data science is still at that early stage and is going to get better. So, what's your reaction to that, because this is really the demand we're seeing is a lot of heavy lifing going on in the data science world, yet there's a lot of runway of more stuff to do. What is that more stuff? >> Right. Yeah, we're seeing the same thing. Last week I was at the Gardener Data and Analytics conference, and that was kind of the take there from one of their lead machine learning analysts was this is still really early days for data science software. So, there's a lot of Apache projects out there. There's a lot of other open source activity going on, but there are very few vendors that bring to the table an integrated kind of full platform approach to the data science workflow, and that's what we're bringing to market today. Let me be clear, we're not trying to replace R, or Python, or MLlib, because those are the tools of the data scientists. They're not going anywhere. They spent eight years in their phD program working with these tools. We're not trying to change that. >> They're fluent with those tools. >> Very much so. They're also spending a lot of time doing feature engineering. Some research reports, say between 70 and 80% of their time. What we bring to the table is a visual drag and drop environment to do feature engineering a much faster, more efficient way than before. So, there's a lot of different kind of desperate siloed applications out there that all do interesting things on their own, but what we're doing is we're trying to bring all of those together. >> And the trends are reduce the time it takes to do stuff and take away some of those tasks that you can use machine learning for. What unique capabilities do you guys have? Talk about that for a minute, just what Pentaho is doing that's unique and added value to those guys. >> So, the big thing is I keep going back to the data preparation part. I mean, that's 80% of time that's still a really big challenge. There's other vendors out there that focus on just the data science kind of workflow, but where we're really unqiue is around being able to accommodate very complex data environments, and being able to onboard data. >> Give me an example of those environments. >> Geospatial data combined with data from your ERP or your CRM system and all kinds of different formats. So, there might be 15 different data formats that need to be blended together and standardized before any of that can really happen. That's the complexity in the data. So, Pentaho, very consistent with everything else that we do outside of machine learning, is all about helping our customers solve those very complex data challenges before doing any kind of machine learning. One example is one customer is called Caterpillar Machine Asset Intelligence. So, their doing predictive maintenance onboard container ships and on ferry's. So, they're taking data from hundreds and hundreds of sensors onboard these ships, combining that kind of operational sensor data together with geospatial data and then they're serving up predictive maintenance alerts if you will, or giving signals when it's time to replace an engine or complace a compressor or something like that. >> Versus waiting for it to break. >> Versus waiting for it to break, exactly. That's one of the real differentiators is that very complex data environment, and then I was starting to move toward the other differentiator which is our end to end platform which allows customers to deliver these analytics in an embedded fashion. So, kind of full circle, being able to send that signal, but not to an operational system which is sometimes a challenge because you might have to rewrite the code. Deploying models is a really big challenge within Pentaho because it is this fully integrated application. You can deploy the models within Pentaho and not have to jump out into a mainframe environment or something like that. So, I'd say differentiators are very complex data environments, and then this end to end approach where deploying models is much easier than ever before. >> Perhaps, let's talk about alternatives that customers might see. You have a tool suite, and others might have to put together a suite of tools. Maybe tell us some of the geeky version would be the impendent mismatch. You know, like the chasms you'd find between each tool where you have to glue them together, so what are some of those pitfalls? >> One of the challenges is, you have these data scientists working in silos often times. You have data analysts working in silos, you might have data engineers working in silos. One of the big pitfalls is not really collaborating enough to the point where they can do all of this together. So, that's a really big area that we see pitfalls. >> Is it binary not collaborating, or is it that the round trip takes so long that the quality or number of collaborations is so drastically reduced that the output is of lower quality? >> I think it's probably a little bit of both. I think they want to collaborate but one person might sit in Dearborn, Michigan and the other person might sit in Silicon Valley, so there's just a location challenge as well. The other challenge is, some of the data analysts might sit in IT and some of the data scientists might sit in an analytics department somewhere, so it kind of cuts across both location and functional area too. >> So let me ask from the point of view of, you know we've been doing these shows for a number of years and most people have their first data links up and running and their first maybe one or two use cases in production, very sophisticated customers have done more, but what seems to be clear is the highest value coming from those projects isn't to put a BI tool in front of them so much as to do advanced analytics on that data, apply those analytics to inform a decision, whether a person or a machine. >> That's exactly right. >> So, how do you help customers over that hump and what are some other examples that you can share? >> Yeah, so speaking of transformative. I mean, that's what machine learning is all about. It helps companies transform their businesses. We like to talk about that at Pentaho. One customer kind of industry example that I'll share is a company called IMS. IMS is in the business of providing data and analytics to insurance companies so that the insurance companies can price insurance policies based on usage. So, it's a usage model. So, IMS has a technology platform where they put sensors in a car, and then using your mobile phone, can track your driving behavior. Then, your insurance premium that month reflects the driving behavior that you had during that month. In terms of transformative, this is completely upending the insurance industry which has always had a very fixed approach to pricing risk. Now, they understand everything about your behavior. You know, are you turning too fast? Are you breaking too fast, and they're taking it further than that too. They're able to now do kind of a retroactive look at an accident. So, after an accident, they can go back and kind of decompose what happened in the accident and determine whether or not it was your fault or was in fact the ice on the street. So, transformative? I mean, this is just changing things in a really big way. >> I want to get your thoughts on this. I'm just looking at some of the research. You know, we always have the good data but there's also other data out there. In your news, 92% of organizations plan to deploy more predictive analytics, however 50% of organizations have difficulty integrating predictive analytics into their information architecture, which is where the research is shown. So my question to you is, there's a huge gap between the technology landscapes of front end BI tools and then complex data integration tools. That seems to be the sweet spot where the value's created. So, you have the demand and then front end BI's kind of sexy and cool. Wow, I could power my business, but the complexity is really hard in the backend. Who's accessing it? What's the data sources? What's the governance? All these things are complicated, so how do you guys reconcile the front end BI tools and the backend complexity integrations? >> Our story from the beginning has always been this one integrated platform, both for complex data integration challenges together with visualizations, and that's very similar to what this announcement is all about for the data science market. We're very much in line with that. >> So, it's the cart before the horse? Is it like the BI tools are really driven by the data? I mean, it makes sense that the data has to be key. Front end BI could be easy if you have one data set. >> It's funny you say that. I presented at the Gardner conference last week and my topic was, this just in: it's not about analytics. Kind of in jest, but it drove a really big crowd. So, it's about the data right? It's about solving the data problem before you solve the analytics problem whether it's a simple visualization or it's a complex fraud machine learning problem. It's about solving the data problem first. To that quote, I think one of the things that they were referencing was the challenging information architectures into which companies are trying to deploy models and so part of that is when you build a machine learning model, you use R and Python and all these other ones we're familiar with. In order to deploy that into a mainframe environment, someone has to then recode it in C++ or COBOL or something else. That can take a really long time. With our integrated approach, once you've done the feature engineering and the data preparation using our drag and drop environment, what's really interesting is that you're like 90% of the way there in terms of making that model production ready. So, you don't have to go back and change all that code, it's already there because you used it in Pentaho. >> So obviously for those two technologies groups I just mentioned, I think you had a good story there, but it creates problems. You've got product gaps, you've got organizational gaps, you have process gaps between the two. Are you guys going to solve that, or are you currently solving that today? There's a lot of little questions in there, but that seems to be the disconnect. You know, I can do this, I can do that, do I do them together? >> I mean, sticking to my story of one integrated approach to being able to do the entire data science workflow, from beginning to end and that's where we've really excelled. To the extent that more and more data engineers and data analysts and data scientists can get on this one platform even if their using R and WECCA and Python. >> You guys want to close those gaps down, that's what you guys are doing, right? >> We want to make the process more collaborative and more efficient. >> So Dave Alonte has a question on CrowdChat for you. Dave Alonte was in the snowstorm in Boston. Dave, good to see you, hope you're doing well shoveling out the driveway. Thanks for coming in digitally. His question is HDS has been known for mainframes and storage, but Hitachi is an industrial giant. How is Pentaho leveraging Hitatchi's IoT chops? >> Great question, thanks for asking. Hitatchi acquired Pentaho about two years ago, this is before my time. I've been with Pentaho about ten months ago. One of the reasons that they acquired Pentaho is because a platform that they've announced which is called Lumata which is their IoT platform, so what Pentaho is, is the analytics engine that drives that IoT platform Lumata. So, Lumata is about solving more of the hardware sensor, bringing data from the edge into being able to do the analytics. So, it's an incredibly great partnership between Lumata and Pentaho. >> Makes an eternal customer too. >> It's a 90 billion dollar conglomerate so yeah, the acquisition's been great and we're still very much an independent company going to market on our own, but we now have a much larger channel through Hitatchi's reps around the world. >> You've got IoT's use case right there in front of you. >> Exactly. >> But you are leveraging it big time, that's what you're saying? >> Oh yeah, absolutely. We're a very big part of their IoT strategy. It's the analytics. Both of the examples that I shared with you are in fact IoT, not by design but it's because there's a lot of demand. >> You guys seeing a lot of IoT right now? >> Oh yeah. We're seeing a lot of companies coming to us who have just hired a director or vice president of IoT to go out and figure out the IoT strategy. A lot of these are manufacturing companies or coming from industries that are inefficient. >> Digitizing the business model. >> So to the other point about Hitachi that I'll make, is that as it relates to data science, a 90 billion dollar manufacturing and otherwise giant, we have a very deep bench of phD data scientists that we can go to when there's very complex data science problems to solve at customer sight. So, if a customer's struggling with some of the basic how do I get up and running doing machine learning, we can bring our bench of data scientist at Hitatchi to bear in those engagements, and that's a really big differentiator for us. >> Just to be clear and one last point, you've talked about you handle the entire life cycle of modeling from acquiring the data and prepping it all the way through to building a model, deploying it, and updating it which is a continuous process. I think as we've talked about before, data scientists or just the DEV ops community has had trouble operationalizing the end of the model life cycle where you deploy it and update it. Tell us how Pentaho helps with that. >> Yeah, it's a really big problem and it's a very simple solution inside of Pentaho. It's basically a step inside of Pentaho. So, in the case of fraud let's say for example, a prediction might say fraud, not fraud, fraud, not fraud, whatever it is. We can then bring that kind of full lifecycle back into the data workflow at the beginning. It's a simple drag and drop step inside of Pentaho to say which were right and which were wrong and feed that back into the next prediction. We could also take it one step further where there has to be a manual part of this too where it goes to the customer service center, they investigate and they say yes fraud, no fraud, and then that then gets funneled back into the next prediction. So yeah, it's a big challenge and it's something that's relatively easy for us to do just as part of the data science workflow inside of Pentaho. >> Well Arick, thanks for coming on The Cube. We really appreciate it, good luck with the rest of the week here. >> Yeah, very exciting. Thank you for having me. >> You're watching The Cube here live in Silicon Valley covering Strata Hadoop, and of course our Big Data SV event, we also have a companion event called Big Data NYC. We program with O'Reilley Strata Hadoop, and of course have been covering Hadoop really since it's been founded. This is The Cube, I'm John Furrier. George Gilbert. We'll be back with more live coverage today for the next three days here inside The Cube after this short break.

okay we're back this is Dave vellante and silicon angles continuous coverage of EMC well we're back with Dave Cahill we had to take a break to interview Sanjay mirchandani and Dave thanks for letting us call inaudible there we were talking about SolidFire you unique focus on cloud service bars you're the only all flash array company focusing exclusively on cloud service providers you were talking about how you're in beta you're working at aha get a lot of good feedback bring us back to that and give us a quick update on that program yeah so we are like I said before we're in early access for the select group of cloud provider customers will continue to beat on the product with them over the course of the next few months and then towards the end of the year will go full GA to the broader market you know when market focus from our standpoint is large-scale multi-tenant clouds and where that's most prevalent today is public clouds large-scale virtual private clouds and private cloud providers yeah so um seen a lot of action in this space obviously across the entire hierarchy right and we saw EMC were here at emc world they just made a big acquisition I don't know how big actually there's a lot of rumors about the number yeah yeah I had rich Napolitano on earlier the acquisitions going to be part of his group and he said we never announced the number you don't know that I'm I said I called 400 the globe did I called 400 the global be fact what they'd say for 20 30 for 30 I had called 400 but I mean you know yeah the mark is frothy but it's a huge market it's got to be 20 plus billion yeah you know of total available market and you guys got to be excited about that on the one hand it's validation on the other hand it might be like oh oh yeah now we got to move yeah you know it when you're at the intersection of flash and cloud your life's noisy to begin with right and so in some ways EMC doesn't do us any favors by paying for 30 million for extreme I oh but but at the end of the day it's an incredible validation of the opportunity and the opportunity here isn't flesh EMC did not pay 430 million for flash they paid for a next gen art architecture capable of scaling out on a new medium and that's the difference I mean you can look at this market and it is it is so noisy and everyone's raising their hand and throwing I ops in a box and saying I'm in business but the trick is you know when you're architecting for scale it's a totally different set of design constraints and I think what you saw with emc is they're so close to the flash market that they were able to see that hey you know what we cannot retrofit an existing architecture into this problem we need to go get our own you know extreme IO slot it in they grabbed it early enough they can influence development they can spread it across their lineup I mean I think it's a great move but for us it's an incredible validation of the challenge that we're trying to solve every day which is scale out next-gen scale-out storage systems with flash as a means to an end but but flash is just the beginning of the story otherwise you're dead in this space so you're saying that the EMC moved to acquire extremely Oh was an admission that can do that the traditional controller-based architectures aren't going to cut it in this market space and so they had that piece with the enterprise flash drives and they had a PCI you know connect with VF cash and is a big opportunity in between that they were missing well I mean you know they have a whole portfolio right they called it baskin-robbins you could take you take VF cash you take thunder whenever it comes out you take extreme I oh and then you take their legacy and then you let you know emc Salesforce as long as you position it accordingly have at it but the trick is you know when do those flavors start dripping into each other right and as long as you segment them based on workload of customers that appropriately that's fine this is the key Dave the software and the management capabilities around that infrastructure and that's you know listen the flash is a is a commodity component of the architecture you know we're in and to me it is it is just the beginning of the innovation you take this hardware without the ability to scale without efficiency without performance control without complete automation you can't drive the economics necessary to take this flash and you know let's go at two for two or three percent of the market today with super high performance I ops to open up the rest of that market you need software and you've got to crack the code on the economics of efficiency automation performance control to open up that market much wider than just that two to three percent of the workloads that needs screaming fast I ops you know last year at vmworld we talked to some of your early customers and one of the things that we uncovered in those discussions was their different from the traditional enterprise guys right there thinking about running a business we were just talking to Sanjay Mirchandani about transforming IT go do an IT as a service and I'll tell you he's way ahead of the average I teashop most I tea shops are just starting to think about this transformation where's cloud service providers that's their business yeah and so one of things they said to us was look we're looking we're interested in the capability that companies like SolidFire bring because we can add value on top of that or we can sell that value to our customers right so it's not a cost plus model it's a hey this is something you need and you'll pay through the nose for because it's quality of service around applications is that is that bearing out to be true in your early beta trials and I mean this the cloud provider market is survival of the fittest right the biggest difference at the highest level is you know you've got guys traditional enterprises where I t is a cost center for this cloud service provider set I t is a profit center right and these guys look at it in terms of quality of service cost of service or breadth of service and if they're not improving or differentiating relative to the gorillas in the space on you know quality of service cost of service of breathless service that they're going to be out of business and that's the mandate that they have and so it is totally about delivering a service to their end customers not just turning a bunch of knobs to a captive user base which is what traditional enterprise IT is about ok so I'll give you the last word you know what's next what should we be looking for from from from SolidFire over the next six months yeah so from a SolidFire perspective and I think the most interesting thing for us is is just heads down and development right now so over the next six months we're going to continue to push forward with the early access customers let them prove out the solution and let them start to charge to market with their respective services and also I think you're going to see the market developed as well where cloud providers realize that it's not just about hosting data they need to host applications they need to compete on breadth of services relative to Amazon and for that that requires different mindsets and requires different architectures you think we're going to see you emerge this year a new definition of what's what was traditionally known as tier 1 storage you know the emc v-max the the IBM ds8000 HDS I mean those are it goes guys are the only tier 1 players you think that we're going to see a new definition there that's around multi-tenant around supporting horizontal applications across the port so I don't as much look at it in terms of tears I always break the market into either workloads or customer sets and I think of or than anything else you're going to see this customer set continue to emerge that cares about large-scale multi-tenant cloud environments yeah when I say to I don't mean tiering I don't confuse you with that I mean do you mean the last you're right versus module yeah ok ok all right ya know in that sense I do think that yes there is a new class of guys going at that performance tier I mean that's another thing that emc did with extreme IO is you know look at the Prophet pool that was at risk where is the MC you know that sin is flowering and market right edge end of the day 430 million is because of barges nothing yeah relative to the opportunity there Dave Cahill hey thanks very much great to see you man right that's all a good trip back keep it right there with right back