hey welcome back everybody Jeff Rick here or the cube conversation and the SiliconANGLE cubes Palo Alto studio a little bit of a break and the crazy conference season so here to kind of fix the gear and take things up and sit down and in the context of a conversation outside of a show to really get the update and we're really excited to be joined here by two guests who are announcing a pretty exciting deal that's happening today is who you shoot a CTO of Hitachi Data scissors welcome again to you and jack mazzoni vice president storage networking at brocade welcome thank you so let's just jump right into it tell everybody what happened today and why this is big news yeah sure I'm gonna start it and so what we're announcing today is broke aids developed its its next-gen called gen-6 fibre channel switches and it's a whole portfolio and we're very excited that hitachi who resells the OEM are our product to to their customer base is launching on the state as well so we're very excited about that and it's big news right and so you'll be able to buy this product today from hitachi for all the great customers that we have out there today and that's the big announcement excellent and why is this important to your customers well this is just the next evolution in fibre channel I mean 32 gigabit per second don't you know we were just on 16 now not long ago and so it's going to open up a lot of bandwidth open up you know more workload being processed provide new opportunities for new applications as well so it's funny a lot a lot of talk on you know already it in the end of Moore's law we're going to be able to squeak out more compute power outage micro processors and stuff but it sounds like you guys are squeezing out a lot more performance on the network yeah I know absolutely and one thing that you know Hugh mentioned earlier which I thought was great is you know when you get performance like this in the network and you just get performance in general enables consolidation enables efficiencies right and when flash is able to go and allow you to do let's say the same or more amount of workloads with less course that's a good thing right and and the networks then got to be able to handle that and it's that kind of efficiencies that when we can jointly bring to our customers that allows them to then spend the time and think about how they transform their IT operations right into this digital transformation era into into enabling IT to be the strategic foundation to go drive the enterprise right and I know sometimes it's hard to to make that connection all the way from Genesis fibre channel to that that's how that connection goes so so it's it's been a proven winner to drive performance it saves money it saves it enables innovation and I think the commitment that brocade and Hitachi have had to to quality to the highest levels of reliability and customer service over the years has really been a cornerstone of our success it's been a great partnership I know our CEO likes to say we partner better than anybody in the industry and that's absolutely true and Hitachi has just been one of those fantastic partners for us for over a decade now so let's unpack that a little bit why is partnership so important and not only just specifically between the two companies here but you know we go to a ton of shows and every show now even if it's a specific vendor like the pentaho show is a whole ecosystem right nobody can do it alone anymore and there's a really kind of renewed focus around the ecosystem and and everyone kind of coming together at the end of the day provide solutions to customers that are going to solve problems so it's a very important piece of it yeah and I think you've a great example that is if it really is a requirement if you think about private cloud infrastructures and converge infrastructures you're bringing so many elements together to deliver a total solution and Hitachi UCP is a great example where you have you know great technologies from hitachi in there we've been able to participate some of our fibre channel as well as our IP storage switches we were able to participate with that and so really I think if you want to participate in a cloud type of architecture whether it's public private hybrid you're going to have to partner you're going to have to particles you may not have all the technologies you may not have all the specialties and customers could require that on at some some levels that's kind of my take on it yes I mean you know we could have tried to develop our own fibre channel switches but you know that would have taken a lot more effort and time and distraction from what our core competencies are you know I mean brocade has a conference season networking both IP and fibre channel networking so it doesn't make any sense for us to try to do that which is better to partner with that right so and the future is going to be all about partnering and and more toward open source to right and the other thing that we find over and over again is really the changing expectations of the way software performs and we hear it all the time you know that why doesn't the software at my work perform like the software on my phone and why isn't it faster and why isn't it more integrated with other sources of information so the demand for better faster stronger applications is only going to increase right nobody wants less data though he wants less performance buddy wats less latency and especially in kind of an API world where all these applications are now not just siloed stacks of applications but they're pulling data from all sorts of places the speed and latency really becomes critical yeah I know I absolutely right and that's why I think this announcement and the construct of the you know the all-flash data center and all the advancements happening with flash is so important it's that linkage and then what the applications can do once they take advantage that you know I always tell people it's like remember the first time your laptop went to a all flash disk remember that experience like via the old spinning disk you're booting up well go to windows right and then you with all flash it was like that emotional experience or how great it was right you take that level at an enterprise level right where you have thousands and thousands of thousands of disks running thousands of applications and now you bring in flash and then around the corner you ring in nvme it's amazing to think about what's going to be coming down the future right and we're very excited about our position it really being it that the the central point of if you will where all this information flow has to go through the network and you know whether it's fibre channel whether it's IP you know we're going to keep to our core values which is you know the highest levels of qualities resiliency bringing in the analytics and partner partner with the top quality companies in the world such as itachi and what was interesting about this release is you added a lot more than a tease a lot more manageability lot more reporting a lot more visibility you know one of the big themes obviously in big data is to move from you know reactive to predictive too prescriptive right and so to have the management layer to have kind of the extra amount of information that you can take advantage of because you've got excess capacity and the pipes if you will and better connectivity to the infrastructure enables a whole different layer of management is which is if you've talked about you and prior interviews you people have to manage a lot more right they're not managing individual boxes anymore now whole different scale man need to be able to automate that those management tools helps us to automate that the infrastructure management also the security part is very important you know the security that brocade brings them into their right into the switch itself right and the security is an interesting point right because that's again a consistent theme everywhere we go it's the old moat just doesn't work anymore the mode and the castle walls now you really have to have security baked in all over the place and the data layer the networking layer all over the place it was the interesting thing is if you think about fiber channel all right let's just offer five channels of technology it is fundamentally right more secure than Ethernet oh we love you know really a great IP portfolio and everything but if you think about Ethernet or excuse me fibre channel when you plug in it it's off by default well first it's a separate network all together right so that's that's one layer secure but it's an off by default meaning that just get you plug in doesn't mean you have access to anything you know you got to go through one man here go there's only going to go through some other stuff but some people say its complexity but but you're at least now actively saying how are the communication is going to happen thin within the this network or either that's really the opposite right because the benefit ethering you plug it in and hey everybody's connected right that's what you want but but when it comes to enterprise let's say storage applications that needs a really but is that the behavior you want that anything that just plugs into it all of a sudden now can connect and and that's one thing that gets kind of lost sometimes than the discussions and the monitor data centers and here I'm really glad that you brought it up and you dropped out of to Jeff it's it's we realize that we're adding more things into it right we're adding more capabilities for in-flight encryption you mentioned forward error correction so the other capabilities were built in it so we take security very seriously and and inherently I think that's another reason that the viability of fibre channel has remained for as long as it has been yeah and it just own it one more time you know kind of what are some of the specific benefits that came out of you two working together for this launch how are you really kind of taking advantage of each other's strengths to really provide a better solution today that people can go out and get well one of the things is they offer backward compelled compatibility we're with two generations right right and that enables us we have a lot of legacy things that we've got to bring forward they don't just rip everything out and put in all these stuff turn the data center off for the weekend is my bonus so you know it gives us that easy transition migration into these higher higher technology levels big one yeah a big one yeah and I think when when the in the porn part two is when we deliver our systems to itachi they test it with their latest and greatest storage they do this full you know systems total solution test so when a customer that brings it into the environment it's it's been fully tested completely NM by brocade and hitachi and then to Hugh's point it's it also then works its backward compatible with everything in the environment nothing's going to you know that nothing will ever break but you know so much time and effort is put into making sure everything runs to seamless as possible because again you have to think about the environments that we're in all right those from mission-critical big environments they got to solve some serious problems they're not up for science projects they're not for risk right yes they have to advance the technology but it's got it done be done in a way that a mitigator essence done a responsible way and that's where I think when you bring their storage and our network together as well as their servers right we have our technology part of their server solutions as well you get some very compelling solutions all right well congratulations to both of you and also to the team's I'm sure there was a lot of work that went up into this day and it's always a relief to get here so thanks for stopping by and sharing the story thank you absolutely right with you and Jack I'm chef Rick you're watching the Q's the cube conversation from Palo Alto thanks for watching we'll see you next time

hi everybody Jeff Rick here with the Q we're having a cute conversation in the Palo Alto studio something that we do when we have a little break in the show schedule we can take a minute catch our breath and still sit down with the tech leaders that you want to hear from but now we can do it in the studio outside the context of the hustle and bustle of a show and really excited to have a true industry veteran he's been around for probably longer than he wants me to say on air so I'll let him say how long but who is she - the CTO of Hitachi Data Systems welcome thank you Jeff great to see you pleasure to be here well doing a little research for this interview you've been around for a while you've done a number of interviews and the thing that struck me was kind of that maybe the last big trend that you were so excited about server virtualization and what a phenomenal difference that made in the marketplace as well as your business are we going through another one of those now yes well we're you know we're going through this digital transformation and I guess IDC is the one that started that term and it's based upon you know the social mobile analytics and cloud or smack because they called it and that has brought some new technologies and be able to create some new innovations in terms of how businesses can transform themselves right Hitachi Data Systems you guys are you guys are way down in the bowels of these big systems you guys are powering a lot of the storage and and you came from the mainframe business so how is it affecting your business how are you seeing you know real concrete changes in what your customers are asking you for and how you see their business changing yes well we started it as well we started as mainframes and then we transition to storage from the mainframe businesses that are declined but we're more than storage you know we have now we have an x86 of server platform a blade server that enables us to provide a converged solution along with our networking partners like brocade and these converts oceans are kind of the basis for private clouds because it eliminates all the the need for infrastructure connectivity and things like that so you can roll in one of these things plug in a the power plug on the network and and actually pick an application from a table menu of tables templates and be off and running so it makes it very easy to move into this new phase of digital transformation yeah cuz it's funny because on the infrastructure side you know it's kind of production line 101 as soon as you take care of one piece in the production line then you move to your next point of failure you move to your next point of failure you know between compute and and and storage and networking everyone seem to see the kind of networking was kind of the slowest leg of the three and kind of coming up to the modern architecture but now with this type of announcement they're really bringing their game up quite a bit right yeah no Gen 6 is really going to open up a lot of bandwidth and I ops for us and move a lot of the actually you know it's the peaks that we worry about right we have to over configure for the peaks but they've got this you know 32 gigabits per second yes the old mob no problem right everybody calls me everybody calls mom on Mother's Day and AT&T doesn't have to build the whole network out for Mother's Day but Mother's Day only comes once a year yeah yeah the other huge trend that you've talked about extensively which is another driver behind this is really software defined and how software-defined is spreading throughout many parts of the infrastructure and and adding a whole new layer of flexibility expandability elasticity to what customers can do with their infrastructure right yeah software-defined is is key to this transformational transformation that we're talking about and to us Software Defined you know many times people consider software-defined as a way of commoditizing the hardware and to us is much different than that it's really the communication between hardware and the application layer a good example is v-ball from VMware where we can publish our unique capabilities up through the vasa interface API and vSphere can see our capabilities and they find a virtual volume or on their capabilities and on our part we can see into vmware know that we're talking or configuring for a virtual machine not just presenting up Lunz and you know blocks but we can actually recognize that this virtual machine is higher priority than others and we can allocate to the right resources right so it's a communication process and a synergy between applications and hardware infrastructure and then what this has enabled what you've talked about in numerous times too is the ability for an individual to manage a whole lot more in terms of infrastructure storage etc so now as the as the you know kind of amount of stuff that I'm responsible for goes up you know the management and the management tools and the ability to manage this this bigger more complex things becomes much more significant yeah much simpler you know the old view of infrastructure or the data center it was sort of like a triangle you know with with the base of it being the infrastructure costs and the operations and all that the top of it was was the smaller part was what we focused on the applications and analytics what we have to do now is turn that triangle upside down so we focused less on the infrastructure software do you find helps us do that cloud helps us to do that and automate that so that we can spend most of our effort on the application the end user analytics right we hear that time and time again especially with with the DevOps ethos and what amazon has done with you know swipe your card infrastructure that it's really the application that drives everything and there's a there's an expectation in the developer world that now with containers that the application or the infrastructure to just respond and what I need from the application as opposed to limiting my application development based on what I think or I got away from them to spin up a new server or whatever that's completely flip-flopped as you said yeah I mean you make a good point on it's very disruptive I mean not just on the infrastructure side but it's also in development side as you as you talked about so DevOps and agile and scrum and those things are very important so instead of the waterfall approach we took the development right that's too slow we've got to go you know be faster and using these technologies are one thing but how we use that technology and innovation we put into that is what really makes a difference right and you put in the game like we said you've been in the game for a while and and you've mentioned in a number of your interviews you know that these little guys have driven kind of this last big wave of innovation but there's a new one coming on we hear about it all the time it's sio T Internet of Things now as sensors get cheap and actually a benefit of these is now all the sensors that are in them they are less expensive and much more pervasive so now we can put them on dogs you can put them on shipping boxes from Amazon you can put them on all kinds of things you know from your point of view as you start to see IOT build and the momentum building that's a lot of hype probably right now but it's coming right and big companies like GE are behind it and a lot of players are behind it what does that make you think how excited are you about IOT is there some specific challenges you're looking forward to taking down or DC is just kind of the next big step function of kind of demand for the big three of compute networking and storage yeah it's it's another integration process between the information technology we have grew up with the data centers and the operational technology that comes from those sensors how do we bring those things together you know we have you know we have to be able to bridge that too one of the ways we can do that is with several things we have to bridge we have to bridge the infrastructure and then that's software-defined we have to bridge the data and so we have to move more toward object stores with more enriched metadata and we've got to bridge the information so the the data that comes from aisle key is different from your structured data center but you need to bring together that Oracle or s ap data together with this sensor data that comes in and integrate that together so we acquired a company last year called Pentaho that does that allows me to integrate all these things and the way it we have all these connectors to all these disparate types of databases is that it's open source so open source contributes a lot of this we just harden it and provide a subscription maintenance for that so open source is another key driver for for enabler for this transformation did you even talked about the transformation at Hitachi going from proprietary Asics proprietary software to more open source and Intel chips and again kind of leveraging best-of-breed at scale and bringing that type of capability into your right you know the other thing is the Intel's roadmap I mean that is amazing how they went to all these cores and everything and so that is enabled us to do away with a lot of the Asics we use to have to make we do have some ASICs and FPGAs for special purpose but primarily its standard Intel memory and cores and that what that enables us to do is to have a straw floor hypervisor for storage in other words all our mid-range you remember how we used to have separate mid-range and enterprise storage right now that's all running all with one hypervisor storage hypervisor it's interesting we I think was at HP maybe were talked about you know this IOT the concept of kind of IT versus ot and congratulations on the Pentaho acquisition we're at Pentaho world to create a great event great show a lot of traction but you know the ot the operational technology that runs shop floors that people at GE or work that's been cranking along all the time then yeah the IT is kind of two separate worlds and this in this IOT really is bringing those two worlds together and the connectivity together of the devices in the sensors and the shopfloor versus the IT systems you know and what's fortunate for us is he taught you data systems is our parent company has been in the IOT oh well the operational world they build nuclear reactors or trains locomotives and all the infrastructure types of things right and so we're able to bring that expertise together with our expertise and information systems and create this IOT solution right spot right we're in a great spot so a little more specific about the announcement today you're partnering with with brocade on this Gen 6 mhm what does it mean to you for attach II data systems what does it mean for your customers oh well it enables us you know we're going to all flash I mean I think we've already passed the tipping point for all flash you know with our 6.4 terabyte flash drive so we're actually cheaper than lower cost total cost of ownership than hard drives and so the cost is not a factor anymore and then all the surveys the Gartner just did a survey said that you know the users of flash reported you know savings not only in power cooling maintenance and performance normal things but also things like licensing costs because they don't have to license as many cores or instances of databases because of performance of flash so what this Gen 6 does it just opens up the highway or the lanes as Jack was talking about for us to be able to drive more workload through there right and and possibly even reduce the footprint even further by making better utilization of what we have and not have as many cores and instances of applications and as you were talking about a little bit online it's beyond just flash or the all flash array but really now looking down the road and potentially the all flash data center and the impacts of that is gonna have as these data centers keep getting bigger bigger the demands the loads are going up enough power continues to be an issue but this is a complete game-changer in terms of it all right you know all flash arrays were the hot thing right the investors are just big VCS are going crazy about those things investing a lot of money into them but you know the small flash arrays are really appliances if you want an all flash data center you still have to worry about all the enterprise things around availability you know replication disaster recovery security features shredding encryption and all that those things come with an enterprise array so if you're talking about all enterprise all flash Data Center it's more than just an all flash array you've got to expand that requirements to include all the enterprise requirements we traditionally had right so and that's that's why I Jen brocade is so the Gen 6 is so important to this right because not only does it give us the performance but it also has some additional availability features like they have forward error correction for in-stream types of error Corrections it has F CSP they do chap you know like a challenge handshake authentication protocol that we have with with Ethernet they do that with fiber channel and so we you had those additional capabilities and in the Fibre Channel switches now right in six really really just in sync with software-defined everything right it's not beads now you have management you have software capabilities you have all kinds of writings that you can now add in and as you said what's the point of hooking up a really fast drive to it'll hold an old legacy connection system that really wasn't built for the performance that you get out and the i/o insight which is key to seeing seeing that whole network at sandwich there so before I let you go running out of time just kind of get your perspective as to where we are today in kind of the IT industry with these massive shifts in terms of you know cloud and big data now being an asset and on liability and flash even the all flash data center and and mobile and around the corner IOT is you kind of sit back you know on a Friday night maybe with a glass of wine and think wow this is just crazy for all the innovation you live through and seeing how do you rank where we are today and what do you think about when you look out over the - yeah I don't know you know I've been in this business a long time but every year it just seems to be getting you know more and more the world is just expanding you know we see it you know so much data being created and we know we can't store all that data it's a part of the things that we'll have to struggle with is how what do we save and what we don't save and what can we recreate just from metadata so metadata Dappy stores become more important but you know today we're in this transition we we have to have sort of take it bimodal approach we still have our course systems that we need to take care of and nurture and grow and scale but we also need to then move into the the new the new innovations are the things that are that are not as atomic and as we have in our data center but eventual consistency things like that so we have both worlds but we need to be able to bridge the information the data and the infrastructure between the two and and networking is a key piece of that bridging the shortage of opportunity going forward no all right you thanks for taking a few minutes out of your day appreciate thank you all right who you sheet I'm chef Ricky you're watching Q conversations so looking angles to be the cue production thanks for watching

>> Welcome back everyone. CUBE live coverage here in Las Vegas for AWS Amazon Web Services, reinvent 2021. In person event on the floor, back in business, theCUBE. Two live sets pumping out content left and right. Three and a half days of wall to wall overage, over 120 interviews, stream 28 hours literally on the main site as well as on the CUBE zone. Go to CUBEreinvent.com to get all the action, all the videos will be there. Of course theCUBE.net. I'm John Furrier, your host, with Dave Nicholson my cohost this week and Sarbjeet Johal cloud strategist, influencer, all around great guy, CUBE alumni, here to break down reinvent in context to the cloud industry. Sarbjeet, great to see you, thanks for coming on. >> Good to see you guys in person finally. >> I'm so excited. I did all these interviews the past two years in person and I've been remote, now were in person, great to do it, everyone's excited. 27,000 people here at reinvent. Stand in line for classes. By the way, they're not offering these classes online, only the leadership classes and the keynote. If you're not here, you're not getting the classes. >> I like the vibe actually. I thought it would be more subdued but it is better than what I thought and energy is here. It's not like 2019, it's not. >> That's 60,000 people, you couldn't even get through the hallway. Any company would love to have 27,000 people but I got to say, this year we were just talking earlier on the segment this morning, I wanted to get your thoughts on this, you go back 15 years ago when AWS rolled out, you have EC2, S3, SQS, you had to roll your own. Basically your alternative was better than building a data center or hosting on a colo. So great, check, you don't have to buy the technology tax. I think you had to fill in the glue layers, you had to kind of roll your own and build it up. Now everyone is scaling up and next gen cloud is a completely different architecture. You got serverless, you got all the glue layers pretty much there, and you can still add stuff on it, so a completely different mindset. Changing the startup speed game. Changing the enterprise. Looking pretty good. What's your reaction to the new architecture in cloud vis a vis where it came from? >> My reaction to the new architecture is that number one it's just new. We change stuff all the time in software stacks and what I was grasping within myself sitting in my hotel in the morning listening to Warner's keynote was that we have started to accumulate the technology debt even in cloud. We cooked up some some stuff with the scripts and we automated stuff with programing, language of your choice, or CLIs. Then became the cloud formation automation, orchestration of your cloud stack, if you will. Then Hashicorp are like, so Hashicorp are sitting on the side there. But now there's another abstraction layer on top of that which was announced during Warner's keynote today. I think the new abstraction layers leave the pervious architectures a little stale. It's always like, what should you do? Should you refactor your existing stacks or should you not touch that? Just go from now on on the new architecture? I think it's getting busy, complicated, a lot of number of services. >> What do you think other people are saying? I saw you did a little snippet with Dion Hinchcliffe online, nice Tweet there, you got a big video coming out. As you talk to other folks and influencers and people in the front lines, what are they saying about Amazon Reinvent this year? >> I think almost everybody's saying that number of services is expanding exponentially. I was thinking that 200 plus number of services or whatever that number is today, it's mind boggling. I totally understand that when you have two teams that they want to take the credit for creating a new service and they want to publish it. They want to do a press release and all that. But my request to all cloud providers, mainly three, is to not call everything a new service. Call that feature of a service. So number of services has to be reduced, collapsed if you will. We need umbrella services and then under that there should be features of services, that's one thing. Another feedback I got from some second tier partners is that they have the competency program for partners. They announced that. They had that earlier but new competencies. It leaves the second or third tier partners in the cold. Only the first tier partners can get those competencies because for that they have to send a lot of money, train people, then they get that check box, oh, you can do this. >> This whole services thing and what you call a service, if you called everything a service a new feature of DNS or a new thing here and there, serverless, there's be thousands of features, services. I think Amazon, I think they culled it down to like, 200, is the number we hear. >> But isn't that part of the role of the partner, the services provider, the consultancy, to act as a bridge between all of those services and features, whatever you want to call them and figuring out exactly what the end user customer actually needs? The idea that AWS is messaging here is targeted directly towards end user customers. There's a lot to be desired there because how do you translate that? I'm thinking, compare and contrast that with the Steve Jobs approach of there shall be three. There will be a large, a medium and a small. I know that this is more complex, but when you come out and you say, 475 different kinds of instances, you're leaving that to your partners to translate. To your point, if you're segregating those partners into categories where only a top tier has access to everything, interesting place to be. >> A couple of discussions I had with partners was that I actually suggested them to create a bank of reference architectures, we call that in Amazon terms. But it's not only technical side of things, but business as well. They need to create some principle based architectures and have a bank of that and then prescribe that to their customers base. I think that's the only way to simplify these things because as you said, if you have 200 different types of instances, for instance, (laughs), it is hard. It is really hard. >> I want to get your thoughts, we talk about this on Twitter all the time so the folks watching, if you want to follow our rants and raves on Twitter, follow us on Twitter you'll get all the action, all the influencers are there. Competition. I've been ranting all week and been saying it for a long time, Microsoft's not even close to Amazon. I'm a bit over the top but I'll just say that if Amazon goes unchecked, Microsoft's ecosystem's going to get decimated. Why would I want to run software, my software, on a suboptimal performance infrastructure? Microsoft had Windows back in the day and had the system software and the application suite but they encouraged developers to build on top of Windows. Their "dot net" or ecosystem. That game's over. I guess Window's runs on Amazon too, whatever. But now the cloud is the Windows. The cloud is the system software. So developers are running on top of the cloud. >> Yes. >> So who wins? >> I think Open wins. Not Open-source. Open-source and Open are different things, we always discuss that. I think Open wins, the close systems have this problem of protectionism which doesn't work, with our little kids at home or your economy as whole. When you protect your local industry, the economy goes down. I've seen that, I'm an economist by education as you guys know. >> Yes. >> I think it's the same, when you protect too much of whatever you have, I think it's has a worse effect. But there's one narrative, Satya sort of narrates if you will, he says that, hey, when you use Windows, you keep everything, 100%. We are not taking a cut. When you're sitting in a cloud marketplace, somebody's getting a cut. That's the argument. >> Terry Chen said, because he puked on what I said, he said better could win. >> Yes. >> That's one thing. Okay, I buy that. Azure could be better in some use cases. But I think over all Amazon wins hands down currently. Certainly with the custom processors. >> You haven't mentioned GCP. >> Actually GCP. >> What can you say about it? >> What you could say is that AWS right now has either constructed or is benefiting from the highest barrier to entry to any business in the history of our planet. You can look at the investment that GCP is making to the tune of six billion dollars a year to go after market share. Are they going after current market share which is arguably the 20% of IT that's in cloud now? Or are they going for future market share which is a piece of the larger pie? When you talk about who wins, I think it's still possible for- >> Hold on, hold on. >> You left Oracle out. I think it's still possible. >> Hold on, hold on, hold on. >> I can tell you about Oracle. >> Hold on, hold on. This is a thought exercise, I'm going to ask you guys this question. It may be rhetorical, you don't need to answer it. If you went to all the people out there buying Azure and GCP, no offense guys, and you said, "Put aside all your credits you've been given, how much are you actually using?" If you take the incentives away, why are you on those clouds from a performance perspective? >> Sorry to cut you off. We know that Oracle uses incentives, X codes, leads for sale, and all that stuff, we know that. A lot of people know that. So cloud became shelfware there, we know the story. I'm leaving Oracle to the side. But I think Google has legs. Google's cloud has legs. They are a very enduring focus company. They are more open-source friendly and data science friendly as well. I think they are actually a number two, personally I believe. I'm a developer by heart, so they are number two developer cloud after Amazon. >> I think it's well know, I agree with you by the way. I think people may not know this but it's well known in the industry that Amazon has been mostly afraid of Google more than Microsoft. I think now because of this market share, the ecosystem war that's going to happen in a very short period of time, Microsoft's more of a threat on paper. But Google's got more threat to sling shot back and front technically because if you look at Graviton, the stack that they're building for ISVs and developers, Amazon's clearly winning. Google can pull that off. If they get it, they got to have their own way. >> Let me tell you, the one thing actually, if we want to know what was the fumble this time? I have some, actually I will talk about it in my radio, if you have enough time here. I think Google will do better because they're open and Amazon is complex. I was thinking during the keynotes, what are the clues to Amazon, AWS, leaving which is helping Google and Azure, mainly Google. Google is simple actually, a lot simpler to use, but again having said that, there's one thing actually, the new term I'm trying to define is the feature proximity. Amazon has feature proximity, like the best. When you are doing one thing and you want to do another thing, they have that all right there. They're ahead of the game. They have their 5G, private 5G on all their stuff, it's very futuristic. >> By the way, I got Amazon to agree to get me some private 5G for when we go back home. We're going to setup an outdoor area for some open CUBE action with some 5G. >> Actually we could put that on a nice van with the logos and all that. We could move around. >> We'll park it right there on El Camino, right next to Stanford University. Maybe we could live in one of those things too. >> Make it a taco truck and I'll join you guys. >> (laughs) Taco truck for free food. >> Yeah, let's do that. >> All seriousness guys, I want to get your thoughts as we wrap up this segment on the analysis of the cloud industry. What do you guys think, your opinion, it's going to take, I'll start by saying I think Amazon, if not contested for their leadership in the performance of silicon and the stack for software developers and owners to run the fastest they can run away with this. I think Microsoft and Google better be cranking right now to make it easy and have silicon advantage as well. I think clearly if the ecosystem's going to be at play, because the shift is happening to modernize software development, low code, no code, every shift everyone will go to the best performance, independent of cost and incentives. Amazon's got lower cost too so they got the fly wheel going. >> I can make mine short. I think GCP can also be successful. But I think already the amount of momentum that AWS has, the wind behind it's sails, I was at EMC for many years and we used to joke about our arch nemesis Hitachi Data Systems and saying that they were quite discouraged every morning as they woke up learning that they were a year further behind. Every night they went to sleep. They woke up the next day and they were a year further behind. Watching the announcements coming out of this event this week, I think there are some people at GCP and Microsoft and others who have that sense. But having said that, we're at the dawn of at era of cloud. There's plenty of room for a lot of players. When you give us your thoughts, I'd like your answer to the question, how much are consumers in the driver's seat today? Will the customers be able to demand multi sourcing? >> I think customers, you work with your money. Customers can demand that but at the same time customers can get stuck in a platform and they can't get out. We usually talk about when to lock in. There's one thing that Amazon keeps saying that we are open, we are open and the other vendors are like, these brands. I think that kind of narrative can come bite back to them. It's not a good thing to say. You don't want to be cocky about your features or you are the best and all that stuff. I think you want to stay humble and respect the other guys as well because they are coming right behind you. I think the key is developers. I have the bias towards developers because I was a developers but I totally believe deep down, actually I have tried to put my developer hat off and still think that way about these constructs. Developers are the people who call the shots. If you are not developer friendly you can't do much. >> That's a good point. >> That's my warning to Amazon. Don't go away from developers. You are number one developer cloud, stay there. This refocus is good, but put that to the side, not make that front center. Google has made that front center, I think that's a mistake. >> Yeah, you have the features, the right features, but again, speed, performance. Developers, capture the opportunity. Developers want to move fast. That's the entrepreneurship. Sarbjeet, great to have you on theCUBE, great to see you. >> Thanks for having me here, I enjoyed it. Great set here. >> All right, Dave Nicholson's here. Dave Nicholson, CUBE host. I'm John Furrier. You're watching theCUBE, the world leader in technology coverage. We'll be back with more live coverage from Reinvent after this short break. (upbeat music)

[Announcer] Live, from Las Vegas, it's theCube. Covering VMworld 2018, brought to you by VMware and its ecosystem partners. >> Welcome back, we're in Las Vegas and you're watching theCube. My cohost is John Trayor, I'm Stu Miniman, happy to welcome back to the program, Bob Madaio. >> Thanks Stu, I'm so glad to be here. >> Alright, so Bob, you're the Vice President of Infrastructure Solutions Marketing, and big difference, last year, you were with, was it, HDS? >> I was with Hitachi Data Systems. >> And now it's Hitachi Vantara and you had a little less facial hair when I talked to you last. >> You know it was around about November, I said, I might do theCube again next year, so I need to look different. >> Yeah, I had a, I had one Cube guy this year, he had got like almost a mountain man beard. And the week before he shaved it because he was coming back on theCube. And he was like, yeah I didn't but beards, no beards, diversity is what we like on theCube. >> Got to make the videos look different right? So next year I'll be beardless again, we'll do it again. It'll be fun. >> Alright, so I guess the follicle discussion's interesting but the Hitachi story is an interesting one you know Hitachi of course, huge company, lot of different technologies there, but bring us up to speed with what came together with Hitachi Vantara. >> Sure for a reminder of what we did, so we were Hitachi Data Systems, that's a part of the company I was with and again Hitachi Limited, out of Japan very large, you know, over 80 billion dollar organization of which Hitachi Data Systems used to be the IT arm that took those solutions to market around the world. What we did is, many might remember we had purchased Pentaho the open source analytics, you know, great a ETL blending capability. We brought them into the family with Hitachi Data Systems. We also had a sister company that was called Hitachi Insight Group. Hitachi Insight Group was really there to kick start our efforts around IoT. And if you've heard us talk about our Lumada Platform, if you look at what strings all this together, we've been having a lot, and I'm sure we'll talk about it here, of conversations about data. How do we help our customers with data? You know of course we've had a history in storage, but how do we bring it together, analyze it, bring new things, make that infrastructure more flexible? So that was what Vantara was. It was the bringing together of those three entities, and we continue to add. So, we're doing more and going to bring more companies into the fold. >> I love that Bob. I mean, we know the trend we've been watching for quite a number of years is, IT is going from that cost center over on the side that said, "No" to, to survive, you'd better be responding to the business, tie closely to the business or the business will go elsewhere. >> Yes indeed. >> For those solutions. And in the same way storage can't just be some growing expense that, you know, is I can't manage it I can't do this, to data is the life blood of business today. >> You know it's, I get to see some customers, not always as many as I'd like, but work closely with our field. And I was at this great customer of ours who's a regional bank and I was talking to, it was fundamentally a very storage-y audience. And I was, let's be honest, I was the corporate guy, I was a bit of the appetizer before the technical team, and I was having a data conversation. And we have this thing that, maybe we'll talk about, we call it the stairway of value and how customers should think of their value getting, you know, more important and how they can help, IT can help expose that value. And I was going through this model and I was worried, man, I might be losing this audience. But the lead person was writing, and I kind of stopped and said, is this relevant to you guys? And he said you know, I'm presenting on data to the organization next week, and I'm taking notes. And so what we're seeing is storage people, they also want to be able to have this conversation. How can what we do to make storage more accessible, move that data more quickly, valuable to the organization, to your point. >> Stairway to value, that's the power ballad for IT of the future, right? >> It does have a nearly built-in theme song, although we haven't gone there yet. For us actually, what it is is, we talk about the base layer sort of storing and protecting, and then it's enriching the data. So if you think of, often that's a meta data conversation. How do we bring more value, explain that data, make it easier to use? Then we get up into activate. That's blending maybe. You have the static systems. You want to build a repository for analytics. How do we help you activate that? And that really puts you on the path for monetization and that's the M. So we call it our SEAM model. >> So Bob, I love Hitachi Vantara and the idea of it. I got to say I understood Hitachi Data Systems better, because it's a storage, it was a you know, very, very smart, super smart storage company and you could compare it to other storage companies. But now, I'm just curious, in your, as you go and talk to customers, does that change who you talk with? And because, Hitachi Vantara as part of Hitachi too is about the industrialization of, of data and everything from oil fields and all the way down to, you know, a box in my office that might store my data. So, you know, but you've got the open source crowd and data scientists, you've got all the industrial and medical and health care stuff. As well as still these super smart storage scientists there. So how do you start that conversation and who do you end up talking with? >> You know it's very interesting. I mean, there are some companies that we approach at a Hitachi level and they're going to be major manufacturing projects or government projects, and we can bring the whole set. But oftentimes we are leveraging where a customer knows us and branching into new areas. So the storage base that we have is the most obvious to leverage. But what we're doing now is things like, we have some IT automation and analytics tools that help our customers know what's going on with the systems in their environment and how to take processes out. Well we can bring Pentaho in and tie in non-storage systems, non-IT systems like security, power and cooling, and really give a whole new dashboard. So that's a new entrance. And then the IT team can be an advocate to help you meet new business people. We also go in and speak to the business of course. We can do that through, we have IT governance go to markets, and data analytics go to market motion. And we're beginning to blend those better and better, but to be fair there are still some silos in how we talk to the customer depending on the audience. But what we see is if we can use data as a bridge, that's when the audiences sometimes meet each other, you know, for the first time it seems. >> Alright, so I love some of where this is going. Let's think down a level. You do the infrastructure solutions group, >> I do, yeah. >> So when you talk about, you know, CI and HCI and all those pieces. We're talking multi-cloud, a lot of this stuff, you know, what's the latest? What are the conversations you're having with customers about that? >> Yeah, very good. And really for us it's all been about agility. You know, data agility sure, but you can't make your data agile if you're infrastructure is very, you know, static. And so it doesn't take much to convince a customer we can build them trusted storage. That's like telling them the sky is blue, if they know Hitachi, they know this. What our conversations are now is about, what about the rest of your applications that surround this? On that trusted storage, how do we cloud enable it? What can we do there? On HCI and converge, obviously here at VMware, we partner deeply with VMware, so we are working with, for instance, how do we run some of our applications in the AWS VMware cloud, as well as be that HCI or that rack scale system on-site that manages it? So we're really having this agility conversation. How do we build the systems to be ready for this onslaught of data? Because it's great to have an IoT conversation, which remains of interest, but the reality is the systems folks need to be ready for that wave that's coming at them, and current process of just, I'm going to add controllers, I mean, that's not the way to think about it anymore. There's new types of systems that are making customer lives easier. >> Right, so from the VMware standpoint, I believe on-site is part of the partnership. >> Yeah, yeah, yeah. >> Anything in particular VMware specific. >> Yeah, across the portfolio. So of course on the storage we work with Vwalls and we do all the protection and integration with SRM and the like but, but really what's of course, hot, is hyper converge and we have our unified compute platform, HC line, that is based on Vsan. And that's doing very well. We actually had a session here with some great customers. So both Kanagra brands and MCL told their stories of picking Hitachi and they've seen some great results. So that business is doing very well. We've also introduced what we call unified compute platform RS for the rack-scale infrastructure. And we do a number of things with that. So we'll do bare metal systems for, you know, analytics workloads, but what's really got people excited is we sell a complete package with VMware cloud foundation. And that gets customers, not only ready to get up6 to hybrid cloud quickly on-site, but really have that hybrid ability. And so we're beginning to do things like certify core applications so they can test. We have a tech preview out on our Hitachi content platform, Object Store, it's actually in the app store for VMware's AWS cloud. Now, it's a tech preview from us because we know it works, but there's a scale thing. And you know Hitachi, right? It's going to work perfectly before we let our customers go crazy. So, we're really getting into those hybrid conversations and also enabling it as a service. I don't know if we talked about the as-a-service cloud that we have on offer too. >> But, no, please do, yeah. >> On top of all that technology, one of the hot offerings we have is called Hitachi Enterprise Cloud. And we have a VMware based offering, which has been doing very well and a much newer container-based platform. So on the VMware offering, really it's all of the VMware tools, but a customer never touches any of it. They don't touch our storage, the servers. It is an as-a-service model that we come in with services, help them bring in their applications, help build the service catalog for that customer and really, all they do is consume the service. So while the hardware might be on-site, it's really, they're largely indifferent to it. We do all the underlying capabilities, upgrades and such and they just provide out services to the business. So it's a really great option that people don't even know we offer. >> Yeah, well absolutely. You've had a number of conversations here at the show, it's, the customers have, the companies that have decades of appearance, you start with that base level of trust and therefore, you can help customers. You might not be the bleeding edge, but when you're there, customers know, oh wait, you're going to be around. I know that this thing's baked and ready when we get there. >> You know, the bleeding edge is fun, and there maybe some things we do, but I think it's fair enough that maybe that isn't always us. But I, but I think I have heard us called the adults in the room from time to time. And over at the booth we hear a lot of these. You know, we've been playing with this but it's going to get real. What do you guys do in this space? And while it is maybe some fun marketing being that bleeding edge, it is great to know that when it really matters, customers always trust us. And that's a huge vote of confidence. >> Alright, yep, Bob, really appreciate the update there. Absolutely, technologies like IoT, rapidly go from, this is super early but I need things we can trust. So absolutely, congrats on the progress. >> Thank you. >> We look forward to seeing, you know, how Hitachi and you know, the beard look next time we see you. >> Look forward to it. >> For John Troyer, I'm Stu Miniman. Back with more coverage from VMworld 2018 soon. Thanks for watching theCube.

>> Narrator: 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, and this is our second day covering PentahoWorld 2017. theCUBE was here in 2015 when Pentaho had just been recently acquired by Hitachi. We then, let's see, around September timeframe we saw Hitachi rebrand, Hitachi Data Systems rebrand as Hitachi Vantara, bringing together three components of its business, the Hitachi Data Systems business, the Hitachi Insights business, and of course, the Pentaho Analytics platform. We heard yesterday from Brian Householder, the president and COO of Hitachi Vantara, what the strategy was. I thought he was a very crisp, clear presenter. The strategy made a lot of sense, it resonated. Obviously a lot of execution to be done. And then subsequently at the last two days we've heard largely from Pentaho practitioners who are applying this end to end analytics platform to really transform their businesses, to really become data driven supporting those digital transformations. So pretty positive story overall. A lot of work to be done. We got to see how this whole edge to outcome plays out. Sounds good. There's got to be some execution there. We got to see the ecosystem grow for sure. These guys got a great story. This conference should explode. >> It's really a validation for Pentaho. They've been on the market for more than a decade now as the spearhead for the open source analytics revolution in business analytics, and in predictive modeling, and in data integration, all of it open source. And they've come very far and they're really a blue chip solution program. I think this show has been a great validation of Pentaho's portfolio presence in the market. Now Hitachi Vantara has a gem of a core asset. Clearly, the storage market, the data center converged infrastructure, the core Hitachi Data Systems product lines, are starting to experience the low growth that such a mature space experiences. And clearly they're placing a strong bet on Hitachi Vantara that the IoT, that the edge analytics market, will just boom wide open. Hitachi Insight Group, which was only created last year by their corporate parent, was chartered to explore opportunities in IoT. They've got the Lumata platform. They had, Hitachi Next, their conference last month, focused on IoT. I think that's really the capstone, the Lumata portfolio, in this overall story. Now, I think what we're hearing this week is that great, they've got the components, the building blocks, of potential growth, but I don't think they're going to be able to achieve takeoff growth until such time, Hitachi Vantara, they have a stronger, more credible reach out to the developer community, specifically the developers who are building the AI and machine learning for deployment to the edge. That will require to have credibility in that space. Clearly it's going to have to be the new set of frameworks, such as TensorFlow, and MXNet, and Fee-an-o, and so forth. They're going to need some sort of a modeling framework or abstraction from it that sits on top of the Pentaho platform or really across all of their offerings, including Lumata, and enables a developer to using, the mainstream application developer to use code, whether it be Python or R or Java, whatever, to build the deep learning and AI models at the highest level of abstraction, the business level of abstraction, then to automatically compile those models, which are computational graphs, down to formats that are optimized and efficient to run on devices of all sorts, chip sets of all sorts, that are increasingly resource constrained. They're not there yet. I'm not hearing that overall developer story at this show. I think they've got a lot of smart people, including Brian, pushing them in that direction. Hopefully next year's PentahoWorld or however they may rebrand this show, I think they'll probably have more of that put together, but we'll keep on waiting to see. >> And that's something that I pushed on a little bit this week. In particular, that requires a whole new go to market where the starting point is developers and then you're nurturing those developers. And certainly Pentaho has experience with community editions, but that was more to get enterprise buyers to kind of try before they buy. As you know well, Jim, the developer community is, they're very fickle, they're persnickety, they're demanding, and they're super smart, and they can be your best advocates or they'll just ignore you. That's just kind of the way it is with developers. And if you can appeal to them you can get a foothold in markets. We've seen it. Look at what Microsoft has done, look at what Amazon has done, certainly Docker, you know, on and on and on. >> Community marketing that's full bore (mumbles) user groups, developer days, hackathons, the whole nine yards, I'm not seeing a huge emphasis on community marketing in that really evangelistic sense. They need to go there seriously. They need to win the hearts and minds of the next generation developer, the next generation developer who actually won't care about whether it's TensorFlow backends or the other ones. What they will care is the high level framework, and really a collaborative framework, that's a solution provider gives them for their teams to collaborate on building and training and deploying all this stuff. I'm not hearing from this solution provider, devops really, here this year. Hopefully in the coming years there will be. Other vendors are a bit further along than they are. We see a bit further along IBM is. We see a bit further along like Cloudera and others are in putting together really a developer friendly ecosystem of components within a broader data lake framework. >> Yeah, and that's not been the historical Pentaho DNA. However, as you know, to reach out, have a community effort to reach out to developers requires resources and commitment, and it's not a one shot deal. But, it also requires a platform, and what we're seeing today is the formation of that. The reformation of Hitachi into Hitachi Vantara with a lot of resources that has a vision of a platform, of which Pentaho is a critical component, but it's going to take a lot of effort, a lot of cultivating. I presume they're having those conversations internally. They're not ready to have them externally, which is I presume why they're not having them. But that's something that we're going to certainly watch for in the coming years. What else? You gave a talk this afternoon. >> Yeah, AI is Eating the Edge, and it was well received. In fact, when I prepared my thoughts and my research about a month ago for this event I was thinking, "Am I way too far ahead?" This is Pentaho. I've been of course familiar with them since their inception. I thought, "Are there other users? "Are there developers? "Is their community going deep into AI "and all the IoT stuff?" And the last day or so here at this event it's like, "Whoa, everybody here is into that. "They know this stuff." So, not only was I relieved that I wouldn't have to explain the ABCs of all that, they were ahead of me in terms of the questions I got. The questions are, once again, what framework should we adopt for AI, the whole TensorFlow, all those framework wars, which I think are sort of overblown and they will be fairly soon, it'll be irrelevant, but those kinds of questions. Those are actually developer level questions that people are just here and they're coming to me with. >> Well, you know, I tell you, I'm no expert in frameworks, but my advice would be whatever framework you adopt you're probably not going to be using that same framework down the road. So you have to be flexible as an organization. A lot of technical leaders tell me this is look, technology is going to come and it's going to go. We got to have great people. We've got to be able to respond to the market requirements. We have to have processes that allow us to be proactive and responsive, and that your choice of framework should ensure that it doesn't constrict you in those areas. >> And you know, the framework that actually appeals to this crowd, including the people in my room, it's a wiki bot framework, it's also what Brian Hopkins of Forrester presented, the three tier architecture. There's the edge devices. There are the gateways or hubs. There's the cloud. We call them primary, secondary, tertiaries. Whatever you call them, you put different data, you put different analytics on each of those tiers. And then really in many ways in a modular fashion then you begin to orchestrate with Kubernetes and so forth these AI infused apps and these distributed architectures, like self driving vehicles or whatever. And the buzz I've been getting here, including in my session, everybody is saying, "Yeah, that's exactly the way to go." In other words, thinking in those terms prevents you as a developer from thinking that AI has to be some monolithic frigging stack on one single node. No, it actually has to be massively parallel and distributed, because these are potentially very compute intensive applications. I think there's a growing realization in the developer community that when you're talking about developing AI you're really talking about developing two core workloads. There's the inferencing, which is where the magic happens in terms of predictions and classifications, but even more resource consumptive is the training that has to happen in the cloud, and that's data, that's exabytes, petabytes intensive potentially. That's compute intensive. Very different workload. That definitely needs to happen in the cloud primarily. There's a little bit of federated training that goes out to the edge, but that's really the exception right now. So there's a growing realization in the developer community that boy, we better get a really good platform for training. And actually they could leverage, we've seen it in our research of wiki bot is that, many AI developers, many deep learning developers, actually leverage their Spark clusters for training of TensorFlow and so forth, because of in memory massive parallelism, so forth and so on. I think there will be a growing realization in the developer community that the investments they've been making in Hadoop and Spark will just be leveraged for this growing stack, for training if nothing else. >> Well, in 8.0 that was sort of the big buzz here. And you and I talked at the open with Rebecca, our other co-host, about 8.0 A lot of incremental improvements. But you know what, in talking to customers that's kind of what they want. They want Pentaho to do a good job of incorporating, curating, open source content, open source platforms and products, bringing them into their system, and making sure that their customers can take advantage of them. That's what they consistently kept asking for. They weren't freaked out about lack of AI and lack of deep learning and ML and Weka is fine. Now maybe it's a blind spot, I don't know. >> No, no, actually I've had 24 hours since they announced to chew on it. In fact, I have a SiliconANGLE article going up fairly soon with essentially my trip report and my basic takeaway. And actually what I like about 8.0 is that it focuses on streaming, bringing open source analytic streaming more completely into the Pentaho data integration platform, in other words, their stronger interoperability with Spark streaming, with Kafka, and so forth, but also they have the ability within 8.0 to better match realtime streaming workloads to execution engines in a distributed fabric. In other words, what I think that represents not only in terms of Hitachi Vantara's portfolio, but in terms of where the industry is going with all things to do with big data applications whether or not they involve AI is streaming is coming into the mainstream, pun intended, and data at rest platforms are starting to become marginalized in a lot of applications. In other words, Hadoop is data at rest par excellence, so are a fair number of other no SQL platforms. Those are not going away. Those are the core of your data lakes. But most development is being developed now, most AI and machine learning is being developed for streaming environments that increasingly are edge oriented. So Pentaho, Hitachi Vantara, for 8.0 have put in the right incremental features for the market that lies ahead. So in many ways I think that was actually a well thought out release for this particular event. >> Great. Okay, some of the highlights here. We had a lot of different industries, gaming, we had experts on autonomous vehicles, we had the NASDAQ guys on, that was a very interesting segment, the German police interview you did, the chief data officer of community colleges in Indiana. So, a lot of diversity, which underscores the platformness of Pentaho. It's not some industry specific system. It is a horizontal capabilities platform. Final thoughts on the show, some interesting things that you saw, things you learned? >> Yeah, on the show itself, they did a really good job. Hitachi Vantara, of course it's a new brand, but it's an old company, and it's even an old established set of product teams that have come together in a hurry essentially, though it's really been two years since the acquisition. They did a really good job of presenting a unified go to market message. That's a good start They've done a good job of the fact that they had these two shows in a rapid sequence, Hitachi Next, which was IoT and Lumata, but it was Hitachi Vantara, and now this one where it's all data analytics. The fact that here in the peak of fall event season they had these two shows really highlighting their innovations and their romance for those two core of their portfolio, and have done a good job of positioning themselves in each case, that shows that the teams are orchestrating well in terms of at least go to market presenting their value prop. I think in terms of the actual, we've had a lot of great customer and partner interviews on this show. And I think, you mentioned gaming first, I wasn't actually on the gaming related CUBE interview, but gaming is a hot, of course it's a hot, hot market for AI increasingly. A lot of AI that gets developed now for lots of applications involves simulations of whatever scenario you're building, including like autonomous vehicles. So gaming is in many ways a set of practices that are well established and mature that are becoming fundamental to development of all AI, because you're developing synthetic data based on simulation environments. The fact that Hitachi Vantara has strong presence as a data provider in the gaming market I think in many ways indicates that they've got ... It's a crowded marketplace. They have much larger competitors and deeper pocketed, but I think the fact is they've got all the piece parts needed to be a roaring success in this new era, and they've got strong and very loyal customers I'm discovering, not discovering, I've known this all along. But, since I've rejoined the analysts' space it's been revalidated that Pentaho how strong in blue chip they are. Now that they're a new brand in a new era, they're turning themselves around fairly well. I don't think that they'll be isolated by ... Clearly, I mean, with AI ... AI right now belongs to AWS and Microsoft and Google and IBM to some degree. We have to recognize that the Hitachi Vantaras of the world right now are still a second tier in that arena. They probably have to hitch their wagon to at least one of those core cloud providers as a core partner going forward to really prevail. >> Dave: Which they can do. >> Yeah, they can do. >> Alright. Jim, thanks very much for closing with me. Thanks to you all for watching. theCUBE puts out a lot of content. You can go to SiliconAngle.com to see all the news. theCUBE.net is where we host all these videos. Wikibon.com is our research site, so check that out, as well. We've got CrowdChats going on, CrowdChat.net. It's just unbelievable. >> Unbelievable. >> Rush of content. We're all about the data, we're all about sharing, so check those sites out. Thanks very much to the crew here. Great job. And next week a lot going on. We're in New York City. We've got some stuff going on there. Want to thank our sponsor, without whom this show, this CUBE show, would not be possible, Hitachi Vantara slash Pentaho. >> Thank you to sunny Orlando. It's great and wonderful. >> This has been theCUBE at PentahoWorld 2017. We'll see you next time. Thanks for watching. (techno 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.

>> Narrator: Live from Orlando, Florida, its theCUBE. Covering Pentaho World 2017. Brought to you by Hitachi Vantara. >> We are kicking off day one of Pentaho World. Brought to you, of course, by Hitachi Vantara. I'm your host, Rebecca Knight, along with my co-hosts. We have Dave Vellante and James Kobielus. Guys I'm thrilled to be here in Orlando, Florida. Kicking off Pentaho World with theCUBE. >> Hey Rebecca, twice in one week. >> I know, this is very exciting, very exciting. So we were just listening to the key notes. We heard a lot about the big three, the power of the big three. Which is internet of things, predictive analytics, big data. So the question for you both is where is Hitachi Vantara in this marketplace? And are they doing what they need to do to win? >> Well so the first big question everyone is asking is what the heck is Hitachi-Vantara? (laughing) What is that? >> Maybe we should have started there. >> We joke, some people say it sounds like a SUV, Japanese company, blah blah blah. When we talked to Brian-- >> Jim: A well engineered SUV. >> So Brian Householder told us, well you know it really is about vantage and vantage points. And when you listen to their angles on insights and data, anywhere and however you want it. So they're trying to give their customers an advantage and a vantage point on data and insights. So that's kind of interesting and cool branding. The second big, I think, point is Hitachi has undergone a massive transformation itself. Certainly Hitachi America, which is really not a brand they use anymore, but Hitachi Data Systems. Brian Householder talked in his keynote, when he came in 14 years ago, Hitachi was 80 percent hardware, and infrastructure, and storage. And they've transformed that. They're about 50/50 last year. In terms of infrastructure versus software and services. But what they've done, in my view, is taken now the next step. I think Hitachi has said, alright listen, storage is going to the cloud, Dell and EMC are knocking each others head off. China is coming in to play. Do we really want to try and dominate that business? Rather, why don't we play from our strengths? Which is devices, internet of things, the industrial internet. So they buy Pentaho two years ago, and we're going to talk more about that, bring in an analytics platform. And this sort of marrying IT and OT, information technology and operation technology, together to go attack what is a trillion dollar marketplace. >> That's it so Pentaho was a very strategic acquisition. For Hitachi, of course, Hitachi data system plus Hitachi insides, plus Pentaho equals Hitachi Vantara. Pentaho was one of the pioneering vendors more than a decade ago. In the whole open source analytics arena. If you cast your mind back to the middle millennium decade, open source was starting to come into its own. Of course, we already had Linux an so forth, but in terms of the data world, we're talking about the pre-Hadoop era, the pre-Spark era. We're talking about the pre-TensorFlow era. Pentaho, I should say at that time. Which is, by the way, now a product group within Hitachi Vantara. It's not a stand alone company. Pentaho established itself as the spearhead for open-source, predictive analytics, and data mining. They made something called Weka, which is an open-source data mining toolkit that was actually developed initially in New Zealand. The core of their offering, to market, in many ways became very much a core player in terms of analytics as a service a so forth, but very much established themselves, Pentaho, as an up and coming solution provider taking a more or less, by the book, open source approach for delivering solutions to market. But they were entering a market that was already fairly mature in terms of data mining. Because you are talking about the mid-2000's. You already had SaaS, and SPSS, and some of the others that had been in that space. And done quite well for a long time. And so cut ahead to the present day. Pentaho had evolved to incorporate some fairly robust data integration, data transformation, all ETL capabilities into their portfolio. They had become a big data player in their own right, With a strong focus on embedded analytics, as the keynoters indicated this morning. There's a certain point where in this decade it became clear that they couldn't go it any further, in terms of differentiating themselves in this space. In a space that dominated by Hadoop and Spark, and AI things like TensorFlow. Unless they are part of a more diversified solution provider that offered, especially I think the critical thing was the edge orientation of the industrial internet of things. Which is really where many of the opportunities are now for a variety of new markets that are opening up, including autonomous vehicles, which was the focus of here all-- >> Let's clarify some things a little bit. So Pentaho actually started before the whole Hadoop movement. >> Yeah, yeah. >> That's kind of interesting. You know they were young company when Hadoop just started to take off. And they said alright we can adopt these techniques and processes as well. So they weren't true legacy, right? >> Jim: No. >> So they were able to ride that sort of modern wave. But essentially they're in the business of data, I call it data management. And maybe that's not the right term. They do ingest, they're doing ETL, transformation anyway. They're embedding, they've got analytics, they're embedding analytics. Like you said, they're building on top of Weka. >> James: In the first flesh and BI as a hot topic in the market in the mid-200's, they became a fairly substantial BI player. That actually helped them to grow in terms of revenue and customers. >> So they're one of those companies that touches on a lot of different areas. >> Yes. >> So who do we sort of compare them to? Obviously, what you think of guys like Informatica. >> Yeah, yeah. >> Who do heavy ETL. >> Yes. You mentioned BI, you mentioned before. Like, guys like Saas. What about Tableau? >> Well, BBI would be like, there's Tableau, and ClickView and so forth. But there's also very much-- >> Talend. >> Cognos under IBM. And, of course, there's the business objects Portfolio under SAP. >> David: Right. And Talend would be? >> In fact I think Talend is in many ways is the closest analog >> Right. >> to Pentaho in terms of predominatly open-source, go to market approach, that involves both the robust data integration and cleansing and so forth from the back end. And also, a deep dive of open source analytics on the front end. >> So they're differentiation they sort of claim is they're sort of end to end integration. >> Jim: Yeah. >> Which is something we've been talking about at Wikibon for a while. And George is doing some work there, you probably are too. It's an age old thing in software. Do you do best-of-breed or do you do sort of an integrated suite? Now the interesting thing about Pentaho is, they don't own their own cloud. Hitachi Vantara doesn't own their own cloud. So they do a lot of, it's an integrated pipeline, but it doesn't include its own database and other tooling. >> Jim: Yeah. >> Right, and so there is an interesting dynamic occurring that we want to talk to Donna Perlik about obviously, is how they position relative to roll your own. And then how they position, sort of, in the cloud world. >> And we should ask also how are they positioning now in the world of deep learning frameworks? I mean they don't provide, near as I know, their own deep learning frameworks to compete with the likes of TensorFlow, or MXNet, or CNT or so forth. So where are they going in that regard? I'd like to know. I mean there are some others that are big players in this space, like IBM, who don't offer their own deep learning framework, but support more than one of the existing frameworks in a portfolio that includes much of the other componentry. So in other words, what I'm saying is you don't need to have your own deep learning framework, or even open-source deep learning code-based, to compete in this new marketplace. And perhaps Pentaho, or Hitachi Vantara, roadmapping, maybe they'll take an IBM like approach. Where they'll bundle support, or incorporate support, for two or more of these third party tools, or open source code bases into their solution. Weka is not theirs either. It's open source. I mean Weka is an open source tool that they've supported from the get go. And they've done very well by it. >> It's just kind of like early day machine leraning. >> David: Yeah. >> Okay, so we've heard about Hitachi's transformation internally. And then their messaging today was, of course-- >> Exactly, that's where I really wanted to go next was we're talking about it from the product and the technology standpoint. But one of the things we kept hearing about today was this idea of the double bottom line. And this is how Hitachi Vantara is really approaching the marketplace, by really focusing on better business, better outcomes, for their customers. And obviously for Hitachi Vantara, too, but also for bettering society. And that's what we're going to see on theCUBE today. We're going to have a lot of guests who will come on and talk about how they're using Pentaho to solve problems in healthcare data, in keeping kids from dropping out of college, from getting computing and other kinds of internet power to underserved areas. I think that's another really important approach that Hitachi Vantara is taking in its model. >> The fact that Hitachi Vantara, I know, received Pentaho Solution, has been on the market for so long and they have such a wide range of reference customers all over the world, in many vertical. >> Rebecca: That's a great point. >> The most vertical. Willing to go on camera and speak at some length of how they're using it inside their business and so forth. Speaks volumes about a solution provider. Meaning, they do good work. They provide good offerings. They're companies have invested a lot of money in, and are willing to vouch for them. That says a lot. >> Rebecca: Right. >> And so the acquisition was in 2015. I don't believe it was a public number. It's Hitachi Limited. I don't think they had to report it, but the number I heard was about a half a billion. >> Jim: Uh-hm >> Which for a company with the potential of Pentaho, is actually pretty cheap, believe it or not. You see a lot of unicorns, billion dollar plus companies. But the more important thing is it allows Hitachi to further is transformation and really go after this trillion dollar business. Which is really going to be interesting to see how that unfolds. Because while Hitachi has a long-term view, it always takes a long-term view, you still got to make money. It's fuzzy, how you make money in IOT these days. Obviously, you can make money selling devices. >> How do you think money, open source anything? You know, so yeah. >> But they're sort of open source, with a hybrid model, right? >> Yeah. >> And we talked to Brian about this. There's a proprietary component in there so they can make their margin. Wikibon, we see this three tier model emerging. A data model, where you've got the edge in some analytics, real time analytics at the edge, and maybe persists some of that data, but they're low cost devices. And then there's a sort of aggregation point, or a hub. I think Pentaho today called it a gateway. Maybe it was Brian from Forester. A gateway where you're sort of aggregating data, and then ultimately the third tier is the cloud. And that cloud, I think, vectors into two areas. One is Onprem and one was public cloud. What's interesting with Brian from Forester was saying that basically said that puts the nail in the coffin of Onprem analytics and Onprem big data. >> Uh-hm >> I don't buy that. >> I don't buy that either. >> No, I think the cloud is going to go to your data. Wherever the data lives. The cloud model of self-service and agile and elastic is going to go to your data. >> Couple of weeks ago, of course we Wikibon, we did a webinar for our customers all around the notion of a true private cloud. And Dave, of course, Peter Burse were on it. Explaining that hybrid clouds, of course, public and private play together. But where the cloud experience migrates to where the data is. In other words, that data will be both in public and in private clouds. But you will have the same reliability, high availability, scaleability, ease of programming, so forth, wherever you happen to put your data assets. In other words, many companies we talk to do this. They combine zonal architecture. They'll put some of their resources, like some of their analytics, will be in the private cloud for good reason. The data needs to stay there for security and so forth. But much in the public cloud where its way cheaper quite often. Also, they can improve service levels for important things. What I'm getting at is that the whole notion of a true private cloud is critically important to understand that its all datacentric. Its all gravitating to where the data is. And really analytics are gravitating to where the data is. And increasingly the data is on the edge itself. Its on those devices where its being persistent, much of it. Because there's no need to bring much of the raw data to the gateway or to the cloud. If you can do the predominate bulk of the inferrencing on that data at edge devices. And more and more the inferrencing, to drive things like face recognition from you Apple phone, is happening on the edge. Most of the data will live there, and most of the analytics will be developed centrally. And then trained centrally, and pushed to those edge devices. That's the way it's working. >> Well, it is going to be an exciting conference. I can't wait to hear more from all of our guests, and both of you, Dave Vellante and Jim Kobielus. I'm Rebecca Knight, we'll have more from theCUBE's live coverage of Pentaho World, brought to you by Hitachi Vantara just after this.

>> Narrator: Live from Orlando, Florida. It's TheCUBE covering PentahoWorld 2017. Brought to you by Hitachi Vantara. >> Welcome back to Orlando everybody, this is PentahoWorld #Pworld17. This is TheCUBE, the leader in live tech coverage. Brian Householder is here, he's the president and COO of Hitachi Vantara. Brian, thanks for taking some time out. >> Brian: My pleasure, thanks for having me. >> You're welcome. Let's start with Hitachi and Hitachi Vantara. You guys announced that just about a month or so ago? >> Brian: Yeah. >> People are asking, what is Hitachi Vantara, it brings together some of the three of the key pillars of your organization, so explain that to us. >> Yeah, so, we've been doing a ton of transformation here over the last 10, 15 years for Hitachi and the original Hitachi Data Systems. So really, what we have been transitioning to is a data company. And frankly, today 60% of our revenue comes from software and services, and we wanted to actually then formalize that more and then create this new company for Hitachi. So basically, we are the data arm for Hitachi, and so we created this company called Hitachi Vantara, and that does include the Pentaho organization, that includes what we call the Hitachi inside organization, which is all of our IoT assets, and includes Hitachi Data Systems. That's really the data arm, so Hitachi Vantara is the data arm for Hitachi. And so the mission of Vantara is, how do we help our customers deliver what we call edge to outcomes, which is really, wherever your data gets created, wherever environment it happens to be, if you're actually getting into IoT environments or what have you, we can actually then help you deliver the outcome that you actually need for your business. >> So I got to ask you about the name. Vantara, you think advantage, vantage point, insights. Where's the name come from, where's the meaning there? >> I've been through the whole branding process, so it's not. We ended up basically, number one wanted to make sure that we had a suggestive name. And most global companies have a suggestive name. And so Hitachi's obviously always going to be at the forefront of what we do. Vantara was a combination of a few different words. You mentioned them. One was around advantage, so how do we actually help customers take advantage of their data, and that's really what we wanted to go do. How do you have a vantage point? So, how do you actually then help customers really see across their environment. And then we also wanted to give a nod to kind of our virtualization heritage as well, and that's where the V comes from. And so that's really where we came up with Hitachi Vantara. It's exciting to have, really, in terms of teaching the marketplace around more what we do. It's ironic, again, I have a chance to talk to companies all over the world, and there's two comments I typically hear from customers. When we talk about Hitachi, and what we're doin', and our social innovation strategy, or any of the digital innovations that we do. Usually the first one's Wow. And the second one is I didn't know you did that. And that gets into, I didn't know you did those artificial intelligence technology, I didn't know that you did that around machine learning, I didn't know you actually did these kinds of solutions. And so really, this is us making sure the market understands what we're up to, and making sure that we can actually let people know all the great things that Hitachi's all about. >> So a lot of people don't know, well, you and I have known each other since before Pentaho started back in the late 90's, I think we met. And you've always been sort of focused on areas of innovation. You came into Hitachi I think over a decade ago. >> Brian: Yeah, 14 years ago. >> When Hitachi was largely a infrastructure company, kind of predominantly storage company. Talk about the transformation that you and your colleagues effected at Hitachi Data Systems and what your mission was and how far you've come. >> I've been here over 14 years, and when we first came in, yes, Hitachi Data Systems back then was mainly an infrastructure company. I mean, greater than 80% of our revenue came from hardware, and about 20% of our revenue came from software and services, so our job, and again it wasn't just me, there was a number of us that kind of came on board, to how do we really help shift this model from moving beyond infrastructure, much more into a data and software type offering. So really, over the years, we made some massive changes. And this gets into obviously acquisitions, Pentaho fit into that as well, so that's really kind of front and center with our data strategy. But, if you start talking about the offerings that we ended up doing, you know now Hitachi Vantara. So if you look at the combintations of the acquisitions and transformations we've done to date, including the Pentaho organization, and including all the innovations we've done around IoT and Lumada, that organization is, 60% of our revenue comes from software and services. That's much more of all the data solutions that we go do. So we still provide the infrastructure for companies, but it's much more around how does that infrastructure help you drive the right kind of data strategy for your organization. >> So you've done a lot of M&A over the years, and you personally have been, I know, involved in it. You said in your keynote that you looked at all the big data companies, you chose Pentaho, executives often say that, but you did have the pick of the litter at the time. One of the things you said that you were very interested in the open source component. >> Brian: Yes. >> That Pentaho brought. I want you to talk about the go-to-market of open source, and software, and how that's different than the traditional hardware world. I mean, it kind of starts with developers, right? >> Brian: It does. >> Maybe discuss that a little bit. >> Just back on the reason why we ended up choosing that. Really, our strategy's all around being open, and so I think that open culture, that open environment. Having customers use what technologies they want for their environment is very critical for us. So we do talk a lot about that, around how do we make sure we don't lock customers in, how do we make sure that they can actually use the technologies that they want, and we certainly saw the trend even three, four years ago around customers are going to move much more towards leveraging the open source communities, and we wanted them to embrace this, that's the reason for the Pentaho piece. Yes, now, a commercial open source model is different, we knew that going in. Certainly, the ecosystem is radically different, the developer community's radically different. What we needed to do is really allow and get Pentaho to make sure that becomes a front and center portion of our business when it comes to some of the new data solutions that we actually provide. And that gets into these events, this gets into how do we actually want to continue to foster the developer community, and then really how do we actually want to make sure we're adding value above and beyond what actually happens out in the open source community. And I think that gets into this whole delivering edge to outcomes for our customers. And Pentaho fits into that a little bit, but there's also a lot of other pieces around that, whether that be around IoT, around the sensor environment, how do you create and move from the digital to the physical worlds, and then ultimately out to what customers care about, which is really delivering the outcomes that they want for their business. >> I want to translate something you just said, adding value beyond what the open source world can do. I translate that into, you got to make money. And a way to make money, you can have a pure open source model, but it's very very difficult. There's one example in Red Hat, but most companies struggle to do that. You've got to have a hybrid, right. >> Brian: We do. >> Maybe discuss the profitability and margin model, from your perspective, so you can continue to fund that $3 billion in R&D. >> So I think if you look at it more kind of, if you look at our customer base, our customer base is really around the global 2000 is where we shine the most. So a lot of the open source community stuff is amazing, but if you want to start talking about doing things at scale, that's really where we come into play. So if you start talking about, we want to scale up a Pentaho set of products, or the overall Hitachi Vantara sets of products, that's really where we think we add a lot of the value. That's really where our commercial piece of the equation comes into play, and that's really where we actually go out there and shine with customers. Number one, customers don't want to deploy all that open source and have to manage it, but more importantly, when they start getting into these massive scale environments, this gets into how do you actually do distributed nodes, how do you actually then scale up these environments to not these small 50 terabyte lakes, but we're talking about petabytes and petabyte type scale. That's really where we shine, and that gets into not just the software components, but a lot of the services and integration. What a lot of partnerships that we do to help customers get that involved. >> Yeah, you do complex well. That's one of the things you said in your keynote. You also made the point, and I want to push on this a little bit. Talking about data ownership, and protection of customers data, you don't own your own cloud, or maybe you do somewhere inside the giant Hitachi organization, but that's not your schtich, you're not AWS or Google or Azure. You made the point that it's your data, so I want to push at that a little bit, because you also put up a slide that was very impressive about the capabilities of Hitachi Vantara. X is a service, solutions and services, data science, and machine learning, et cetera, domain expertise. If it's the customers data, okay, but you've got these other capabilities, and you're feeding that data into models, and those models get trained from the data, and they essentially, I have a hard time understanding where the data and the models leave off. So those models contain IP from the data. How do you ensure for your customers that the models don't go to their competitors, for example. Or, do they go to the competitors, and you're transparent about that. Maybe talk about that a little bit. >> Yeah, well we're certainly not lookin' to have customers IP at all go to our competitors, or anything around the learnings or knowledge that we actually have there. So I think the knowledge that we learn with our customers, I think hopefully adds value for them, but it's ultimately, that's their domain, if you will. So that's stuff that we want to go do. If you start talking about the original point around the ownership, we do want customers to own their own data, not us. And I think there's lot of companies out there that are actually very interested, even though they won't say it, that they want to actually own the customers data. And so I think what we're looking to go do, is really how do we actually help partner with our customers, to make sure that they have the keys to their kingdom, have the keys to their data, wherever they want to put it. And so this is not just the Pentaho assets, if you will, we have a number of other assets around content, doing this Hitachi content platform or what have you, that allows customers to put their data wherever they want it to be, but makes sure that they actually have control over that, which really gets into more of the metadata layer, to different areas that they can actually make sure that they know where all their data is, what's happening with their data. If you want to actually run a bunch of models in terms of what's happening on the machine learning or what have you, those are all things that we actually want to partner with our customers, and then the domain science, and if you talk about the data scientists and what we're actually learning from that, the knowledge around how to solve a particular problem is fine, but when it comes to the algorithms and all that, that's all the customers data. >> Okay, so you're not in the business, obviously, of taking models and bringing 'em to the competition, 'cause you said a lot of those big internet companies will say, oh no, it's your data, but you had made the point in your keynote, well you just look at their behavior, and then, you know, judge for yourself. >> Yeah, exactly. >> Let's talk about edge to outcomes. The edge is obviously an interesting area, it seems to be exploding. This notion of putting things at the edge, and then everything goes to the cloud is not likely, you're going to have a lot of stuff in between. When you first acquired Pentaho, we saw the interesting vision of bringing analytics and IoT, and OT, IT and OT, together. >> Right. >> So what's your vision for how the edge will evolve and how you guys add value there. >> I think if you look at the highest level, there's a big pendulum swing as we all know. I mean you go from main frame days, to the open system distributed days, and then much more towards a centralized cloud days, to much more of an edge. So I think we're moving in that direction, I think we need to, and I think the biggest thing that we look for is follow the data. And so wherever the data gets created, that's where some of the processing is going to have to occur. We all know the examples. Uber is not going to send information to the cloud to decide if you need to stop at a stop sign, it just doesn't happen. And so if you look at all of these edge-like devices, whether it be a car, or whether it be any kind of gateway, a sensor, or what have you, there is going to be some level of analytics that's going to have to occur at that edge, depending on, how much real time information that you need, or what you're exactly asking them to do. And that would include even analytics when it comes to video, video surveillance, things along those lines. And then, how do you then start matching that in terms of then bringing those data points into the broader ecosystem in terms of what's happening. If you wanted to actually analyze all the cameras, let's say, at this resort, you're going to have to do some things at the edge, but then centrally you can start moving those things a little bit more centrally. If you want to start then bringing those across a campus environment as well, you're going to have multiple layers, but the way we look at it is follow the data. If you've got all the data over here, you're going to have to have analytics over there. So I think a lot of people say or have this belief that data's going to move to where the analytics are, and we believe it's the exact opposite. You have to have the analytics be where the data gets created. And I think that's a really fundamental shift, maybe, in terms of our approach relative to what others are after. >> And that underscores your philosophy there, and by the way we would agree with that, I mean we see the edge as obviously very cost sensitive, you're going to persist only what you need to persist at the edge, and then bring pieces back maybe to some kind of aggregation point, and then up to the cloud for all the deep analysis and model training and the like. Do you agree with that sort of three tier model? >> Totally agree, yeah, and I think that that kind of hub, or gateway, or what have you, is going to depend on the kinds of data that you're looking at, and the analysis, but you will have to have some kind of model that's going to aggregate things over time, just depending on how much data's out there, exactly what you're looking to go do, how quickly do you actually need to get the analytics into the overall deep learning model. And so I think all of those architectures will evolve, but we definitely believe you're going to have the edge, you're going to have some kind of aggregation point, some hub, some gateway, or what have you, and then the overall kind of model. Whether that's your cloud in the public cloud or what have you that's doing all the aggregation and analytics across all your data points. >> Well, I think that's a really good point, the third tier that I'm calling the cloud, it's really three and three-A, which is public cloud and on-prem cloud. >> Correct. >> Okay, and then last question, I know you got to go. In putting together this new global conglomerate, how are you spending your time, what kinds of things are you lookin' at when you put on the binoculars, maybe not the telescope, I thought Brian from Forrester was right, your three year plan you might as well throw it out tomorrow. >> Right. >> But just in the near to mid-term, where are you spending your time, what kind of things are you thinking about? >> Certainly a lot of time with customers and partners, for sure, and that's why these kinds of events are great. 'Cause we can actually have a number of customers come in together. That was a big event we had 30 days ago as well. Great event, certainly I spent a fair amount of my time there. The other one's really around our team. We are changing up a lot of the leadership on our team to help us in terms of what's the next level or phase of our transformation, and to your point, we've gone from this company of old, 15 years ago, to now a company that we've got this data company for Hitachi, Hitachi Vantara, 60% of our revenue is software and services, this includes the $1.2 billion of acquisitions we've done over the last, you know, five to ten years. All of the other aspects. The team, and we talked about this earlier, but the team, the people, is really where it's at. We have a few new leaders on our team, which are amazing, and this is around whether it be on our sales organization, or product or what have you. I'm spending a fair amount of my time with our team. We'll be at an off site all next week as well, just making sure we're aligned on what's the next phase of executing on this strategy. >> Well, it's been interesting to watch this portion of Hitachi evolve. You guys emphasize culture, you got a great culture, and you're a great leader, I really appreciate you spending the time. >> Thanks so much Dave, yeah, appreciate it. Thank you. >> You're welcome. Alright, keep right there everybody, we'll be back with our next guest right after this short break. (light techno music)

>> Announcer: Live from Midtown Manhattan it's theCUBE. Covering Big Data New York City 2017 brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Hey, welcome back everyone live here in New York City it's theCUBE's special presentation Big Data NYC. This is our fifth year doing our own event here in New York City, our eighth year covering the Hadoop World ecosystem from the beginning. Through eight years, it's had a lot evolutions, Hadoop World, Strata Conference, Strata Hadoop, now it's called Strata Data happening right around the corner. We run our own event here, talk about thought leaders and the expert CEO's, entrepreneurs. Getting the data for you, sharing that with you. I'm John Furrier co-host theCUBE with my co-host here Jim Kobielus who's the Lead Analyst at Wikibon Big Data. And Chuck Yarbough who's the Vice President at Pentaho Solutions part of Hitachi's new Vantara. A new company created just announced last week. Hitachi in a variety of their portfolio technologies into a new company, out to bring in a lot of those integrated solutions. Chuck great to see you again, theCUBE alumni. We chatted multiple times at Pentaho World, going back 2015. >> Always he always great to be at theCUBE. >> What a couple of years it's been. Give us quickly hard news, it's pretty awesome you guys have a variety of things at Pentaho you know with Hitachi, that happened, now the market's evolved, what's this new entity, this new company they're bringing together? >> Yes, so the big news Hitachi Vantara. So what that is, two years ago Hitachi Data Systems acquired Pentaho and so fast forward two years. A new company gets created from Hitachi Data Systems. Pentaho, in a third organization at Hitachi called the Insight Group so Hitachi Insight Group. Those three groups come together to form Hitachi Vantara >> What's the motivation behind that. I mean, I go connect the dots but I want to hear your perspective because it really is about pulling things together. The trend this year the show is as Jim calls it, hybrid data, integrated data. Things seem to be coming together, is that part the purpose? What's the reason behind pulling this together? >> Yeah, I think there's a lot of reasons. One of them is what we're seeing not just in our own business, but in our customers business, and that is digital transformation. Right, this this need to evolve So Hitachi Vantara is all about data and analytics. And a big focus of what we do is what Pentaho's been doing for years which is driving in all kinds of data, big data, all data. I think we're getting on the cusp of closing out the big data term, but you know, it's all data right. >> Data everywhere, every application. >> And applying analytics across the board. One of the big initiatives, part of why Pentaho was originally acquired we were actually Hitachi Data Systems was a customer of Pentaho when we got acquired, so we we knew each other pretty well. And part of the reason for that acquisition was to drive analytics in around internet of things. The IoT space, which is something that Hitachi being a very large IT and operational technology, OT, company probably does as well as anybody if not better. >> So going back couple of years, I'm just looking at my notes here from our our video index. You visited theCUBE in 2015, but really the concepts have evolved significantly. I want to just highlight a few of them. What data warehouse optimizations, we talk about that. Data refinery concepts, 360 view as applied to big data. Again that was foundational concepts that all are in play right now. >> Absolutely. >> What is the update in those areas? Because refinery, everyone talks about data refinery, you know, oil, the easy oil example but I mean, come on, data is everywhere it is most important, you can use it multiple times unlike oil, as you were pointing out. >> So interesting you bring that up. So to me data refinery in a digital transformation really in an IoT world where lots of data is is streaming through in fact, yesterday I read something by IDC that 95% of all data in the future and the data growth is dramatic it's 10x what it is today in just a few years. 95% of the that growth of data's IoT related. The question is how are you using most of that, right, and what what are you going to do with it. So that data's is streaming through, there's a lot happening, we can do things at the edge, we can apply analytics and filtering and do things. But ultimately that data is going to land somewhere and that's where that refinery, think of it as the big data center refinery, right, where I'm going to take that large amount of data and do the things that Jim does, you know and apply machine learning and deep algorithms too really. >> I had some thoughts on the IoT Jim and I were arguing, not arguing, discussing, with others in theCube about the role. >> We were bickering. >> The role of the edge because I was saying the refiner of the data can come back depending on what kind of data or you push compute to the edge, kind of known concepts, people been discussing that. But the issue is been, how do you view the edge? I'd love to get your reaction to that question because a lot of people are saying you have to think of IoT as a completely different category, than just cloud, than just data center, because the way some people are looking at IoT I know this can be semantics whether it's industrial or just straight internet of things device, or person, that is a different animal when it comes to like what you call it and how it gets put into a bucket. I mean most people put a lot of the IT bucket but. Some are saying IT edge should be completely different category of how you look at those problems. Your thoughts on how that IoT conversation shape. >> The question I always ask when I'm talking to somebody about the edge is, well what do you mean? Because it is something that can be defined a little bit differently but in an industrial IoT context I think, you know we look at it as one, you you have to know what those things are you have to really understand them. And part of understanding those things is having a digital representation of what those things are. >> A digital twin? >> A digital twin. Right, or asset avatar, as we call it at Hitachi. >> Oh I like that. >> So this idea of really managing those assets, understanding what they are and then being able to know what the current state, what the previous state, things are like that are. And then that refinery we just talked about is sort of where that information goes to so you can do other kinds of analytics right. But when you're talking about the edge, typically what we're seeing is the kinds of analytics might happen at the edge, are probably more around filtering you know, it's not quite as complex of analytics that's what we're seeing today. Now, the future I don't know. >> Sort of tiered analytics from the edge on in with more minimal, I mean, not minimal that's the wrong term, with a more narrowly scoped inference. Like predictions and so forth being handled at the edge with larger more complex models being like deep learning whatever being processed in the cloud is that it? >> Yeah that's exactly the way that I see it. Now the other thing about the edge, depends on who you're talking to, again, but what is an edge device or the the gateways or the compute right, so part of IoT is in my mind, it's not cloud, it's not on-prem or it's not, I mean it's a little bit of everything right, it depends on the use case and what you're operating. We have a customer who does trains as a service in England, in Europe, and so they don't sell the trains anymore they actually manufacture trains, and they sell the service of getting a passenger from here to there. But for them, edge is everything that happens on those trains. And tracking, as a digital representation, the train and then being able to drill down deeper and deeper, and you, know one of the things that I understand is one of the major delays for train service is doors opening and closing or being delayed, so maybe that comes down to a small part and the vibration of it and tracking that. So you've got to be able to track that appropriately. Now, on a train you might have a lot of extra space so you could put compute devices that have a lot of power. >> What's interesting you said the edge, in this context, is everything that happens on that train. In other words, it sounds like all the real world outcomes that are enabled, perhaps optimized, by embedding of the analytics in those physical devices or in that entire vehicle that is essentially. One way that you're describing the edge which is not a single device but as a complete assembly of devices that play together. Amongst themselves and in with the services in the cloud. Is that a logical sort of framework? >> That's why I said I usually ask what do we mean by edge. If you've got millions, thousands, whatever, devices out there feeding sensors whatever feeding this data, collecting, processing you know there's some some level of edge computing gateways, processes that are going to happen. >> Well, my question for ya, I'd like to get your thoughts, as we, again we're having a, we love the hyperbio we think its completely legit and it's going to be continued to be hyped because it's obvious what you see with IoT standing on the edge. But lot of customers we talked to are like, look I got a lot going on I got application development I got to break out my security got to build that up. I've got data governance issues, and now you throw in IoT over the top. They're like, I'm choking in projects. So they they come down to one of a selection criteria. How do they define a working IoT project? And the trend that we're seeing is that it has to do with their industrial equipment or something related to their business. Call it industrial IoT, because if they have something in their business, say trains, as a critical part of what they do, that's easy to say let's justify this. Everything else then tends to go on the back burner, if they don't have clear visibility of what their instrumenting. That's kind of weird do you agree with that? Do you see a pattern as well as what customers are doing by saying I'm going to bring this project in and were going to connect our IoT. >> That's exactly what I see. Industrial internet of things is where I see the biggest value today when you have trains or mining equipment or you know whatever. >> John: Whatever your business runs. >> Your manufacturing line right. and being able to a fine tune those lines to either predicts failures, maybe improve quality. Those are those are impactful and they can be done right now today and that's what we're seeing is kind of the big emerging thing. IoT's interesting to talk about, the reality is it's really digital transformation that we're seeing. Companies transforming into new business models, doing things significantly different to grow into the future. And IoT is an enabler of that. So you're not going to see IoT everywhere today. >> The low hanging fruit is where it gets to the real business. >> Yeah, but it's going to go across all verticals, right, no doubt. >> So what solutions does Pentaho have for digital twins, or managing digital twins, the objects, the data itself, within and IoT context, is this something you're engaged in already? >> So within the Hitachi Vantara, the larger company. Bigger company, we have, we have what we call our Lumada IoT Platform and in that there is this asset avatar technology that that does exactly what you're describing. Now I'm going to throw quick plug out if you don't mind. Pentaho World in a couple, in about a month. >> John: theCUBE will be there. >> theCUBE will be there, and we're excited to have theCUBE and we're going to we're going to give you complete information about asset avatar with all the right people. >> There's a movie in there somewhere I could feel it, Avatar two. There's a lot of great representations of data I want to get your thoughts on how the new firm's going to solve customer problems. Because now as the customer see this new entity from you guys, Vantara's been doing real well, we covered the acquisition and you were kind of left alone Pentaho was integrating in, but it wasn't like a radical shift. Now there's some movement, what does it mean to the customer, what's the story to the customer. >> You know I think it's great news for the customer because Pentaho's always been very customer focused. But when you look at Hitachi Vantara the wealth of technology and expertise. Everything from all of the the great IT oriented stuff that Hitachi Data Systems has done and been well known for in the past still exists. But this broader focus of taking data and processing it in a variety of ways to solve real business problems. All the way to orchestrating machine learning in applying algorithms and then with the Hitachi. >> What specifically in Hitachi is coming into this? Because again this is again a focused solution company now with data, so Hitachi Data Centers, >> Yeah, so Hitachi Data Systems, think of it as the the infrastructure company. Hitachi Insight was the really focused largely on the IoT platform development, with some Pentaho assets and then the Pentaho business. But here's the thing about Hitachi, very large company, builds everything. Mining equipment and and all kinds of stuff. So nobody understands how all those things fit together better, I believe, than Hitachi. But some of the things that we have at that organization is this idea of the Hitachi labs. And data scientists that are really doing interesting things Jim you'd love to get more embedded into what some of those things are, and making that available to customers is a huge opportunity for customers to now be able to embrace a lot of the technologies we've been talking about. I said last year that this year was going to be the year of machine learning. And if you look through the expo hall that's what everybody's talking about. Right, it's AI or machine learning. >> I'm wondering if you're commercializing R&D that's coming straight out of Hitachi labs already or whether the Vantara combination will enable that. In other words, more innovation straight out of the labs, into into the commercial arena. >> That's something that we are absolutely trying to to, right because there's great things that these lab organizations and at Hitachi they're big labs. They're really legit, I kind of joke about that. The kinds of stuff that they're able to bring about now, Pentaho is part of the engine to help actually commercialize those things. >> Chuck I know you're looking forward to Pentaho World I'll give you the final word here in this segment how you see the big data worlds evolve. Take your Pentaho hat off and put your industry guru hat on. What's happening, I mean this AI watch, that's pretty obvious, not a lot of blockchain discussion which is going to completely open up some things we getting on the decentralized application market which is going to compliment the distributed nature of how we see a date analytics flow and certainly the immutability of it's interesting. But that's kind of down the road. But here you're starting to see the swim lanes in the industry, you've seen people who've been successful and the ones who have fallen by the wayside. But now the customers, they want real solutions. They don't want more hype, they don't want another eighth year of hype, they want OK let's get into the real meat and potatoes of data impact to my organization, call it digital transformation. What's happening, what is going on the landscape. >> So you know I mentioned before and to me it's digital transformation which is a big huge thing. But that's what companies are interested in that's what they're beginning to think. If they're not thinking about those things they're falling behind, five or six, seven years ago we talked about the same exact thing with big data. It's like a big data is really you know it's a big opportunity and they're like well I don't know those that didn't adopt it aren't necessarily in a position now to transform digitally and to do some of the things that they're going to need to evolve into new business opportunities. >> And the big data examples of winner is the ones who actually made it valuable. Whether it's insight that converted to a new customer or change an outcome in a positive way, they go that wouldn't have been possible without data. The proof points kind of hit the table. >> That's right the other thing is you know, who's going to win, who's going to lose. I think people that are implementing technology for technology's sake are going to lose. People that are focused on the outcomes are going to win. That's what it is, technology enables all that but you've really got to be focused on. I want to get your quick, one more quick thing, before we go I know we got we're tight on time but I want to get thoughts on the open ecosystem. Open source going to whole other level. The projections are code will be shipping at an exponential rate, it's be a lot of onboarding of new stuff, so open obviously works, community models work, partnering is critical. So we're seeing that good partnerships, not fake deals or optical deals or Barney deals, whatever you want to call it. But real partnerships. You starting to see technology partnerships. What's your view on that, how is the new Vantara going to go forward, are you going to continue to do partnerships and what's the strategy? >> Yeah I think the opportunity with one, Hitachi Vantara is we have a breadth that can touch many different aspects. So as Pentaho we had great partnerships, very meaningful but it always comes down to what we doing for the customer. How are we changing things for customer. So I'm not a believer in those Barney kind of relationships those are nice but let's talk about what we're doing for customers. >> Yeah, real proof points. >> You guys will continue to parner. >> Yes, we will continue to do that. >> Okay great, Chuck, thank you so much. CUBE coverage Live in New York City in Manhattan it's theCUBE with Big Data NYC, out fifth year doing our own event in conjunction with Strata Data. Now bless the new name of the show. It was Strata Hadoop, Hadoop World before that. But we're still theCUBE covering eight years of the action here back with more after this short break.

(gentle, upbeat music) >> Live from the Sands Convention Center in Las Vegas, Nevada, it's theCUBE, at AWs re:Invent 2014. Brought to you by headline sponsors Amazon and Trend Micro. >> Okay, welcome back everyone, we are here live at Amazon Web Services re:Invent 2014, this is theCUBE, our flagship program, where we go out to the events and extract synth from the noise. I'm John Furrier, the Founder of SiliconANGLE, I'm joined with my co-host Stu Miniman from wikibon.org, our next guest is James Hamilton, who is Vice President and Distinguished Engineer at Amazon Web Services, back again, second year in a row, he's a celebrity! Everyone wants his autograph, selfies, I just tweeted a picture with Stu, welcome back! >> Thank you very much! I can't believe this is a technology conference. (laughs) >> So Stu's falling over himself right now, because he's so happy you're here, and we are too, 'cause we really appreciate you taking the time to come on, I know you're super busy, you got sessions, but, always good to do a CUBE session on kind of what you're workin' on, certainly amazing progress you've done, we're really impressed with what you guys've done other this last year or two, but this year, the house was packed. Your talk was very well received. >> Cool. >> Every VC that I know in enterprise is here, and they're not tellin' everyone, there's a lot of stuff goin' on, the competitors are here, and you're up there in a whole new court, talk about the future. So, quickly summarize what you talked about in your session on the first day. What was the premise, what was the talks objective, and what was some of the key content? >> Gotcha, gotcha. My big objective was the cloud really is fundamentally different, this is not another little bit of nomenclature, this is something that's fundamentally different, it's going to change the way our industry operates. And what I wanted to do was to step through a bunch of examples of innovations, and show how this really is different from how IT has been done for years gone by. >> So the data center obviously, we're getting quotes after quotes, obviously we're here at the Amazon show so the quotes tend to be skewed towards this statement, but, I'm not in the data center business seems to be the theme, and, people generally aren't in the data center business, they're doing a lot of other things, and they need the data centers to run their business. With that in mind, what are the new innovations that you see coming up, that you're working on, that you have in place, that're going to be that enabler for this new data center in the cloud? So that customers can say hey, you know, I just want to get all this baggage off my back, I just run my business agile and effectively. Is it the equipment, is it the software, is it the chips? What're you doing there from an innovation standpoint? >> Yeah, what I focused on this year, and I think it's a couple important areas are networking, because there's big cost problems in networking, and we've done a lot of work in that area that we think is going to help customers a lot; the second one's database, because databases, they're complicated, they're the core of all applications, when applications run into trouble, typically it's the database at the core of it, so those are the two areas I covered, and I think that's two of the most important areas we're working right now. >> So James, we've looked back into people that've tried to do this services angle before, networking has been one of the bottlenecks, I think one of the reasons XSBs failed in the '90s, it was networking and security, grid computing, even to today. So what is Amazon fundamentally doing different today, and why now is it acceptable that you can deliver services around the world from your environment? What's different about networking today? >> It's a good question. I think it's a combination of private links between all of the regions, every major region is privately linked today. That's better cost structure, better availability, lower latency, scaling down to the data center level we run all custom Amazon designed gear, all custom Amazon designed protocol stacks. And why is that important? It's because cost of networking is actually climbing, relative to the rest of compute, and so, we need to do that in order to get costs under control and actually continue to be able to draw up costs. Second thing is customers need more networking-- more networking bandwidth per compute right now, it's, East/West is the big focus of the industry, because more bandwidth is required, we need to invest more, fast, that's why we're doing private gear. >> Yeah, I mean, it's some fascinating statistics, it's not just bandwidth, you said you do have up to 25 terabytes per second between nodes, it's latency and jitter that are hugely important, especially when you go into databases. Can you talk about just architecturally, what you do with availability zones versus if I'm going to a Google or a Microsoft, what does differentiate you? >> It is a little bit different. The parts that are the same are: every big enterprise that needs highly available applications is going to run those applications across multiple data centers, that's, so-- The way our system works is you choose the region to get close to your users, or to get close to your customers, or to be within a jurisdictional boundary. From down below the region, normally what's in a region is a data center, and customers usually are replicating between two regions. What's different in the Amazon solution, is we have availability zones within region; each availability zone is actually at least one data center. Because we have multiple data centers inside the same region it enables customers to do realtime, synchronous replication between those data centers. And so if they choose to, they can run multi-region replication just like most high end applications do today, or, they can run within an AZ, synchronous multiplication to multiple data centers. The advantage of that, is it takes less administrative complexity, if there's a failure, you never lose a transaction, where in multi-region replication, it has to be asynchronous because of the speed of light. >> Yeah, you-- >> Also, there's some jurisdictional benefits too, right? Say Germany, for instance, with a new data center. >> Yep. Yeah, many customers want to keep their data in region, and so that's another reason why you don't necessarily want to replicate it out in order to get that level of redundancy, you want to have multiple data centers in region, 100% correct >> So, how much is it that you drive your entire stack yourself that allows you to do this, I think about replication solutions, you used SRDF as an example. I worked for that, I worked for EMC for 10 years, and just doing a two site replication is challenging, >> It's hard. >> A multi site is differently, you guys, six data centers and availabilities on a bungee, you fundamentally have a different way of handling replication. >> We do, the strategy inside Amazon is to say multi-region replication is great, but because of the latency between regions, they're a long way apart, and the reality of speed of light, you can't run synchronous. If data centers are relatively close together in the same region, the replication can be done synchronously, and what that means is if there's a failure anywhere, you lose no transactions. >> Yeah. So, there was a great line you had in your session yesterday, that networking has been anti-Moore's law when it comes to pricing. Amazon is such a big player, everybody watches what you do, you buy from the ODMs, you're changing the supply chain. What's your vision as to where networking needs to go from a supply chain and equipment standpoint? >> Networking needs to be the same place where servers went 20 years ago, and that is: it needs to be on a Moore's law curve where, as we get more and more transistors on a chip, we should get lower and lower costs in a server, we should get lower and lower costs in a network. Today, an ASIC is always, which is the core of the router, is always around the same price. Each generation we add more ports to that, and so effectively we got a Moore's law price improvement happening where that ASIC stays the same price, you just keep adding ports. >> So, I got to jump in and ask ya about Open Compute, last year you said it's good I guess, I'm a fan, but we do our own thing, still the case? >> Yeah, absolutely. >> Still the case, okay doing your own thing, and just watching Open Compute which is a like a fair for geeks. >> Open Compute's very cool, the thing is, what's happening in our industry right now is hyper-specialization, instead of buying general purpose hardware that's good for a large number of customers, we're buying hardware that's targeted to a specific workload, a specific service, and so, we're not--I love what happens with Open Compute, 'cause you can learn from it, it's really good stuff, but it's not what we use; we want to target our workloads precisely. >> Yeah, that was actually the title of the article I wrote from everything I learned from you last year was: hyper-specialization is your secret sauce, so. You also said earlier this week that we should watch the mobile suppliers, and that's where service should be in the future, but I heard a, somebody sent me a quote from you that said: unfortunately ARM is not moving quite fast enough to keep up with where Intel's going, where do you see, I know you're a fan of some of the chip manufacturers, where's that moving? >> What I meant with watch ARM and understanding where servers are going, sorry, not ARM, watch mobile and understand where servers is going is: power became important in mobile, power becomes important in servers. Most functionalities being pulled up on chip, on mobile, same thing's happening in server land, and so-- >> What you're sayin' is mobile's a predictor >> Predicting. >> of the trends in the data center, >> Exactly, exactly right. >> Because of the challenges with the form factor. >> It's not so much the form factor, but the importance of power, and the importance of, of, well, density is important as well, so, it turns out the mobile tends to be a few years ahead, but all the same kinds of innovations that show up there we end up finding them in servers a few years later. >> Alright, so James, we've been, at Wikibon have a strong background in the storage world, and David Floyer our CTO said: one of the biggest challenges we had with databases is they were designed to respond to disk, and therefore there were certain kind of logging mechanisms in place. >> It's a good point. >> Can you talk a little bit about what you've done at Amazon with Aurora, and why you're fundamentally changing the underlying storage for that? >> Yeah, Aurora is applying modern database technology to the new world, and the new world is: SSDs at the base, and multiple availability zones available, and so if you look closely at Aurora you'll see that the storage engine is actually spread over multiple availability zones, and, what was mentioned in the keynote, it's a log-structured store. Log-structured stores work very very nicely on SSDs, they're not wonderful choices on spinning magnetic media. So this, what we're optimized for is SSDs, and we're not running it on spinning disk at all. >> So I got to ask you about the questions we're seeing in the crowd, so you guys are obviously doing great on the scale side, you've got the availability zones which makes a lot of sense certainly the Germany announcement, with the whole Ireland/EU data governance thing, and also expansion is great. But the government is moving fast into some enterprises, >> It's amazing. >> And so, we were talking about that last night, but people out there are sayin' that's great, it's a private cloud, the governments implementing a private cloud, so you agree, that's a private cloud or is that a public-- >> (laughing) It's not a private cloud; if you see Amazon involved, it's not a private cloud. Our view of what we're good at, and the advantages cloud brings to market are: we run a very large fleet of servers in every region, we provide a standard set of services in all those regions, it's completely different than packaged software. What the CIA has is another AWS region, it happens to be on their site, but it is just another AWS region, and that's the way they want it. >> Well people are going to start using that against you guys, so start parsing, well if it's private, it's only them then it's private, but there's some technicalities, you're clarifying that. >> It's definitely not a private cloud, the reason why we're not going to get involved with doing private clouds is: product software is different, it's innefficient, when you deliver to thousands of customers, you can't make some of the optimizations that we make. Because we run the same thing everywhere, we actually have a much more reliable product, we're innovating more quickly, we just think it's a different world. >> So James, you've talked a lot that scale fundamentally changes the way you architect and build things; Amazon's now got over a billion customers, and it's got so many services, just adding more and more, Wikibon, actually Dave Vellante, wrote a post yesterday said that: we're trying to fundamentally change the economic model for enterprise IT, so that services are now like software, when Microsoft would print an extra disk it didn't cost anything. When you're building your environment, is there more strain on your environment for adding that next thousand customers or that next big service or, did it just, do you have the substrate built that's going to help it grow for the future? >> It's a good question, it varies on the service. Usually what happens is we get better year over year over year, and what we find is, once you get a service to scale, like S3 is definitely at scale, then growth, I won't say it's easy, but it's easier to predict because you're already on a large base, and we already know how to do it fairly well. Other services require a lot more thought on how to grow it, and end up being a lot more difficult. >> So I got some more questions for ya, go on to some of the personal questions I want to ask you. Looking at this booth right here, it's Netflix guys right there, I love that service, awesome founder, just what they do, just a great company, and I know they're a big customer. But you mentioned networks, so at the Google conference we went to, Google's got some chops, they have a developer community rockin' and rollin', and then it's pretty obvious what they're doin', they're not tryin' to compete with Amazon because it's too much work, but they're goin' after the front end developer, Rails, whatnot, PHP, and really nailing the back end transport, you see it appearing, really going after to enable a Netflix, these next generation companies, to have the backbone, and not be reliant on third party networks. So I got to ask you, so as someone who's a tinkerer, a mechanic if you will of the large scale stuff, you got to get rid of that middleman on the network. What's your plans, you going to do peering? Google's obviously telegraphing they're comin' down that road. Do you guys meet their objective? Same product, better, what's your strategy? >> Yeah, it's a great question. The reason why we're running private links between our regions is the same reason that Google is, it's lower cost, that's good, it's much, much lower latency, that's really good, and it's a lot less jitter, and that's extremely important, and so it's private links, peering, customers direct connecting, that's all the reality of a modern cloud. >> And you see that, and do you have to build that in? Almost like you want to build your own chips, I'd imagine on the mobile side with the phone, you can see that, everyone's building their own chips. You got to have your own network stuff. Is that where you guys see the most improvement on the network side? Getting down to that precise hyper-specialized? >> We're not doing our own chips today, and we don't, in the networking world, and we don't see that as being a requirement. What we do see as a requirement is: we're buying our own ASICs, we're doing our own designs, we're building our own protocol stack; that's delivering great value, and that is what's deployed, private networking's deployed in all of our data centers now >> Yeah, I mean, James I wonder, you must look at Google, they do have an impressive network, they've got the undersea cables, is there anything you, that you look at them and saying: we need to move forward and catch up to them on certain, in certain pieces of the network? >> I don't think so, I think when you look at any of the big providers, they're all mature enough that they're doing, at that level, I think what we do has to be kind of similar. If private links are a better solution, then we're all going to do it, I mean. >> It makes a lot of sense, 'cause it, the impact on inspection, throttling traffic, that just creates uncertainty, so. I'm a big fan, obviously, of that direction. Alright, now a personal question. So, in talking to your wife last night, getting to know you over the years here, and Stu is obviously a big fan. There's a huge new generation of engineers coming into the market, Open Compute, I bring that up because it's such a great initiative, you guys obviously have your own business reasons to do your own stuff, I get that. But there's a whole new culture of engineering coming out, a new home brew computer club is out there forming right now my young son makes his own machines, assembling stuff. So, you're an inspiration to that whole group, so I would like you to share just some commentary to this new generation, what to do, how to approach things, what you've learned, how do you come over, on top of failure, how do you resolve that, how do you always grow? So, share some personal perspective. >> Yeah, it's an interesting question. >> I know you're humble, but, yeah. >> Interesting question. I think being curious is the most important thing possible, if anybody ever gets an opportunity to meet somebody that's the top of any business, a heart surgeon, a jet engine designer, an auto mechanic, anyone that's in the top of their business is always worth meeting 'cause you can always learn from them. One of the cool things that I find with my job is: because it spans so many different areas, it's amazing how often I'll pickup a tidbit one day talking to an expert sailor, and the next day be able to apply that tidbit, or that idea, solving problems in the cloud. >> So just don't look for your narrow focus, your advice is: talk to people who are pros, in whatever their field is, there's always a nugget. >> James a friend of mine >> Stay curious! >> Steve Todd, he actually called that Venn diagram innovation, where you need to find all of those different pieces, 'cause you're never going to know where you find the next idea. So, for the networking guys, there's a huge army of CCIEs out there, some have predicted that if you have the title administrator in your name, that you might be out of a job in five years. What do you recommend, what should they be training on, what should they be working toward to move forward to this new world? >> The history of computing is one of the-- a level of abstraction going up, never has it been the case those jobs go away, the only time jobs have ever gone away is when someone stated a level of abstraction that just wasn't really where the focus is. We need people taking care of systems, as the abstraction level goes up, there's still complexity, and so, my recommendation is: keep learning, just keep learning. >> Alright so I got to ask you, the big picture now, ecosystems out here, Oracle, IBM, these big incumbents, are looking at Amazon, scratching their head sayin': it's hard for us to change our business to compete. Obviously you guys are pretty clear in your positioning, what's next, outside of the current situation, what do you look at that needs to be built out, besides the network, that you see coming around the corner? And you don't have to reveal any secrets, just, philosophically, what's your vision there? >> I think our strategy is maybe a little bit, definitely a little bit different from some of the existing, old-school providers. One is: everyone's kind of used to, Amazon passes on value to customers. We tend to be always hunting and innovating and trying to lower costs, and passing on the value to customers, that's one thing. Second one is choice. I personally choose to run my XQL because I like the product I think it's very good value, some of our customers want to run Oracle, some of our customers want to run my XQL, and we're absolutely fine doing that, some people want to run SQL server. And so, the things that kind of differentiate us is: enterprise software hasn't dropped prices, ever, and that's just the way we were. Enterprise software is not about choice, we're all about choice. And so I think those are the two big differences, and I think those ones might last. >> Yeah, that's a good way to look at that. Now, back to the IT guy, let's talk about the CIO. Scratchin' his head sayin': okay, I got this facilities budget, and it's kind of the-- I talked to once CIO, hey says: I spend more time planning meetings around facilities, power, and cooling, than anything else on innovation, so. They have challenges here, so what's your advice, as someone who's been through a lot of engineering, a lot of large scale, to that team of people on power and cooling to really kind of go to the next level, and besides just saying okay throw some pots out there, or what not, what should they be doing, what's their roadmap? >> You mean the roadmap for doing a better job of running their facilities? >> Yeah, well there's always pressure for density, there's power's a sacred (laughs) sacred resource right now, I mean power is everything, power's the new oil, so, power's driving everything, so, they have to optimize for that, but you can't generate more power, and space, so, they want smaller spaces, and more efficiency. >> The biggest gains that are happening right now, and the biggest innovations that have been happening over the last five years in data centers is mostly around mechanical systems, and driving down the cost of cooling, and so, that's one odd area. Second one is: if you look closely at servers you'll see that as density goes up, the complexity and density of cooling them goes up. And so, getting designs that are optimized for running at higher temperatures, and certified for higher temperatures, is another good step, and we do both. >> So, James, there's such a diverse ecosystem here, I wonder if you've had a chance to look around? Anything cool outside of what Amazon is doing? Whether it's a partner, some startup, or some interesting idea that's caught your attention at the show. >> In fact I was meeting with western--pardon me, Hitachi Data Systems about three days ago, and they were describing some work that was done by Cycle Computing, and several hundred thousand doors-- >> We've had Cycle-- >> Jason came on. >> Oh, wow! >> Last year, we, he was a great guest. >> No, he was here too, just today! >> Oh, we got him on? Okay. >> So Hitachi's just, is showing me some of what they gained from this work, and then he showed me his bill, and it was five thousand six hundred and some dollars, for running this phenomenally big, multi-hundred thousand core project, blew me away, I think that's phenomenal, just phenomenal work. >> James, I really appreciate you coming in, Stu and I really glad you took the time to spend with our audience and come on theCUBE, again a great, pleasurable conversation, very knowledgeable. Stay curious, and get those nuggets of information, and keep us informed. Thanks for coming on theCUBE, James Hamilton, Distinguished Engineer at Amazon doing some great work, and again, the future's all about making it smaller, faster, cheaper, and passing those costs, you guys have a great strategy, a lot of your fans are here, customers, and other engineers. So thanks for spending time, this is theCUBE, I'm John Furrier with Stu Miniman, we'll be right back after this short break. (soft harmonic bells)