(techno music) >> Announcer: Live, from downtown San Francisco, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit 2018. Brought to you by IBM. >> Welcome back to San Francisco everybody, this is theCUBE, the leader in live tech coverage. We're here at the Parc 55 in San Francisco covering the IBM CDO Strategy Summit. I'm here with Joel Horwitz who's the Vice President of Digital Partnerships & Offerings at IBM. Good to see you again Joel. >> Thanks, great to be here, thanks for having me. >> So I was just, you're very welcome- It was just, let's see, was it last month, at Think? >> Yeah, it's hard to keep track, right. >> And we were talking about your new role- >> It's been a busy year. >> the importance of partnerships. One of the things I want to, well let's talk about your role, but I really want to get into, it's innovation. And we talked about this at Think, because it's so critical, in my opinion anyway, that you can attract partnerships, innovation partnerships, startups, established companies, et cetera. >> Joel: Yeah. >> To really help drive that innovation, it takes a team of people, IBM can't do it on its own. >> Yeah, I mean look, IBM is the leader in innovation, as we all know. We're the market leader for patents, that we put out each year, and how you get that technology in the hands of the real innovators, the developers, the longtail ISVs, our partners out there, that's the challenging part at times, and so what we've been up to is really looking at how we make it easier for partners to partner with IBM. How we make it easier for developers to work with IBM. So we have a number of areas that we've been adding, so for example, we've added a whole IBM Code portal, so if you go to developer.ibm.com/code you can actually see hundreds of code patterns that we've created to help really any client, any partner, get started using IBM's technology, and to innovate. >> Yeah, and that's critical, I mean you're right, because to me innovation is a combination of invention, which is what you guys do really, and then it's adoption, which is what your customers are all about. You come from the data science world. We're here at the Chief Data Officer Summit, what's the intersection between data science and CDOs? What are you seeing there? >> Yeah, so when I was here last, it was about two years ago in 2015, actually, maybe three years ago, man, time flies when you're having fun. >> Dave: Yeah, the Spark Summit- >> Yeah Spark Technology Center and the Spark Summit, and we were here, I was here at the Chief Data Officer Summit. And it was great, and at that time, I think a lot of the conversation was really not that different than what I'm seeing today. Which is, how do you manage all of your data assets? I think a big part of doing good data science, which is my kind of background, is really having a good understanding of what your data governance is, what your data catalog is, so, you know we introduced the Watson Studio at Think, and actually, what's nice about that, is it brings a lot of this together. So if you look in the market, in the data market, today, you know we used to segment it by a few things, like data gravity, data movement, data science, and data governance. And those are kind of the four themes that I continue to see. And so outside of IBM, I would contend that those are relatively separate kind of tools that are disconnected, in fact Dinesh Nirmal, who's our engineer on the analytic side, Head of Development there, he wrote a great blog just recently, about how you can have some great machine learning, you have some great data, but if you can't operationalize that, then really you can't put it to use. And so it's funny to me because we've been focused on this challenge, and IBM is making the right steps, in my, I'm obviously biased, but we're making some great strides toward unifying the, this tool chain. Which is data management, to data science, to operationalizing, you know, machine learning. So that's what we're starting to see with Watson Studio. >> Well, I always push Dinesh on this and like okay, you've got a collection of tools, but are you bringing those together? And he flat-out says no, we developed this, a lot of this from scratch. Yes, we bring in the best of the knowledge that we have there, but we're not trying to just cobble together a bunch of disparate tools with a UI layer. >> Right, right. >> It's really a fundamental foundation that you're trying to build. >> Well, what's really interesting about that, that piece, is that yeah, I think a lot of folks have cobbled together a UI layer, so we formed a partnership, coming back to the partnership view, with a company called Lightbend, who's based here in San Francisco, as well as in Europe, and the reason why we did that, wasn't just because of the fact that Reactive development, if you're not familiar with Reactive, it's essentially Scala, Akka, Play, this whole framework, that basically allows developers to write once, and it kind of scales up with demand. In fact, Verizon actually used our platform with Lightbend to launch the iPhone 10. And they show dramatic improvements. Now what's exciting about Lightbend, is the fact that application developers are developing with Reactive, but if you turn around, you'll also now be able to operationalize models with Reactive as well. Because it's basically a single platform to move between these two worlds. So what we've continued to see is data science kind of separate from the application world. Really kind of, AI and cloud as different universes. The reality is that for any enterprise, or any company, to really innovate, you have to find a way to bring those two worlds together, to get the most use out of it. >> Fourier always says "Data is the new development kit". He said this I think five or six years ago, and it's barely becoming true. You guys have tried to make an attempt, and have done a pretty good job, of trying to bring those worlds together in a single platform, what do you call it? The Watson Data Platform? >> Yeah, Watson Data Platform, now Watson Studio, and I think the other, so one side of it is, us trying to, not really trying, but us actually bringing together these disparate systems. I mean we are kind of a systems company, we're IT. But not only that, but bringing our trained algorithms, and our trained models to the developers. So for example, we also did a partnership with Unity, at the end of last year, that's now just reaching some pretty good growth, in terms of bringing the Watson SDK to game developers on the Unity platform. So again, it's this idea of bringing the game developer, the application developer, in closer contact with these trained models, and these trained algorithms. And that's where you're seeing incredible things happen. So for example, Star Trek Bridge Crew, which I don't know how many Trekkies we have here at the CDO Summit. >> A few over here probably. >> Yeah, a couple? They're using our SDK in Unity, to basically allow a gamer to use voice commands through the headset, through a VR headset, to talk to other players in the virtual game. So we're going to see more, I can't really disclose too much what we're doing there, but there's some cool stuff coming out of that partnership. >> Real immersive experience driving a lot of data. Now you're part of the Digital Business Group. I like the term digital business, because we talk about it all the time. Digital business, what's the difference between a digital business and a business? What's the, how they use data. >> Joel: Yeah. >> You're a data person, what does that mean? That you're part of the Digital Business Group? Is that an internal facing thing? An external facing thing? Both? >> It's really both. So our Chief Digital Officer, Bob Lord, he has a presentation that he'll give, where he starts out, and he goes, when I tell people I'm the Chief Digital Officer they usually think I just manage the website. You know, if I tell people I'm a Chief Data Officer, it means I manage our data, in governance over here. The reality is that I think these Chief Digital Officer, Chief Data Officer, they're really responsible for business transformation. And so, if you actually look at what we're doing, I think on both sides is we're using data, we're using marketing technology, martech, like Optimizely, like Segment, like some of these great partners of ours, to really look at how we can quickly A/B test, get user feedback, to look at how we actually test different offerings and market. And so really what we're doing is we're setting up a testing platform, to bring not only our traditional offers to market, like DB2, Mainframe, et cetera, but also bring new offers to market, like blockchain, and quantum, and others, and actually figure out how we get better product-market fit. What actually, one thing, one story that comes to mind, is if you've seen the movie Hidden Figures- >> Oh yeah. >> There's this scene where Kevin Costner, I know this is going to look not great for IBM, but I'm going to say it anyways, which is Kevin Costner has like a sledgehammer, and he's like trying to break down the wall to get the mainframe in the room. That's what it feels like sometimes, 'cause we create the best technology, but we forget sometimes about the last mile. You know like, we got to break down the wall. >> Where am I going to put it? >> You know, to get it in the room! So, honestly I think that's a lot of what we're doing. We're bridging that last mile, between these different audiences. So between developers, between ISVs, between commercial buyers. Like how do we actually make this technology, not just accessible to large enterprise, which are our main clients, but also to the other ecosystems, and other audiences out there. >> Well so that's interesting Joel, because as a potential partner of IBM, they want, obviously your go-to-market, your massive company, and great distribution channel. But at the same time, you want more than that. You know you want to have a closer, IBM always focuses on partnerships that have intrinsic value. So you talked about offerings, you talked about quantum, blockchain, off-camera talking about cloud containers. >> Joel: Yeah. >> I'd say cloud and containers may be a little closer than those others, but those others are going to take a lot of market development. So what are the offerings that you guys are bringing? How do they get into the hands of your partners? >> I mean, the commonality with all of these, all the emerging offerings, if you ask me, is the distributed nature of the offering. So if you look at blockchain, it's a distributed ledger. It's a distributed transaction chain that's secure. If you look at data, really and we can hark back to say, Hadoop, right before object storage, it's distributed storage, so it's not just storing on your hard drive locally, it's storing on a distributed network of servers that are all over the world and data centers. If you look at cloud, and containers, what you're really doing is not running your application on an individual server that can go down. You're using containers because you want to distribute that application over a large network of servers, so that if one server goes down, you're not going to be hosed. And so I think the fundamental shift that you're seeing is this distributed nature, which in essence is cloud. So I think cloud is just kind of a synonym, in my opinion, for distributed nature of our business. >> That's interesting and that brings up, you're right, cloud and Big Data/Hadoop, we don't talk about Hadoop much anymore, but it kind of got it all started, with that notion of leave the data where it is. And it's the same thing with cloud. You can't just stuff your business into the public cloud. You got to bring the cloud to your data. >> Joel: That's right. >> But that brings up a whole new set of challenges, which obviously, you're in a position just to help solve. Performance, latency, physics come into play. >> Physics is a rough one. It's kind of hard to avoid that one. >> I hear your best people are working on it though. Some other partnerships that you want to sort of, elucidate. >> Yeah, no, I mean we have some really great, so I think the key kind of partnership, I would say area, that I would allude to is, one of the things, and you kind of referenced this, is a lot of our partners, big or small, want to work with our top clients. So they want to work with our top banking clients. They want, 'cause these are, if you look at for example, MaRisk and what we're doing with them around blockchain, and frankly, talk about innovation, they're innovating containers for real, not virtual containers- >> And that's a joint venture right? >> Yeah, it is, and so it's exciting because, what we're bringing to market is, I also lead our startup programs, called the Global Entrepreneurship Program, and so what I'm focused on doing, and you'll probably see more to come this quarter, is how do we actually bridge that end-to-end? How do you, if you're startup or a small business, ultimately reach that kind of global business partner level? And so kind of bridging that, that end-to-end. So we're starting to bring out a number of different incentives for partners, like co-marketing, so I'll help startups when they're early, figure out product-market fit. We'll give you free credits to use our innovative technology, and we'll also bring you into a number of clients, to basically help you not burn all of your cash on creating your own marketing channel. God knows I did that when I was at a start-up. So I think we're doing a lot to kind of bridge that end-to-end, and help any partner kind of come in, and then grow with IBM. I think that's where we're headed. >> I think that's a critical part of your job. Because I mean, obviously IBM is known for its Global 2000, big enterprise presence, but startups, again, fuel that innovation fire. So being able to attract them, which you're proving you can, providing whatever it is, access, early access to cloud services, or like you say, these other offerings that you're producing, in addition to that go-to-market, 'cause it's funny, we always talk about how efficient, capital efficient, software is, but then you have these companies raising hundreds of millions of dollars, why? Because they got to do promotion, marketing, sales, you know, go-to-market. >> Yeah, it's really expensive. I mean, you look at most startups, like their biggest ticket item is usually marketing and sales. And building channels, and so yeah, if you're, you know we're talking to a number of partners who want to work with us because of the fact that, it's not just like, the direct kind of channel, it's also, as you kind of mentioned, there's other challenges that you have to overcome when you're working with a larger company. for example, security is a big one, GDPR compliance now, is a big one, and just making sure that things don't fall over, is a big one. And so a lot of partners work with us because ultimately, a number of the decision makers in these larger enterprises are going, well, I trust IBM, and if IBM says you're good, then I believe you. And so that's where we're kind of starting to pull partners in, and pull an ecosystem towards us. Because of the fact that we can take them through that level of certification. So we have a number of free online courses. So if you go to partners, excuse me, ibm.com/partners/learn there's a number of blockchain courses that you can learn today, and will actually give you a digital certificate, that's actually certified on our own blockchain, which we're actually a first of a kind to do that, which I think is pretty slick, and it's accredited at some of the universities. So I think that's where people are looking to IBM, and other leaders in this industry, is to help them become experts in their, in this technology, and especially in this emerging technology. >> I love that blockchain actually, because it's such a growing, and interesting, and innovative field. But it needs players like IBM, that can bring credibility, enterprise-grade, whether it's security, or just, as I say, credibility. 'Cause you know, this is, so much of negative connotations associated with blockchain and crypto, but companies like IBM coming to the table, enterprise companies, and building that ecosystem out is in my view, crucial. >> Yeah, no, it takes a village. I mean, there's a lot of folks, I mean that's a big reason why I came to IBM, three, four years ago, was because when I was in start-up land, I used to work for H20, I worked for Alpine Data Labs, Datameer, back in the Hadoop days, and what I realized was that, it's an opportunity cost. So you can't really drive true global innovation, transformation, in some of these bigger companies because there's only so much that you can really kind of bite off. And so you know at IBM it's been a really rewarding experience because we have done things like for example, we partnered with Girls Who Code, Treehouse, Udacity. So there's a number of early educators that we've partnered with, to bring code to, to bring technology to, that frankly, would never have access to some of this stuff. Some of this technology, if we didn't form these alliances, and if we didn't join these partnerships. So I'm very excited about the future of IBM, and I'm very excited about the future of what our partners are doing with IBM, because, geez, you know the cloud, and everything that we're doing to make this accessible, is bar none, I mean, it's great. >> I can tell you're excited. You know, spring in your step. Always a lot of energy Joel, really appreciate you coming onto theCUBE. >> Joel: My pleasure. >> Great to see you again. >> Yeah, thanks Dave. >> You're welcome. Alright keep it right there, everybody. We'll be back. We're at the IBM CDO Strategy Summit in San Francisco. You're watching theCUBE. (techno music) (touch-tone phone beeps)

>> Narrator: Live from Las Vegas, it's theCUBE! Covering IBM Think 2018. Brought to you by IBM. >> Hello everyone and welcome back to theCUBE's exclusive, three days of coverage here at IBM Think 2018. I'm John Furrier co-host with Dave Vellante, hosting three days and next is Joel Horowitz, Vice President Strategic Partnerships and Offering, of The Digital Business Group. >> Thanks. >> Welcome back to theCUBE. Good to see you. >> Good to see you guys. Thanks for having me here. >> Thanks for coming on. >> You've been on theCUBE, probably so many times, talking big data, talking analytics, now, in your new role in The Digital Group, the digital transformation. I really want to just ask you right off the bat about your new role, and how it relates to the changing ecosystem. >> Joel: Yeah. >> All of these markets are changing big time, the role of the ecosystem, the leverage that they have with technology and the value propositions, whether it's decentralized applications in Blockchain to storage and infrastructure, and big data. What is your role, take a minute to explain what you're doing, because you have a unique position, because this demand for partnerships, this demand for collaboration at many levels. What's the latest? >> So I would describe my role as being a champion of our partners, for sure. I look at, you know, I take, a very outside in perspective on IBM. Joining just over three years ago now, I came in, really through analytics, as you know, focused on machine learning, data science, and the growth of A.I. at that time. Last year I was part of the corporate development team over there. So looking, really, at a lot of the industry trends and what's going on, as well, in analytics, data, and A.I. This year, you know, we recognize that we're only going to do so many strategic partnerships a year, right, where there's probably a handful that we're going to work with. For example, last year we did a great partnership with Lightbend to bring their reactive platform to IBM, and we launched the iPhone 10, with Verizon on Lightbend's platform. But, these days, my team, can't be everywhere, obviously, and part of the value of digital, and that route to market is really the idea that partner should be able to self service. So, you know, my job this year, is frankly to put myself out of a job, right. Meaning, if I can get, you know, 70% of the work my team does, right, contracting, legal, setting up, provisioning, all of that on our cloud, and partners can just do that themselves. Then we'll capture a much larger swath of the emerging A.I., data, and cloud market. >> I want to talk about the killer app creating value and then the role the market place is playing. You mentioned self service. I want to kind of go down that. Before we get there, I want to get your thoughts on this because I noticed, in your role you're covering, it's cutting across a lot of different things, and you know we've been talking about cloud, as a horizontally disrupting technology, >> Joel: Yeah. >> Certainly in the data space you saw that. And stacks will be horizontally scalable with the cloud. >> Yeah. >> But you could be vertical specialization in the applications. So I noticed you're covering analytics, Watson, Cloud, hybrid cloud, emerging technologies. >> Yeah. >> Blockchain, and many others. >> Yeah. >> So talk about, it's obvious you guys are now cutting across, horizontally, across the different IBM divisions. Is that by design? >> Yeah. >> What's the impact of the ecosystem and partners for that horizontally cut over? >> Yeah, I know, I mean it's a great question, I think. Look, there are some specific design patterns that we see across every technology, across every, you know, business at IBM. One design pattern is pretty obvious, you saw it with the launch of the IBM cloud private data. Following up on last years IBM Cloud Private. And that design pattern is really about people containerizing applications. And so, at the end of the week, we have the business partner, or PartnerWorld Leadership conference. Excuse me. Where a number of our partners really are looking at how do I bring that work load to the cloud. And it's not so much the cloud is the end point. That's really the starting off point to A; Get much wider distribution and B; Be able to take advantage of a lot of these emerging technologies, like Blockchain, like A.I. Like IOT, and numerous others, Quantum, et cetera, they'll just keep coming. So really cloud to me is just a way for us to open the door to a lot of the technology that's flooding the market. >> Dave: Joel, can you talk about partnership, you mentioned before that you guys are kind of selective, John calls them Barney deals, ya know. I love you, you love me. You guys sound like you don't look for those, not volume, it's quality. >> Yeah. >> What are the criteria that you're looking for? How do you get value out of those? How do you measure that value out of the partnerships? If someone is a prospective partner out there, how should I be interacting with you? >> Yeah, I think, there's probably two steps. I think one is really recognizing that, in my own personal view, is that we really want to partner with folks who embrace open standards. Now I'm not going to like go as far to say open source, 'cause I think there is a lot that goes into that. But I will say open standards, meaning, not these like large monolithic applications, but can you actually integrate with us in some meaningful way? And to do that, that's why we actually started on this new platform that we are launching today. Called IBM Partner Self-service. Is the ability to first integrate with IBM. So, if you can demonstrate that you can build with IBM first, whether that's a startup, an ISV, a business partner. Like that's criteria number one. Criteria number two is are you a trusted partner? So, do you actually have the same level of competency that we would expect from, frankly, our own sellers, and our own people. And so, to do that, we've also launched new competency paths for business partners and partners as well. So, those are the two major criterias. And then the third one, which I think is kind of the holy grail, is selling with IBM. So we also launched a sell with path today where you can actually list in our marketplace. And then we will actually help you reach new markets. And then demonstrate there's clients, there's a client need that really wants our joint solution, right? And so, to me, those are the three things, to re-state. Like, you know, building with us, having a level of competency with us, and then demonstrating client success with us. >> Okay, so, integrate, you really don't need you guys to do that. I can just dive in and do that. Bake it out a little bit, and then approach you. What kind of help do you give? Do you have programs once you get by those gates? >> So, you know, I would categorize into two groups, I think we have a ton of online support. So, you know, we even embrace Slack at IBM. If you're not aware of that, we have Slack everywhere. And, so, for a self service, I want to say, look, what does zero touch mean, right, in this day and age, for a partner. And so, they can go to our site today, and actually get, you know, sign up for Slack, and talk directly to our technical specialist as well as to our developer advocates. And so, on the enablement and integration side, my colleague, Angel Diaz and team, have done a great job of launching hundreds of IBM code patterns. So that you can just pick these artifacts up, these assets up, and leverage them to integrate all sorts of capabilities into your product. >> You know, Dave, I want to get your thoughts on this, because you and I have been talking about the API integration, and I want to get back to Joel's point in a second because I think this is critical for startups and ecosystem partners. API's are the (speaking quickly) for developers right now, so if I don't want to take a big chance on being all in on IBM, say I want to kick the tires, API's are critical. So the question is, are you seeing that traction on your side of the house, in terms of the end now, since the level of API integration, is that the touchpoint? Is it like the beginning phases? And what level of commitment that you're seeing with people. >> Well, John, to me it comes down to innovation, and it's interesting because Joel came out of the data world. To me, the innovation in the next 10 years starts with data. The second component of that innovation, I think, over the next decade or so is going to be, really, A.I., whether you call it cognitive or machine intelligence or artificial intelligence. And then third, I think is cloud economics and that's really where the API economy fits in. You got to have API'S to integrate, as Joel was saying. You've got to have marginal... You've got to have scale, marginal costs go to zero eventually. You've got to have network effects and you've got to be able to track startups, which is another question I have. >> Now Joel, back to you, on the start on the integration, whether it's a startup or a big company. It used to be, the old days, you got to go all in. You've got to get the developer kit, >> Joel: Yeah. >> Download it, line it to a swim lane, get deeper, prove your value. >> Yeah. >> Find the value's faster; what's the first hurdle if someone wants, hey I want to give IBM a shot here? Love the sell, holy grail option, is it API'S, can people integration on their own? Talk about that specific first step because some people might open up the door and go whoa! There's more here than I thought. Or, wow, there's some real tech. Or, I don't want to use IBM tech, I want to use some of mine. There's that first indifference point. >> Yeah, I think there are areas where we've seen dramatic customer experience improvements. So to give one example, as we've partnered with Ubisoft, Redstorm last year around a new title game that they released called Star Trek Bridge Crew, and so, you know, to me, we went on our own merit, and I think that publisher chose IBM because Watson Conversation is absolutely the best on the market. And so what that did is it enabled game players, their end customer, their end user, to speak into a VR headset and just give commands, as you would naturally. And so, I think a lot of, as you think about IBM, it's, yeah, we've made it completely easy to access our API'S. I think, there's a great quote from the founder of Flickr that I read years ago, I'll go dig it up for you guys later, but it was along the lines of business development means, today is exposing your API'S, like, that's it! And, on the other side of it, we give a lot away in terms of cloud credits, right, and so, today, if you go and sign up on our self service platform, we'll give you $10,000 a month in free cloud credits to build and build quickly. Because, at the end of the day, if it's not self service, if it requires more heavy lifting, then, frankly, we're not doing our jobs. And so that's my commitment, is to make sure that is available, is accessible, and there's experts there that can help you on your journey. >> So that attracts startups, obviously, 10K a month is a honey pot for those guys. What about existing IBM clients that want to get to the cloud. Migrate to the cloud. How do you help those guys? >> Yeah, so, in the migration front, we have a great team in place with IBM services, who basically have set up a migration factor, if you will, and there are numerous ways to chart your course to the cloud. Whether it's, you know, full cloud or hybrid cloud, or some offloading, some aspects to the cloud. There's a lot of different paths you can take and so to do that, we're offering $50,000 in migration credits for the first couple months. We're also offering 35% off for professional services. So, we have a great offer going on over the next few months to help people make that first step. >> Incentives are key. >> And, look, we're here with you so it's not like, here, throwing it over the fence, and good luck! You know, tweet at me, instant message me, I'm around. And I will be absolutely committed to partner success. >> Yeah, you know, incentives are critical, that's going to get the market going. But, the end of the day, it's the type of value, and I want to get your thoughts, it's something that's come up that I've heard people talk about in the hallways and other conferences. They kind of chirp about "Hey, you know, "I'd like to get this, from suppliers. "I want to see more tools, more programs "to help me get more customers, to get more value. "I'm building apps, but also got a business to run." What are some of the conversations you've had over the past year with customers and partners? Stack rank the top three or four things that they talk about, either their pain points or things that are on their mind, that's worth noting? >> I mean, I would say first and foremost, I mean, me, myself, being in a startup at H2O. Three, four years ago. We used to walk in there and sell into the data scientists, right, so if you don't know H2O, they're a great company, a machine learning company, but we would get the data scientists really excited about working with our product, and then lo and behold, we'd get to the CIO office saying, "Hey, what is this stuff? "Get it out of here." You know, Hadoop was the same way, by the way, 2010 working at AVG, like, we'd bring in Hadoop. Like what is this data like thing? There's no governance, it's a mess. Where they could really, you know, work with IBM, where they see value from IBM is when we go into the CIO office together and say, look, we've demonstrated that there's value here. We've demonstrated that there's actual customer need. We can create a lot of help in terms of getting the rest of the organization bought in. Put in the right governance around it. Because, look, I mean GDPR is real, it's a big deal. Like, data privacy, is huge. So, you know, Rob Thomas likes to say, "You can't have good A.I. without I.A." I think that's a great information architecture. So, I agree, and so I think that's what the number one benefit is. Really get in there, move quickly, demonstrate value, and then when you're ready to make that next step of how you roll that out to the rest of the enterprise, that's when IBM becomes a huge help. >> You know, you mentioned GDPR. With regulatory issues now are becoming criteria for a lot of application developers that are small that may not have the resources to handle the right to get your name out of a database or other tools, and other regulations, certainly. Decentralize applications with Blockchain, another regulatory challenge-- >> Yep. >> Opportunity as well. Are you guys having those kinds of conversations, like putting specific things in place beyond GDPR, and if so what regulatory and legal things do you see out there that could be blockers for customers, that you guys hope to go after? >> I mean, I don't think there's a one word answer here. I do think that you take it on a case by case basis. I think you're seeing different countries adopt GDPR differently. Germany, obviously, being a very strict kind of country in doing that. So, you know, IBM services, as well as our analytics team, are really focused on that. I think, like I said, what you saw with ICP data coming out this week, I think that's a really important way to look at it. My own personal view, I think, for sure there's a lot of compliance, They have to look at, and understand the workflow, workflows of how people are using that data, as well as application architecture is big. And those are all the considerations, I think, that you are going to see as people move. I read a statistic that 40% of all CSP'S, MSP'S, are moving, are growing, like it's 40% growth from IBC, 50% of all developers are now embedding A.I. So, this market is growing and growing fast. But, you're right. If folks out there aren't really taking GDPR seriously, you can get yourself into some hot water. >> Well, we've observed that scale matters, certainly, whether it's a partner or cloud, that gets, that helps people. >> Yeah. >> Joel, well, thanks for coming onto theCUBE, we really appreciate it. >> Yeah, my pleasure. >> Before we end, I want to get your thoughts, just share with the folks that are watching. What kind of deals do you want to do? What's on your radar? What's the priorities for you? From a strategic business development standpoint. To develop across that horizontally scalable, IBM division space, as well as technology space? >> You know, it's not what deals I want to do, it's really what deals our partners want to do. >> Come on, your in charge, come on. >> It's really what deals our partners want to do, ya know. I mean, look, I get excited about transforming industries, I really do, so I look at, not what's the transactional partnership, like go, we'll do something, and there's some revenue, or something. I look at how do we transform an industry? >> Let me rephrase the question. What's on the priority list for you guys, from a transformational area, that's important for your partners. >> Yeah, I would say for sure, obviously, A.I. is huge. Obviously data is huge, obviously cloud is huge. But, looking really specific, I think you just add tech after each industry. So Addtech, Fintech, Healthtech obviously. Game tech and, I think, probably the last one, to me personally, is the most exciting. We signed an amazing deal with Unity at the end of last year, the start of this year. In fact GDC game developer conference is going on as we speak in San Francisco. So half my team right now is over there, demonstrating Watson as like VR, AR, and it's not just for games, right. It's like with BMW and VW doing some cool stuff there as well. So, I'm really excited about the, AR, VR, industry growing, especially with our partner Unity. >> There's a new creative out there-- >> Can I jump in before you exit? I want to ask you a follow up on that, because if transformation is sort of the target for your partnerships. Healthcare is an area that should be transformed. But, needs to be transformed, but it's hard to transform healthcare. >> Joel: It is, yeah. >> Do you feel like you could start moving the needle from a partnership perspective? Or is that going to take some more time? >> You know, I think there's a lot of great work being done there. I do believe... Look, in general, I think we can move a lot faster with partners, in fact, I like to call it like the Nordstrom model. Right? Like IBM in the past has been Barney's of New York, forever, right? From a branding and from how we partner with folks, like I think we need to move more to a Nordstrom, like, yeah, we'll sell our own offerings off the rack, but then we need to help partners come in and create the right styles for the right need and the right industry. >> Yeah and then there's a Nordstrom Rack you're going to need to put that on. (laughing) Over technology goes the Nordstrom Rack. Joel Horowitz, thanks for coming out. Vice President Strategic Partnerships and Offerings, here on theCUBE. I'm John Furrier with Dave Vellante, with three days of IBM Think live streaming, all of the videos will be up on thecube.net sports live now. Youtube.com/siliconangle for all the ondemands when the show's over. We'll be right back with more after this short break. (light techno music)

>> Welcome everyone to the first ever U.S. user conference of Apache Flink, sponsored by data Artisans, the creators of Flink. The conference kicked off this morning with some very high-profile customer use cases, including Netflix and Uber, which were quite impressive. We're on the ground at the Kabuki Hotel in San Francisco and our first guest is Dean Wampler, VP of fast data engineering at Lightbend. Welcome Dean. >> Thank you. Good to see you again George. >> So, big picture context setting, Spark exploded on the scene, blew away the expectations, even of their creators, with the speed and the deeply integrated libraries, and essentially replaced MapReduce really quickly. >> Yeah. >> So what is behind Flink's rapid adoption? >> Right, I think it's an interesting story and if you'd asked me a year ago, I probably would've said, well I'm not sure we really need Flink, Spark seems to meet all our needs. But, I pretty quickly changed my mind as I got to know about Flink because, it is a broad ecosystem, there's a wide variety of problems people are trying to solve, and what Flink is doing very well is solving low latency streaming, but still at scale, like Spark. Where Spark is still primarily a mini-batch model, so it has longer latency. And Flink has been on the cutting edge too, of embracing some of the more advanced streaming scenarios, like proper handling of late arrival of data, windowing semantics, things like this. So it's really filling an important niche, but a fairly broad niche that people have. And also, not everybody needs the full-featured capabilities of Spark like batch analytics or whatever, and so having one tool that's focused just on processing streams is often a good idea. >> So would that relate to a smaller surface area to learn and to administer? >> I think it's a big part of it, yeah. I mean Spark is incredibly well engineered and it works very well, but it's a bigger system so there's going to be more to run. And there is something very attractive about having a more focused tool that, you know, less things to break basically. >> You mention sort of lower-latency and a few extra, a few fewer bells and whistles. Can you give us some examples of use cases where you wouldn't need perhaps all of the integrated libraries of Spark or the big footprint that gives you all that resilience and, you know, the functional programming that lets you sort of, recreate lineage. Tell us sort of how a customer who's approaching this should pick the trade-offs. >> Right. Well normally when you have a low latency problem, it means you have less time to do work, so you tend to do simpler things, in that time frame. But, just to give you a really interesting example, I was talking with a development team at a bank recently that does credit card authorizations. You click by on a website and there's maybe a few hundred milliseconds when the user is expecting a reply, right. But it turns out there's so many things going on in that loop, from browser to servers and back that they only have about ten milliseconds, when they get the data, to make a decision about whether this looks fraudulent or it looks legit, and they make a decision. So ten milliseconds is fairly narrow, that means you have to have your models already done and ready to go. And a quick way to actually apply them, you know, take this data, ask the model is this okay, and get a response. So, a lot of it is kind of boiling down to that, it's either, I would say one of two things, it's either I'm doing basic filtering, transforming of data, like raw data coming into my environment/ Or I have some maybe more sophisticated analytics that are running behind the scenes, and then in real time, so it's, so to speak, data is coming in and I'm asking questions against those models about this data, like authorizing credit cards. >> Okay, so to recap, the low latency means you have to have perhaps scored your models already. Okay, so trained and scored in the background and then, with this low latency solution you can look up, key based look up I guess, to an external store, okay. So how is Lightbend making it simple to put, what essentially has to be for any pipeline it appears, multiple products together seamlessly. >> That is the challenge. I mean it would be great if you could just deploy Flink, and that was the only thing you needed or Kafka, or pick any one of them. But of course, the reality is, we always have to integrate a bunch of tools together, and it's that integration that's usually the hard part. How do I know why this thing's misbehaving, when maybe it's something upstream that's misbehaving? That sort of thing. So, we've been surveying the landscape to understand, first of all, what are the tools that seem to be most mature, most vibrant as a community, that address the variety of scenarios people are trying to deal with, some of which we just discussed. And what are the kind of integration problems that you have to solve to make these reliable systems? So we've been building a platform, called the Fast Data Platform, that's approaching its first beta, that is designed to help solve a lot of those problems for you, so you can focus on your actual business problems. >> And from a customer point of view, would you take end-to-end ownership of that solution, so that if they chose you could manage it On-Prem or in the Cloud, and handle level three support across the stack? >> That's an interesting question. We think eventually we'll get to that point of more of a service offering, but right now most of the customers we're talking to are still more interested in managing things themselves, but not having as much of a hassle of doing it themselves. So what we're trying to balance is tooling that makes it easier to get started quickly and build applications, but also leverages some of the modern, like machine-learning, artificial intelligence stuff to automatically detect and correct for a lot of common problems, and other management scenarios. So at least it's not quite as, you're on your own, as it could be if you were just trying to glue everything together yourself. >> So if I understand, it sounds like the first stage in the journey is, help me rationalize what I'm trying to get to work together On-Prem, and part of that is using machine-learning now, as part of management. And then, over time, this management gets better and better at root-cause analysis and auto-remediation, and then it can move into the Cloud. And these disparate components become part of a single SAS solution, under the management. >> That's the long-term goal, definitely yeah. >> Looking out at where all this intense interest is right now in IOT applications. We can't really go back to the Cloud for, send all the data back to the Cloud, and get an immediate answer, and then drive an action. How do you see that shaping up in terms of what's on the edge and what's on the Cloud? >> Yeah, that's a really interesting question, and there are some particular challenges, because a lot of companies will migrate to the Cloud in a peace meal fashion, so they've got a sort of hybrid deployment scenario with things On-Premise and in the Cloud, and so forth. One of the things you mentioned that's pretty important, is I've got all this data coming in, how do I capture it reliably? So, tools like Kafka are really good for that and Pravega that Strachan from EMC mentioned, is sort of filling the same need, that I need to capture stuff reliably, serve downstream consumers, make it easy to do analytics over this stream that looks a lot different than a traditional database, where it's kind of data at rest, it's not static, but it's not moving. So, that's one of the things you have to do well, and then figure out how to get that data to the right consumer, and account for all of the latencies, like if I needed that ten millisecond credit card authorization, but I had data split over my On-Premise and my Cloud environment, you know, that would not work very well. So there's a lot of that kind of architecture of data flow, so it becomes really important. >> Do you see Lightbend offering that management solution that enforces SLAs or do you see sourcing that technology from others and then integrating it tightly with the particular software building blocks that make up the pipeline? >> It's a little of both. We're sort of in the early stages of building services along those lines. Some of the technology we've had for a while, our Akka middleware system, and the streaming API on top of it would be really good for basing that kind of a platform, where you can think about SLA requirements and trading off performance, or whatever, versus getting answers in a reasonable time, good recovery and error scenarios, stuff like that. So it's all early days, but we are thinking very hard about that problem, because ultimately, at the end of the, that's what customers care about, they don't care about Kafka versus Spark, or whatever. They just care about, I've got data coming in, I need an answer, and ten milliseconds or I lose money, and that's the kind of thing that they want you to sell for them, so that's really what we have to focus on. >> So, last question before we have to go, do you see potentially a scenario where there's one type of technology on the edge, or many types, and then something more dominant in the Cloud, where basically you do more training, model training, and out on the edge you do the low latency predictions or prescriptions. >> That's pretty much the architecture that has emerged. I'm going to talk a little bit about this today, in my talk, where, like we said earlier, I may have a very short window in which I have to make a decision, but it's based on a model that I have been building for a while and I can build in the background, where I have more tolerance for the time it takes. >> Up in the Cloud? >> Up in the Cloud. Actually this is kind of independent of deployment scenario, but it could be both like that, so you could have something that is closer to the consumer of the data, maybe in the Cloud, and deployed in Europe for European customers, but it might be working with systems back in the U.S.A. that are doing the heavy-lifting of building these models and so forth. We live in such a world where you can put things where you want, you can move things around, you can glue things together, and a lot of times it's just knowing what's the right combination of stuff. >> Alright Dean, it was great to see you and to hear the story. It sounds compelling. >> Thank you very much. >> So, this is George Gilbert. We are on the ground at Flink Forward, data Artisans user conference for the Flink product, and we will be back after this short break.