(bright upbeat music) >> Welcome to theCUBE's continuing coverage of AMD's fourth generation EPYC launch, along with the way that Dell has integrated this technology into its PowerEdge server lines. We're in for an interesting conversation today. Today, I'm joined by Dilip Ramachandran, Senior Director of Marketing at AMD, and Juergen Zimmermann. Juergen is Principal SAP Solutions Performance Benchmarking Engineer at Dell. Welcome, gentlemen. >> Welcome. >> Thank you David, nice to be here. >> Nice to meet you too, welcome to theCUBE. You will officially be CUBE alumni after this. Dilip, let's start with you. What's this all about? Tell us about AMD's recent launch and the importance of it. >> Thanks, David. I'm excited to actually talk to you today, AMD, at our fourth generation EPYC launch last month in November. And as part of that fourth generation EPYC launch, we announced industry-leading performance based on 96 cores, based on Zen 4 architecture. And new interfaces, PCIe Gen 5, as well as DDR5. Incredible amount of memory bandwidth, memory capacity supported, and a whole lot of other features as well. So we announced this product, we launched it in November last month. And we've been closely working with Dell on a number of benchmarks that we'd love to talk to you more about today. >> So just for some context, when was the last release of this scale? So when was the third generation released? How long ago? >> The third generation EPYC was launched in Q1 of 2021. So it was almost 18 to 24 months ago. And since then we've made a tremendous jump, the fourth generation EPYC, in terms of number of cores. So third generation EPYC supported 64 cores, fourth generation EPYC supports 96 cores. And these are new cores, the Zen 4 cores, the fourth generation of Zen cores. So very high performance, new interfaces, and really world-class performance. >> Excellent. Well, we'll go into greater detail in a moment, but let's go to Juergen. Tell us about the testing that you've been involved with to kind of prove out the benefits of this new AMD architecture. >> Yeah, well, the testing is SAP Standard Performance benchmark, the SAP SD two tier. And this is more or less a industry standard benchmark that is used to size your service for the needs of SAP. Actually, SAP customers always ask the vendors about the SAP benchmark and the SAPS values of their service. >> And I should have asked you before, but give us a little bit of your background working with SAP. Have you been doing this for longer than a week? >> Yeah, yeah, definitely, I do this for about 20 years now. Started with Sun Microsystems, and interestingly in the year 2003, 2004, I started working with AMD service on SAP with Linux, and afterwards parted the SAP application to Solaris AMD, also with AMD. So I have a lot of tradition with SAP and AMD benchmarks, and doing this ever since then. >> So give us some more detail on the results of the recent testing, and if you can, tell us why we should care? >> (laughs) Okay, the recent results actually also surprised myself, they were so good. So I initially installed the benchmark kit, and couldn't believe that the server is just getting, or hitting idle by the numbers I saw. So I cranked up the numbers and reached results that are most likely double the last generation, so Zen 3 generation, and that even passed almost all 8-socket systems out there. So if you want to have the same SAP performance, you can just use 2-socket AMD server instead of any four or 8-socket servers out there. And this is a tremendous saving in energy. >> So you just mentioned savings in terms of power consumption, which is a huge consideration. What are the sort of end user results that this delivers in terms of real world performance? How is a human being at the end of a computer going to notice something like this? >> So actually the results are like that you get almost 150,000 users concurrently accessing the system, and get their results back from SAP within one second response time. >> 150,000 users, you said? >> 150,000 users in parallel. >> (laughs) Okay, that's amazing. And I think it's interesting to note that, and I'll probably say this a a couple of times. You just referenced third generation EPYC architecture, and there are a lot of folks out there who are two generations back. Not everyone is religiously updating every 18 months, and so for a fair number of SAP environments, this is an even more dramatic increase. Is that a fair thing to say? >> Yeah, I just looked up yesterday the numbers from generation one of EPYC, and this was at about 28,000 users. So we are five times the performance now, within four years. Yeah, great. >> So Dilip, let's dig a little more into the EPYC architecture, and I'm specifically also curious about... You mentioned PCIe Gen five, or 5.0 and all of the components that plug into that. You mentioned I think faster DDR. Talk about that. Talk about how all of the components work together to make when Dell comes out with a PowerEdge server, to make it so much more powerful. >> Absolutely. So just to spend a little bit more time on this particular benchmark, the SAP Sales and Distribution benchmark. It's a widely used benchmark in the industry to basically look at how do I get the most performance out of my system for a variety of SAP business suite applications. And we touched upon it earlier, right, we are able to beat a performance of 4-socket and 8-socket servers out there. And you know, it saves energy, it saves cost, better TCO for the data center. So we're really excited to be able to support more users in a single server and meeting all the other dual socket and 4-socket combinations out there. Now, how did we get there, right, is more the important question. So as part of our fourth generation EPYC, we obviously upgraded our CPU core to provide much better single third performance per core. And at the socket level, you know, when you're packing 96 cores, you need to be able to feed these cores, you know, from a memory standpoint. So what we did was we went to 12 channels of memory, and these are DDR5 memory channels. So obviously you get much better bandwidth, higher speed of the memory with DDR5, you know, starting at 4,800 megahertz. And you're also now able to have more channels to be able to send the data from the memory into the CPU subsystem, which is very critical to keep the CPUs busy and active, and get the performance out. So that's on the memory side. On the data side, you know, we do have PCIe Gen five, and any data oriented applications that take data either from the PCIe drives or the network cards that utilize Gen five that are available in the industry today, you can actually really get data into the system through the PCIe I/O, either again, through the disk, or through the net card as well. So those are other ways to actually also feed the CPU subsystem with data to be processed by the CPU complex. So we are, again, very excited to see all of this coming together, and as they say, proof's in the pudding. You know, Juergen talked about it. How over generation after generation we've increased the performance, and now with our fourth generation EPYC, we are absolutely leading world-class performance on the SAP Sales and Distribution benchmark. >> Dilip, I have another question for you, and this may be, it may be a bit of a PowerEdge and beyond question. What are you seeing, or what are you anticipating in terms of end user perception when they go to buy a new server? Obviously server is a very loose term, and they can be configured in a bunch of different ways. But is there a discussion about ROI and TCO that's particularly critical? Because people are going to ask, "Well, wait a minute. If it's more expensive than the last one that I bought, am I getting enough bang for my buck?" Is that going to be part of the conversation, especially around power and cooling and things like that? >> Yeah, absolutely. You know, every data center decision maker has to ask the question, "Why should I upgrade? Should I stay with legacy hardware, or should I go into the latest and greatest that AMD offers?" And the advantages that the new generation products bring is much better performance at much better energy consumption levels, as well as much better performance per dollar levels. So when you do the upgrade, you are actually getting, you know, savings in terms of performance per dollar, as well as saving in space because you can consolidate your work into fewer servers 'cause you have more cores. As we talked about, you have eight, you know. Typically you might do it on a four or 8-socket server which is really expensive. You can consolidate down to a 2-socket server which is much cheaper. As also for maintenance costs, it's much lower maintenance costs as well. All of this, performance, power, maintenance costs, all of that translate into better TCO, right. So lower all of these, high performance, lower power, and then lower maintenance costs, translate to much better TCO for the end user. And that's an important equation that all customers pay attention to. and you know, we love to work with them and demonstrate those TCO benefits to them. >> Juergen, talk to us more in general about what Dell does from a PowerEdge perspective to make sure that Dell is delivering the best infrastructure possible for SAP. In general, I mean, I assume that this is a big responsibility of yours, is making sure that the stuff runs properly and if not, fixing it. So tell us about that relationship between Dell and a SAP. >> Yeah, for Dell and SAP actually, we're more or less partners with SAP. We have people sitting in SAP's Linux lab, and working in cooperative with SAP, also with Linux partners like SUSE and Red Hat. And we are in constant exchange about what's new in Linux, what's new on our side. And we're all a big family here. >> So when the new architecture comes out and they send it to Juergen, the boys back at the plant as they say, or the factory to use Formula One terms, are are waiting with baited breath to hear what Juergen says about the results. So just kind of kind of recap again, you know, the specific benchmarks that you were running. Tell us about that again. >> Yeah, the specific benchmark is the SAP Sales and Distribution benchmark. And for SAP, this is the benchmark that needs to be tested, and it shows the performance of the whole system. So in contrast to benchmarks that only check if the CPU is running, very good, this test the whole system up from the network stack, from the storage stack, the memory, subsystem, and the OS running on the CPUs. >> Okay, which makes perfect sense, since Dell is delivering an integrated system and not just CPU technology. You know, on that subject, Dilip, do you have any insights into performance numbers that you're hearing about with Gen four EPYC for other database environments? >> Yeah, we have actually worked together with Dell on a variety of benchmarks, both on the latest fourth generation EPYC processors as well as the preceding one, the third generation EPYC processors. And published a bunch of world records on database, particularly I would say TPC-H, TPCx-V, as well as TPCx-HS and TPCx-IoT. So a number of TPC related benchmarks that really showcase performance for database and related applications. And we've collaborated very closely with Dell on these benchmarks and published a number of them already, and you know, a number of them are world records as well. So again, we're very excited to collaborate with Dell on the SAP Sales and Distribution benchmark, as well as other benchmarks that are related to database. >> Well, speaking of other benchmarks, here at theCUBE we're going to be talking to actually quite a few people, looking at this fourth generation EPYC launch from a whole bunch of different angles. You two gentlemen have shed light on some really good pieces of that puzzle. I want to thank you for being on theCUBE today. With that, I'd like to thank all of you for joining us here on theCUBE. Stay tuned for continuing CUBE coverage of AMD's fourth generation EPYC launch, and Dell PowerEdge strategy to leverage it.

(bright music) >> Hello everyone and welcome back to theCUBE's live coverage here in San Francisco, California for AWS Summit 2022. I'm John Furrier, your host of theCUBE. Two days of coverage, AWS Summit 2022 in New York city's coming up this summer, we'll be there as well. Events are back. theCUBE is back. Of course, with theCUBE virtual, CUBE hybrid, the cube.net. Check it out, a lot of content this year more than ever. A lot more cloud data, cloud native, modern applications, all happening. Got a great guest here. Jeremy Burton, CUBE alumni, CEO of Observe, Inc. in the middle of all the cloud scale, big data, observability. Jeremy, great to see you. Thanks for coming on. >> Always great to come and talk to you on theCUBE man. It's been a few years. >> Well, you got your hands. You're in the trenches with great startup, good funding, great board, great people involved in the observability space, hot area, but also you've been a senior executive. President of Dell, EMC, 11 years ago you had a vision and you actually had an event called cloud meets big data. >> Jeremy: Yeah. >> And it's here. You predicted it 11 years ago. Look around, it's cloud meets big data. >> Yeah, the cloud thing I think was probably already a thing, but the big data thing I do claim credit for sort of catching that bus early, We were on the bus early and I think it was only inevitable. Like if you could bring the economics and the compute of cloud to big data, you could find out things you could never possibly imagine. >> So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved. The board level, the founders, the people there, cloud, Amazon, what's going on here? You're doing a startup as the CEO at the helm, chief of Observe, Inc., which is an observability, which is to me in the center of this confluence of data, engineering, large scale integrations, data as code, integrating into applications. It's a whole another world developing, like you see with Snowflake, it means Snowflake is super cloud as we call it. So a whole nother wave is here. What's this wave we're on? How would you describe the wave? >> Well, a couple of things. People are, I think, riding more software than ever before. Why? Because they've realized that if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think more applications now than any point, not just ever, but the mid nineties. I always looked at as the golden age of application development. Now, back then people were building for Windows. Well now they're building for things like, AWS is now the platform. So you've got all of that going on. And then at the same time, the side effect of these applications is they generate data and lots of data and the transactions, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can I understand who my best customers are? What I sell today? If people came to my website and didn't buy, then why not? Where did they drop off? All of that they want to analyze. And the answers are all in the data. The question is, can you understand it? >> In our last startup showcase, we featured data as code. One of the insights that we got out of that, and I want to get your opinion on or reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse, and then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more effort to say, let's go look at the data, 'cause now machine learning is getting better. Not just train once, they're iterating. This notion of iterating and then pivoting, iterating and pivoting That's a Silicon Valley story. That's like how startups were, but now you're seeing data being treated the same way. So now you have this data concept that's now part of a new way to create more value for the apps. So this whole new cycle of data being reused and repurposed, then figure it out. >> Yeah, yeah, I'm a big fan of, years ago, just an amazing guy, Andy McAfee, at the MIT labs. I spent time with and he had this line, which still sticks to me this day, which is look, he said, I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And this has going back 10 years when he was saying these kind of things and certainly, research is on the forefront. But I think starting to see that mindset of the MIT research be mainstream in enterprises. They're realizing that, yeah, it is about the data. If I can better understand my data better than competitor, then I've got an advantage. And so the question is how? What technologies and what skills do I need in my organization to allow me to do that? >> So let's talk about Observe, Inc. You're the CEO. Given you've seen the waves before, you're in the front lines of observability, which again is in the center of all this action. What's going on with the company? Give a quick minute to explain Observe for the folks who don't know what you guys do. What's the company doing? What's the funding status? What's the product status? And what's the customer status? >> Yeah, so we realized, a handful of years ago, let's say five years ago. Look, the way people are building applications is different. They're way more functional. They change every day. But in some respects there are a lot more complicated. They're distributed, microservices architectures. And when something goes wrong, the old way of troubleshooting and solving problems was not going to fly because you had so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So that's observability. It's actually a term that goes back to the 1960s. It was, a guy called, like everything in tech, it's a reinvention of something from years gone by, but there's a guy called Rudy Coleman in 1960s, kind of term. And the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for the best part of four years now. It took us three years just to build the product. I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You need a lot of functionality to have something that's credible with a customer. So yeah, this last year, we did our first year selling. We've got about 40 customers now. We got great investors Sutter Hill Ventures. Mike Speiser who was really the first guy in the Snowflake and the initial investor. We're fortunate enough to have Mike on our board. And part of the Observe story is closely knit with Snowflake because all of that telemetry data, we store in there. >> So I want to pivot to that. Mike Speiser, Snowflake, Jeremy Burton, theCUBE kind of same thinking. This idea of a super cloud or what Snowflake became. >> Jeremy: Yeah. >> Snowflake is massively successful on top of AWS. And now you're seeing startups and companies build on top of Snowflake. >> Jeremy: Yeah. >> So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, like as Jerry Chen in Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with Snowflake's. So as a startup, what's your view on building on top of say a Snowflake or an AWS, because again, you got to go where the data is. You need all the data. >> Jeremy: Yeah. >> What's your take on that? >> Having enough gray hair now. Again, in tech, I think if you want to predict the future, look at the past. And 20 years ago, 25 years ago, I was at a smaller company called Oracle. And an Oracle was the database company and their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms. One, Windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And then that was the ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years, gray hairs, the platform isn't the operating system anymore. The platform is AWS, Google cloud. I probably look around if I say that in. >> It's okay. But Hyperscale. >> Yeah. >> CapEx built out. >> That is the new platform. And then Snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say the big data world, what Oracle did for the relational data world way back 25 years ago. And then there are folks like us come along and of course my ambition would be, look, if we can be as successful as an SAP building on top of Snowflake, as they were on top of Oracle, then we'd probably be quite happy. >> So you're building on top of Snowflake? >> We're building on top of Snowflake a hundred percent. And I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that's a risk. >> Are you still on the board? >> Yeah, I'm still on the board. Yeah. That's a risk I'm prepared to take. I am long on Snowflake. >> It sounds, well, you're in a good spot. Stay on the board then you'll know as going on. Okay, seriously, this is a real dynamic. >> Jeremy: It is. >> It's not a one off. >> Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS, it is an order of magnitude more than Microsoft was 25 years ago with windows. And so I believe the opportunity for folks like Snowflake and folks like Observe, it's an order magnitude more than it was for the Oracle and the SAPs of the old world. >> Yeah, and I think this is something that this next generation of entrepreneurship is the go big scenario is you got to be on a platform. >> Yeah and it's quite easy. >> Or be the platform, but it's hard. There's only like how many seats are at that table left. >> Well, value migrates up over time. So when the cloud thing got going, there were probably 10, 20, 30, rack space and there's 1,000,001 infrastructure for service, platform as a service. My old employee EMC, we had Pivotal. Pivotal was a platform as a service. You don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to extract a real business, you got to move up, you got to add value, you got to build databases, then you got to build applications. >> It's interesting. Moving from the data center to the cloud was a dream for starters 'cause they didn't have to provision the CapEx. Now the CapEx is in the cloud. Then you build on top of that, you got Snowflake. Now you got on top of that. >> The assumption is almost that compute and storage is free. I know it's not quite free. >> Yeah, it's almost free. >> But as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've got to get into. >> And I think the platform enablement to value. So if I'm an entrepreneur, I'm going to get a serious multiple of value in what I'm paying. Most people don't even blink at their AWS bills unless they're like massively huge. Then it's a repatriation question or whatever discount question. But for most startups or any growing company, the Amazon bill should be a small factor. >> Yeah, a lot of people ask me like, look, you're building on Snowflake. You're going to be paying their money. How does that work with your business model? If you're paying them money, do you have a viable business? And it's like, well, okay. We could build a database as well in Observe, but then I've got half the development team working on something that will never be as good as Snowflake. And so we made the call early on that, no, we want to innovate above the database. Snowflake are doing a great job of innovating on the database and the same is true with something like Amazon, like Snowflake could have built their own cloud and their own platform, but they didn't. >> Yeah and what's interesting is that Dave Vellante and I have been pointing this out and he's obviously more on Snowflake. I've been looking at Databricks and the same dynamics happening. The proof is the ecosystem. >> Yeah. >> If you look at Snowflake's ecosystem right now and Databricks, it's exploding. The shows are selling out. This floor space is booked. That's the old days at VMware. The old days at AWS. >> One and for Snowflake and any platform provider, it's a beautiful thing because we build on Snowflake and we pay their money. They don't have to sell to us. And we do a lot of the support. And so the economics work out really, really well if you're a platform provider and you've got a lot of ecosystems. >> And then also you get a trajectory of economies of scale with the institutional knowledge of Snowflake, integrations, new products, you're scaling and step function with them. >> Yeah, we manage 10 petabytes of data right now. When I arrived at EMC in 2010, we had one petabyte customer. And so at Observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so being able to rely on a platform that can manage that is invaluable. >> Well, Jeremy, great conversation. Thanks for sharing your insights on the industry. We got a couple minutes left, put a plug in for Observe. What do you guys do? You got some good funding, great partners. I don't know if you can talk about your POC customers, but you got a lot of high ends folks that are working with you. You get in traction. >> Yeah >> Scales around the corner sounds like. Is that where you at? Pre-scale? >> We've got a big announcement coming up in two or three weeks. We've got new funding, which is always great. The product is really, really close. I think, as a startup, you always strive for market fit, at which point can you just start hiring salespeople and the revenue keeps going. We're getting pretty close to that right now. We've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, which is our sweet spot to begin with, but we're starting to get some really interesting enterprise type customers. We're F5 networks. We're POC in right now with Capital One. We've got some interesting news around Capital One coming up. I can't share too much, but it's going to be exciting. And like I said, Sutter Hill continue to stick. >> And I think Capital One's a big Snowflake customer as well, right? >> They were early and one of the things that attracted me to Capital One was they were very, very good with Snowflake early on and they put Snowflake in a position in the bank where they thought that snowflake could be successful. And today that is one of Snowflake's biggest accounts. >> Capital One, very innovative cloud. Obviously, AWS customer and very innovative. certainly in the CISO and CIO. On another point on where you're at. So you're pre-scale meaning you're about to scale. >> Jeremy: Right. >> So you got POCs. What's that trajectory look like? And you see around the corner, what's going on? What's around the corner that you're going to hit the straight and narrow and gas it fast? >> Yeah, the key thing for us is we got to get the product right. The nice thing about having a guy like Mike Speiser on the board is he doesn't obsess about revenue at this stage. His questions at the board are always about like, is the product right? Is the product right? Have you got the product right? 'Cause we know when the product's right, we can then scale the sales team and the revenue will take care of itself. So right now all the attention is on the product. This year, the exciting thing is we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the New Relics and AppDynamics, the last generation of APM tools. You're going to be able to do that within Observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one 'cause we complete the trifecta, the logs. >> What's the secret sauce of observe if you put it into a sentence, what's the secret sauce? >> I think, an amazing founding engineering team, number one. At the end of the day, you have to build an amazing product and you have to solve a problem in a different way and we've got great long term investors. And the biggest thing our investors give is, actually it's not just money, it gives us time to get the product right. Because if we get the product right, then we can get the growth. >> Got it. Final question while I got you here. You've been on the enterprise business for a long time. What's the buyer landscape out there? You got people doing POCs, Capital One scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Obviously, we're seeing people go in and dip into the startup pool because new ways to refactor their business, restructure. So a lot of happening in cloud. What's the criteria? How are enterprises engaging in with startups? >> Yeah, enterprises, they know they've got to spend money transforming the business. I almost feel like my old Dell or EMC self there, but what we were saying five years ago is happening. Everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or take a bet on new technology in order to help them do that. So I think you've got buyers that A, have money, B, are prepared to take risks, and it's a race against time to get their offerings in this new digital footprint. >> Final, final question. What's the state of AWS? Where do you see them going next? Obviously, they're continuing to be successful. How does cloud 3.0? Or they always say it's day one, but it's maybe more like day 10, but what's next for AWS? Where do they go from here? Obviously, they're doing well and they're getting bigger and bigger. >> Yeah, it's an amazing story. We are on AWS as well. And so I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They have an early leads. And if you look at where, maybe the likes of Microsoft lost the plot in the late nineties, it was they stopped really caring about developers and the folks who are building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they have an amazing head start. And if they did more, if they do more than that, that's what's going to keep this juggernaut rolling for many years to come. >> They got the Silicon and they got the Stack developing. Jeremy Burton inside theCUBE, great resource for commentary, but also founding with the CEO of a company called Observe, Inc. In the middle of all the action and the board of Snowflake as well. Great startup. Thanks for coming on theCUBE. >> Always a pleasure. >> Live from San Francisco's theCUBE. I'm John Furrier, your host. Stay with us. More coverage from San Francisco, California after the short break. (soft music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante nvidia wants to completely transform enterprise computing by making data centers run 10x faster at one tenth the cost and video's ceo jensen wang is crafting a strategy to re-architect today's on-prem data centers public clouds and edge computing installations with a vision that leverages the company's strong position in ai architectures the keys to this end-to-end strategy include a clarity of vision massive chip design skills a new arm-based architecture approach that integrates memory processors i o and networking and a compelling software consumption model even if nvidia is unsuccessful at acquiring arm we believe it will still be able to execute on this strategy by actively participating in the arm ecosystem however if its attempts to acquire arm are successful we believe it will transform nvidia from the world's most valuable chip company into the world's most valuable supplier of integrated computing architectures hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll explain why we believe nvidia is in the right position to power the world's computing centers and how it plans to disrupt the grip that x86 architectures have had on the data center for decades the data center market is in transition like the universe the cloud is expanding at an accelerated pace no longer is the cloud an opaque set of remote services i always say somewhere out there sitting in a mega data center no rather the cloud is extending to on-premises data centers data centers are moving into the cloud and they're connecting through adjacent locations that create hybrid interactions clouds are being meshed together across regions and eventually will stretch to the far edge this new definition or view of cloud will be hyper distributed and run by software kubernetes is changing the world of software development and enabling workloads to run anywhere open apis external applications expanding the digital supply chains and this expanding cloud they all increase the threat surface and vulnerability to the most sensitive information that resides within the data center and around the world zero trust has become a mandate we're also seeing ai being injected into every application and it's the technology area that we see with the most momentum coming out of the pandemic this new world will not be powered by general purpose x86 processors rather it will be supported by an ecosystem of arm-based providers in our opinion that are affecting an unprecedented increase in processor performance as we have been reporting and nvidia in our view is sitting in the poll position and is currently the favorite to dominate the next era of computing architecture for global data centers public clouds as well as the near and far edge let's talk about jensen wang's clarity of vision for this new world here's a chart that underscores some of the fundamental assumptions that he's leveraging to expand his market the first is that there's a lot of waste in the data center he claims that only half of the cpu cores deployed in the data center today actually support applications the other half are processing the infrastructure all around the applications that run the software defined data center and they're terribly under utilized nvidia's blue field three dpu the data processing unit was described in a blog post on siliconangle by analyst zias caravala as a complete mini server on a card i like that with software defined networking storage and security acceleration built in this product has the bandwidth and according to nvidia can replace 300 general purpose x86 cores jensen believes that every network chip will be intelligent programmable and capable of this type of acceleration to offload conventional cpus he believes that every server node will have this capability and enable every packed of every packet and every application to be monitored in real time all the time for intrusion and as servers move to the edge bluefield will be included as a core component in his view and this last statement by jensen is critical in our opinion he says ai is the most powerful force of our time whether you agree with that or not it's relevant because ai is everywhere an invidious position in ai and the architectures the company is building are the fundamental linchpin of its data center enterprise strategy so let's take a look at some etr spending data to see where ai fits on the priority list here's a set of data in a view that we often like to share the horizontal axis is market share or pervasiveness in the etr data but we want to call your attention to the vertical axis that's really really what really we want to pay attention today that's net score or spending momentum exiting the pandemic we've seen ai capture the number one position in the last two surveys and we think this dynamic will continue for quite some time as ai becomes the staple of digital transformations and automations an ai will be infused in every single dot you see on this chart nvidia's architectures it just so happens are tailor made for ai workloads and that is how it will enter these markets let's quantify what that means and lay out our view of how nvidia with the help of arm will go after the enterprise market here's some data from wikibon research that depicts the percent of worldwide spending on server infrastructure by workload type here are the key points first the market last year was around 78 billion dollars worldwide and is expected to approach 115 billion by the end of the decade this might even be a conservative figure and we've split the market into three broad workload categories the blue is ai and other related applications what david floyer calls matrix workloads the orange is general purpose think things like erp supply chain hcm collaboration basically oracle saps and microsoft work that's being supported today and of course many other software providers and the gray that's the area that jensen was referring to is about being wasted the offload work for networking and storage and all the software defined management in the data centers around the world okay you can see the squeeze that we think compute infrastructure is gonna gonna occur around that orange area that general-purpose workloads that we think is going to really get squeezed in the next several years on a percentage basis and on an absolute basis it's really not growing nearly as fast as the other two and video with arm in our view is well positioned to attack that blue area and the gray area those those workload offsets and the new emerging ai applications but even the orange as we've reported is under pressure as for example companies like aws and oracle they use arm-based designs to service general purpose workloads why are they doing that cost is the reason because x86 generally and intel specifically are not delivering the price performance and efficiency required to keep up with the demands to reduce data center costs and if intel doesn't respond which we believe it will but if it doesn't act arm we think will get 50 percent of the general purpose workloads by the end of the decade and with nvidia it will dominate the blue the ai and the gray the offload work when we say dominate we're talking like capture 90 percent of the available market if intel doesn't respond now intel they're not just going to sit back and let that happen pat gelsinger is well aware of this in moving intel to a new strategy but nvidia and arm are way ahead in the game in our view and as we've reported this is going to be a real challenge for intel to catch up now let's take a quick look at what nvidia is doing with relevant parts of its pretty massive portfolio here's a slide that shows nvidia's three chip strategy the company is shifting to arm-based architectures which we'll describe in more detail in a moment the slide shows at the top line nvidia's ampere architecture not to be confused with the company ampere computing nvidia is taking a gpu centric approach no surprise obvious reasons there that's their sort of stronghold but we think over time it may rethink this a little bit and lean more into npus the neural processing unit we look at what apple's doing what tesla are doing we see opportunities for companies like nvidia to really sort of go after that but we'll save that for another day nvidia has announced its grace cpu a nod to the famous computer scientist grace hopper grace is a new architecture that doesn't rely on x86 and much more efficiently uses memory resources we'll again describe this in more detail later and the bottom line there that roadmap line shows the bluefield dpu which we described is essentially a complete server on a card in this approach using arm will reduce the elapsed time to go from chip design to production by 50 we're talking about shaving years down to 18 months or less we don't have time to do a deep dive into nvidia's portfolio it's large but we want to share some things that we think are important and this next graphic is one of them this shows some of the details of nvidia's jetson architecture which is designed to accelerate those ai plus workloads that we showed earlier and the reason is that this is important in our view is because the same software supports from small to very large including edge systems and we think this type of architecture is very well suited for ai inference at the edge as well as core data center applications that use ai and as we've said before a lot of the action in ai is going to happen at the edge so this is a good example of leveraging an architecture across a wide spectrum of performance and cost now we want to take a moment to explain why the moved arm-based architectures is so critical to nvidia one of the biggest cost challenges for nvidia today is keeping the gpu utilized typical utilization of gpu is well below 20 percent here's why the left hand side of this chart shows essentially racks if you will of traditional compute and the bottlenecks that nvidia faces the processor and dram they're tied together in separate blocks imagine there are thousands thousands of cores in a rack and every time you need data that lives in another processor you have to send a request and go retrieve it it's very overhead intensive now technologies like rocky are designed to help but it doesn't solve the fundamental architectural bottleneck every gpu shown here also has its own dram and it has to communicate with the processors to get the data i.e they can't communicate with each other efficiently now the right hand side side shows where nvidia is headed start in the middle with system on chip socs cpus are packaged in with npus ipu's that's the image processing unit you know x dot dot dot x pu's the the alternative processors they're all connected with sram which is think of that as a high speed layer like an layer one cache the os for the system on a chip lives inside of this and that's where nvidia has this killer software model what they're doing is they're licensing the consumption of the operating system that's running this system on chip in this entire system and they're affecting a new and really compelling subscription model you know maybe they should just give away the chips and charge for the software like a razer blade model talk about disruptive now the outer layer is the the dpu and the shared dram and other resources like the ampere computing the company this time cpus ssds and other resources these are the processors that will manage the socs together this design is based on nvidia's three chip approach using bluefield dpu leveraging melanox that's the networking component the network enables shared dram across the cpus which will eventually be all arm based grace lives inside the system on a chip and also on the outside layers and of course the gpu lives inside the soc in a scaled-down version like for instance a rendering gpu and we show some gpus on the outer layer as well for ai workloads at least in the near term you know eventually we think they may reside solely in the system on chip but only time will tell okay so you as you can see nvidia is making some serious moves and by teaming up with arm and leaning into the arm ecosystem it plans to take the company to its next level so let's talk about how we think competition for the next era of compute stacks up here's that same xy graph that we love to show market share or pervasiveness on the horizontal tracking against next net score on the vertical net score again is spending velocity and we've cut the etr data to capture players that are that are big in compute and storage and networking we've plugged in a couple of the cloud players these are the guys that we feel are vying for data center leadership around compute aws is a very strong position we believe that more than half of its revenues comes from compute you know ec2 we're talking about more than 25 billion on a run rate basis that's huge the company designs its own silicon graviton 2 etc and is working with isvs to run general purpose workloads on arm-based graviton chips microsoft and google they're going to follow suit they're big consumers of compute they sell a lot but microsoft in particular you know they're likely to continue to work with oem partners to attack that on-prem data center opportunity but it's really intel that's the provider of compute to the likes of hpe and dell and cisco and the odms which are the odms are not shown here now hpe let's talk about them for a second they have architectures and i hate to bring it up but remember the machine i know it's the butt of many jokes especially from competitors it had been you know frankly hpe and hp they deserve some of that heat for all the fanfare and then that they they put out there and then quietly you know pulled the machine or put it out the pasture but hpe has a strong position in high performance computing and the work that it did on new computing architectures with the machine and shared memories that might be still kicking around somewhere inside of hp and could come in handy for some day in the future so hpe has some chops there plus hpe has been known hp historically has been known to design its own custom silicon so i would not count them out as an innovator in this race cisco is interesting because it not only has custom silicon designs but its entry into the compute business with ucs a decade ago was notable and they created a new way to think about integrating resources particularly compute and networking with partnerships to add in the storage piece initially it was within within emc prior to the dell acquisition but you know it continues with netapp and pure and others cisco invests they spend money investing in architectures and we expect the next generation of ucs oh ucs2 ucs 2.0 will mark another notable milestone in the company's data center business dell just had an amazing quarterly earnings report the company grew top line revenue by around 12 percent and it wasn't because of an easy compare to last year dells is simply executing despite continued softness in the legacy emc storage business laptop the laptop demand continued to soar in dell server business it's growing again but we don't see dell as an architectural innovator per se in compute rather we think the company will be content to partner with suppliers whether it's intel nvidia arm-based partners or all of the above dell we think will rely on its massive portfolio its excellent supply chain and execution ethos to compete now ibm is notable for historical reasons with its mainframe ibm created the first great compute monopoly before it unwind and wittingly handed it to intel along with microsoft we don't see ibm necessarily aspiring to retake that compute platform mantle that once once held with mainframes rather red hat in the march to hybrid cloud is the path that we think in our view is ibm's approach now let's get down to the elephants in the room intel nvidia and china inc china is of course relevant because of companies like alibaba and huawei and the chinese chinese government's desire to be self-sufficient in semiconductor technology and technology generally but our premise here is that the trends are favoring nvidia over intel in this picture because nvidia is making moves to further position itself for new workloads in the data center and compete for intel's stronghold intel is going to attempt to remake itself but it should have been doing this seven years ago what pat gelsinger is doing today intel is simply far behind and it's going to take at least a couple years for them to really start to to make inroads in this new model let's stay on the nvidia v intel comparison for a moment and take a snapshot of the two companies here's a quick chart that we put together with some basic kpis some of these figures are approximations or they're rounded so don't stress over it too much but you can see intel is an 80 billion dollar company 4x the size of nvidia but nvidia's market cap far exceeds that of intel why is that of course growth in our view it's justified due to that growth and nvidia's strategic positioning intel used to be the gross margin king but nvidia has much higher gross margins interesting now when it comes down to free cash flow intel is still dominant as it pertains to the balance sheet intel is way more capital intensive than nvidia and as it starts to build out its foundries that's going to eat into intel's cash position now what we did is we put together a little pro forma on the third column of nvidia plus arm circa let's say the end of 2022. we think they could get to a run rate that is about half the size of intel and that can propel the company's market cap to well over half a trillion dollars if they get any credit for arm they're paying 40 billion dollars for arm a company that's you know sub 2 billion the risk is that because of the arm because the arm deal is based on cash plus tons of stock it could put pressure on the market capitalization for some time arm has 90 percent gross margins because it pretty much has a pure license model so it helps the gross margin line a little bit for this in this pro forma and the balance sheet is a swag arm has said that it's not going to take on debt to do the transaction but we haven't had time to really dig into that and figure out how they're going to structure it so we took a took a swag in in what we would do with this low interest rate environment but but take that with a grain of salt we'll do more research in there the point is given the momentum and growth of nvidia its strategic position in ai is in its deep engineering they're aimed at all the right places and its potential to unlock huge value with arm on paper it looks like the horse to beat if it can execute all right let's wrap up here's a summary look the architectures on which nvidia is building its dominant ai business are evolving and nvidia is well positioned to drive a truck right to the enterprise in our view the power has shifted from intel to the arm ecosystem and nvidia is leaning in big time whereas intel it has to preserve its current business while recreating itself at the same time this is going to take a couple of years but intel potentially has the powerful backing of the us government too strategic to fail the wild card is will nvidia be successful in acquiring arm certain factions in the uk and eu are fighting the deal because they don't want the u.s dictating to whom arm can sell its technology for example the restrictions placed on huawei for many suppliers of arm-based chips based on u.s sanctions nvidia's competitors like broadcom qualcomm at all are nervous that if nvidia gets armed they will be at a competitive disadvantage they being invidious competitors and for sure china doesn't want nvidia controlling arm for obvious reasons and it will do what it can to block the deal and or put handcuffs on how business can be done in china we can see a scenario where the u.s government pressures the uk and eu regulators to let this deal go through look ai and semiconductors you can't get much more strategic than that for the u.s military and the u.s long-term competitiveness in exchange for maybe facilitating the deal the government pressures nvidia to guarantee some feed to the intel foundry business while at the same time imposing conditions that secure access to arm-based technology for nvidia's competitors and maybe as we've talked about before having them funnel business to intel's foundry actually we've talked about the us government enticing apple to do so but it could also entice nvidia's competitors to do so propping up intel's foundry business which is clearly starting from ground zero and is going to need help outside of intel's own semiconductor manufacturing internally look we don't have any inside information as to what's happening behind the scenes with the us government and so forth but on its earning call on its earnings call nvidia said they're working with regulators that are on track to complete the deal in early 2022. we'll see okay that's it for today thank you to david floyer who co-created this episode with me and remember i publish each week on wikibon.com and siliconangle.com these episodes they're all available as podcasts all you're going to do is search breaking analysis podcast and you can always connect with me on twitter at dvalante or email me at david.valante siliconangle.com i always appreciate the comments on linkedin and in the clubhouse please follow me so you can be notified when we start a room and riff on these topics and don't forget to check out etr.plus for all the survey data this is dave vellante for the cube insights powered by etr be well and we'll see you next time [Music] you

>> Narrator: Live from San Francisco celebrating 10 years of high tech coverage, It's the Cube! Covering VM World 2019 Brought to you by VMware and its ecosystem partners >> Hello everyone and welcome to the Cube's coverage here in San Francisco, California of the VMWorld 2019. I'm John Furrier with my cohost Dave Vellante Dave, 10 years covering VMWorld since 2010, it's been quite a ride, lot of changes. >> Dave: Sure has. >> John: We're going to do a Power Panel our format we normally do it remote guests in our Palo Alto and Boston studios in person because we're here. Why not do it? Of course, Keith Townsend, CTO Advisor friend of the Cube, Cube host sometimes and Sarbjeet Johal, cloud architect cloud expert, friends on Twitter. We're always jammin' on Twitter. So we'll have to take it to the video. Guys, thanks for joining us on the Power Panel. >> Good to see you, Gents. >> Good seein' ya. >> Good to be here. >> Yeah, I, I hope we don't come to blows, Sarbjeet. I mean we've had some passionate conversations over the past couple months. >> Yeah, Santoro, yes, yes. >> John: The activity has been at an all time high. I mean, snark aside, there's real things to talk about. >> Yes. >> I mean we are talking about VMware a software company, staying with their roots. We know what happened in 2016 The Amazon relationship cleared the air so to speak, pun intended. Vcloud air kind of goes it's way stock prices go up and to the right Yeah, fluctuations happening but still financially doing well. >> Keith: Yeah. >> Customers have clarity. They're an operate. They run, they target operators not developers. We're living in a DevOps world we talk about this all the time dev and ops this is the cloud world that they want Michael Dell was on the Cube Dell Technologies owns VMware they put Pivotal on VMware moves are being made. Keith, how do you make sense of it? What's your take? You've been on the inside. >> Well, you know, VMware has a tough time. Pat came in, 2013, we remember it. He said we are going to double down on virtualization. He is literally paying the cost for that hockey stick movement VMware has had this reputation of being an operator based company Infrastructure based, you go into accounts, you're stuck in this IT Infrastructure cells movement. VMware has done awesome over the past year. Few years, I had to eat a little crow and say that the move to eject Pivotal was the right thing for the Stock but for the reputation, VMware is stuck so Pat, what, tallied up 5 billion dollars in sales, in purchases last week to get out of this motion of being stuck in the IT Infrastructure realm Will it pay off? I think it's going to be a good conversation because they're going to need those Pivotal guys to push this PKS vision of theirs. This PKS and Kubernetes vision that they have >> Well they got to figure it out but certainly it's a software world and one of the things that's interesting we were talking before we started is, they are stuck in that operator world but it's part of DevOps, Dev and Ops. This is the world that they operate in Google's cloud shows how to do it. You got SRE's run things and developers this program infrastructure is code. This is the promise of this new generation. Sarbjeet, we talk about it all the time on Twitter developers coding away not dealing with the infrastructure, that's the goal >> Yeah, traditionally, developers never sort of mucked around with infrastructure. Gradually we are moving into where developers have to take care of infrastructure themselves the teams are like two person teams we hear that all the time. They are responsible for running the show from beginning to the end. Operations are under them, it's Dev and Ops are put together, right? But I'll speak from my own personal experience with working at VMware in the past that from all the companies which are operations focused, that's HP, IBM, and Oracle to a certain extent. So portfolio and all that. And BMC, and CA, those are pure companies in the operations space, right? I think VMware is one of those which values software a lot. So it's a purely, inside the VMware it's purely software driven. But to the outside, what they produce what they have produced in the past that's all operations, right? So I think they can move that switch because of the culture and then with Pivotal acquisition I think it will make it much easier because there's some following of the Pivotal stack, if you will the only caveat I think on that side is it is kind of a little bit of interlocking-ish, right? That is one of the fears I have. >> Who's not, even RedHat these days is, locking you in. >> Yeah, you know, I pulled some interesting stat metadata from a blog post from Paul Fazzone announcing the Pivotal acquisition. He mentioned Kubernetes 22 times. He mentioned Pivotal Cloud Foundry once. So VMware is all in on this open-shift type movement I think VMware is looking at the Red shift I mean Red OpenShift acquisition by IBM and thinking, "Man, I wish we didn't have this "Sense of relationship with Pivotal "So we could have went out and bought RedHat." >> Well that's a good point about Kubernetes, I think you're right on that. And remember, we've been covering Open Stack up until about a year ago, and they changed the name it's now something else, but I remember when Open Shift wasn't doing well. >> Keith: I do too! >> And what really was a tipping point for them was they had all the elements, but it was Kubernetes that really put them in a position to take advantage of what they were trying to do and I think you're right, I think VMware sees that, now that IBM owns RedHat and Open Shift, it's clear. But I think the vSphere deal with Project Pacific points out that they want to use Kubernetes as a distraction layer for developers, and have a developer interface to vSphere. So they get the operators with vSphere, they put Kubernetes in there and they say, "Hey developers, use us." Now I think that's a hedge also against Pivotal 'cause if that horse doesn't come across the track to the finish line, you know... >> It's definitely a hedge on Containers just a finer point of what you were saying there was a slight difference in the cash outlay for RedHat, 34 billion versus the cash outlay for Pivotal was 800 million. So they picked up an 800 million dollar asset or a 4 billion dollar asset for 2.7 billion. >> Hold on, explain that because 2.7 billion was the number we reported you're saying that VMware put out only 800 million in cash, which, what's that mean? >> That's correct. So they put out 800 million in cash to the existing shareholders of Pivotal, which is a minority of the shareholders. Michael Dell owns 70% of it, VMware owns 15% of it. So they take the public shareholders get the 800 million >> John: They get taken out, yep. >> Michael Dell gets more VMware stock, so now he owns more of VMware. VMware already owns 15% of Pivotal, so for 800 million, they get Pivotal. >> So, the VMware independent shareholders get... they get diluted. >> Right. >> Did they lose out in the deal is the question and I think the thing that most people are missing in this conversation is that Pivotal has a army of developers. Regardless of whether developers focus on PCF or Kubernetes is irrelevant. VMware has a army, a services army now that they can point towards the industry and say, "We have the chops to have "The conversation around why you should "Come to us for developing." >> So I want to come back to that but just, a good question is, Do the VMware shareholders get screwed? Near term, the stock drops, right? Which is what happens, right? Pivotal was up 77% on the day that the Dow dropped 800 points. Here's where I think it makes sense, and there are some external risks. Pivotal plus Carbon Black, the combination they shelled out 2.7 billion in cash. They're going to add a billion dollars to VMware's subscription business next year. VMware trades at 5x revenue multiple, so the shareholders will, in theory, get back 5 billion. In year two, it's going to be 3 billion that they're going to add to the subscription revenue so in theory, that's 15 billion of value added. I think that goes into the thinking, so, now, are people going to flock to VMware? Are Kubernetes developers going to flock to VMware? I mean to your point, that to me, that's the value of Pivotal is they can get VMware into the developer community. 'Cause where is VMware with developers? Nobody, no developers in this audience. >> That's true. >> What are your guys' thoughts on that? >> Yeah, I think that we have to dissect the workload of applications at the enterprise level, right? There are a variety of applications, right, from SAPs Oracles of the world those are two heavyweights in the application space. And then there's a long trail of ISVs, right. And then there's homegrown applications I think where Pivotal plays a big role is the homegrown applications. When you're shipping a lot as an ISV or within your enterprise, you're writing software you're shipping applications to the user base. It could be internal for partners, for customers, right, I think that's where Pivotal plays Pivotal is pivotal, if you will. >> I think that's a good bet too, one of the things we've been pulling the CESoEs data for when we got reinforced we started pulling CESoEs in our network, and it's interesting. They're under the gun to produce security solutions and manage the vendors and do all that stuff they're all telling us, the majority of them are telling us that they're building their own stacks internally to handle the crisis and the challenge of security, which I think's a leading indicator versus the kind of slow, slower CIO which LOVES multi-anything. Multi-vendor, control, a deal with contracts CESoEs, they don't have the DOGMA because they can't have the DOGMA. They got to deliver and they're saying, "We're going to build a stack "On one cloud. "Have a backup cloud, "I want all my developer resources "On this cloud, not fork my team "And I'm going to build a stack "And then I'm going to ship APIs "And say to my suppliers, in the RFP process, "If you support these APIs, "You could do business with us." >> Keith: So, if you don't -- >> That's kind of a cutting edge. If you don't, you can't, you can't. And that's the new normal. We're seeing it with the Jedi deal with Oracle not getting, playing 'cause they're not certified at the level that Amazon is, and you're going to start to see these new requirements emerging this is a huge point. I think that's where Pivotal could really shine not being the, quote, developer channel for VMware. I think it's more of really writing apps >> And John, I think people aren't even going to question that model. Capital One is probably the poster child for that model they actually went out and acquired a start-up, a security, a container security start up, integrated them into their operations and they still failed. Security in the cloud is hard. I think we'll get into a multi-cloud discussion this is one of the reasons why I'm not a big fan of multi-cloud from an architecture perspective, but from a practical challenge, security is one of the number one challenges. >> That's a great point on Capital One in fact, that's a great example. In fact, I love to argue this point. On Twitter, I was heavily arguing this point which is, yeah, they had a breach. But that was a very low-level it's like the equivalent of a S3 bucket not being configured, right? I mean it was so trivial of a problem but still, it takes one whole-- (hearty laughing) One, one entry point for malware to get in. One entry point to get into any network where it's IOT This is the huge challenge. So the question there is, automation. Do you do the, so, again, these are the, that's a solvable problem with Capital One. What we don't know is, what has Capital One done that we don't know that they've solved? So, again, I look at that breech as pretty, obviously, major, but it was a freakin' misconfigured firewall. >> So, come back to your comments on multi-cloud. I'm inferring from what you said, and I'd love to get your opinion, Sarbjeet. That multi-cloud is not an architectural strategy. I've said this. It's kind of a symptom of multiple vendors playing but so, can multi-cloud become, because certainly VMware IBM RedHat, Google with Anthos, maybe a little bit less Microsoft but those three-- >> Dell Technologies. >> Cisco, Cisco and certainly Dell all talking about multi-cloud is the clear strategy that's where CIOs are going, you're not buying it. Will it ever become a clear strategy from an architectural standpoint? >> Multi-cloud is the NSX and I don't mean NSX in VMware NSX it's the Acura NSX of enterprise IT. The idea of owning the NSX is great it brings me into the showroom, but I am going to buy, I'm going to go over to the Honda side or I'm going to go buy the MDX or something more reasonable. Multi-cloud, the idea, sure it's possible. It's possible for me to own a NSX sports car. But it's more practical for me to be able to shop around I can go to Google via cloud simple I mean I can go via cloud simple to Azure, GCP or I can go BMC, I have options to where I land, but to say that I am going to operate across all three? That's the NSX. >> If you had a NSX sports car, by the way, to use the analogy in my mind is great one, the roads aren't open yet. So, yeah, okay great. (hearty laughing) >> Or you go to Germany and you're in California. So, the transport, and again in the applications you could build tech for good applications all you want, and they're talking about tech for good here but if it's insecure, those apps are going to create more entry points. Again, for cyber threats, for malware, so again, the security equation, and you're right is super important, and they don't have it. >> Dave: What's your thought on all (mumble)? >> Sarbjeet: I think on multi-cloud you are, when you are going to use multi-cloud you going to expand the threat surface if you will 'cause you're putting stuff at different places. But I don't think it, like as you said Dave, the multi-cloud is not more of an architectural choice, it's more like a risk mitigation strategy from the vendor point of view. Like, Amazon, who they don't compete with or who they won't compete with in the future we don't know, right? So... >> You mean within the industry. >> Yeah, within the industry right-- >> Autos or healthcare or... >> Sarbjeet: Yeah, they will, they are talking about that, right? So if you put all, all sort of all your bets on that or Azure, let's say even Azure, right? They are not in that kind of category, but still if you go with one vendor, and that's mission critical and something happens like government breaks them up or they go under, sideways, whatever, right? And then your business is stuck with them and another thing is that the whole US business, if you think about it at a global scale, like where US stands and all that stuff and even global companies are using these hourglass providers based in US, these companies are becoming like they're becoming too big to fail, right? If you put everything on one company, right, and then something happens will we bail them out? Right, will the government bail them out? Like stuff like that. Like banks became too big to fail, I think. I think from that point of view, bigger companies will shift to multi-cloud for, to hedge, right, >> Risk Mitigation >> Risk mitigation. >> Yeah, that's, okay, that's fair. >> I mean, I believe in multi-cloud in one definition only. I think, for now, the nirvana of having different workload management across utility bases, that's fantasy. >> Keith: Yeah, that's fantasy. >> I think you could probably engineer it, but there might not be a workload for that or maybe data analytics I could see moving around as a use case, certainly, but I think-- >> D-R! >> The reality is, is that all companies will probably have multiple clouds, clearly like, if you're going to run Office 365, and it's going to be on Azure, you're an Azure customer, okay. You have Azure cloud. If you're building your security stack on Amazon, and got a development team, you're on Amazon. You got two clouds. You add Google in there, big tables, great for certain things you know, Big Query, you got Google. You might even have Alibaba if you're operating in China So, again, you going to have multiple clouds the question is, the workloads define cloud selection. So, I've been on this thing, if you got a workload, an app, that app should choose its best infrastructure possible that maximizes what the outcome is. >> And John, I think what people fail to realize, that users, when you give them a set of tools, they're going to do what users do, which is, be productive. Just like users went out and took credit cards swiped it and got Amazon. If you, if in your environment you have Amazon you have GCP, you have Azure, you have Salesforce, O-365, and a user has access to all five platforms, whether or not you built a multi-cloud application a user's going to find a way to get their work done with all five, and you're going to have multi-cloud fallout because users will build data sets and workloads across that, even if IT isn't the one that designed it. >> All right, guys, final question of the Power Panel Dave, I want to include this for you too, and I'll weigh in as well. Take a minute to share what you're thinking right now is on the industry. What's taking up your attention? What's dominating your Twittershpere right now? What's the bee in your bonnet? What's the hot-button issue that you're kicking the tires on, learning about, or promoting? Sarbjeet, we'll start with you. What's on top of the mind for you these days? >> I think with talk about multi-cloud all the time, that's in discussions all the time and then Blockchain is another like slow-moving train, if you will, I think it's arriving now, and we will see some solutions coming down the pike from different, like a platformization of the Blockchain, if you will, that's happening, I think those are two actually things I keep my eyes on and how developers going to move, which side to take and then how the AWSs dominance is challenged by Microsoft and Google there's one thing I usually talk about on Twittersphere, is that there's a data gravity and there's a scales gravity, right? So people who are getting trained on Amazon, they will tend to stay with them 'cause that's, at the end of the day, it's people using technology, right? So, moving from one to another is a challenge. Whoever throws in a lot of education at the developers and operators, they will win. >> Keith, what are you gettin' excited about? >> So, CTO advisor has this theory about the data framework, or data infrastructure. Multi-cloud is the conversation about workloads going here, there, irrelevant, it's all about the data. How do I have a consistent data policy? A data protection policy, data management policy across SAS, O-365, Sales Force Workday, my IAF providers, my PATH providers, and OMPRIM, how do I move that data and make sure another data management backup company won Best of VMWorld this year. This is like the third or fourth year and a reason it's not because of backup. It's because CIOs, CDOs are concerned about this data challenge, and as much as we want to talk about multi-cloud, I think well, the industry will discover the problem isn't in Kubernetes the solution isn't in Kubernetes it's going to be one of these cool start-ups or one of these legacy vendors such as NetAp, Dell, EMC that solves that data management layer. >> All right, great stuff. My hot button is cloud 2.0 as everyone knows, I think there's new requirements that are coming out, and what got my attention is this enterprise action of VMware, the CIA deal at Amazon, the Jedi deal show that there are new requirements that our customers are driving that the vendors don't have, and that's a function that cloud providers are going to provide, and I think that's that's the canary in the coal mine. >> I've got to chime in. I've got to chime in. Sorry, Lenard, but it's the combination what excites me is the combination of data plus machine intelligence and cloud scale. A new scenario of disruption moving beyond a remote set of cloud services to a ubiquitous set of digital services powered by data that are going to disrupt every industry. That's what I get excited about. >> Guys, great Power Panel. We'll pick this up online. We'll actually get the Power Panels working out of our Palo Alto studio. If you haven't seen the Power Panels, check them out. Search Power Panels the Cube on Google, you'll see the videos. We talk about an issue, we get experts it's an editorial product. You'll see more of that online. More coverage here at VMWorld 2019 after this short break. (lively techno music)

>> Live from Midtown Manhattan, it's theCUBE. Covering BigData New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. (calm electronic music) >> Basil Faruqui, who's the Solutions Marketing Manger at BMC, welcome to theCUBE. >> Thank you, good to be back on theCUBE. >> So first of all, heard you guys had a tough time in Houston, so hope everything's gettin' better, and best wishes to everyone down in-- >> We're definitely in recovery mode now. >> Yeah and so hopefully that can get straightened out quick. What's going on with BMC? Give us a quick update in context to BigData NYC. What's happening, what is BMC doing in the big data space now, the AI space now, the IOT space now, the cloud space? >> So like you said that, you know, the data link space, the IOT space, the AI space, there are four components of this entire picture that literally haven't changed since the beginning of computing. If you look at those four components of a data pipeline it's ingestion, storage, processing, and analytics. What keeps changing around it, is the infrastructure, the types of data, the volume of data, and the applications that surround it. And the rate of change has picked up immensely over the last few years with Hadoop coming in to the picture, public cloud providers pushing it. It's obviously creating a number of challenges, but one of the biggest challenges that we are seeing in the market, and we're helping costumers address, is a challenge of automating this and, obviously, the benefit of automation is in scalability as well and reliability. So when you look at this rather simple data pipeline, which is now becoming more and more complex, how do you automate all of this from a single point of control? How do you continue to absorb new technologies, and not re-architect our automation strategy every time, whether it's it Hadoop, whether it's bringing in machine learning from a cloud provider? And that is the issue we've been solving for customers-- >> Alright let me jump into it. So, first of all, you mention some things that never change, ingestion, storage, and what's the third one? >> Ingestion, storage, processing and eventually analytics. >> And analytics. >> Okay so that's cool, totally buy that. Now if your move and say, hey okay, if you believe that standard, but now in the modern era that we live in, which is complex, you want breath of data, but also you want the specialization when you get down to machine limits highly bounded, that's where the automation is right now. We see the trend essentially making that automation more broader as it goes into the customer environments. >> Correct >> How do you architect that? If I'm a CXO, or I'm a CDO, what's in it for me? How do I architect this? 'Cause that's really the number one thing, as I know what the building blocks are, but they've changed in their dynamics to the market place. >> So the way I look at it, is that what defines success and failure, and particularly in big data projects, is your ability to scale. If you start a pilot, and you spend three months on it, and you deliver some results, but if you cannot roll it out worldwide, nationwide, whatever it is, essentially the project has failed. The analogy I often given is Walmart has been testing the pick-up tower, I don't know if you've seen. So this is basically a giant ATM for you to go pick up an order that you placed online. They're testing this at about a hundred stores today. Now if that's a success, and Walmart wants to roll this out nation wide, how much time do you think their IT department's going to have? Is this a five year project, a ten year project? No, and the management's going to want this done six months, ten months. So essentially, this is where automation becomes extremely crucial because it is now allowing you to deliver speed to market and without automation, you are not going to be able to get to an operational stage in a repeatable and reliable manner. >> But you're describing a very complex automation scenario. How can you automate in a hurry without sacrificing the details of what needs to be? In other words, there would seem to call for repurposing or reusing prior automation scripts and rules, so forth. How can the Walmart's of the world do that fast, but also do it well? >> Yeah so we do it, we go about it in two ways. One is that out of the box we provide a lot of pre-built integrations to some of the most commonly used systems in an enterprise. All the way from the Mainframes, Oracles, SAPs, Hadoop, Tableaus of the world, they're all available out of the box for you to quickly reuse these objects and build an automated data pipeline. The other challenge we saw, and particularly when we entered the big data space four years ago was that the automation was something that was considered close to the project becoming operational. Okay, and that's where a lot of rework happened because developers had been writing their own scripts using point solutions, so we said alright, it's time to shift automation left, and allow companies to build automations and artifact very early in the developmental life cycle. About a month ago, we released what we call Control-M Workbench, its essentially a community edition of Control-M, targeted towards developers so that instead of writing their own scripts, they can use Control-M in a completely offline manner, without having to connect to an enterprise system. As they build, and test, and iterate, they're using Control-M to do that. So as the application progresses through the development life cycle, and all of that work can then translate easily into an enterprise edition of Control-M. >> Just want to quickly define what shift left means for the folks that might not know software methodologies, they don't think >> Yeah, so. of left political, left or right. >> So, we're not shifting Control-M-- >> Alt-left, alt-right, I mean, this is software development, so quickly take a minute and explain what shift left means, and the importance of it. >> Correct, so if you think of software development as a straight line continuum, you've got, you will start with building some code, you will do some testing, then unit testing, then user acceptance testing. As it moves along this chain, there was a point right before production where all of the automation used to happen. Developers would come in and deliver the application to Ops and Ops would say, well hang on a second, all this Crontab, and these other point solutions we've been using for automation, that's not what we use in production, and we need you to now go right in-- >> So test early and often. >> Test early and often. So the challenge was the developers, the tools they used were not the tools that were being used on the production end of the site. And there was good reason for it, because developers don't need something really heavy and with all the bells and whistles early in the development lifecycle. Now Control-M Workbench is a very light version, which is targeted at developers and focuses on the needs that they have when they're building and developing it. So as the application progresses-- >> How much are you seeing waterfall-- >> But how much can they, go ahead. >> How much are you seeing waterfall, and then people shifting left becoming more prominent now? What percentage of your customers have moved to Agile, and shifting left percentage wise? >> So we survey our customers on a regular basis, and the last survey showed that eighty percent of the customers have either implemented a more continuous integration delivery type of framework, or are in the process of doing it, And that's the other-- >> And getting close to a 100 as possible, pretty much. >> Yeah, exactly. The tipping point is reached. >> And what is driving. >> What is driving all is the need from the business. The days of the five year implementation timelines are gone. This is something that you need to deliver every week, two weeks, and iteration. >> Iteration, yeah, yeah. And we have also innovated in that space, and the approach we call jobs as code, where you can build entire complex data pipelines in code format, so that you can enable the automation in a continuous integration and delivery framework. >> I have one quick question, Jim, and I'll let you take the floor and get a word in soon, but I have one final question on this BMC methodology thing. You guys have a history, obviously BMC goes way back. Remember Max Watson CEO, and Bob Beach, back in '97 we used to chat with him, dominated that landscape. But we're kind of going back to a systems mindset. The question for you is, how do you view the issue of this holy grail, the promised land of AI and machine learning, where end-to-end visibility is really the goal, right? At the same time, you want bounded experiences at root level so automation can kick in to enable more activity. So there's a trade-off between going for the end-to-end visibility out of the gate, but also having bounded visibility and data to automate. How do you guys look at that market? Because customers want the end-to-end promise, but they don't want to try to get there too fast. There's a diseconomies of scale potentially. How do you talk about that? >> Correct. >> And that's exactly the approach we've taken with Control-M Workbench, the Community Edition, because earlier on you don't need capabilities like SLA management and forecasting and automated promotion between environments. Developers want to be able to quickly build and test and show value, okay, and they don't need something that is with all the bells and whistles. We're allowing you to handle that piece, in that manner, through Control-M Workbench. As things progress and the application progresses, the needs change as well. Well now I'm closer to delivering this to the business, I need to be able to manage this within an SLA, I need to be able to manage this end-to-end and connect this to other systems of record, and streaming data, and clickstream data, all of that. So that, we believe that it doesn't have to be a trade off, that you don't have to compromise speed and quality for end-to-end visibility and enterprise grade automation. >> You mentioned trade offs, so the Control-M Workbench, the developer can use it offline, so what amount of testing can they possibly do on a complex data pipeline automation when the tool's offline? I mean it seems like the more development they do offline, the greater the risk that it simply won't work when they go into production. Give us a sense for how they mitigate, the mitigation risk in using Control-M Workbench. >> Sure, so we spend a lot of time observing how developers work, right? And very early in the development stage, all they're doing is working off of their Mac or their laptop, and they're not really connected to any. And that is where they end up writing a lot of scripts, because whatever code business logic they've written, the way they're going to make it run is by writing scripts. And that, essentially, becomes the problem, because then you have scripts managing more scripts, and as the application progresses, you have this complex web of scripts and Crontabs and maybe some opensource solutions, trying to simply make all of this run. And by doing this on an offline manner, that doesn't mean that they're losing all of the other Control-M capabilities. Simply, as the application progresses, whatever automation that the builtin Control-M can seamlessly now flow into the next stage. So when you are ready to take an application into production, there's essentially no rework required from an automation perspective. All of that, that was built, can now be translated into the enterprise-grade Control M, and that's where operations can then go in and add the other artifacts, such as SLA management and forecasting and other things that are important from an operational perspective. >> I'd like to get both your perspectives, 'cause, so you're like an analyst here, so Jim, I want you guys to comment. My question to both of you would be, lookin' at this time in history, obviously in the BMC side we mention some of the history, you guys are transforming on a new journey in extending that capability of this world. Jim, you're covering state-of-the-art AI machine learning. What's your take of this space now? Strata Data, which is now Hadoop World, which is Cloud Air went public, Hortonworks is now public, kind of the big, the Hadoop guys kind of grew up, but the world has changed around them, it's not just about Hadoop anymore. So I'd like to get your thoughts on this kind of perspective, that we're seeing a much broader picture in big data in NYC, versus the Strata Hadoop show, which seems to be losing steam, but I mean in terms of the focus. The bigger focus is much broader, horizontally scalable. And your thoughts on the ecosystem right now? >> Let the Basil answer fist, unless Basil wants me to go first. >> I think that the reason the focus is changing, is because of where the projects are in their lifecycle. Now what we're seeing is most companies are grappling with, how do I take this to the next level? How do I scale? How do I go from just proving out one or two use cases to making the entire organization data driven, and really inject data driven decision making in all facets of decision making? So that is, I believe what's driving the change that we're seeing, that now you've gone from Strata Hadoop to being Strata Data, and focus on that element. And, like I said earlier, the difference between success and failure is your ability to scale and operationalize. Take machine learning for an example. >> Good, that's where there's no, it's not a hype market, it's show me the meat on the bone, show me scale, I got operational concerns of security and what not. >> And machine learning, that's one of the hottest topics. A recent survey I read, which pulled a number of data scientists, it revealed that they spent about less than 3% of their time in training the data models, and about 80% of their time in data manipulation, data transformation and enrichment. That is obviously not the best use of a data scientist's time, and that is exactly one of the problems we're solving for our customers around the world. >> That needs to be automated to the hilt. To help them >> Correct. to be more productive, to deliver faster results. >> Ecosystem perspective, Jim, what's your thoughts? >> Yeah, everything that Basil said, and I'll just point out that many of the core uses cases for AI are automation of the data pipeline. It's driving machine learning driven predictions, classifications, abstractions and so forth, into the data pipeline, into the application pipeline to drive results in a way that is contextually and environmentally aware of what's goin' on. The history, historical data, what's goin' on in terms of current streaming data, to drive optimal outcomes, using predictive models and so forth, in line to applications. So really, fundamentally then, what's goin' on is that automation is an artifact that needs to be driven into your application architecture as a repurposable resource for a variety of-- >> Do customers even know what to automate? I mean, that's the question, what do I-- >> You're automating human judgment. You're automating effort, like the judgments that a working data engineer makes to prepare data for modeling and whatever. More and more that can be automated, 'cause those are pattern structured activities that have been mastered by smart people over many years. >> I mean we just had a customer on with a Glass'Gim CSK, with that scale, and his attitude is, we see the results from the users, then we double down and pay for it and automate it. So the automation question, it's an option question, it's a rhetorical question, but it just begs the question, which is who's writing the algorithms as machines get smarter and start throwing off their own real-time data? What are you looking at? How do you determine? You're going to need machine learning for machine learning? Are you going to need AI for AI? Who writes the algorithms >> It's actually, that's. for the algorithm? >> Automated machine learning is a hot, hot not only research focus, but we're seeing it more and more solution providers, like Microsoft and Google and others, are goin' deep down, doubling down in investments in exactly that area. That's a productivity play for data scientists. >> I think the data markets going to change radically in my opinion. I see you're startin' to some things with blockchain and some other things that are interesting. Data sovereignty, data governance are huge issues. Basil, just give your final thoughts for this segment as we wrap this up. Final thoughts on data and BMC, what should people know about BMC right now? Because people might have a historical view of BMC. What's the latest, what should they know? What's the new Instagram picture of BMC? What should they know about you guys? >> So I think what I would say people should know about BMC is that all the work that we've done over the last 25 years, in virtually every platform that came before Hadoop, we have now innovated to take this into things like big data and cloud platforms. So when you are choosing Control-M as a platform for automation, you are choosing a very, very mature solution, an example of which is Navistar. Their CIO's actually speaking at the Keno tomorrow. They've had Control-M for 15, 20 years, and they've automated virtually every business function through Control-M. And when they started their predictive maintenance project, where they're ingesting data from about 300,000 vehicles today to figure out when this vehicle might break, and to predict maintenance on it. When they started their journey, they said that they always knew that they were going to use Control-M for it, because that was the enterprise standard, and they knew that they could simply now extend that capability into this area. And when they started about three, four years ago, they were ingesting data from about 100,000 vehicles. That has now scaled to over 325,000 vehicles, and they have no had to re-architect their strategy as they grow and scale. So I would say that is one of the key messages that we are taking to market, is that we are bringing innovation that spans over 25 years, and evolving it-- >> Modernizing it, basically. >> Modernizing it, and bringing it to newer platforms. >> Well congratulations, I wouldn't call that a pivot, I'd call it an extensibility issue, kind of modernizing kind of the core things. >> Absolutely. >> Thanks for coming and sharing the BMC perspective inside theCUBE here, on BigData NYC, this is the theCUBE, I'm John Furrier. Jim Kobielus here in New York city. More live coverage, for three days we'll be here, today, tomorrow and Thursday, and BigData NYC, more coverage after this short break. (calm electronic music) (vibrant electronic music)

>> Life from Las Vegas, it's theCube, covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back everyone to theCube's live coverage of the AWS Executive Summit. I'm your host, Rebecca Knight. And I'm joined by Kathleen Natriello. She is the vice president and the head of IT, digital design at Bristol Myers Squibb. And Shalu Chadha, senior technology services lead at Accenture. Thank you so much for coming on theCube. >> Sure. >> Thank you for having us. >> So we're going to talk about Bristol Myers Squibb's journey to the cloud today, but I want. Bristol Myers Squibb is a household name, but I would love you to just start out, Kathleen, by telling our viewers a little bit about Bristol Myers Squibb. Just how big a global pharma company you are. >> Sure. We're a global company, as you said. We have about 23,000 employees all over the world. And we're very focused on our immuno oncology therapies. And the way that they work is that they boost the immune system to fight cancer. So it's a really exciting development that we've had over the years. >> And so what was it, sort of, in the trajectory of Bristol Myers Squibb, that made you realize, as an organization, we need to do things differently? What challenges were you facing? >> So, we're very science focused in terms of developing treatments for our patients. And so our highest priority was our scientists' productivity. And so we started our cloud journey about 10 years ago. And our initial focus was on leveraging burst computing in AWS, which enabled us to spin up enough capacity for our scientists to do research with very large volumes of data. That's one of the things about biopharma. We use very large volumes for genomics research. >> And also, with this partnership, using AWS, you also partner with Accenture. So, can you describe a little bit, Shalu, how the partnership evolved? >> Right. And so that journey that Kathy mentioned, We've been part of that journey for the last two years now. And I think it's this nice partnership between AWS, BMS, and Accenture. And the teams have gone on with a lot of quick successes and early successes. And I think, going forward, the focus is really now businesses is going to look for a lot more demand and agility. Clouded adoption is going to be key in how we actually expand on that. And I know we're talking amongst us to say, how do we get there faster now? >> A little less conversation, a little more action please. >> Yes. (inaudible speech and laughter) >> Exactly. So, let's talk about this journey. So you're not only migrating existing applications, you're also building your own applications. >> Yes. >> What's the, sort of the wisdom behind that strategy? >> A couple of things. So I mentioned earlier that we started our journey with our scientists and we've continued because that's where AWS really delivers significant value for Bristol Myers Squibb. So, what we have done is implemented several AWS cloud services that enable our scientists to use machine learning, artificial intelligence, a lot of computational approaches and simulations that significantly reduce the amount of time it takes them to do an experiment, as well as the cost. Because they no longer have to use actual physical material, or patients, or investigators. They can do it all through simulation and modeling, which is exciting. >> So, I mean, we all know that the drug discovery process takes a long time, and it's tedious, um, cumbersome. So can you actually bring it back down to earth a little bit and say, what have you seen? What are your scientists? In terms of how the drug discovery process is going. >> Yeah. Our scientists are our biggest advocates of the cloud and the capabilities it delivers. And they will report back to us that they are doing things with machine learning and artificial intelligence with these simulations, that they're doing in a few hours, that used to take them weeks and months. And so that's how it's really shortening that cycle. >> And are the patients feeling the benefits yet, too? >> The patients will feel the benefits with our focus on clinical trials. And so, being able to speed up a clinical trial is very helpful. And both from the patient experience, as well as the investigators. >> Shalu, can you talk about some of the other innovation and automation capabilities? >> Yeah. So, BMS is really on this really exciting journey, and now that they've, like Kathy said, extended some of those capabilities and actually building and enabling for the scientists, of the commercial, the brand sites. It's now about, really, what do you do next and how you bring that next wave of innovation. And so, what's been nice at Bristol Myers Squibb and the partnership we have with Accenture here, is really looking at taking some of the learnings we had in the back office, in the finance and the procurement. Where we've actually brought a lot of process efficiency through our bots taking some of that learnings and bringing that across in many other different ways. And now we have bots across legal, compliance, and moving into the clinical area that adverse events. And we're looking at really that part which is how do you actually get quicker with how the patients are going to see both responses to the adverse events, as well as how do you actually accelerate the clinical trial process. And all of those innovations are really possible with what Kathy has set up in her organization. And actually having that digital acceleration competency and be able to take this span enterprise. >> One of the things that's so interesting about these partnerships is how you work together. >> (in unison) Yes. >> And is it that you're focusing on the science and Accenture is thinking about the technology? I mean, are you, sort of, two different groups? Or how are you coming together to collaborate and build a relationship? >> I really see it as three groups. So it's Bristol Myers Squibb that's focused on science as well as the technology. And if I take an example of how that partnership works, when we were doing our migration to the cloud, the more aggressive plan that we have in place right now, Amazon partnered with us on a migration readiness program. And that enabled us to move as much as 400 plus workloads into the cloud and to other locations. And then Accenture partnered with us, as well, to actually move the applications and migrate them to the cloud and the two other locations. So, I really see it as a three way partnership. And part of the way, one of the reasons it's so successful is it's not just BMS partnering with Accenture, and BMS partnering with Amazon, But it's Amazon and Accenture partnering together. And they would come up with ideas on here's what we think will make BMS even more successful. >> And how, and how is that? Is it because you were really grasping their business challenges? Or, I mean, how are you able to come up with? You're not a life science person. >> Right. >> It's, how are you doing that? >> It's a good question, and I think when I reflect on what I experience with other clients, I think what's so tremendously making us successful here is everything is about interest based. And it's about how we start the conversation. The patient in the center. And then it's about who's interests are we serving. Let's be clear. And let's try and try trigress into what's the solution that actually needs that. So, I think, whether, Kathy mentioned it in the cloud cumulus work, or even with the SAPS four journey right now. It's the combination of AWS, BMS, and Accenture in that journey of how we going to solve this together. Those critical and complex programs. >> Kathy, you said that scientists were some of your biggest advocates for going cloud native. I'm curious about the rest of the work force. I mean, has it been, sometimes introducing new technologies and new ways of doing things can cause consternation among your employees. >> Yeah., but in my organization, we bring a lot of change to the rest of the company. And your right. Sometimes it's well received. But I think when it is well received, is when across the company they can see the productivity gain with our robotics process automation. At a digital workforce, people are able to have, they are able to get a lot more done. And so there is acceptance of that. And very often, the business functions are the ones that introduce the new technologies because they're really interested in it and curious. So it works out well. >> So they're getting more done so >> Yes >> So then they're more satisfied with their work and life >> Yes >> And, exactly. So tell our viewers a little bit more about what's next for this partnership, for this relationship, in terms of new technologies. In terms of what you hope to be able to accomplish in the years to come. >> So, I can start. I really think that's what is next for us is to move a little faster. So, in our cloud journey, as I mentioned, we started 10 years ago and then, we've build on what we've learned. So, as an example, we put our commercial data warehouse into a Amazon Redshift. And then that laid the foundation for us to do, for example, rapid data labs. We started by building some data lakes in HR and R and D. And then, by the time we got to doing that for manufacturing, we did it serverless. And so we've had a nice progression based on learning and going the next step. But I think, we're to the point where the technology's evolving so quickly we can move a lot faster and get the benefits faster. So for me, that's what I view as what's next. >> Shalu, anything? >> Yeah. I would just add that I think analytics set the core. I think there is such a strong foundation set here that now it's about how are we going to extrapolate from there. And really look at bot machine learning and what that could do for us. And that, and we will take a lot from what we've learned here today about actually evolving that journey. And I think the best part is the foundation is set strong. And now it's about accelerating into those specific business areas as well. So I would say analytics and really extending our machine learning capabilities. >> So move faster, analytics machine learning. Great. So we're going to be talking about it next year's summit. Well, Kathy and Shalu, thank you so much for coming on theCube. This was a lot of fun. >> Yes. It was. >> (in unison) Thank you. >> I'm Rebecca Knight. We will have more of theCube's live coverage of the AWS Executive Summit coming up in just a little bit.

(upbeat music) >> Live from Washington, D.C., it's theCUBE, covering Inforum D.C. 2018, brought to you by Infor. >> Well, back here on theCUBE, we are at Inforum '18. We're in Washington, D.C. here in the Walter Washington Convention Center. Not far from the White House. It's about a mile that way, and Capitol Hill's about a mile that way, I think. I know we're right in here, but I know we are smack dab in the middle of it. Dave Vellante and John Walls and Kevin Curry, who's the SVP of the global public sector at Infor. Good to have you with us. Good to see you, sir. >> Great to be here. Thanks for your time. >> So public sector, you're in the heart of it here, and you were telling us before we went on the air that you've got more than 700 clients here at the show this week? >> We do, we do. It's the best attendance we've had yet for Inforum, and I joined about six and a half years ago. And we built this business pretty much from the ground up. So it's been a great experience, and now we're starting to get a lot of adoption within the government, across the government, from federal to state to locals. >> What's the process been like, especially across those three, because I assume they're all different? You know, local, state, federal, everybody has different pain points and there's different tolerances. >> They do, they do. I mean, there's different micro-verticals within each of those statements. As an example, if you look at local governments, it could be anything from transit agencies to K-12 schools, to public works, to police, to fire. They all have all different requirements. State's the same thing, whether it's Department of Transportation or Department of Health and Human Services. And then when you get the federal side of it, then it's from the intelligence community to Department of Defense, healthcare within Defense, like the VA and DoD and Defense agencies as well. So it's a pretty wide swatch of use cases and business cases that you need to be able to sell to. >> Charles said something interesting in the keynote today. I want to ask you about it. He said, "We made a strategic decision to go to the cloud. "We didn't want to compete with Google "and Amazon and Microsoft for CloudScale. "That didn't make any sense for us." And he said, "When we were an on-prem software vendor, "we weren't managing servers for our customers." Now what struck me there is if you look back at the software company back in the day, they really didn't care about the server, right? It was just sort of infrastructure. It was kind of irrelevant to them. The cloud feels different. It seems like a more strategic relationship with Amazon. You know, we talk about Teresa Carlson and what a force she is in the government. AWS in the GovCloud has been a huge force. They had a giant lead. So have you been able to draft off that or is it just another sort of infrastructure platform? >> No, they're a major strategic partnership there with AWS and NN4. At the company level, and especially for me, with the government, they've made the right investments at the right time, I mean, and they actually have cloud environments that are very specific to different segments of the government and to different geographies. So as an example, in the federal government they have an intelligence cloud called C2S, which we work with them on. There's a very large procurement out right now for the Department of Defense called Jedi, which Amazon's going after, as well as the other larger cloud providers, so we're obviously riding that horse with AWS. And also for local governments, and they've done all of the compliancy for the government, whether it be FedRAMP, whether it be CJIS for those departments that are worried about the justice type of requirements. And as you get outside of the U.S., they're putting clouds and we're a global company as well, putting clouds in all the right places. They have a G-Cloud offering in the U.K. and as we talked about earlier when we sat down, they're opening a cloud in the Middle East right now too, in Bahrain that I think traces on oil over there as we speak. >> Right, right. The first Middle East country to claim cloud first. But it just seems like there's a strategic advantage there. And even with the other cloud suppliers. I mean, you know, Google's got its niche, big niche, you know, Microsoft, with its software state, but it seems like Amazon, they talk about that flywheel effect, brings certain technologies that, you know, when you talk to Soma, you guys have been able to take advantage of. It just feels a lot different than the old traditional server manufacturer. Oh, it's a Unix box and there's no difference between vendor A, B and C. >> Absolutely correct. And for us, we've taken advantage of the tools that Amazon has and obviously, we're doing all the compliancy on our applications and they've got whole the infrastructure piece of it, so the two work very well together. >> And that has allowed you to focus on your knitting, if you will. >> Yes. >> The things that you do best, which is a micro-verticals, suite across the application portfolio, bringing AI to the equation, automation, we heard a lot about robotic process automation, which is probably a hot topic in the government. >> Yes. I mean, Charles famously, he may have had a quote. I'm sure you heard it. It's friends don't let friends build data centers. >> Great quote. >> You know, that's not a business we're in. We're a software company. >> Right. >> So the public sector, obviously a different animal than the private sector. Very different needs, different constituents, you got tax payers, you got all that. When you bring the technology into the public sector, what does that do for it or how does that have to be, I don't know, re-conformed or adapted? And ultimately, what's the payoff, right? What's the return on that investment? >> So it was actually pretty shocking how quickly the government has adopted and moved towards the cloud. Typically, they're laggards. Everything happens in the commercial market and then government's a little bit of a late adopter, right? But we're seeing them very quickly go to the cloud and there's a lot of reasons for that. One being, you have an aging workforce. Okay, so the baby boomers are all retiring so a lot of that intellectual knowledge is going out the door. Two, is there's some economies of scale to be realized by doing that because once you're in the cloud, I mean, it's up to the vendor who's maintaining it to maintain that for you. So, you know, the people behind the scenes, they have to do it. You know, when you upgrade your software to go from one release to the other, it's automatically done for you. I mean, so there's real cost savings to be had, you know, from a care and feeding perspective there as well. Also a lot of the, on the ERP side of the things, a lot of the systems that are out in the marketplace today that governments have bought, like the Oracles or the SAPs, a lot of these systems are at end-of-life and the companies are no longer supporting them. So it's a re-implementation for them. You know, and so now they're looking, okay, if we have to re-implement and we have to look at our new options, we're going to do it in a cloud. >> So when you've been around as long as I have, Kevin, >> Right. >> you've seen the pendulum swing. You don't have to agree so vehemently. (laughing) But from mainframe to client server and so you're back to the cloud, and now with IoT, it seems like the pendulum is swinging back to a distributed environment. So help us understand where IoT fits to the cloud and even your on-prem business. >> Okay, so like I say, cloud is a pretty broad topic, okay? We have multiple applications that would run in that environment. So when I look at IoT, I think of things like our asset management platform. We have a very strong enterprise asset management platform that runs in the cloud or runs on-prem. And if you think about infrastructure as an example, which government has a lot of, okay. Think about the ability to have sensors on different pieces of equipment and being able to read that information. Think about using drone technology, okay, to be able to do physical inspections under bridges, so you're not having people having to climb around underneath there. I mean, so being able to do live feeds of data and be able to streamline the way you do business and have that automatically captured within an application. So yes, that is one area where we see it. I mean, I think you're going to see more and more of robotics and artificial intelligence and all the things come into play. I think you heard a lot about that here and it's here. I mean, they were things we saw in movies before but now the technology's here today. >> Well, the other thing we heard this morning that Charles has always talked a lot about the data. You guys always talked about your data lake. I like to think of it as a data ocean. You think about all the data out of GT Nexus and, you know, your customers that are providing data to inform. The data model starts to really expand and you guys have seemed to really take advantage of that. Talk about the data, the importance of data, the importance of securing data to the government. >> Well, think about that. I mean, there's islands of information that governments have that if they were able to consolidate that data and put some intelligence into it, be able to make business decisions versus, you know, one system sitting over here, one system sitting over here and none of them ever communicating or talking to each other. You know, the ability to, You could do from anything from, just think about crime statistics, okay? The ability to deploy resources where the crime is and then as it moves, be able to further deploy resources. You know, New York, years ago, did things like that with CompStat when they were cleaning up Times Square and so forth. But just think of that as a concept, realtime being able to manage data. >> So you've got, here at the show, we were talking about earlier, 700 and some odd clients, 725. You've got the federal forum for the first time. Why now? And what are you getting out of that or what do you hope to get out of that at the end of the week? >> So the whole executive team and our board of directors have made significant investments in this marketplace because they understand that government is a very large beast, if you will, and there's a lot of opportunity for deployment of our solutions and there's a real need to solve problems for constituents here as well. So they've made very significant investments in things for security like FedRAMP, compliancy. You know, some companies are doing it on some of their solutions. We're doing it across the board on all the products that we take to the government marketplace. So we're invested in it. You've probably heard today, Charles talked about the fact that we're going to have a federal cloud suite, which we are. So that means federal financials, okay? Actually being able to solve all the problems for the federal government and comply to all their needs and all the things that are part of mandated accounting for the federal government. They made all the right investments and human capital management would be another area. If you think about, we've got an application called Talent Science. The ability to hire the right people for the right job and retain those people. Just think about, ICE is a good example. You heard that they have to hire thousands of people to deploy on the borders, right? How do you quickly ramp and hire these right people if you don't have the right tools to do it? >> You were quoted in TIME magazine, Marc Benioff's new publication, about America's crumbling infrastructure. What role do you see technology playing generally and specifically in for software and helping with that problem? >> So we do a lot today around infrastructure. As an example, we have a very strong presence in transit agencies here in the U.S. New York City runs us, amounts to about a trillion dollars worth of assets there. So anything moving in, out or around the city, so subways, buses, trains, tunnels, bridges, Metro-North, Long Island Rail Road. L.A. runs us, San Francisco runs us, Chicago runs us, Dallas runs us and many others. So we're managing all of that infrastructure. So you hear a lot about infrastructure bills coming out of the federal government. And they're right. I mean, a lot of these tunnel, a lot of these bridges and tunnels and even roadways were built back during World War II, right? And they're aged, you know, they are starting to crumble and there's going to be a lot of money spent to do that and when it comes to rebuilding those types of things, there's a lot of assets that are going to need to be managed, you know, to do that. So we think there's a real opportunity for software such as what we bring to the marketplace to help with that process. >> How about talent retention? I mean, obviously, as administrations come and go, you know, people move, but there's been a lot of brain drain. I mean, take the Patent Office, people in commercial industry stealing some of the best and brightest out of government. Can software play a role in helping better retain, train, you know, evolve growth paths and careers? >> Yes. I guess, in a couple different ways. I mean, number one, I think the applications of today versus the applications of yesterday have changed so much. I mean, you look at, you know, the applications you have on your mobile phone. The ability to have that look and feel, I mean, our kids today are going to go into the workforce and they won't settle for anything less. They're going to want to have that look and feel. They're going to want to have those intuitive type of applications that help them do their job. And that's the kind of offering we're bringing to the marketplace. Then from just actually bringing the right people and we have an application called Talent Science, as an example, where actually there's multiple different areas of your personality that it can determine and map it back to your top performers in your company. And determine the right people for the right job where they'll fit into that environment and then they would thrive hopefully. And it should increase retention on the staff. In government, we've actually sold it to Department of Health and Human Services for hiring case workers. Okay? Or to police departments for hiring of law enforcement. So there's a real opportunity to take those types of applications and do some pretty creative things. >> What's, I hate to say, the pain side of it. But dealing with the government obviously contracts is an issue, right? And a challenge sometimes maybe for you. I'm curious, in a quickly evolving space such as yours, how do you help them keep up with you and their regulatory oversight and whatever mandated restrictions they have? All those things, you know, that come with government. It just doesn't square up with what you do. >> It is, it's a very, again, to your point, it's a different, it's a different industry with different requirements. And everything here is very open and above board. It's open procurements. Everything is competitively bid. There are contractual vehicles that you competitively bid for that'll allow you to be able to do business a lot easier in the future. I mean, in the feds you have things like the GSA 70 Schedule. U.K., you have something called the G-Cloud contract. A lot of states have vehicles where you can bid for it, so all states and local can buy off of those contracts without having to go to a competitive offering. So there's ways that the business can get done without having to go through a lot. >> Every hoop and every, yeah, right. >> The major pain process. But then there's also competitive RFPs, which, you know, well, they'll put a bid out, it'll be very detailed. You have to answer 3,000 requirements. And then after that you'll end up going into an orals and a demo process and, you know, nine months later, they're going to pick a winner. (laughs lightly) Then you go through, but then you have to go through a very painful contract negotiation process. >> That's the process I was talking about. (laughing) Exactly what I was talking about, right. >> Right. >> Yeah, yeah. Well, Kevin, thanks for being with us. We appreciate the time. >> It's my pleasure. >> And it sounds impressive, right, with the turnout you had, so I'm sure you're very, very pleased with the response you've had here on the show for so far. >> I am and I thank you for your time and >> You bet. >> have a good show. >> Look forward to seeing you down the road. Alright, sir, thank you. Back with more here live on theCUBE. We're at Inforum '18 and we are in Washington, D.C. >> I'm quite sure they got me pinned up back here, but I can't-- (upbeat music)

(techno music) >> From Orlando, Florida, it's The Cube. Covering SAP Sapphire Now 2018. Brought to you by NetApp. >> Welcome to The Cube. I'm Lisa Martin with Keith Townsend and we are at SAP Sapphire Now 2018 in Orlando. This is a massive event. Not only are there 20,000 people here but there's about a million engaging with SAP this week online. Amazing! We're joined by a Cube alumni. Welcome back to The Cube >> Thank you Lisa. Chris Hallenbeck. You are the SVP of Database and Data Management at SAP. >> What they tell me. (laughter) >> That's what they tell you. That's what your cards say? >> It is. >> Alright. Well, thanks for coming onto The Cube. So this event is enormous. Sixteen American football fields is this space. You really can close your rings. >> Well, and it is, is the energy is just crazy. It's actually different than other years. I don't know why but it really it is. >> You know yesterday, that's what Keith and I were saying yesterday. Bill McDermott really kicked things off with such enthusiasm and genuine energy. It was really amazing to see that. You don't see that with a lot of, see levels on day one. That energy was really palpable as was. >> Enterprise applications aren't that sexy huh? (crosstalk) >> Apparently they are. >> Well, apparently they are now. >> Who knew? >> Well, and that's the thing too. You guys wanting to be one of the top ten most valuable brands in the world. Up there with Apple, Google. And one of the cool things I saw yesterday on a bus out here was ERP that you can talk to and hear from. So taking this, what was an invisible product and making it now something that people can engage with like a digital assistant at home. Remarkable. >> Well, yeah. No. The user interface which has been a huge, huge thing. We have these massive UX labs throughout the world. We have ones in Palo Alto. We have ones throughout Germany and other locations. And we've been really looking at how people engage with the software. And it's not only through a screen although that's it and we win all these Red Dot awards, the Preeminent Design Award. We get those consistently now, many a year, for the work we're doing within UI which is fabulous work. But we're also again, a lot of people aren't in front of computers anymore. So how can I actually just speak into my phone and get all the information I need? How can I have the device speak to me? How can somebody wearing gloves on an assembly line, automatically they vibrate if they're reaching for the wrong bin and would have grabbed the wrong part which create a faulty defective product. So it's all built in, our actually shoes vibrating if something else happens. And so actually this interaction of sensors in two way, taking IOT data in, and then also feeding it back into signals but that's part of the interface of the software. It's not always sitting in a screen and if you are in front of a screen, they're actually pretty great to use. >> So speaking of these consumer technologies, we've had this expectation and these technologies have changed the expectations of what our business tech is. We expect to be able to do things such as, hey, say what's the latest score from last night's game. And now there's these intelligent streams of having conversations with computers. All that is powered by the data on the backend. SAP traditionally hadn't been. We talked about it on stage this morning. SAP hadn't been known for the type of company to sub at to the real-time data entry, real-time data analytics. >> Yeah. You're all about data management. We heard something on the stage this morning. What was it? Data management suite? (crosstalk) The mature database now. (crosstalk) What is that? What's that about? >> Well, now what we're finding, you know, HANA enabled these incredible use cases and originally we were all, we actually didn't run underneath SAP applications an entire database but really a data platform that people were doing these incredible innovations on. And then of course it really started to get swept underneath and it went under BW and then it became part of Sweden HANA and everyone just focused said, oh yeah, HANA is just gonna be like Netweaver. It's just a system that runs underneath SAP and we kept saying no, it's not, no, it's not. And it was sort of but that was its main, that was where it was mostly getting deployed. And then what you're actually seeing here at Sapphire is this massive breakout of technology in full use use cases. That people are using it outside even non-SAP customers are using it to solve their individual problems. Really going after that huge, that 80% of data which is non-SAP but the challenge there with is how do you handle that? Data is now sitting out in all these different clouds. HANA was known for orchestrating data but it was really designed to do it on premise because we knew not everyone's gonna put data into our system. We came in late, right. And yeah we're the fastest growing but data was sitting in Oracle, and the TIZA and that's coming up and going into data lakes, running on ADO and we could orchestrate and move that data into HANA or do it in place. Go to the cloud, it's totally different. Average customer and CIOs are telling you they have six to eight clouds and you're like, wait, how did you get to six to eight? And you're like, yeah, they've got data in storage just in Azure, in AWS, and in Google but they've also got in all these different cloud applications and a lot are from SAP but a lot aren't and yet and so companies are telling us we've lost the view of who our customer is. We've lost view of our business. Which is the opposite of what you would have expect from this data explosion and, you know, digital transformation which was like showed up and disappeared in like two years but so how do you handle that? If I have data. So much data sitting out there. IOT data in the edge, love file data sitting in object stores, I've got data in different applications, data still on Fram. How can I actually possibly move that? You can't. There's no way to put it all together in one cloud. Everyone says, oh, bring it to my cloud. It's not viable. >> Right. So how do I actually push compute, get the data I need, refine it in place, and orchestrate and move that together with the ultimate security in governance? Which is what our customers are wanting. They're saying, how Chris for our non-SAP data and SAP, can I move data for application integration? How do I do analytics? How can I pre-press data and load it into a data lake, into a data warehouse and then I'll come back and do some other cool stuff on it with data science? And that's all about by combining HANA and data hub together in a suite with deep integrations, technically from a data center readiness it's all as a service runs in the cloud but because we're SAP it's also on Prem enabled if you still want to run it that way. And it allows you to solve these huge data problems and we also help you. We bring SAPs intellectual property of data models to this so you can use things like Enterprise Architecture designer and say look we don't have a model of customer. I'm like, well yeah, what kind of industry are you in? Okay, I've got a high tech customer model pre-built for you so then you don't have to build that from scratch. We bring the things to you. So now you can get very, very quick value right from the implementation within weeks. >> And that speed is obviously essential. >> Well, how does it. (crosstalk) >> HANA's a terror, which it's known for. >> But you're right, sorry Keith, you're right that in the consumer world because we have access to everything everywhere from so many devices, we as business people expect the same thing. >> Yeah. And so that speed is critical. You talk about, you know, multiple clouds, data in so many different sources. It's not valuable unless you can actually harness it and extract insights that may only be viable for a quarter or something like that. >> But nobody even knows where the data is and so you look at like we're about to, we were talking about HANA. I just came back and we're coming out a little bit later the year with HANA data hub 2.3 which is part of HANA data management suite and that actually has a whole metadata repository. So someone who knows what they're doing goes in and maps out where all this data is located and actually they don't have to do it all themselves, it's got heuristic-al and semantic search to automatically map and categorize data. I can then map that back to like my definition of customer or supplier and other things. Now everyone doing all the analytics and doing exactly what you're talking about Keith where can I just say into my phone, hey, someone in board meeting goes hey what were our results within two peak last year over this year and show and break that down by city and have it just pop up. Just like you say to somebody, hey high school football game, didn't those two play together? Anyone can do that on a mobile device but we don't know the data in our own company. How do you do that? And then let HANA data management suite will automatically know where the data is, orchestrate, go get it, pull it together, and deliver that back to a mobile device that you might have spoken into. >> Do you have a favorite customer that articulates just what you said? >> I do. I just actually walked out of a session. It was just and it sounds a little boring but it's incredible what people are doing. So I just walked out of a thing with the Swiss Federal Railways. Sounds boring but you know where. I live in Europe and everything is by rail, right? And so they're doing about 60 percent of the rail traffic there is passengers, 1.25 million passengers a day plus the balance of 40 percent of the trains are freight. They're having a huge problem because you use huge, it's all electrical and they're trying and so when you get up and it's growing rapidly. So they're, and they do their own power with power plants and when they go up with power plants, when they go over peak they have to spot by at just massive times a premium on that data on that. And we're actually doing this a lot of place out of rail but they also use electricity on heaters and other stuff in the cold winters and air conditioners. They're now streaming information off the trains, off of the points all the way along the signals and from all the power plants. They know peak usage. It automatically detects when they're going to go over and rather than going into the plants, it actually cuts the heaters off for a second here or there. There's heaters in all the switching equipment. They know how long they can do it. HANA managed this, this is automatically so it's IOT in but it's automatically making automated business decisions, shutting down systems programmatically, intelligently actually using machine learning and keeping it. So now what they do, so now they don't need to go out to the spot market in buy energy anymore. It has cut their electrical usage by a third. >> How much money have they saved? >> No, what's a third is how much money they've saved. The electricity is still high but they're not buying that really, really >> The premium. expensive premium and so you're streaming data, it's all over, it's all happening in real time, and it's automatically kicking out business processes without human intervention. And then it's a platform for them where they're adding all this new capability to save in other ways and so it's just, you know, simple but clean really good use. Good for the planet. It's great for the customers. And now they have, and by the way, when you hit those peaks, that's when they short-out systems and that's when trains stall out. So actually you're getting better servicing of the trains. So, yeah, it's good storage. >> So edge core cloud, great breakdown of kind of the use case. The data is being collected at the edge. Data may not even be collected in a SAP system? (crosstalk) We're doing great! >> It's reality. >> It is reality and one of the things that I think architecturally that enterprises have a hard time wrapping their head around, HANA in-memory database defeats latency when you're inside the database, when you're inside of the data center, however you were thinking about HANA data management. How does the in-memory database impact and data management impact data retrieved from the edge? Help explain the importance of metadata and willing down that data so that we can get it back to the cloud and process their important data. >> Keith, it's a great question. Sometimes, HANA is not, you know. Although we like to go it's a hammer and we think everything's a nail but sometimes you don't which is why we have data hub. And it has unique capabilities for doing something called data pipelines and movement. So we can actually do all the data transformation movement calling tensor flow in flight. We do this as the data is in movement so we're actually doing all of that processing as it's moving through. If you need extra horsepower and want to combine different data types and there's certain capabilities pipeline engines don't solve well. HANA is a service which HANA is now completely cloud native. They can actually bring up HANA in a few seconds. It will take the data flow in, compute it, it's not being used as database, it's a compute layer out at the edge, the data flows out to move on to the next step usually via a data pipeline from data hub and that service gets shut off. So you just pay from small compute when you need to bring out the big guns and then it moves on. And maybe that data never comes back into a HANA system, maybe it does, but you're using the technological underpinnings of in-memory computing in this way as just literally a flow through compute engine. >> And I think that's the disconnect a lot of organizations have because you associate s4 bases, BW, all these applications on top of the database. They don't think of HANA as something that you can spin up, spin down. >> But that's brand-new and that is what we just announced and went live last week. So HANA was, there's traditional on-prem system, bare-metal, it run virtualized but I mean talking about big arm running HANA systems. Now to actually have it, so HANA as a service came up. We rewrote the entire thing to make it completely cloud native and orchestrated. It's all containerized in elastic. It runs, it came up last week running an AWS and available also in GCP. Our target is a little bit later this year. I always have to use a safe harbor language. It'll be coming up on, it'll be coming up in Azure and after all the rest of SAPs data centers and then also coming out and in Asia through Huawei and coming up in those data centers as well as some others we have planned. And that's where you actually get this fully elastic HANA that's able to come up and come down automatically. >> So this massive transformation that you guys have achieved in 46 years, say 46 years young, 390,000 customers. >> Yeah. SAP didn't get to where it is without having a really robust symbiotic partner relationship ecosystem. We're here in the NetApp booth. There's a 150 partner sessions alone at Sapphire this week. Talk to us a little bit about how the partner ecosystem is helping you guys give customers the flexibility and the choice that they need. >> Yeah, no, and it is. SAP can't do everything. And so a lot of the aspects are that we look at in very different ways. Of course, some companies and the big corporations we deal with need strategic SIs, these strategic integrators to do consulting and other pieces and we work really closely with them on and they have specialized practices and other things on both HANA. They're extending out into the HANA data management suite. We do the same thing since we realize you need boutiques. We're the fastest geospatial engine in the world but that's a very niche piece although geospatials may be the hottest data type out there happening right now. Those are very specialized boutique firms. So we work with all of those and to help our customers when they need that. So we work with a lot of specialists. We work boutiques but we couldn't do this without hardware partners, with storages which is why we allow. There's still a lot of folks running on Prem. So we still have to have all these things so we have HANA tailor data center integration so you can certify your systems like NetApp. You can certify everything else on prem so you don't have to rebuy new hardware. Use what you have. I'm not trying to get you to buy a bunch of new appliances. And then the other one is a lot of is via and OEMs have started building out on HANA but now what they really want to do is go directly on HDMS as the cloud offering because it runs both in any cloud, which is a very unique differentiator that we run in every major cloud out there, as well as coming back and running on-premise. They can play their applications very risk-free with the extreme security and governance we're providing within that stack to build applications that they want to sell and use for enterprises. >> So you've been with SAP about six years you said and even Bill McDermott said in his keynote on day one, biggest Sapphire ever. You've seen a tremendous amount of growth. The momentum here is so palpable. The types of validation that SAP is getting through the voice of the customer, through partners like Netta, the different partner ecosystem. That validation is electric. >> Yeah. >> What excites you about everything that was just announced in the last couple of days about the rest of 2018? Where do you go from here? >> Oh my god! Okay, it's like asking me to pick my favorite child. (crosstalk) But, you know, honestly I get to. You get to see the innovations that I still enjoy. I love the full use use cases because I'm like a compute guy at heart but I see all the applications that we've done in these demonstrations. The fact that people have applications that are giving all of the analytics in line with the transactions on these gorgeous UIs. I mean you run these things on a mobile device that means the data layer has 20 milliseconds to actually not only grab the data but to do all the predictive analytics and everything you see to give you that nice two second screen to screen time on your mobile device and that's what we've worked for six years to enable. And now we're seeing that potential coming out at places like Swiss Rail. Just was talking with Gustav Rossi through the biggest cancer research labs and hospitals throughout all of Europe. They're doing all this genomic research, personalized medicine for cancer patients throughout Europe using HANA. I didn't even know about it, you know, or other ones we talked about beef farmers. Talking about smart farming throughout all the Netherlands. Reducing pesticide use, water usage dramatically down, and they increased yields by 10 percent. I mean and they're doing this on native HANA. So this area for me, the excitement of people and busting out of the SAP core traditional CIO market and moving into this 80% of data is to me exciting that people are seeing that HANA is not just an SAP appliance but it's really a general-purpose data platform for these innovation use cases. >> Helping customers change their business, change industries, save lives, pretty cool stuff. >> Yeah, I think so. >> Chris, thank you so much for stopping by The Cube and sharing with us your enthusiasm and your excitement for what you're doing at SAP. We appreciate it. >> Well, thank you very much. This was awesome. Thank you guys. >> We want to thank you for watching The Cube. Lisa Martin with Keith Townsend at SAP Sapphire 2018. Thanks for watching! (techno music)

(techno music) >> Announcer: It's the Cube, covering Sapphire Now 2017, brought to you by SAP Cloud Platform, and HANA Enterprise Cloud. >> Hey, welcome back to our exclusive SAP coverage here in our studio in Palo Alto, our 4,500 square foot studio. I'm John Furrier. Our three days, we're on third day, of Sapphire Now 2017 coverage. I'm on the phone with RJ Bibby, who's the SAP Global Alliance Manager for SAP. Handles the relationship. RJ, great to have you on the phone and thanks for calling in from Orlando, really appreciate it. >> RJ: You bet, John. Love the Cube. Love SiliconANGLE. We're great partners. It's been a great week and looking forward to talking to you about it. >> Tell us what's going on on the ground. First, give us the updates on day three. So, pretty much everyone's coming-- And always a great activities at night as well. So, SAP, a lot of business done during the day. They work hard. They play hard. But, day three, what's it like? What's settling in as the storylines for Sapphire 2017? >> RJ: Yeah, absolutely. So, you're starting to feel-- You've gone through about-- We're in our third tour. For the partner's community, we're in day four, cause we had the partner day. Last night was the big partner night. We actually NetApped with our partners with Cisco and KPIT did a private event at Universal Studios at the Jimmy Fallon Theme Park that was highly successful. What was great about today, was in the morning, we kicked off will Bill McDermott on stage with Kobe Bryant and Derek Jeter. And it was all about leadership and mentorship and experience in being in the business, whatever industry that you're in for so long and how you just stay creative, hungry, and passionate. And it was packed. One of the comments was they couldn't believe, on the day after the big party night of all the partners that you still have a lot of energy on the floor. Ultimately, it's still about data, which is great for our business that we can get into at NetApp. There's a lot of buzzword bingo going on here, John, all week, whether it's machine to machine, blocked chain, Cloud-- And at the end of it, it's still our customers who we've talked to a lot this week, and wow. What are we going to do with out data? How do we analyze it? And how do we improve that user experience based on all this data that we have? And I think that's one of the things that I see on the floor that's almost overwhelming with the amount of people, 30,000, all the partners. Just a lot of information. And lastly, I'll say, the good news with that is everybody is hungry for content. Whether it's a mini-theater, whether it's at one of the booths, interactions one-on-one, it's people are hungry for what is happening in the industry. And I think that's exciting for all of us. >> Well, we do our part and try and get as much coverage as possible, even if we are going to do it from Palo Alto. Question for you on NetApp. I mean, you guys have been-- The scuttlebutt in Silicon Valley is that NetApp is doing very well with the Hyperscale (mumbles). I know for a fact. I've interviewed the former CEO and others within NetApp. They were really on early with AWS. And obviously, AWS a big part of the announcement at Sapphire. So, you guys are kind of like getting these relationships with these key players. It's changed a little bit of the business model, or culture within NetApp. What's different about NetApp right now? With resect to some of the big players that you've had relationships with. It's not this new relationship with SAP. You guys have a deep relationship. What's changing as the CloudWave hits, as the DataWave hits? Those are the biggest waves hitting the world right now. How are you guys playing in that world? And share some insight there. >> RJ: Absolutely. Great question. 'Cause the world is going through digital transformation and so is NetApp. So, we are actually celebrating our 25th year as a company right now and we've been a traditional, global technology and data management company. And, the digital shift to Hybrid Cloud is where we're moving. So, specifically with partners like AWS, Microsoft and Azure, the Hyperscalers like CenturyLink, it's how we can help our customers really collect, transport, analyze, protect data, in whatever environment they want to hold their data. Whether it's On-Premises, if your in a Cloud, you can choose whatever Hyperscaler you want. You still have to deal with the data. And then, how do we manage it? How do we consume it? Where is dead data that needs to be taken out? So, data's the currency and with our data fabric methodology and tools from software, hardware, we're really able to help manage that complete life cycle, whether it's SAP, or any other type of environment we hold. So, the exciting thing for us, and the stock prices is showing that at an all time high, is what Bill McDermott said on Monday, in the keynote, or excuse me, Tuesday, "Data is the currency. "Our new mission statement is we're trying "to empower our customers to change the world with data." So, back to the buzzWord bingo comment I made earlier, we're still dealing with fact that we have all these great technologies: all these censors, machine-to-machine, On-Print to Cloud. At the heart of everything is the data and what you do with it. And I think that one of the things that NetApp does and the best in the world of, is we continually evolve digital transformations with the tools on how we deal with data. So, that's high level. >> How about the data dynamic? >> Data is the fundamental story, in my opinion. Cloud has been around, the Clouderati. We were part of that from the beginning. Now, Cloud is mainstream. Amazon stock prices looking like a hockey stick now, it's going straight up. But, that took years of development, right? I mean, you saw the Cloud formation coming, really, in the mid-2000s and then, really at 2008, -09, -10 was the foundational years and then the rest is history. Data's now going through the same thing. As people get over themselves and say, "Okay, big data's not a dupe. It's everything." IOT is certainly highlighting a lot of that. SAP has recognized that legacy systems have to move to a MultiCloud and certainly multi-vendor world in a whole new way. But, at the end of the day, you still got to store this stuff. So, that's your business. How are you keeping up with the moving train of data as is architecturally shifts in the marketplace? >> RJ: Great question. I think that we have some of the best minds in Silicon Valley. Again, been there 25 years. I think with the deep relationships we have with companies like SAP. On the front end, I think the one thing that we bring as a value to SAP is the consumption model, life exists. Through owning the data and the user experience, we're able to enable and accelerate the license consumption to the edge. Right from application in to the system. From an architectural standpoint, it still comes down to the thing that we are creating and blabs and launching around, like the data fabric, the tool system, really software. The software that can help from an analytical perspective affect the user experience. Everybody wants it live. And the other part is the data protection and the DR aspect of it. And I think that's another core competency that we're continuing to develop as a service for the customer. So, I hop I've answered your question. >> Yup. >> RJ: But if-- >> (mumbles) a bottom line then, why NetApps? Say I'm a customer. Okay, I get the SAP. Why should I go with you guys over new the Delium see powerhouse over there, or the White-Box Storage? >> RJ: At the end of the day, we are best at capitalizing the value of data in the Hybrid Cloud. Nobody can help collect, analyze, test, and do life-cycle management live like NetApp can. And that's the reason that we are going more upstream, selling like we say at EPC, always selling to the CXO. I think we're changing the landscape from a true storage company on the infrastructure side to a full end-to-end Hybrid Cloud data management portfolio company. And it's been proven by the acquisition of Salazar from bringing Slash in to the portfolio, our cloning, and snapshot capabilities. So, anywhere in the stack at any time during the day when you're looking live at your operations or your data that you can take live snapshots. Just so if there's a glitch from a data protection side, or there's some type of spike from a request on the ticketing side or demand side of your system. So, I think that's some of the things that we're differentiating. And that's the reason that the AWSs and the Azures and the SAPs are so excited about co-innovating together to again, improving the customer experience with their data. >> RJ, final question. What's the net-net? What's the bumper sticker for you this year at Sapphire 2017? What's the walk-away revelation? >> RJ: Well, I think from the SAP side, it's the revelation on the push of Leonardo. I think that SAP-- I'd like to see them continue to hone out the 'what' and the 'if' from partners with Leonardo from blotching in machine-to-machine and IOT. For us, it is the beautiful fact that now at the center of everything that SAP and the ecosystem is trying to do is around the data side of it and it's the actual currency. And the fact that we have kind of the leading-edge tools to enhance the customer experience with our platform for customers' and partners' data is really, really exciting for us. And we're excited. We're all psyched to be partnered with the Cube. And everything we do is in the Cloud. So, I'm here to help. >> Alright. >> RJ, thanks so much for takin' the time callin' in from Orlando. RJ Bibby, SAP Global Alliance Executive with NetApp. He runs the the relationship with NetApp. And again, it's been a long-term relationship. I remember takin' photos on my phone, way back in the day, years ago. So, not a new relationship and continued momentum. Congratulations and thanks for sharing the insight from Orlando. 'Preciate it. >> RJ: You bet. Thanks for the partnership. Have a great day. >> 'Kay, more coverage from the Cube in Palo Alto on SAP, Sapphire 2017 after this short break. Stay with us. (techno music)

>> Narrator: It's theCUBE, covering Sapphire Now 2017, brought to you by SAP Cloud Platform, and HANA Enterprise Cloud. >> Hello everyone, welcome back to our special coverage of SAP Sapphire Now. I'm John Furrier, here in theCUBE's studios of Palo Alto for our three days of wall to wall coverage, breaking down all the news with analysis. Our next guest here on theCUBE is Emily Mui, Senior Director of HANA Cloud Product Marketing at SAP, and Michael Hill, Senior Director of Product Marketing and SAP Cloud Platform. I had a chance to have a conversation around the big news around SAP Cloud Platform and what it means. I had a chance to ask Emily and Michael about the Sapphire impact around this new strategy, and the impact of multi-cloud. Here's the conversation with Michael and Emily. >> Three things to remember, three Cs, it's about helping accelerate cloud adoption, consumption, as well as-- >> [Michael And John] Choice. >> Choice, because of multi-cloud. >> So this is interesting. So the three Cs, I love that, very gimmicky marketing thing that I like. It gets to the point. Choice is huge. Multi-cloud is what everyone's talking about, in essence is what hybrid cloud's turning into. I mean, hybrid cloud has been the defacto norm now everyone's talking about, that is the preferred way most enterprises are using the cloud on premise and some public cloud, call it hybrid. But now, the mobile cloud's out here. There's Amazon Web Service, you've got Google, Azure, so there's a lot of, so the choice is critical, where to put what were clothes. >> And that's what we're hearing from our customers, and that's why we're moving in that direction. Not everyone wants to stick to one infrastructure as a service provider, they've got multiple clouds to manage, and we're enabling that. >> So choice I get. Cloud adoption is essentially creating those APIs to give them that accelerated approach. More cloud adoption means what? I've got be able to run stuff in the cloud faster, so that means getting their apps API, the API economy. And the consumption, is that on the interface side, or what's the consumption piece of it? >> Well, I'm going to let Michael have a swing at it now. >> It's consumption of innovation. So here we're talking about helping companies with digital transformation with things like Internet of Things, which we had in beta, which is now generally available, so customers can intelligently connect people, things, and business processes, all together now. In addition, we've added other great technologies like SAP CoPilot, which is allowing you to talk to your enterprise systems. So initially, that's what with SAPS for HANA. And you can say, "I'm interested in, "tell me all the open orders from the last quarter." And it will intelligently go get that information. >> It's like a voice recognition, all kinds of news things are coming out. >> Absolutely. >> As a user interface, or interface on cloud. >> They're for the enterprise. >> Or IT interface. >> On your phone or on your computer. >> So it's all being automated. We all know AI, that's just, "All our jobs are being automated." But this is specific. You're saying you're going to interface in with like CoPilot. >> Exactly. So you've got that business context. >> All right, let's step back and look at the Lego blocks. The cloud choice, multi-cloud. Let's get in, and then we'll talk about the adoption piece, how you guys are accelerating that through the marketplaces and APIs, and then the consumption through the new interfaces. So start with multi-cloud. What are the big points there? >> Well, the first is the agility that your platform as a service is now available on not just SAP data centers, but Amazon Web Services, Microsoft Azure, and Google Cloud Platform, being delivered. Amazon Web Services is now generally available, Azure is now beta, and there's a preview of Google Cloud Platform. And here you have one cockpit in SAP Cloud Platform to manage this multi-cloud infrastructure. >> So your strategy is to put your platform as a service on the clouds that customers want to run their workloads on? >> Exactly. So customers may already have specific workloads, or they may be working with partners that have workloads in those particular clouds. And now, SAP Cloud Platform can run in that same infrastructure. >> So the plan is to support the platform as a service from SAP on the clouds of choice for the customer. So they want to put stuff on Azure, if it's related to Office 365, or something going on with that, they could put it there. If they want to put some cloud-native on Amazon Web Service, they can. If they want to use Spanner and some TensorFlow, they could put that on Google. >> And to make this happen was really cool thing, is that we did this through our work in Cloud Foundry, and this allows you to bring your own development language, so BYOL. So if you have developers that are working in a particular language that's not supported natively by SAP previously, they can now be instantly productive on building applications on SAP Cloud Platform. >> So Cloud Foundry is the key to success on this? >> Yeah. Exactly. And that bring things like Node.js, and Python, as well as SAPs. >> All the cloud-native goodness that people want from a developer standpoint. >> Exactly. >> But yet, you guys allow it to run on Prim within the SAP constructs. >> Yep. >> All right, let's talk about cloud adoption, 'cause this is where the big rubber hits the road. Emily, we've been talking about the API economy for years. In fact, SAP was early on, and Web Services going through bankrupt. But there's some real value in here, because SAP runs software in some of the biggest businesses, so there's a lot of nuances to SAP. But when you go cloud and cloud-native, you've got to balance preexisting install base legacy with new apps that are being developed, how are you guys going to do that? >> So we announced the API Business Hub around a year ago at Sapphire in 2016, and it has grown tremendously in terms of content. So we had a lot of new APIs that keep getting added every month. And we're into the hundreds now. But it's not just the APIs, we've got integration workflows, there's all kinds of different content that's being added in there to make easier for our customers and partners to be able to leverage, and integrate, and connect, these different application with SAP back-end. So lot of exciting things happening on that end. >> So this allows them to go to the cloud business model. >> Emily: Exactly, right. >> Okay, now back to the consumption pieces, CoPilot. So is this where you guys are looking at where the dynamic nature of cloud can take advantage of the customers, because not only interfacing with, say, voice, for instance, there's others things, like, "Okay, I want to change processes. "I have the Workflow, or I'm doing something, "I want to just, "I'm not a developer, a Python developer, "I want to go in and make some rule changes, "or things of that nature." >> Yeah, so we have the Workflow service, that's also available. We've got a whole host of new capabilities that are coming out, and we'll call it digital edge, giving our customers a digital edge with these new innovative services. >> Edge as the user and also machines. >> Yes. >> That's where the IoT piece comes in. >> Exactly. >> So decision maker or customer says, "Hey, I've done all this stuff in the cloud." All of a sudden, someone says, "Well, we've got to bolt on some industrial data "from machines in our plant or factory." >> In fact, our IoT, the newest set of capabilities for IoT services is available at Sapphire. >> Okay, s\o what's the big takeaway from this? Let's just boil it down. Bottom line, this announcement impacts customers in what way? >> In many ways. We see many of customers wanting to become digital. And we've talked about how we think the benefits of cloud platform has to do with helping our customers become much more agile in how they do business, and SAP is in perfect position to do that. We've been working with companies, enterprises for years with their business processes, helping them optimize it. So that's the other bit, to be able to optimize all their business processes, and through the cloud. And then lastly, digital is the way to that they want to go. They know they want to be able to adopt all these new technologies. AI is so exciting. The CoPilot, if you've seen the demo, and you can see it at show floor here at Sapphire, it's amazing. Just the fact that you can talk to it, create an order, do some search, talk to it. I know that's how my kids, how they get through everyday life. They don't go look up anything anymore, they don't even Google, just talk. >> It's very dynamic. Certainly, the kids are an indicator, that you see if they want things, have the ability to move things around like the Lego blocks or composability. >> Yeah, so the speed, so that's why we love talking about accelerating consumption, and choice, and cloud adoption, because the speed of which everyone is adopting new technologies is just astronomical. >> Michael, comment on that point, because I always, this is our eight year covering Sapphire with theCUBE. It's our first year we're doing it from the studio as well. But Bill McDermott has always been on this with the whole dashboarding thing. If you look at SAP, the speed of business, how (mumbles) year that was. But each year, he never really changed, it's been the same arc, might've been a zigzag here and there, a little success factors here and there, all this kind of integration you guys have done. But it's been the same message, data's at the heart of the customers' outcomes. And the dashboards of old were data warehouses. But now he was showing a vision where, with the speed of data, the speed of software, you can get your business dashboard at your fingertips. That's what the customers are looking for. Your thoughts? >> It's not only being able to get that information at your fingertips, but actually being able to do something about it. So you can build those applications that can make an impact. So if you have, you're using our iOS SDK, and you've build that Apple interface, you have a nice interface that you can move an order, or you can do something about it while you're traveling. So you have this great dashboard, but now it's actionable. >> And this is the big difference, this is what makes his original vision, which certainly you can replicate with SAP's suite of data, and data and software, to a whole nother dimension of new apps. So app developers can come in and create these apps, and create new value propositions. >> Absolutely. >> All right, so how do they do that? What's the advice the customers, as they look at this new announcement, the impact of them, what does it mean to customer? Pick your cloud of choice? Use the APIs? >> Plenty of choices, and of course, we offer them a lot of guidance too, right? Because we've got a lot of great customers that are using the cloud platform today, some of which are presenting here at Sapphire. Karma Automotive, we love their story. They used to be Fisker Automotive, an all electronic vehicle. And it's amazing that the things that they want to do, and they're using the cloud platform in order to do that. But it's just another example of an innovative company that's looking to work with a company like SAP, and do everything in the cloud, building an application that will make it easier in terms of IoT, the sensors, and things like that, so they can track it to be able to take action on it. So it's very exciting. So lots of new things that are happening. >> I think there's two things that jump out at me, just to summarize the freedom that developers in the cloud-native world can do to create new apps, that also blend in on all of the existing value that SAP's already doing in the marketplace, that's always been, that was something that I observed last year, this is now a realization of that. But two, is now the customers now have a choice to put whatever they want in whatever cloud. And to me, what we've seen on theCUBE over the many interviews we've done, people who follow theCUBE know we've talked to a lot of people, is the workloads find their homes, some like Amazon, some like Azure, some like Google, and I think that is what customers are telling us, and you guys are now offering that choice. "Hey, put some workloads over there. "It doesn't matter where you want to put 'em, "we're just going to run 'em with--" >> And where we can help is really on the business service side. We have the right types of application services within the platform as a service offering, to enable them to create those types of apps to support their business. >> Applications, data, value for customers. >> And it's the integration of data into the application, because that's what's important. >> There'll be a new generation of application developers. We're standing up application like PowerPoint slides, really composing apps, that is the DevOps mainstream trend. Emily, thanks so much for sharing the great news. Michael, good to see you. Thanks for coming on theCUBE. Special Sapphire Now 2017 coverage. Breaking the news of the three Cs, multi-cloud, SAP's new announcement in Orlando. This is theCUBE coverage. More coverage after this short break.

(upbeat music) >> Hello, and welcome to theCUBE special coverage of Sapphire Now we're here in Palo Alto. Sapphire now SAPs premier conference in Orlando. We are in Palo Alto, we have folks on the ground in Orlando. Special three days of wall-to-wall coverage. Tuesday, Wednesday, and Thursday. Taking you through all the action from our new studio in Palo Alto, 4,500 square feet. Our chance to cover events when we can't get there in person we certainly can cover it from here. And that's what we're going to be doing for the next three days; we're going to have stories on the ground, no story is too small. We're going to chase 'em all down. We have people calling in, we have folks on the ground that'll be Skyping in, calling in, whatever it takes to get the story out to you, we're going to do it and, certainly, expert coverage from inside the studio here. We got George Gilbert from Wikibon and a variety of folks who did not make it to Orlando will be coming into Palo Alto to sit down and talk with us. I'm John Furrier, my co-host is Jeff Frick. Jeff, we'll do whatever it takes. We'll cover from our studio, we'll go to Orlando virtually we got the Twitter hashtag, Sapphirenow, we're on that. We have folks on the ground, a lot of great news coming out of Sapphire. >> What do ya think? I mean, you were just as Dell EMC World last week and the story was all about, kind of, hybrid cloud and customer choice and it sounds like that's a recurring theme here at SAP, where they've got a lot of cloud options based on what their customer wants to do. >> I mean, if you, I mean this sounds really bad to say for someone who follows the tech industry but I just think this digital transformation thing is just over-played. But it's the, it's the Groundhog's Day moment. The movie just keeps replaying itself. Digital transformation, digital transformation, and, again, just like every other commerce, like Dell EMC World and every other one, digitally transforming your business is the theme. Little bit played, I would say business transformation is, I would say, the next chapter of what's happening and what you see from these shows. Specifically, at Dell EMC World, US ServiceNow, OpenStack, all the different events, Red Hat's been the one we been going to this past couple weeks is the business impact of the technology and SAP highlights that with their results and their keynotes in the news letter drops today, which is, look it, they have been doing SAP for all the top companies powering with SAP. As in Oracle. But now the customers want to go beyond the legacy SAP. And this has been a challenge for SAP over the past five years. They've had all the right messaging, digital dashboards, real time for business, all there. But the problem was they were missing a big piece of it. That is a cloud native and really aligning with the explosive growth of cloud computing, cloud native. Which is the new application developer. This new class of developer is emerging and that's different than the in-house SAP guys, by the way, which is still a massive market. >> Sure. >> That's the big trend. And of course, machine learning, AI, the kinds of design tooling that you'd expect to see, they're calling that Leonardo. >> I think it really shows the power of the consumer and the impact that the big public clouds have had on the marketplace, right? With Google, and with Amazon, especially Microsoft, as well, coming into play. And I think it's, what's interesting on the SAP tact is they have their own cloud. But now they've, you know, are very aggressively following up on an earlier announcement at Google Cloud Platform Show. With more announcements at this show and then they continue to strengthen their relationship with Amazon. So, it's a pretty interesting place, if you're an SAP customer, really having options around where, what cloud and what cloud deployment is really no longer an argument. You've got a lot of options at SAP, very different than Oracle, which is still pretty much exclusively Oracle on the Oracle cloud. Very different kind of a tact. >> Yeah and just reading the hard news from from hitting the ground today down in Orlando is the key points, I'll just summarize it real quick. Expanded SAP Leonardo, Digital Innovation System, SAP Google Expand the Strategic Partnership, SAP Cloud Platform accelerates adoption and proves choice advances consumption for customers. That, essentially, is it. And there's a lot of other subtext going on on Enterprise Cloud, a lot of other massive pockets. But in terms of top-level news, it's Leonardo, okay? Leonardo Da Vinci, dead, creative genius. Okay? But that is all about providing the tools for business to be successful in a digital world. But to me, the big story, Jeff, is the transformation of what used to be called HANA Cloud Platform to SAP Cloud Platform. This is their platform as a service bet around winning the new developers, the cloud native. Last year at Sapphire, we actually had theCUBE on the ground they announced a deal with Apple computer around iOS and developers. That, now, has chip as a general availability so you're seeing SAP bringing two worlds together. The Cloud Native World, which they never played in much to the SAP Eco System, which is flush with cash. There's a ton of money to be made in that world. The install base is massive, now you have Cloud-Computing Hybrid Cloud with the HANA Cloud Platform, I mean the SAP Cloud Platform to bring that in. Again, I still can't even get it right. >> And so, let's just break it down as simply as you can, John. Why do they change the name? And what exactly do they have today? >> Well, here's the first of all problem. I'm so used to saying HANA because they have been branding HANA on >> They been bangin' HANA for the decade, or forever. >> It's just like, in my brain. I just can't get it out. SAP HANA, so anytime, and they actually called it HANA Cloud Platform before. >> Right, right. >> But HANA is such a massive set of capabilities that they really wanted to break out the platform as a service, which is the Cloud Native play, where all the action is for developers. From HANA, a viable product that they have that everyone's using. So, they have two clouds that we can say. SAP Cloud Platform, that's in Cloud Native, and then, HANA Enterprise Cloud. One's a delivery mechanism and one's a developer environment; it's the way I like to think about it. I'm a HANA customer, I'm going to need Enterprise Cloud to take my HANA solution and extend it up with self-service or provisioning, some partnership with AWS Google and the different clouds, getting my legacy HANA Enterprise software to be cloud enabled. That's HANA Enterprise Cloud. SAP Cloud Platforms for folks who don't, who like DevOps, the Cloud Native world that we cover deeply. >> Okay, and then, how do you look at the kind of Google partnership, Google Cloud Platform versus AWS partnership. SAP's goin' dual-track, is it just simply to have choice based on what their customers, are they fundamentally different relationships? How do you read that? >> This is where I think SAP's got genius going on. But if they might screw it up because they can't get out of their own way. >> Jeff: Can't use genius anymore, we've had enough geniuses. >> So, so, this could be a brilliant strike of move for SAP. I think it's a brilliant move in the way they're playing it out. But, again, like I said, SAP, they might not be able to get out of their own way. That's going to be their issue. But from a functionality standpoint, this multi-cloud opportunity; they've been with Amazon for many many years. They announced a partnership with Google which is just kind of toe in the water. That's tryin' to advance pretty quickly. Not a lot of meat on the bone there. And Azure relationships. So, SAP wants to put their cloud platform, that platform as a service, in all the different major clouds so that their legacy can work on pram and in whichever cloud the customer chooses. >> Yeah, I think there is, >> I think, that is a multi-cloud strategy that is viable for SAP. Unlike, say, Oracle, which isn't multi-cloud, it's Oracle Cloud. >> Right, right, right. >> So, you know the SAP Oracle, you know, head-to-head thing has been kind of, like, taking completely different paths. Someone will be right. >> Right. But I think there's more meat on the bone with the Google thing than, maybe, maybe we know of, or are aware of, or whatever. I mean, Burnt did come and get in the keynote with Diane Greene at Google Cloud Platform. And, you know, I think it's relatively significant. What'll be interesting to see how it shapes out and, again, what are the customer choices that are going to drive them to Amazon or to SB Cloud or to the Google cloud. I guess at the end of the day it's about choice and I know that was a big theme at Dell EMC World. Is that everyone has to cater to the choice of the customer or else it's just too easy for them to flip a lot of these other clouds. >> I mean, when I say, "not ready for primetime," I mean, Google's got a lot of work to do. SAP as a company is not as far down the road with Google as they are with Amazon and Azure, just to make my point clear. >> Okay. >> But the do have our announcing additional certifications of the coinnovation between SAP and Google. Between SAP Cloud Platform and Google Cloud Platform. IOT, machine learning, they certified SAP NetWeaver in a variety of S4 HANA, business warehousing; essentially more market place to accelerate the digital transformation. And, again, this is all about SAP co-locating in Google. >> Right, right. >> If a customer wants to take advantage of TensorFlow and all the goodness of, say, Google. That's a good move for SAP and, again, I think this is a brilliant strategy for SAP if they don't screw it up. >> Right, right. And potentially, that's the bridge to, like you said, it's been a little bit of Groundhog Day with cloud, cloud, cloud. But what's really the theme of 2017 is AI machine learning and it's an interesting bridge with Google Cloud, to their TensorFlow as another way to bring AI machine learning into the application learning into the application. >> So, Jeff, we've been covering a lot of events. One comment, I will say, is that SAP always has great messaging. >> I got to say, because we've been covering out eighth year covering Sapphire Now. We've only missed, like, two years over that time span. It's a lot like Oracle on the sense that it's a very business oriented event, but they have good pulse. Bill McDermott, great communicator, great customer-focused person. Always has his hand on the pulse. They have great messaging. And they tend to pick the right waves. And they've had some false starts with cloud, they've bought, had some acquisitions, things been cobbled together, but they've never wavered from their mission. And the mission has always been powering the speed of business, great software solutions. The issue is, they're moving off of SAP to new cloud solutions, so SAP is taking a proactive strike to say, look here, we can play in the cloud, therefore this multi-cloud game is critical for the growth of SAP, in my opinion. >> How much of the SAP in cloud will be new greenfield opportunities, or people want the flexibility, and a lot of the attributes of cloud versus, they're not migrating old R3 instances into the cloud. I mean, this is, I would assume, mainly new greenfield opportunities. >> Well, I think it's both. I mean, I think you have greenfield developers basically that are being hired by their customers to build apps, top line driven apps, and also, you know, some consolidation apps. But mainly, you know, their customers are hiring developers. Hey, we need a mobile app for our business, so you need to have data, you need to have some domain expertise. But at the end of the day, the system of records probably stored in some SAP system somewhere. So what they're trying to do is decouple the dependency between that developer, but still use SAP, but and offer an extension of SAP. It really is an opportunity, in my mind, for that to happen, and also partners. Look at Accenture, Capgemini, all these different partners. They are poised to create some great value and make some cash along the way. Remember the minicomputer boom. People who lined their pockets with cash were the integrators. The large global system integrators. So I think that, and the channel partners are going to have a great opportunity to take advantage of preexisting legacy accounts and to grow them further. >> Well, they certainly have a giant ecosystem. There's no doubt about it. It's one of the startup challenges that, new company starters to build that ecosystem. I mean, they have a giant ecosystem. So, what are you looking for this week besides the obvious announcement? And kind of tells that you want to see to let you know that SAP continues to be on track and move with the shifting tides of the market trends? >> Well do me, I'm looking at the multi-cloud story. It's a good story. Not sure how baked it is, but from a story standpoint, I really like it. I think that whoever can really crack the code on multi-cloud in a viable way is going to be a winner. So to me, I'm going to be looking heavily at the multi-cloud stuff coming out of Orlando. I'm interested to see how the developer traction pans out. I'm really interested in following up on the Apple relationship and see how that pans out. And then ultimately, how the rest of SAP can transform as a business. Because SAP tends to have a lot of buzzwords, a lot of word salad, not a lot of, you know, breaking it down and orchestrating. So to me, SAP, where I'm critical of them is, they kind of can't get out of their own way, Jeff. So, sometimes they kind of get caught in that old world thinking when the world is moving very very fast. Look at Amazon Web Services, you look at what Google's doing, you look at where Vmware is changing. Vmware started Pat Gelsinger. He was in the dumps in 2016, now he's flying high. He went from almost being fired, stock had a 52 week low, to them soaring. They have a market cap that's greater than HPE. So these old incumbent like SAP, they have to transform their culture, get relevant, and get real. And if they can't show the proof points with customer wins and partners, and multi-cloud, then they're going to be on shaky ground. So that's what I'm looking for. >> Jeff: All right, so should be a good week. I'm looking forward to it. >> Okay, we are here in the Palo Alto studio, our new 4,500 square foot operation. We can do coverage here, and then have on the ground coverage of which we will be doing all week Tuesday, Wednesday, and Thursday for our SAP Sapphire Now. We've got great guests coming in, great editorial coverage. I want to thank our sponsors, SAP, for, you know, allowing us to do this and continuing theCUBE tradition at Sapphire Now. I'm John Furrier with Jeff Frick. More coming after this short break.

>> Announcer: From San Jose, California, it's The Cube, covering Big Data Silicon Valley 2017. >> Welcome back everyone. We are at Big Data Silicon Valley, running in conjunction with Strata + Hadoop World in San Jose. I'm George Gilbert and I'm joined by Raymie Stata, and Raymie was most recently CEO and Founder of Altiscale. Hadoop is a service vendor. One of the few out there, not part of one of the public clouds. And in keeping with all of the great work they've done, they got snapped up by SAP. So, Rami, since we haven't seen you, I think on The Cube since then, why don't you catch us up with all that, the good work that's gone on between you and SAP since then. >> Sure, so the acquisition closed back in September, so it's been about six months. And it's been a very busy six months. You know, there's just a lot of blocking and tackling that needs to happen. So, you know, getting people on board. Getting new laptops, all that good stuff. But certainly a huge effort for us was to open up a data center in Europe. We've long had demand to have that European presence, both because I think there's a lot of interest over in Europe itself, but also large, multi-national companies based in the US, you know, it's important for them to have that European presence as well. So, it was a natural thing to do as part of SAP, so kind of first order of business was to expand over into Europe. So that was a big exercise. We've actually had some good traction on the sales side, right, so we're getting new customers, larger customers, more demanding customers, which has been a good challenge too. >> So let's pause for a minute on, sort of unpack for folks, what Altiscale offered, the core services. >> Sure. >> That were, you know, here in the US, and now you've extended to Europe. >> Right. So our core platform is kind of Hadoop, Hive, and Spark, you know, as a service in the cloud. And so we would offer HDFS and YARN for Hadoop. Spark and Hive kind of well-integrated. And we would offer that as a cloud service. So you would just, you know, get an account, login, you know, store stuff in HDFS, run your Spark programs, and the way we encourage people to think about it is, I think very often vendors have trained folks in the big data space to think about nodes. You know, how many nodes am I going to get? What kind of nodes am I going to get? And the way we really force people to think twice about Hadoop and what Hadoop as a service means is, you know, they don't, why are you asking that? You don't need to know about nodes. Just store stuff, run your jobs. We worry about nodes. And that, you know, once people kind of understood, you know, just how much complexity that takes out of their lives and how that just enables them to truly focus on using these technologies to get business value, rather that operating them. You know, there's that aha moment in the sales cycle, where people say yeah, that's what I want. I want Hadoop as a service. So that's been our value proposition from the beginning. And it's remained quite constant, and even coming into SAP that's not changing, you know, one bit. >> So, just to be clear then, it's like a lot of the operational responsibilities sort of, you took control over, so that when you say, like don't worry about nodes, it's customer pours x amount of data into storage, which in your case would be HDFS, and then compute is independent of that. They need, you spin up however many, or however much capacity they need, with Spark for instance, to process it, or Hive. Okay, so. >> And all on demand. >> Yeah so it sounds like it's, how close to like the Big Query or Athena services, Athena on AWS or Big Query on Google? Where you're not aware of any servers, either for storage or for compute? >> Yeah I think that's a very good comparable. It's very much like Athena and Big Query where you just store stuff in tables and you issue queries and you don't worry about how much compute, you know, and managing it. I think, by throwing, you know, Spark in the equation, and YARN more generally, right, we can handle a broader range of these cases. So, for example, you don't have to store data in tables, you can store them into HDFS files which is good for processing log data, for example. And with Spark, for example, you have access to a lot of machine learning algorithms that are a little bit harder to run in the context of, say, Athena. So I think it's the same model, in terms of, it's fully operated for you. But a broader platform in terms of its capabilities. >> Okay, so now let's talk about what SAP brought to the table and how that changed the use cases that were appropriate for Altiscale. You know, starting at the data layer. >> Yeah, so, I think the, certainly the, from the business perspective, SAP brings a large, very engaged customer base that, you know, is eager to embrace, kind of a data-driven mindset and culture and is looking for a partner to help them do that, right. And so that's been great to be in that environment. SAP has a number of additional technologies that we've been integrating into the Altiscale offering. So one of them is Vora, which is kind of an interactive sequel engine, it also has time series capabilities and graph capabilities and search capabilities. So it has a lot of additive capabilities, if you will, to what we have at Altiscale. And it also integrates very deeply into HANA itself. And so we now have that for a technology available as a service at Altiscale. >> Let me make sure, so that everyone understands, and so I understand too, is that so you can issue queries from HANA and they can, you know, beyond just simple sequel queries, they can handle the time series, and predictive analytics, and access data sort of seamlessly that's in Hadoop, or can it go the other way as well? >> It's both ways. So you can, you know, from HANA you can essentially federate out into Vora. And through that access data that's in a Hadoop cluster. But it's also the other way around. A lot of times there's an analyst who really lives in the big data world, right, they're in the Hadoop world, but they want to join in data that's sitting in a HANA database, you know. Might be dimensions in a warehouse or, you know, customer details even in a transactional system. And so, you know, that Hadoop-based analyst now has access to data that's out in those HANA databases. >> Do you have some Lighthouse accounts that are working with this already? >> Yes, we do. (laughter) >> Yes we do, okay. I guess that was the diplomatic way of saying yes. But no comment. Alright, so tell us more about SAPs big data stack today and how that might evolve. >> Yeah, of course now, especially that now we've got the Spark, Hadoop, Hive offering that we have. And then four sitting on top of that. There's an offering called Predictive Analytics, which is Spark-based predictive analytics. >> Is that something that came from you, or is that, >> That's an SAP thing, so this is what's been great about the acquisition is that SAP does have a lot of technologies that we can now integrate. And it brings new capabilities to our customer base. So those three are kind of pretty key. And then there's something called Data Services as well, which allows us to move data easily in and out of, you know, HANA and other data stores. >> Is it, is this ability to federate queries between Hadoop and HANA and then migration of the data between the stores, does that, has that changed the economics of how much data people, SAP customers, maintain and sort of what types of apps they can build on it now that they might, it's economically feasible to store a lot more data. >> Well, yes and no. I think the context of Altiscale, both before and after the acquisition is very often there's, what you might call a big data source, right. It could be your web logs, it could be some IOT generated log data, it could be social media streams. You know, this is data that's, you know, doesn't have a lot of structure coming in. It's fairly voluminous. It doesn't, very naturally, go into a sequel database, and that's kind of the sweet spot for the big data technologies like Hadoop and Spark. So, those datas come into your big data environment. You can transform it, you can do some data quality on it. And then you can eventually stage it out into something like HANA data mart, where it, you know, to make it available for reporting. But obviously there's stuff that you can do on the larger dataset in Hadoop as well. So, in a way, yes, you can now tame, if you will, those huge data sources that, you know, weren't practical to put into HANA databasing. >> If you were to prioritize, in the context of, sort of, the applications SAP focuses on, would you be, sort of, with the highest priority use case be IOT related stuff, where, you know, it was just prohibitive to put it in HANA since it's mostly in memory. But, you know, SAP is exposed to tons of that type of data, which would seem to most naturally have an afinity to Altiscale. >> Yeah, so, I mean, IOT is a big initiative. And is a great use case for big data. But, you know, financial-to-financial services industry, as another example, is fairly down the path using Hadoop technologies for many different use cases. And so, that's also an opportunity for us. >> So, let me pop back up, you know, before we have to wrap. With Altiscale as part of the SAP portfolio, have the two companies sort of gone to customers with a more, with more transformational options, that, you know, you'll sell together? >> Yeah, we have. In fact, Altiscale actually is no longer called Altiscale, right? We're part of a portfolio of products, you know, known as the SAP Cloud Platform. So, you know, under the cloud platform we're the big data services. The SAP Cloud Platform is all about business transformation. And business innovation. And so, we bring to that portfolio the ability to now bring the types of data sources that I've just discussed, you know, to bear on these transformative efforts. And so, you know, we fit into some momentum SAP already has, right, to help companies drive change. >> Okay. So, along those lines, which might be, I mean, we know the financial services has done a lot of work with, and I guess telcos as well, what are some of the other verticals that look like they're primed to fall, you know, with this type of transformational network? >> So you mentioned one, which I kind of call manufacturing, right, and there tends to be two kind of different use cases there. One of them I call kind of the shop floor thing. Where you're collecting a lot of sensor data, you know, out of a manufacturing facility with the goal of increasing yield. So you've got the shop floor. And then you've got the, I think, more commonly discussed measuring stuff out in the field. You've got a product, you know, out in the field. Bringing the telemetry back. Doing things like predictive meetings. So, I think manufacturing is a big sector ready to go for big data. And healthcare is another one. You know, people pulling together electronic medical records, you know trying to combine that with clinical outcomes, and I think the big focus there is to drive towards, kind of, outcome-based models, even on the payment side. And big data is really valuable to drive and assess, you know, kind of outcomes in an aggregate way. >> Okay. We're going to have to leave it on that note. But we will tune back in at I guess Sapphire or TechEd, whichever of the SAP shows is coming up next to get an update. >> Sapphire's next. Then TechEd. >> Okay. With that, this is George Gilbert, and Raymie Stata. We will be back in few moments with another segment. We're here at Big Data Silicon Valley. Running in conjunction with Strata + Hadoop World. Stay tuned, we'll be right back.

>> Announcer: Live from San Jose, California, it's theCUBE, covering Big Data Silicon Valley 2017. (light techno music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Big Data SV, wrapping up with two days of wall-to-wall coverage of Big Data SV which is associated with Strata Comp, which is part of Big Data Week, which always becomes the epicenter of the big data world for a week here in San Jose. We're at the historic Pagoda Lounge, and we're excited to have our next two guests, talking a little bit different twist on big data that maybe you hadn't thought of. We've got Ravi Dharnikota, he is the Chief Enterprise Architect at SnapLogic, welcome. - Hello. >> Jeff: And he has brought along a customer, Katharine Matsumoto, she is a Data Scientist at eero, welcome. >> Thank you, thanks for having us. >> Jeff: Absolutely, so we had SnapLogic on a little earlier with Garavs, but tell us a little bit about eero. I've never heard of eero before, for folks that aren't familiar with the company. >> Yeah, so eero is a start-up based in San Francisco. We are sort of driven to increase home connectivity, both the performance and the ease of use, as wifi becomes totally a part of everyday life. We do that. We've created the world's first mesh wifi system. >> Okay. >> So that means you have, for an average home, three different individual units, and you plug one in to replace your router, and then the other three get plugged in throughout the home just to power, and they're able to spread coverage, reliability, speed, throughout your homes. No more buffering, dead zones, in that way back bedroom. >> Jeff: And it's a consumer product-- >> Yes. >> So you got all the fun and challenges of manufacturing, you've got the fun challenges of distribution, consumer marketing, so a lot of challenges for a start-up. But you guys are doing great. Why SnapLogic? >> Yeah, so in addition to the challenges with the hardware, we also are a really strong software. So, everything is either set up via the app. We are not just the backbone to your home's connectivity, but also part of it, so we're sending a lot of information back from our devices to be able to learn and improve the wifi that we're delivering based on the data we get back. So that's a lot of data, a lot of different teams working on different pieces. So when we were looking at launch, how do we integrate all of that information together to make it accessible to business users across different teams, and also how do we handle the scale. I made a checklist (laughs), and SnapLogic was really the only one that seemed to be able to deliver on both of those promises with a look to the future of like, I don't know what my next Sass product is, I don't know what our next API point we're going to need to hit is, sort of the flexibility of that as well as the fact that we have analysts were able to pick it up, engineers were able to pick it up, and I could still manage all the software written by, or the pipelines written by each of those different groups without having to read whatever version of code they're writing. >> Right, so Ravi, we heard you guys are like doubling your customer base every year, and lots of big names, Adobe we talked about earlier today. But I don't know that most people would think of SnapLogic really, as a solution to a start-up mesh network company. >> Yeah, absolutely, so that's a great point though, let me just start off with saying that in this new world, we don't discriminate-- (guest and host laugh) we integrate and we don't discriminate. In this new world that I speak about is social media, you know-- >> Jeff: Do you bus? (all laugh) >> So I will get to that. (all laugh) So, social, mobile, analytics, and cloud. And in this world, people have this thing which we fondly call integrators' dilemma. You want to integrate apps, you go to a different tool set. You integrate data, you start thinking about different tool sets. So we want to dispel that and really provide a unified platform for both apps and data. So remember, when we are seeing all the apps move into the cloud and being provided as services, but the data systems are also moving to the cloud. You got your data warehouses, databases, your BI systems, analytical tools, all are being provided to you as services. So, in this world data is data. If it's apps, it's probably schema mapping. If it's data systems, it's transformations moving from one end to the other. So, we're here to solve both those challenges in this new world with a unified platform. And it also helps that our lineage and the brain trust that brings us here, we did this a couple of decades ago and we're here to reinvent that space. >> Well, we expect you to bring Clayton Christensen on next time you come to visit, because he needs a new book, and I think that's a good one. (all laugh) But I think it was a really interesting part of the story though too, is you have such a dynamic product. Right, if you looked at your boxes, I've got the website pulled up, you wouldn't necessarily think of the dynamic nature that you're constantly tweaking and taking the data from the boxes to change the service that you're delivering. It's not just this thing that you made to a spec that you shipped out the door. >> Yeah, and that's really where the auto connected, we did 20 from our updates last year. We had problems with customers would have the same box for three years, and the technology change, the chips change, but their wifi service is the same, and we're constantly innovating and being able to push those out, but if you're going to do that many updates, you need a lot of feedback on the updates because things break when you update sometimes, and we've been able to build systems that catch that that are able to identify changes that say, not one person could be able to do by looking at their own things or just with support. We have leading indicators across all sorts of different stability and performance and different devices, so if Xbox changes their protocols, we can identify that really quickly. And that's sort of the goal of having all the data in one place across customer support and manufacturing. We can easily pinpoint where in the many different complicated factors you can find the problem. >> Have issues. - Yeah. >> So, I've actually got questions for both of you. Ravi, starting with you, it sounds like you're trying to tackle a challenge that in today's tools would have included Kafka at the data integration level, and there it's very much a hub and spoke approach. And I guess it's also, you would think of the application level integration more like the TIBCO and other EAI vendors in a previous generation-- - [Ravi] Yeah. >> Which I don't think was hub and spoke, it was more point to point, and I'm curious how you resolve that, in other words, how you'd tackle both together in a unified architecture? >> Yeah, that's an excellent question. In fact, one of the integrators' dilemma that I spoke about you've got the problem set where you've got the high-latency, high-volume, where you go to ETL tools. And then the low-latency, low-volume, you immediately go to the TIBCOs of the world and that's ESB, EAI sort of tool sets that you look to solve. So what we've done is we've thought about it hard. At one level we've just said, why can integration not be offered as a service? So that's step number one where the design experience is through the cloud, and then execution can just happen anywhere, behind your firewall or in the cloud, or in a big data system, so it caters to all of that. But then also, the data set itself is changing. You're seeing a lot of the document data model that are being offered by the Sass services. So the old ETL companies that were built before all of this social, mobile sort of stuff came around, it was all row and column oriented. So how do you deal with the more document oriented JSON sort of stuff? And we built that for, the platform to be able to handle that kind of data. Streaming is an interesting and important question. Pretty much everyone I spoke to last year were, streaming was a big-- let's do streaming, I want everything in real-time. But batch also has it's place. So you've got to have a system that does batch as well as real-time, or as near real-time as needed. So we solve for all of those problems. >> Okay, so Katharine, coming to you, each customer has a different, well, every consumer has a different, essentially, a stall base. To bring all the telemetry back to make sense out of what's working and what's not working, or how their environment is changing. How do you make sense out of all that, considering that it's not B to B, it's B to C so, I don't know how many customers you have, but it must be in the tens or hundreds. >> I'm sure I'm not allowed to say (laughs). >> No. But it's the distinctness of each customer that I gather makes the support challenge for you. >> Yeah, and part of that's exposing as much information to the different sources, and starting to automate the ways in which we do it. There's certainly a lot, we are very early on as a company. We've hit our year mark for public availability the end of last month so-- >> Jeff: Congratulations. >> Thank you, it's been a long year. But with that we learn more, constantly, and different people come to different views as different new questions come up. The special-snowflake aspect of each customer, there's a balance between how much actually is special and how much you can find patterns. And that's really where you get into much more interesting things on the statistics and machine learning side is how do you identify those patterns that you may not even know you're looking for. We are still beginning to understand our customers from a qualitative standpoint. It actually came up this week where I was doing an analysis and I was like, this population looks kind of weird, and with two clicks was able to send out a list over to our CX team. They had access to all the same systems because all of our data is connected and they could pull up the tickets based on, because through SnapLogic, we're joining all the data together. We use Looker as our BI tool, they were just able to start going into all the tickets and doing a deep dive, and that's being presented later this week as to like, hey, what is this population doing? >> So, for you to do this, that must mean you have at least some data that's common to every customer. For you to be able to use something like Looker, I imagine. If every customer was a distinct snowflake, it would be very hard to find patterns across them. >> Well I mean, look at how many people have iPhones, have MacBooks, you know, we are looking at a lot of aggregate-level data in terms of how things are behaving, and always the challenge of any data science project is creating those feature extractions, and so that's where the process we're going through as the analytics team is to start extracting those things and adding them to our central data source. That's one of the areas also where having very integrated analytics and ETL has been helpful as we're just feeding that information back in to everyone. So once we figure out, oh hey, this is how you differentiate small businesses from homes, because we do see a couple of small businesses using our product, that goes back into the data and now everyone's consuming it. Each of those common features, it's a slow process to create them, but it's also increases the value every time you add one to the central group. >> One last question-- >> It's an interesting way to think of the wifi service and the connected devices an integration challenge, as opposed to just an appliance that kind of works like an old POTS line, which it isn't, clearly at all. (all laugh) With 20 firmware updates a year (laughs). >> Yeah, there's another interesting point, that we were just having the discussion offline, it's that it's a start-up. They obviously don't have the resources or the app, but have a large IT department to set up these systems. So, as Katharine mentioned, one person team initially when they started, and to be able to integrate, who knows which system is going to be next. Maybe they experiment with one cloud service, it perhaps scales to their liking or not, and then they quickly change and go to another one. You cannot change the integration underneath that. You got to be able to adjust to that. So that flexibility, and the other thing is, what they've done with having their business become self-sufficient is another very fascinating thing. It's like, give them the power. Why should IT or that small team become the bottom line? Don't come to me, I'll just empower you with the right tool set and the patterns and then from there, you change and put in your business logic and be productive immediately. >> Let me drill down on that, 'cause my understanding, at least in the old world was that DTL was kind of brittle, and if you're constantly ... Part of actually, the genesis of Hadoop, certainly at Yahoo was, we're going to bring all the data we might ever possibly need into the repository so we don't have to keep re-writing the pipeline. And it sounds like you have the capability to evolve the pipeline rather quickly as you want to bring more data into this sort of central resource. Am I getting that about right? >> Yeah, it's a little bit of both. We do have a central, I think, down data's the fancy term for that, so we're bringing everything into S3, jumping it into those raw JSONs, you know, whatever nested format it comes into, so whatever makes it so that extraction is easy. Then there's also, as part of ETL, there's that last mile which is a lot of business logic, and that's where you run into teams starting to diverge very quickly if you don't have a way for them to give feedback into the process. We've really focused on empowering business users to be self-service, in terms of answering their own questions, and that's freed up our in list to add more value back into the greater group as well as answer harder questions, that both beget more questions, but also feeds back insights into that data source because they have access to their piece of that last business logic. By changing the way that one JSON field maps or combining two, they've suddenly created an entirely new variable that's accessible to everyone. So it's sort of last-leg business logic versus the full transport layer. We have a whole platform that's designed to transport everything and be much more robust to changes. >> Alright, so let me make sure I understand this, it sounds like the less-trained or more self-sufficient, they go after the central repository and then the more highly-trained and scarcer resource, they are responsible for owning one or more of the feeds and that they enrich that or make that more flexible and general-purpose so that those who are more self-sufficient can get at it in the center. >> Yeah, and also you're able to make use of the business. So we have sort of a hybrid model with our analysts that are really closely embedded into the teams, and so they have all that context that you need that if you're relying on, say, a central IT team, that you have to go back and forth of like, why are you doing this, what does this mean? They're able to do all that in logic. And then the goal of our platform team is really to focus on building technologies that complement what we have with SnapLogic or others that are accustomed to our data systems that enable that same sort of level of self-service for creating specific definitions, or are able to do it intelligently based on agreed upon patterns of extraction. >> George: Okay. >> Heavy science. Alright, well unfortunately we are out of time. I really appreciate the story, I love the site, I'll have to check out the boxes, because I know I have a bunch of dead spots in my house. (all laugh) But Ravi, I want to give you the last word, really about how is it working with a small start-up doing some cool, innovative stuff, but it's not your Adobes, it's not a lot of the huge enterprise clients that you have. What have you taken, why does that add value to SnapLogic to work with kind of a cool, fun, small start-up? >> Yeah, so the enterprise is always a retrofit job. You have to sort of go back to the SAPs and the Oracle databases and make sure that we are able to connect the legacy with a new cloud application. Whereas with a start-up, it's all new stuff. But their volumes are constantly changing, they probably have spikes, they have burst volumes, they're thinking about this differently, enabling everyone else, quickly changing and adopting newer technologies. So we have to be able to adjust to that agility along with them. So we're very excited as sort of partnering with them and going along with them on this journey. And as they start looking at other things, the machine learning and the AI and the IRT space, we're very excited to have that partnership and learn from them and evolve our platform as well. >> Clearly. You're smiling ear-to-ear, Katharine's excited, you're solving problems. So thanks again for taking a few minutes and good luck with your talk tomorrow. Alright, I'm Jeff Frick, he's George Gilbert, you're watching theCUBE from Big Data SV. We'll be back after this short break. Thanks for watching. (light techno music)