>> Narrator: From Chicago, it's theCUBE covering Veritas Vision's Solution Day 2018. Brought to you by Veritas. >> Welcome back to the Windy City everybody. We're here covering the Veritas Solution Days in Chicago. I'm Dave Vellante, and you're watching theCUBE, the leader in live tech coverage. Robert Swanson is here, CUBE alum from DC Vast, he runs sales at the organization. Great to see you again, thanks for coming back on. >> You as well, thanks for having me. >> You're very welcome. So last year we were at the Aria in Las Vegas, we talked a lot about Cloud and the big tent event, now Veritas is doing these Solution Days, going out to where the customers are. It's probably good for you 'cause you're Chicago based, right? >> Absolutely, yeah, it's good to have the event here in my hometown. >> So how was this for you today? What'd you learn, what's the conversation been like? >> Yeah, no, it was a good morning, I like having the regional approach, a little bit more of an intimate event, had a variety of customers here and colleagues of Veritas as well. It was definitely a great event this morning. >> Lot of hot stuff going on in data protection. There's Cloud, there's multi-Cloud security and data protection are kind of coming together. The distributive data center on the Edge, new ways, new modes of protecting data. What are you seeing as some of the big drivers out there as you talk to customers? >> That's a great question and you really can't avoid the subject of Cloud. At first I think we looked at data protection really as, excuse me, Cloud, as an enabler for data protection so thinking about on-premise data and how the Cloud can help protect that. Especially for mid-market companies, it really allowed them to do some really cool retention and disaster recovery things that they might not have been able to do before or afford to be able to do before. Now we're looking it more about, alright, there's workloads in the Cloud, there's Cloud native data, what do you do with that? The Cloud providers are guaranteeing you or providing you some SLAs or guidelines around availability but that's not backup so now what do we do with the Cloud native data? Really though, as workloads start getting put out, not only into the big hyperscale or Clouds, but into Office 365 and different file share services, and in SAS applications. It truly is IT anywhere now which really creates a challenge for data protection. I mean, I feel like data management and data protection, the complexity and challenge of it has just grown exponentially in the last few years because now there is important, sensitive data everywhere that companies have to figure out how to maintain and protect and secure and really work for them. >> Wonder if you could talk about just your businesses, the whole partner channel is just fascinating, something we've been tracking now for a while. Cloud was sort of a shot across the bow to a lot of business models. It used to be, hey, I'm going to take a bunch of margin, and resell a product, and buy a boat. But that's changed, you can't just be a quote unquote box seller, that's a metaphor just for reselling somebody else's technology. You have to be a solution provider. So Cloud was in one regards a threat, but it's become an opportunity. How have you guys responded? Talk about the shift toward a solution mindset. >> Yeah, no, you're absolutely right, it really is. The channel's at a bit of an inflection point with the Cloud and contrary to some popular belief, it's not our mission as a channel company to resell hardware or some piece of software. It's getting more and more important for our partners to be people that can be companies that can offer us technology to help kind of fit in to our model and not necessarily vice versa. So now... the Cloud providers have changed the, you know where the abstraction layer occurs and there's so much automation out there that some things that we might used to provide services or manage services around low-level sys admin type task, keep the lights on kind of things, are done in an automated manner right now. We really have to redefine what we do for our customers and Cloud is important so it's really helping customers identify, where is the appropriate place to run a workload? What's better on PREM, what's better in the Cloud? Make sure you have that data portability. We have to be able to provide them guidance and services and really help in that regard as they're navigating it with us. So helping them identify where to put things, how to protect things, how to manage the data, and really how to optimize the spend as well, is something we've kind of pivoted towards. >> It's becoming more complicated. Okay, it used to be, I've got an application server, I'm going to bolt on some back up because I've got to back up the data, okay, done. Virtualization changed things quite a bit but now you've got Clouds, you've got multiple Clouds, you've got SAS, you've got distributed data. You've got to worry about, okay as you were saying, where do I put that data? You're thinking about recovery. How fast can I recovery, so where does that recovery data live? And then, who's managing this whole thing? So I would think there's a huge opportunity for you guys to come in, consult with customers, architect solutions that actually address every customer's different, their unique situations. Maybe you could discuss that a little bit and how you're helping folks. >> The lines are really starting to get blurred too on what you do with data. What's securing it versus protecting it, versus backing it up, versus replicating it, versus it being discoverable. I think that's one of the areas where we're seeing Veritas really kind of evolve. I have the experience in data management and now with some of the technologies that they're launching kind of a platform with some of their different technologies containerized and put on to a single platform I think is really seeing all of this whole concept of data management converging. >> So where do you see this whole thing going? Last question is, you looked out two, three, four, five years, you're going to have lots of Clouds, you're going to have Edge, you've got all this data, digital transformation. Specifically in the context of data protection, how do you see that evolving and what does it look like in the next four or five years? >> I think I used the term already, data portability, and workload portability, and I like that and I think that's where it's going 'cause as the public Cloud market and even non-PREM private Cloud market continue to evolve, it's really going to be about portability. Where is the most appropriate place to run a workload to have certain data? Is it in the public Cloud, is it on-prem, and maybe that changes, right? Maybe the cost modeling changes, maybe the performance requirements changed, so that needs to be portable but with portability, we have to be able to follow that data and those workloads and be able to have some kind of consistent way to protect them. I really think that's the evolution, that's kind of the arms race with a lot of the vendors in this space right now and what everybody's trying to do 'cause that's where it's all headin'. >> Alright Bob, great, thanks very much for coming back in theCUBE, really good to see you again. 85% I think of Veritas's business goes through the channel, critical partners like you make it all happen. So I really appreciate your perspectives, thank you. >> Thanks again for having me, thanks for coming to Chicago. Hope to see you here again. >> You're welcome. Keep it right there everybody, we'll be back with our next guest right after this short break. You're watching theCUBE at Veritas Vision Solution Days from Chicago. Be right back. (digital music)

(royal music) >> Announcer: John Cleese. >> There's a lot of people out there who have no idea what they're doing, but they have absolutely no idea that they have no idea what they're doing. Those are the ones with the confidence and stupidity who finish up in power. That's why the planet doesn't work. >> Announcer: Knowledgeable, insightful, and a true gentleman. >> The guy at the counter recognized me and said... Are you listening? >> John Furrier: Yes, I'm tweeting away. >> No, you're not. >> I tweet, I'm tweeting away. >> He is kind of rude that way. >> You're on your (bleep) keyboard. >> Announcer: John Cleese joins the Cube alumni. Welcome, John. >> John Cleese: Have you got any phone calls you need to answer? >> John Furrier: Hold on, let me check. >> Announcer: Live from San Jose, it's the Cube, presenting Big Data Silicon Valley, brought to you by Silicon Angle Media and its ecosystem partners. (busy music) >> Hey, welcome back to the Cube's continuing coverage of our event, Big Data SV. I'm Lisa Martin with my co-host, George Gilbert. We are down the street from the Strata Data Conference. This is our second day, and we've been talking all things big data, cloud data science. We're now excited to be joined by the CEO of a company called Data Science, Ian Swanson. Ian, welcome to the Cube. >> Thanks so much for having me. I mean, it's been a awesome two days so far, and it's great to wrap up my trip here on the show. >> Yeah, so, tell us a little bit about your company, Data Science, what do you guys do? What are some of the key opportunities for you guys in the enterprise market? >> Yeah, absolutely. My company's called datascience.com, and what we do is we offer an enterprise data science platform where data scientists get to use all they tools they love in all the languages, all the libraries, leveraging everything that is open source to build models and put models in production. Then we also provide IT the ability to be able to manage this massive stack of tools that data scientists require, and it all boils down to one thing, and that is, companies need to use the data that they've been storing for years. It's about, how do you put that data into action. We give the tools to data scientists to get that data into action. >> Let's drill down on that a bit. For a while, we thought if we just put all our data in this schema-on-read repository, that would be nirvana. But it wasn't all that transparent, and we recognized we have to sort of go in and structure it somewhat, help us take the next couple steps. >> Ian: Yeah, the journey. >> From this partially curated data sets to something that turns into a model that is actionable. >> That's actually been the theme in the show here at the Strata Data Conference. If we went back years ago, it was, how do we store data. Then it was, how do we not just store and manage, but how do we transform it and get it into a shape that we can actually use it. The theme of this year is how do we get it to that next step, the next step of putting it into action. To layer onto that, data scientists need to access data, yes, but then they need to be able to collaborate, work together, apply many different techniques, machine learning, AI, deep learning, these are all techniques of a data scientist to be able to build a model. But then there's that next step, and the next is, hey, I built this model, how do I actually get it in production? How does it actually get used? Here's the shocking thing. I was at an event where there's 500 data scientists in the audience, and I said, "Stand up if you worked on a model for more than nine months "and it never went into production." 90% of the audience stood up. That's the last mile that we're all still working on, and what's exciting is, we can make it possible today. >> Wanting to drill down into the sort of, it sounds like there's a lot of choice in the tools. But typically, to do a pipeline, you either need well established APIs that everyone understands and plugs together with, or you need an end to end sort of single vendor solution that becomes the sort of collaboration backbone. How are you organized, how are you built? >> This might be self-serving, but datascience.com, we have enterprise data science platform, we recommend a unified platform for data science. Now, that unified platform needs to be highly configurable. You need to make it so that that workbench, you can use any tool that you want. Some data scientists might want to use a hammer, others want to be able to use a screwdriver over here. The power is how configurable, how extensible it is, how open source you can adopt everything. The amazing trends that we've seen have been proprietary solutions going back decades, to now, the rise of open source. Every day, dozens if not hundreds of new machine learning libraries are being released every single day. We've got to give those capabilities to data scientists and make them scale. >> OK, so the, and I think it's pretty easy to see how you would have incorporate new machine learning libraries into a pipeline. But then there's also the tools for data preparation, and for like feature extraction and feature engineering, you might even have some tools that help you with figuring out which algorithm to select. What holds all that together? >> Yeah, so orchestrating the enterprise data science stack is the hardest challenge right now. There has to be a company like us that is the glue, that is not just, do these solutions work together, but also, how do they collaborate, what is that workflow? What are those steps in that process? There's one thing that you might have left out, and that is, model deployment, model interpretation, model management. >> George: That's the black art, yeah. >> That's where this whole thing is going next. That was the exciting thing that I heard in terms of all these discussion with business leaders throughout the last two days is model deployment, model management. >> If I can kind of take this to maybe shift the conversation a little bit to the target audience. Talked a lot about data scientists and needing to enable them. I'm curious about, we just talked with, a couple of guests ago, about the chief data officer. How, you work with enterprises, how common is the chief data officer role today? What are some of the challenges they've got that datascience.com can help them to eliminate? >> Yeah, the CIO and the chief data officer, we have CIOs that have been selecting tools for companies to use, and now the chief data officer is sitting down with the CEO and saying, "How do we actually drive business results?" We work very closely with both of those personas. But on the CDO side, it's really helping them educate their teams on the possibilities of what could be realized with the data at hand, and making sure that IT is enabling the data scientists with the right tools. We supply the tools, but we also like to go in there with our customers and help coach, help educate what is possible, and that helps with the CDO's mission. >> A question along that front. We've been talking about sort of empowering the data scientist, and really, from one end of the modeling life cycle all the way to the end or the deployment, which is currently the hardest part and least well supported. But we also have tons of companies that don't have data science trained people, or who are only modestly familiar. Where do, what do we do with them? How do we get those companies into the mainstream in terms of deploying this? >> I think whether you're a small company or a big company, digital transformation is the mandate. Digital transformation is not just, how do I make a taxi company become Uber, or how do I make a speaker company become Sonos, the smart speaker, it's how do I exploit all the sources of my data to get better and improved operational processes, new business models, increased revenue, reduced operation costs. You could start small, and so we work with plenty of smaller companies. They'll hire a couple data scientists, and they're able to do small quick wins. You don't have to go sit in the basement for a year having something that is the thing, the unicorn in the business, it's small quick wins. Now we, my company, we believe in writing code, trained, educated, data scientists. There are solutions out there that you throw data at, you push a button, it gets an output. It's this magic black box. There's risk in that. Model interpretation, what are the features it's scoring on, there's risk, but those companies are seeing some level of success. We firmly believe, though, in hiring a data science team that is trained, you can start small, two or three, and get some very quick wins. >> I was going to say, those quick wins are essential for survivability, like digital transformation is essential, but it's also, I mean, to survival at a minimum, right? >> Ian: Yes. >> Those quick wins are presumably transformative to an enterprise being able to sustain, and then eventually, or ideally, be able to take market share from their competition. >> That is key for the CDO. The CDO is there pitching what is possible, he's pitching, she's pitching the dream. In order to be able to help visualize what that dream and the outcome could be, we always say, start small, quick wins, then from there, you can build. What you don't want to do is go nine months working on something and you don't know if there's going to be outcome. A lot of data science is trial and error. This is science, we're testing hypotheses. There's not always an outcome that's to be there, so small quick wins is something we highly recommend. >> A question, one of the things that we see more and more is the idea that actionable insights are perishable, and that latency matters. In fact, you have a budget for latency, almost, like in that short amount of time, the more sort of features that you can dynamically feed into a model to get a score, are you seeing more of that? How are the use cases that you're seeing, how's that pattern unfolding? >> Yeah, so we're seeing more streaming data use cases. We work with some of the biggest technology companies in the world, so IoT, connected services, streaming real time decisions that are happening. But then, also, there are so many use cases around org that could be marketing, finance, HR related, not just tech related. On the marketing side, imagine if you're customer service, and somebody calls you, and you know instantly the lifetime value of that customer, and it kicks off a totally new talk track, maybe get escalated immediately to a new supervisor, because that supervisor can handle this top tier customer. These are decisions that can happen real time leveraging machine learning models, and these are things that, again, are small quick wins, but massive, massive impact. It's about decision process now. That's digital transformation. >> OK. Are you seeing patterns in terms of how much horsepower customers are budgeting for the training process, creating the model? Because we know it's very compute intensive, like, even Intel, some people call it, like, high performance compute, like a supercomputer type workload. How much should people be budgeting? Because we don't see any guidelines or rules of thumb for this. >> I still think the boundaries are being worked out. There's a lot of great work that Nvidia's doing with GPU, we're able to do things faster on compute power. But even if we just start from the basics, if you go and talk to a data scientist at a massive company where they have a team of over 1,000 data scientists, and you say to do this analysis, how do you spin up your compute power? Well, I go walk over to IT and I knock on the door, and I say, "Set up this machine, set up this cluster." That's ridiculous. A product like ours is able to instantly give them the compute power, scale it elastically with our cloud service partners or work with on-prem solutions to be able to say, get the power that you need to get the results in the time that's needed, quick, fast. In terms of the boundaries of the budget, that's still being defined. But at the end of the day, we are seeing return on investment, and that's what's key. >> Are you seeing a movement towards a greater scope of integration for the data science tool chain? Or is it that at the high end, where you have companies with 1,000 data scientists, they know how to deal with specialized components, whereas, when there's perhaps less of, a smaller pool of expertise, the desire for end to end integration is greater. >> I think there's this kind of thought that is not necessarily right, and that is, if you have a bigger data science team, you're more sophisticated. We actually see the same sophistication level of 1,000 person data science team, in many cases, to a 20 person data science team, and sometimes inverse, I mean, it's kind of crazy. But it's, how do we make sure that we give them the tools so they can drive value. Tools need to include collaboration and workflow, not just hammers and nails, but how do we work together, how do we scale knowledge, how do we get it in the hands of the line of business so they can use the results. It's that that is key. >> That's great, Ian. I also like that you really kind of articulated start small, quick ins can make massive impact. We want to thank you so much for stopping by the Cube and sharing that, and what you guys are doing at Data Science to help enterprises really take advantage of the value that data can really deliver. >> Thanks so much for having datascience.com on, really appreciate it. >> Lisa: Absolutely. George, thank you for being my co-host. >> You're always welcome. >> We want to thank you for watching the Cube. I'm Lisa Martin with George Gilbert, and we are at our event Big Data SV on day two. Stick around, we'll be right back with our next guest after a short break. (busy music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering Veritas Vision 2017. Brought to you by Veritas. (rippling music) >> Welcome back to The Aria in Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. We go out to the events and extract the signal from the noise. My name is Dave Vellante, I'm here with Stuart Miniman, who's my cohost for the week. Bob Swanson is here, he's the head of sales for dcVAST out of Chicago. Bob, thanks for coming on theCUBE! >> Thanks for having me, guys. >> So, well first of all, the show, how's it going for you? We've now got enough data, it's been a couple of days, a few days perhaps for you. What's the vibe like, what are the conversations like? >> Yeah, it's been a great week. This is the very tail end of the event, so a little exhausted. But it's been exciting, there's been a good buzz at the event and we get a lot of our customers here, and just kind of seeing the buzz and the pace of innovation that's goin on here with Veritas, you know, it has been exciting. >> Tell us more about dcVAST. You're focused on IT infrastructure services, but dig a little deeper. Right, yep, so we're headquartered in Chicago, Illinois, and you're right, we do infrastructure and cloud services. So we do support-type services with a seven by 24 call center, have different managed service offerings, different cloud offerings, and certainly do consulting and project work as well. >> Yeah, and Bob, so what does multi-cloud mean to your customers? (chuckles) >> It's only natural that if they're not there today, then they're going to be multi-cloud at some point. So, Veritas here is pretty uniquely positioned. to be able to get customers there. It's all about flexibility and data portability. So, I think where infrastructure and storage and data protection is sometimes not that exciting of a conversation, now kind of changing the conversation, the data management, 'cause everybody needs their data to become more productive for them. It changes the conversation, has a little more sizzle. >> Okay, but you know, your primary area of focus is infrastructure services, so that means first and foremost, every year you got to help me lower my costs, right, you've been hearing that, I'm sure, for years, and help me improve my operational efficiency. And you do that, and really attack my labor problem, IT labor problem so I can focus on my business, right? Are those still the big overriding themes? Oh, yeah, there's no question. I mean, I think the public cloud has been probably the most disruptive thing in our space since the internet. And it's making customers re-evaluate all cost and really how they're doing things, and different consumption and financial models. So, the technology is cool, and we like that conversation, but it naturally brings a big financial and cost savings, and do-more-with-less element to all the conversations. >> So what are the big trends that you're seeing in marketplace, what are the conversations like with your customers? >> Yeah, and I'll give you an example. I think customers have different approaches to cloud, right, some cloud-first, everything's got to go. Others maybe want to keep more of their workloads on premise. And in one customer example, where they said, hey, we want to move all non-production out to the cloud and it was a single cloud provider. And they got about 40% of what they were looking to move out there and they reached what they thought their estimated budget was going to be. So at that point, having that portability and having the tool sets to be able to move those workloads around becomes very important from a financial standpoint. >> So, I wonder if we can unpack those. Cloud first, and then these other guys on-prem. The motivation for cloud first, and the type of company. Do they tend to be a smaller companies, or do you see larger companies saying hey, we're going all in? I mean, you've seen some stories in the press, you know, large company, GE's going all to the cloud, okay I'm sure there's still a lot of on-prem going on there. What do you see? >> Yeah, you're right. A lot of small business is certainly, it makes sense for them, any startups too are pretty much born in the cloud now. You're not going to have too many financial backers that are going to want a startup to be spending too much money on data center, or buying hardware. But the established large enterprises, too, are kind of all over the map, but there are already some of them that are taking this cloud first approach. But, the large enterprises and companies that have been around, where it's not kind of a clean slate, naturally it's going to be hybrid and ultimately there's probably a lot of predictable static workloads that are, at the end of the day, going to be cheaper to run on-prem than they are out in the public cloud. Public cloud's great for the stuff that's not predictable, or is very dynamic, so we're seeing, and I am from Chicago and so we say the coasts move faster, maybe, than the Midwest does as well, but we're seeing varying degrees of adoption and strategy. >> But the business in the data center's good right now, I mean, the market's sort of booming, but if you roll back a few years, you guys must have thought, and maybe you're still thinking it, okay, see this cloud that's coming. Like you said, it's one of the most disruptive, if not the most disruptive in a while, and it's aiming right at the heart of your business, infrastructure services. So how have you responded to that, you must be riding the wave now of data center growth and investment, but strategically, what are you thinking about in your firm? >> Yeah, I mean, there's no question. We've had to pivot. But it does create opportunity. And we do need to help our customers be able to be most cost-effectively managing their workload, right, helping them with that. So where there's challenge and change, there's certainly inopportunity. And we've seen it. >> So, but my understanding, your firm also offers managed cloud offerings. That's been one of the things we've looked at is the channel, can they get on board, can they offer that, how is it working with the big cloud providers, and yeah, let's start there. >> Yeah, that's a good question, and a lot of people have a misperception that the cloud is kind of the easy button. (laughter) But at the end of the day-- >> Stu: Maybe 10 years ago we thought that-- >> Dave: You have your hoodie. >> Right, but I mean, people need to realize the same architecture and security considerations are there as they are for on-premise, so it's not the easy button, and you can just kind of set it and forget it. So some people that are underestimating that still need help from a third party like ourselves to be able to help them manage it. >> Could you speak about the maturation of your support services? >> Yeah, we started doing a lot of hardware support years ago when the business was founded in 1989. And at that time, it was a lot of Unix-based engineering workstations and kind of morphed into servers and storage and other data center equipment, and then started doing a lot more software support, which all can be delivered remotely, for the most part. From time to time, you may need to be onsite for something, so that kind of changes the logistical model, and now with the cloud as well, we've just kind of evolved in that direction. >> And how about the Veritas relationship? What's that been like, you know, the Symantec sale, any comments on how that's evolved, and where do you see that going? >> Yeah, we've been a long-time Veritas partner, and really the reason why we first got started with them was because they were relatively platform-agnostic, and supported and endorsed heterogeneity. And in the old Foundation Suite days, which now their InfoScale product, it's obviously had some name changes, it didn't matter what operating system, didn't matter which array vendor you used. And it's good to have friends in the industry and alliances, but there's also some benefit of staying relatively agnostic like Veritas has, and that message resonates now more than ever with all the different cloud providers out there, and just being able to be interoperable with a lot of different technologies. >> What's your customer's reaction been to all the announcements that Veritas has been making here? >> Yeah, yeah, everyone's excited. Now it's getting the word out. And I mentioned pace of innovation earlier, and it seems to have gone from zero to 100, really, really fast. So, that's exciting. It shows commitment, I think, from the new executive leadership team at Veritas, and their backers at Carlyle as well. So, you know, I think it's an exciting time for Veritas, and for us as a partner as well, and our customers. >> And anything you want to see out of those guys? From your perspective, in the partner standpoint, in the voice of the customer, what's on their to-do list? >> Yeah, and I mean, the concept of data management, looking at it holistically is important. After people and intellectual property, data's the most valuable asset a company has, and a lot of the intellectual property resides in the form of data as well. So, it's an exciting place to be as we kind of see the industry shift. >> Dave: Cubs or White Sox? >> Bob: Cubbies! >> Hey, well, congratulations on that! >> Yeah, it's been a-- >> Really, really Cubbies, not just White Sox, oh, the Cubbies won it? >> No, Cubbies all the way. >> Hardcore Cubbies fan. >> Diehard, absolutely, yep. >> Well, you're welcome for Theo Epstein. We gave Theo, and Lester, you know. And Lackey. (laughs) >> You know, Theo seems to have the Midas touch, you know, and it's interesting too, you can use sports analogies for a lot of things, and Theo's a guy who was a little disruptive by using data and analytics in his approach to managing a baseball team. >> Right, right, well, good. That's great. It was an exciting World Series last year. Hope it can be as exciting again. Must have been insane in Chicago. >> Absolutely, yep, getting ready for another run this year, hopefully. >> Excellent, well, Bob, thanks very much for coming on theCUBE. Really appreciate it. >> Thanks again, gentlemen. >> You're welcome, all right, keep it right there, buddy, we'll be back to wrap up Vision 2017. This is theCUBE. (rippling music)

>> Voiceover: Live from Las Vegas, it's theCUBE. Covering InterConnect 2017. Brought to you by IBM. >> Okay, welcome back, everyone. We are live in Las Vegas for IBM InterConnect 2017. This is IBM's Cloud show and, now, data show. This is theCUBE's coverage. I'm John Furrier with my cohost, Dave Vellante. Our next guest is Meg Swanson, VP of Marketing for Bluemix, the whole kit and caboodle, SoftLayer of Bluemix. Now you get to watch some data platform, IOT. The Cloud's growing up. How you doing? Good to see you again. >> It's good. Good to see you guys. Every time we get together, it's just huge growth. Every time, every month to month. Under Bluemix, we've pulled together infrastructure. The area that was called SoftLayer. And because we had developers that absolutely you need a provision down to bare metal servers, all the way up to applications. So we pulled the infrastructure together with the developer services, together with our VMware partnership, all in a single console. Continuing to work on, with clients, on just having a unified experience. That's why we have it under the Bluemix brand. >> You knew us when we were just getting theCUBE started. We knew you when you were kicking off the developer program, with Bluemix, was announced here in theCUBE. Seems like 10 dog years ago, which is about 50 years, no, that was, what, four years ago now? Are you four years in? >> I think so. Yeah, 'cause I remember running from the Hakkasan club, we had just ended a virtual reality session, and I had to run, and then I sat down, and we started immediately talking about Bluemix 'cause we just launched it. >> So here's the update. You guys have been making a lot of progress, and we've been watching you. It's been fantastic, 'cause you really had to run fast and get this stuff built out, 'cause Cloud Native, it wasn't called Cloud Native back then, it was just called Cloud. But, essentially, it was the Cloud Native vision. Services, microservices, APIs, things, we've talked about that. What's the progress? Give us the update and the status, and where are you? >> Yeah, obviously just massive growth in services and our partners. When you look at, we had Twitter up with us today, we've had continual growth in the technology partners that we bring to bear, and then also definitely Cloud Native. But then also helping clients that have existing workloads and how to migrate. So, massive partnerships with VMware. We also just announced partnership with Intel HyTrust on secure cloud optimization. When we first met, we talked so much about you're going to win this with an ecosystem. And the coolest thing is seeing that pay off every day with the number of partners that we've been so blessed to have coming to us and working together with us to build out this ecosystem for our clients. >> And what's the differentiator, because what's happening now is you're starting to see the clear line of sight from the big cloud players. You have you guys, you have Oracle, you see Microsoft, you see SAP, you all got the version of the cloud. And it's not a winner-take-all market, it's a multi-cloud world, as we're seeing. Certainly open-source is driving that. How do you guys differentiate, and is it the same message? What's new in terms of IBM's differentiators? What's the key message? >> That we're absolutely staying core to the reason we went into this business. We are looking at, what are the challenges that our clients are looking to solve? How do we build out the right solutions for them? And look at the technologies they're using today, and not have them just forklift everything to a public cloud, but walk with them every step of the way. It's absolutely been about uncovering the partnerships between on-premises and the Cloud, how you make that seamless, how you make those migrations in minutes versus hours and days. The growth that we've seen is around helping clients get to that journey faster, or, if they're not meant to go fully public Cloud, that's okay, too. We've been absolutely expanding our data centers, making sure we have everything lined up from a compliance standpoint. Because country to country, we have so many regulations that we need to make sure we're protecting our clients in. >> I want to ask you, and David Kenny referenced it a little bit today, talked about we built this for the enterprise, it didn't stem out of a retailer or a search. I don't know who he was talking about, but Martin Schroeter, on the IBM earnings call, said something that I want to get your comment on, and if we can unpack a little bit. He said, "Importantly, we've designed Watson "on the IBM Cloud to allow our clients "to retain control of their data and their insights, "rather than using client data "to educate a central knowledge graph." That's a nuance, but it's a really big statement. And what's behind that, if I can infer, is use the data to inform the model, but we're not going to take your data IP and give it to your competitors. Can you explain that a little bit, and what the philosophy is there? >> Yeah, absolutely. That is a core tenet of what we do. It's all about clients will bring their data to us to learn, to go to school, but then it goes home. We don't keep client data, that's critical to us that everything is completely within the client's infrastructure, within their data privacy and protection. We are simply applying our cognitive, artificial intelligence machine learning to help them advance faster. It's not about taking their insights in learning and fueling them into our Cloud to then resell to other teams. That, absolutely, it's great that you bring up that very nuanced point, but that's really important. In today's day and age, your data is your lifeblood as a company, and you have to trust where it's going, you have to know where it's going, and you have to trust that those machine learnings aren't going to be helping other clients that are possibly on the same cloud. >> Is it your contention that others don't make that promise, or you don't know, or you're just making that promise? >> We're making that promise. It's our contention that the data is the client's data. You look at the partnerships that we've made throughout Cloud, throughout Watson, it's really companies that have come to us to solve problems. You look at the healthcare industry, you look at all these partnerships that we have. Everything that we've built out on the IBM Cloud and within Watson has been to help advance client cases. You rarely see us launching something that's completely unique to IBM that hasn't been built together with a client, with a partner. Versus, there are other companies out there in this market where they're constantly providing infrastructure to run their own business, maybe their own retail store, and their own search engine. And they will continue to do that, and they absolutely should, but at the end of the day, when you're a client, what do you want to do? Are you trying to build somebody else's business, or do you want someone who's going to be all in on your business and helping you advance everything that you need to do. >> Well, it seems like the market has glombed on to public data plus automation. But you're trying to solve a harder problem. Explain that. >> When you look at the clients that we're working with and the data that we're working with, it's not just information that's out there to work in a sandbox environment and it's available to anyone, baseball statistics or something that's just out there in the wild. Every client engagement we're in, this is their critical data. You look at financial services. We just launched the great financial services solutions for developers. You look at those areas, and, oh my word, you cannot share that data, yet those clients, you look at the work we're doing with H&R Block, you have to look at, that is absolutely proprietary data, but how do we send in cognitive to help us learn, to help teach it, help teach them alongside, for the H&R Block example, the tax advisor. So we're helping them make their business better. It's not as if we ingested all of the tax data to then run a tax solution service from IBM. It's a nuance, but it's an important nuance of how we run this company. >> So seven years ago, I met this guy, and he said, the 2010 John, you said, "Data is the new development kit." And I was like, "What are you talking about?" But now we see this persona of data scientist and data engineer and the developer persona evolving. How are you redefining the developer? >> Yeah, it's a great point, because we see cognitive artificial intelligence machine learning development in developers really emerging strong as a career path. We see data scientists, especially where as you're building out any application, any solution, data is at the core. So, you had it 10 years ago, right? (laughs) >> (mumbles) But I did pitch it to Dave when I first met him in 2010. No, but this is the premise, right? Back then, web infrastructure, web scale guys were doing their own stuff. The data needs to be programmable. We've been riffing on this concept, and I want to get your thoughts on this. What DevOps was for infrastructurous code, we see a vision in our research at Wikibon that data as code, meaning developers just want to program and get data. They don't want to deal with all the under-the-hood production, complicated stuff like datasets, the databases. Maybe the wrangling could be done by another process. There's all this production heavy lifting that goes on. And then there's the creativity and coolness of building apps. So now you have those worlds starting to stabilize a bit. Your thoughts and commentary on that vision? >> Yeah, that's absolutely where it has been heading and is continuing to head. And as you look at all the platforms that developers get to work in right now. So you have augmented reality, virtual reality are not just being segmented off into a gaming environment, but it's absolutely mainstream. So you see where developers absolutely are looking for. What is a low-code environment for? I'd say more the productivity. How do I make this app more productive? But when it comes to innovation, that's where you see, that's where the data scientist is emerging more and more every day in a role. You see those cognitive developers emerging more and more because that's where you want to spend all your time. My developers have spent the weekend, came back on Monday, and I said, "What'd you do?" "I wrote this whole Getting Started guide "for this Watson cognitive service." "That's not your job." "Yeah, but it's fun." >> Yeah, they're geeking out on the weekends, having some beer and doing some hackathons. >> It's so exciting to see. That's where, that innovation side, that's where we're seeing, absolutely, the growth. One of the partnerships that we announced earlier today is around our investment in just that training and learning. With Galvanize. >> What was the number? How much? >> 10 million dollars. >> Evangelizing and getting, soften the ground up, getting people trained on cognitive AI. >> Yeah, so it's really about making an impactful investment in the work that we started, actually a couple years ago when we were talking, we started building out these Garages. The concept was, we have startup companies, we starting partnering with Galvanize, who has an incredible footprint across the globe. And when you look at what they were building, we started embedding our developers in those offices, calling them Garages because that is your workshop. That's where you bring in companies that want to start building applications quickly. And you saw a number of the clients we had on stage today consistently, started in the Garage, started in the Garage, started in the Garage. >> Yeah, we had one just on theCUBE earlier. >> Yeah, exactly, so they start with us in the Garage. And then we wanted to make sure we're continuing to fuel that environment because it's been so successful for our clients. We're pouring into Galvanize and companies in training, and making sure these areas that are really in their pioneering stages, like artificial intelligence, cognitive, machine learning. >> On that point, you bring up startups and Garage, two-prong question. We're putting together, I'm putting together an enterprise-readiness matrix. So you have startups who are building on the Cloud, who want to sell to the enterprise. And then you have enterprises themselves who are adopting Hybrid Cloud or a combination of public, private. What does enterprise-readiness mean to you guys? 'Cause you guys have a lot of experience. Google next, they said, "We're enterprising." They're really not. They're not ready yet, but they're going that way. You guys are there. What is enterprise-readiness? >> Yeah, and I see a lot of companies have ambitions to do that, which is what we need them to do. 'Cause as you mentioned, it's a multi-cloud environment for clients, and so we need clouds to be enterprise-ready. And that really comes down to security, compliance, scalability, multiple zones. It comes down to making sure you don't have just five developers that can work on something, but how do you scale that to 500? How do you scale that to 500,000? You've got these companies that you have to be able to ensure that developers can immediately interact with each other. You need to make sure that you've got the right compliance by that country, the data leaving that country. And it's why you see such a focus from us on industry. Because enterprise-grade is one thing. Understanding an industry top to bottom, when it comes to cloud compliance is a whole other level. And that's where we're at. >> It's really hard. Most people oversimplify Cloud, but it's extremely difficult. >> It is, 'cause it's not just announcing a healthcare practice for Cloud doesn't mean you just put everybody in lab coats and send out new digital material. It is you have to make sure you've got partnerships with the right companies, you understand all the compliance regulations, and you've built everything and designed it for them. And then you've brought in all the partner services that they need, and you've built that in a private and a public cloud environment. And that's what we've done in healthcare, that's what we're doing in finance, you see all the work we're doing with Blockchain. We are just going industry by industry and making sure that when a company comes to us in an industry like retail, or you saw American Airlines on stage with us today. We're so proud to be working with them. And looking at everything that they need to cover, from regulation, uptime, maintenance, and ensuring that we know and understand that industry and can help, guide, and work alongside of them. >> In healthcare and financial services, the number of permutations are mind-boggling. So, what are you doing? You're pointing Watson to help solve those problems, and you're codifying that and automating that and running that on the Cloud? >> That's a part of it. A part of it is absolutely learning. The whole data comes to school with us to learn, and then it goes back home. That's absolutely part of it, is the cognitive learning. The other part of it is ensuring you understand the infrastructure. What are the on-premises, servers that that industry has? How many transactions per second, per nanosecond, are happening? What's the uptime around that? How do you make sure that what points you're exposing? What's the security baked into all of that? So, it's absolutely, cognitive is a massive part of it, but it is walking all the way through every part of their IT environment. >> Well, Meg, thanks for spending the time and coming on theCUBE and giving us the update. We'll certainly see you out in the field as we cover more and more developer events. We're going to be doing most, if not all, of the Linux foundation stuff. Working a lot with Intel and a bunch of other folks that you're partnering with. So, we'll see you guys out at all the events. DockerCon, you name it, they're all there. >> We'll be there, too, right with them. >> Microservices, we didn't even get to Kubernetes, we could have another session on containers and microservices. Meg Swanson, here inside theCUBE, Vice President of Bluemix Marketing. It's theCUBE, with more coverage after this short break. Stay with us, more coverage from Las Vegas. (techno music)

>>Live from Las Vegas, Nevada. It's the queue at IBM interconnect 2015 brought to you by headline sponsor IBM. >>Hey, welcome back everyone. We are live in Las Vegas. This is the cube Silicon angle's flagship program. We go out to the events and extract the signal from the noise. I'm John furrier with Dave Alante host. Our next guest is Meg Swanson, director of marketing for IBM blue mix and with psyched to have her back on the cube last year we interviewed you one year ago in blue mix got kicked off. It was just a beta. Now it's blowing up huge and all the great success. Welcome back and congratulations. Right. >>Thank you. It's been a, it's been quite a year of Steve Robinson says if we kind of count these and joggers feels a bit like seven and it's been absolutely exciting. So we've in a span of a year, cause when we met at polls we were just at beta, you know we were, we were onboarding developers, getting feedback and now we have over 102 services on the platforms. They're rolling out rapidly and we have the deployment models with public, private and then we announced local at the show and it's just been, it's been tremendous. >>But before we get into some of the details, there's a lot of things to highlight. I want to just say congratulations because we cover a lot of companies you want to win when we meet people and they say they're going to do something and then they do it and do more and over and over achieve on the, on the mission. Cause you guys were very cautious at first you got Bloomix out there and then the wind was your back. The CEO says we need to win cloud. Right? And so you get the little reorg going on. Nancy Pearson was on yesterday, shows a little, a little bit of color on that and now you've got developers, you've got resources at your disposal. So take us through that. What happened? I mean I'll see blue mix hit a nerve obviously right out of the gate the signups were pretty strong, but we didn't hit that tipping point. When did you take us through the tipping point? When did it go? Oh my God, we've got a tiger by the tail. It was when the resources came in, was it before or after? >>It has a bit before that. So it's really your middle of, of last year. So as we, we had incredible adoption early on. So really building Bloomix from an open source perspective, building on cloud Foundry, strong partnerships with cloud Foundry and the team. And then just onboarding service after service. It truly owned reticent and all the different partners that we've had. And then around October was when we brought the Watson services on and we had been steadily growing, you know, the developer following and the babies that was pre yes. And uh, and the teams have always a mix is a platform that we're serving up. Um, you know, the IBM, uh, services plus our third party and open source. So we, even though we asked, we just reorganized, we've been working across the team since day one because we have the internet of things services, which are fantastic. Those are taking off really well. And we have the Watson teams, we have the mobile teams, the DevOps teams. So we're constantly working across and now we're reorganized into the cloud unit, which is fantastic because it just helps accelerate even more so >>you know, any, any agile business that has continuous integration like the cloud internally, you have to kind of think that way. And we're hearing that I internally at IBM does a transformation to be more agile, to go faster, which everyone's saying go fast. Everyone wants you to go fast. The CEOs, they said that yesterday, um, was, it was the tipping point that you had success and you doubled down on it was there, the proof point was Watson says, Hey look it, we can do this. Was that the key enabler? >>Yeah, the tipping point for us was really in the early stages, listening to developer feedback and making sure that we were re architecting and designing the product, that we have an incredible onboarding experience. So it developers where we know from marketing standpoint, we were getting the word out and really focusing on building community. So, you know, a few months into the year we started just very small grassroots meetup groups. Right now we have 71 countries every other week having meetups for their building applications on Bloomix. So for us it was, it was getting that community started and then having the community realize that we were taking their feedback on board and we would get, even on our Twitter handle, we'd get updates saying, Whoa, thanks Bloomix didn't, didn't realize you were listing to a, to the feedback and they, and they would mentioned what they had, you know, tweeted at us as far as um, input and how we'd made the change. And so every other day we're posting, you know, blog posts with updates on how we're working with developers. Just to make it a lot easier. >>Matt, can you talk about your open source strategy and how it's evolved as a company? I mean, IBM was, I think the first large enterprise company to get dive into open source and you went in big billion dollar investment way back when the Linux stories were now, but it's really evolved. Um, you use your, your muscle, your money and your vision and, and your open source of history, you know, in the community. How has it evolved? How is it changing? >>IBM for over 20 years we've been driving and fueling and having engineers really involved in open source community and helping to move that community along lifted up and and really anything that you're doing, especially from a hybrid cloud standpoint, you have to have open standards, you have to build an open architecture, you have to be embracing, you know, all the various open source technologies that are out there. You saw the work that we're doing and you spoke with the Docker team yesterday and, and so from our perspective is there's, there's no other way it is open by design. So all of our teams are very focused on making sure that we're working with the cloud Foundry foundation and getting input from all of the companies that are involved in that foundation. Because together we are going to create, you know, open standards and drive and momentum. Because if you're an independent developer or even if you're a large enterprise acting at the speed of an independent developer like we saw yesterday with city, you've got to be able to move and be portable. And if you're locked into proprietary standards, you're, you're just really, there's, there's nowhere you to go in this new world and this all the integration that you need. >>Okay. But there's another nuance there that I want to explore with you is that in the old days, it used to be you'd have a committee, right? Right. Everybody would maybe pay to get into the committee and they'd set a bunch of standards. Nine times out of 10 or 99 out of a hundred that it would flop. Right. And people, a lot of people said that would happen. For instance, with cloud Foundry, you guys came in and gave it a big lift. They're talking to that way around the open data platform now. So what's the difference? Is it just that there's an open source component to it? Is it that simple? >>Is the community, so, I mean, open source is successful because of the community. Listening to the community and sharing the community has a voice. And then the companies that are involved at, you know, at maybe more of a, you'll see that the table from a leadership perspective with the foundations, it's their, their role and their mission to be listening to the community and bring those forward. If any of those fail and you know, the companies involved aren't listening to the community or the community's not engaged and doesn't feel engaged and they're not innovating the platform, it's not going to work. So that's why we're very focused on building the sense of community, listening to what's out there and then enhancing. So you on the announcement with the Docker around enterprise grade containers, we were very specific with the way we approached that and named that. And you look at your, the secure gateway that needs to be added. You look at, um, the enhancements we've made from cloud Foundry on auto scaling. So really looking at what is the community looking for and then how do we then pay it back. >>So what's the message to developers? I mean, it sounds awesome. It's not easy. What you just described. Just Oh yeah, let's get the community. Well, it's hard to build community. So what's the message to developers? They have a lot of choices, a lot of options, and they spend time in various areas. What's the message to them from IBM, >>from an over an open source standpoint, just to be involved, be committed, be any, there are projects every day within the open source community where you can contribute code and you can be involved. And it's really about being very active and vocal and having, having a seat at the table. So I mean our teams, we're constantly looking through stack overflow in the feedback that we see their feedback on Reddit, feedback on get hub, you know, how, how often is the code being for blood? What kind of adoption metrics are we seeing? So from a developer standpoint, I would say, you know, it's time to lean in and be very involved because I mean not just IBM, but all the companies that we're working with across absolutely listening. And I mean this is such an era for developers where they, they have a seat at, at this big community table. It's not easy, but it's the right thing to do. The >>Docker and the register, this is modern stuff that developers want doctors. The hottest trend, you know, I was talking to dr folks, we interviewed Solomon years or couple of years ago in the cube before they changed their name even it was like, and we're so excited and all of a sudden they're now the bell of the ball. As you say, everyone wants to get married with Docker. Red is also is compelling node. These are cutting edge technologies that are part of the integrated stack. So how do you guys talk about that? In contrast to say Amazon, because Amazon and developers are used to these things. Elastic means stuff. They have auto-scaling. What do you guys have now that's direct, directly competitive with Amazon? >>Well, from a, from an application development standpoint, I see where we've gotten advantage is you look at the history of IBM around dev ops, right? So bringing together development operations in this continuous delivery life cycle and really looking at how are you going to quickly build an application and then that's, that's not the end of it, right? You now have to make sure from a security standpoint or you know, and you've heard from Mark Zonoff yesterday and the team on how are we providing strong security tools where you can do, you know in process application scanning and then you've got to deploy, you've got to auto scale, you've got to bring it back and you've got maybe an issue you've got to remediate and then redeploy. So for us it's really looking at at mobile app development and web development in that developer life cycle. And then in our conversations with our partners, the open source community, it's ensuring that we are helping to accelerate that every step of the way. >>I mean the announcement around API harmony, great example where we've got kind of the era of the impatient developer and we're all of us where you don't want to spend time writing a line of code if it's already been written. You don't want to spend time, you know, creating integration and creating API APIs if they're already out there. What you need are the tools at your fingertips where you can quickly build an application, search all the API APIs that are available and your private API APIs, you know, connect that into your mobile applications so you're to market faster. And then it's about you're enhancing and uh, you know, and, and really bringing different, yeah. >>So what do you say the developer out there that's watching this gives it the profile. Yeah, I'm comfortable. Amazon, I'm not sure I should go on blue mix. Maybe I should, maybe the best move was not to move or maybe they have something I want that I don't know about. So talk about those two scenarios. Cause like they're comfortable, they're like, okay, I, I'm fearful of moving over cause I'm comfortable over here with my tooling. Um, you know, developers are cause you work with them and then there's also the fear of missing out. Like, can I do better on Bloomex? So that's a common theme that we're hearing on developers. So how do you, how do you talk to those specifics? >>Yeah, and we, uh, we have those conversations, uh, quite a bit. And it's really about looking ahead at your strategy and at what point, especially for uh, developers within large enterprises. At what point do you need to connect with the backend systems? At what point do you need to ensure that you've got secure connectors? Our European clients are Latin American clients. They had concerns around data privacy, right? And so how are you sure that even the data centers that it's hosted in, you know, we have 40 data centers within software and growing every day and those are owned by IBM. Those are secured and it's really looking at where are you going to go as you expand your application. And do you have the right partner in place, the right steps along the way that you can, and more importantly, that you're not locked in. Because as much as, I mean, we have a lot of heart for Bloomex and what we're building, we want to ensure that we've built it to be open because we also want to have know low barrier exit. We want to make sure it's a great experience and it's our job to make sure that we've got the right services. The right time. >>So you don't, they don't feel locked in. So lock in is the lock in is a satisfaction >>yeah. Experience. It's not a, Oh I can't move because it's going to be too expensive to, you know. Right. And then there is a sense of, of expense that we're starting to see around the hidden cost of data. And as you may have walked into what you thought was a freemium model with some of the providers that are out there and you're scaling and now you have an ornament amount of data coming in and you're looking to store and provision that we are hearing, I mean the, there are hidden costs there that are also going to opening the door to other players that we've, we've, we know that we understand, uh, what you're gonna be facing down the road. So we've built the, the pricing, the application, the platform to allow for that. Whereas there are other platforms that haven't, because it is, you know, working at that kind of volume and scales a bit bit new to them and having to move that >>data is a problem too. So you mentioned 40 data centers, the more the merrier. I say here's some of the statistics. What's happening? How many services we did a little bit yesterday. Go a little deeper. What's exciting? What are the, the, the proud pieces of the, the platform that you can share with the developers? >>Yeah, it's been the integration. It's high integration between the design teams and in listening to developer feedback and then constantly designing the platform to have an amazing onboarding experience. So we announced yesterday the, uh, the Watson zones and the internet of things zone. And these are really designed to be, uh, a way to onboard into blue mix for developers that give you all the tools and resources and training that you need in order to start using cognitive applications like Watson. Because it is as exciting as the Watson services are, you do have a moment where you sit back and think, how am I going to use the power of Watson in my application? So we're creating these onboarding zones. So that's been huge advancement. Really excited about that. You're gonna see a lot more zones come out from us this year. And then the area of internet of things. So we have our, our IOT services. You had Nigel and Ian on yesterday from silver Hawk and power boat racing with internet things. They're fantastic. >>How about business outcomes? Get to finish the race and when you know the stories to the monitors, so you know if your heart rates going over right, >>that's pretty important data. And uh, so, so what we've seen to the exciting areas are really the zones and then the adoption and growth around internet of things space. And, uh, it's, it's a funny art. Our teams of developers that are out working with clients and out working with startups. If you open up their bags, they're probably gonna find a light bulb, a pebble watch. Um, but to connectors, I'm surprised anybody can get their report security nowadays that's on our team because we have all these demonstrations that we're doing with clients of, you know, imagine if you have, if you're trying to create a smart building for your employees and you have their mobile devices that are sensing and, and pinging the, um, the thermostat system, the lighting system. I'm the office. And as they're driving in and getting in proximity, things start turning on inside the office. So we do downloads with light bulbs and watches and, and really are starting to think through this smarter planet and smarter cities initiative with internet of things. And how are you using Bloomix and the power of cloud to now bring that to life within, uh, within cities and within enterprises? >>Go ahead. What's the developer persona look like these days when you're talking about the startup she talked to you? Think of the hoodies you think about the enterprise guys. So those two worlds coming together, >>they are in, in the fact that a lot of large enterprises are building innovation centers inside of themselves. And so they have, um, whether it's, if they have foundries or innovation centers or groups of developers, they're really looking to harness that, that speed and uh, an innovation that we've seen from, you know, some of the enterprise developers. And then also the big advancement that we've seen is the continual growth of the hackathons. So, you know, we know city we've been partnering with at and T as well on, on creating as many opportunities for their internal developers and external ecosystem of developers to be bringing forward new ideas to them. And then what we, we don't talk about as much publicly are the internal hackathons we do inside of large corporations. So we work with the CIO, his office, we go in 24 hour period and their developers are working on Bloomex within 24 hours. Well, depending on the number of, of it of developers they have, we'll have, you know, 50 75 a hundred mobile apps that are built. And then shark tank style, you know, they pitch the apps to their CIO and we vote on them together, you know, with the company. And then that's the roadmap for, you know, their 2015 plan and what applications they're going to bring tomorrow market. >>So talk about the geekiness of IBM and we were talking about this on the intro about what IBM should be doing, obviously where we're editorializing and pining, but um, it's known as kind of like the big company is slow old IBM, big blue, big iron and you guys are trying to be cool to see the keynotes out here. We may see that, but you guys actually have a geeky kind of community going out with this dev thing, which we've been following the past couple of years. It's pretty cool. Um, IBM is a geek culture. I mean it's got a lot of geeks that IBM, and that's a bad word we heard in New York, but a lot of computer science is um, technical people, very awesome bench of talent and patents. Right? So I'll ask, coming to bear, we're hearing, so share with the folks out there that are watching, what's it like at IBM? It's geeky. Is it? Is it, you said they carry gadgets around, I mean, is that the way people are at IBM? I mean, what's the culture like? Your group is, I think one of the ones that are kind of the edgiest. I think it's definitely not a mall culture. >>This multiple pockets. You've got a conservative customer base, but the average to be good, you gotta be, >>yeah, you gotta be kidding. It's about being authentic. So we're not trying to be anything. We're not. And when you look at me, you met, you know, the teams that I've gone through. We've got Jeff's lawyer and Marvin Goldman running around on our teams and, and we have massive development labs, you know, OBS, developers within, you know, high fund, our, our London facilities. And this is going on every day. So we're not putting on airs. You're not pretending. This is truly what our teams are doing. So we have, you know, Joshua Carr in the UK is constantly with, um, you know, with, with children in schools, showing them how to fly a drone with a banana, right where you do the device connectors. That wasn't because it was a stunt that we were trying to pull. It's just truly what they do. And we're very involved in the STEM initiatives for schools. >>I'm very involved in, you know, our distinguished engineers working through. So, but to attract developers and to get them in gray shade into your platform on board, you're judged by the company kids, they want to see themselves there. Right? So that's, there's a culture of developers now, I don't want to say brogrammers but like in this, the youngest guns are like, they've never loaded Linux on machines. They always say what bloats off where it's all cloud to them. So you're born in the cloud. So that's just a complete cultural shift, right, to talk about you guys have that mojo internally or, yes, it's about, it's about taking what we know inside the company and exposing that to developers and creating that developer to develop our connection. And you mentioned programmers. I mean we have Lauren Schaffer, we have a number of female developers on our teams and we are very much focused on ensuring that we're leading and making sure that we are creating a very balanced on environment of developers and leading in that area of making sure we have a lot of diversity. >>And so it's really about, from a marketing standpoint, it's, you know, you don't market to developers. Yeah, no, your technical chops or what's the market and you make sure that what they're interested in and what thereafter we're going to connect them with an IBM development team or is somebody else in the community through developer works that's working on it as well. And it's that local community. There's local connections headfake developers as we learned that. No, and my team, my marketing team, it's half developers, half data analysts. I mean we are, I mean EDC shifts inside of IBM marketing. I mean it's all data driven. I'm using the entire portfolio SAS portfolio we have with, you know, Unica, Coremetrics and, and then every day giving developers more trends and more technologies to play with your kid in the candy store. They ask you the, um, the question that's on my mind is what was the big learnings over the year that you guys walked away? >>What was magnified this year? Y'all see, you launched it a year ago, you have some growth, right? What's the learnings that was magnified for your team and the whole group? I'd say the speed. Um, so when you talked about, you know, agile development, agile delivery, you look at going from, you know, a few services to 102, you now have to re reinvent the way product development is done inside the company. So it's cloud versus mobile first. And it's really looking at across all the services we have, how long can they be a beta, how long, you know, are we going to do testing? What is the beta to general availability, onboarding for developers and migration path. Because a lot of companies will launch a beta, you're using the beta, you're embedded in it, and then all of a sudden it goes generally available and you have to rip and replace. Like that's horrible. And you know, experience. So we've, the biggest change I've seen is just the agile delivery and the speed at which internally to IBM we're working and learning from our partners that we're onboarding, bringing more and more partners every day. >>We got a break, but I want to ask you one final question. What's the coolest thing that you guys have done with Blumix internally? >>So internally it's been the Watson services and the Watson hackathons. So, uh, we are doing message resonance and sentiment analysis, so you can actually take a memos that are written or uh, or external documentation, run it through message resonance and, and start creating profiles of, of messaging. So it's been a, so you've got traditional writers, you know, geeking out of it and now they're uploading their content into the mobile applications and, uh, and you're then changing the way that, >>yeah, we had, we did a test, Adam sent us a link for the beta with the blue mix and we took all our chats and the social group has an amazing crowd chats, a zillion people on it and it's a huge transcript. I just cut and paste the transcript into the site and it spit out like the top things. And it was like, you know, openness cause it's a, it's a Twitter, Twitter, Twitter chat and they gave it a little, all the sentiment. I was like, wow, this is awesome so we could see where this going. So, um, that's cool. Thanks for coming. Thanks for coming on the cube again. Great to see you. Congratulations and keep us posted and we'll bull up. Keep checking in with you on the progress. This is the cube. We'll be right back live in Las Vegas after this short break.

>> from Boston, Massachusetts. It's the queue covering active eo 2019. Data driven you by activity. >> Welcome back to Boston, Everybody. Money >> belong here with my co host, a student of John >> Kerry's. Also here today You watching the Cuban leader and on the ground tech coverage. This is day one of active fio 19 data driven content Conference hashtag data driven 19 red cara minuses. Here is the senior vice president of fantasy Sports A draftkings Greg. Thanks for coming on. What a cool title. >> Yeah, it's It's, you know, I was joking with my wife. Anytime you could be working fantasy sports, it's a great place to be. Everybody's a little bit jealous. >> So the formula is easy, right? Offer big giant prizes and everybody comes And that's all there is suing. Anybody can come >> in. I just have the dream job right now. >> So hugely competitive market. You guys, you become the >> leader. We were in the radio. Check out your websites. I mean, take us through the draft kings and your ascendancy. How you got here? >> So, you know, company started in 2012 initially around sort of the major big American sports on DH. Then really a CZ. We started scale that we saw there was a huge consumer interest in the product players that would come on. We're very, very, very sticky. Um, and we've just been kind of, you know, pushing, pushing on growing that using these. So the initial founders are three former analyst. So come on. It's always been sort of a very analytically driven company. So they looked at what we were dealing with, and it was we had L TVs that were way higher than our cracks. So let's keep marketing and growing and growing and growing and finding out ways to offer a better product. So, over 2015 we did a major marketing blitz, blew up the company Absolutely huge. Um, and since then we've been just constantly innovating, adding new sports, adding new features on DH, adding ways toe on the product. And then even more recently, just about a year ago, we expanded also into online sports betting over New Jersey has that's become a legal product across the U. S. So it's been a great time to be at the company a lot of fun. >> What what was your first sport was like Amazon started in books and then, you know, scaled out what was your first sport. So it's actually the first sport was >> baseball because of the time that they actually launched. So is the middle of April. Sporting calendar is a little bit thin. Right then, so is it was baseball to start, and then once football season started, that's really when things take on >> 2015 is when you started the marketing blitz and I remember just here in the ads and it was just intense, like a while. This company's going for it. So you sort of took >> all the chips I went >> all in and it worked. Yeah, I mean, it's part of the, you know, the lifeblood of the company. It's We're a company that ends up being taking risks, but we take calculated risks. So at any given point, you sort of say, like, Hey, what is the what is the range of outcomes over here? We're not playing for second place. We want to be a market leader, so you have to take risks in order, be a market leader. So let's take calculated risks. Let's make sure we're not being insane, but you know we did the math. We figured out what? This is A This is a worthwhile shot. We pushed him for it. Andi really took off from their love to bet on >> sure things. Yeah, well, Greg, we know the people that play the fantasy for it feel that data is what differentiates whether they're going to live in, you know, winner lose. Talk to us a little bit about the data journey inside your business And how that helped differentiate draftkings in the market. Yes. So we think Death draftkings >> is one of the most analytically based companies in the, you know, definitely in the market, but also into sort of like General Cos right now we use our analytics platform to inform pretty much everything we dio on. Go to your point. You're joking. You know, it seems like fantasy sports is easy throughout some giant prizes there, and everything will take care of itself. You know, running a fantasy sports car company. If you throw out a contest that's too big, you lose a ton of money. There's a lot of asymmetric risk in the business where if we're right, we make a little bit more. But if we're wrong. We lose a ton very, very, very fast. So our ability to be very, very sound analytically is what allows us to sort of pushed the envelope and grow, grow, grow but not, you know, lose our heads along the way. You know, some of the fun of that is really, you know, when we first ran, I think one of the most game changing contest we ran was actually back in October of 2014. It was the very first millionaire maker contest I could still remember. It was Week five of the 2020 14 NFL season where we said, Hey, this it's crazy. We need crazy things that happen in order for it to work. But if we're on a $20 contest to enter with $1,000,000 top prize and 2,000,000 of total prizes, it could go viral, go absolutely crazy. And if it loses, here's how it'll losing. Here's how much will hurt us. It's a worthwhile risk. Let's go for it. So that sort of energy of, you know, doing discipline analysis and constantly sort of them. Taking the risk on the back of it is what allowed us to build >> up the brand value that you would have got out of that was sort of worth that risk in part anyway. And you wouldn't have to hurt presumably. >> Exactly. We knew our downside. As long as you know your downside, you're normally in a pretty good spot to take those risks. >> So where do you >> see this All going mean? So the company has grown. You're at this kind of critical mass now, Like we said, highly competitive, you know, knock down. You know, if you take your eye off the ball. So how do you guys keep this going? >> So we have a huge challenge ahead of us over the next couple of years, as sports betting becomes legal across the US, we need to make sure that we are one of the top competitors in that market. Sports betting in the US, we expect to be an absolutely enormous market. It will probably be significantly larger than the fantasy sports market in terms of absolute revenue and even, you know, on order of magnitude more competitive. So we need to be executing each step along the way a CZ markets open up. We need to be able to get into getting two market very, very fast. And that means our tech team needs to be working feverishly to make sure that we can hit the requirements that each legislator and each regulator puts on market entry in their state. We didn't mean making sure we're constantly figuring out what are the product elements that are absolutely critical for our for our users. Is it Maura around the live betting experiences that around the different markets that you offer? It's around pricing. And how do we find these things, these different lovers and told them to make sure that we're putting out a great product for users. And if we do that and throw a great product after users were pretty sure we can make you want >> to be one stop shopping presumably, right? I mean, all sports, right? But But then you've got these niche sports betting. I mean eggs, invest. Example. I could think of this horse racing. You know where it is alive. It's gonna video. It's got commentators on the ground that you know the business really well. Is >> that Is that the strategy to go sort of horizontal and so be a one stop shop or you >> gonna sort of pick your spots? What is the day to tell you? >> You know, I think we're constantly talking about it. One of the things that allowed our fantasy sports business to grow so fast was going a little bit more horizontal. So we offered Gulf in Mass at a time period when the primary competitors and the space vandal did not. On DH, we built that product into one of our largest sports. It's, you know, right up there with MLB in terms of the actual size that that comes in a Z have gone also horizontal, we pulled in other places, like NASCAR. Mm, a great sports that people are interested in. It gets more users into our platform. And honestly, if uses are interested in a product, we don't want them to have to go elsewhere. We want to be able to have the offerings that any sort of, you know, critical mass type environment is going toe is gonna have >> Well, it's that experience, right? Well, I like to shop in Amazon. You do, too, because I >> trusted. And it's the same user experience. So, Greg, one of things >> I'm hearing from you is something that everybody tries for, but it's really challenging that speed. How do you react that fast and move the company into new markets and new offerings and keep innovating? You know, culturally technology wise, you know, How does Draftkings do that? You know, I think a za company, you know, from really every single person that we recruit in higher We've been actually execution Aly disciplined throughout the company's history. It's It's something that our founders did a great job of instilling in the culture right at the gates. I mean, we've tried to foster all the way along the way, which is all the best strategies of the world. They're going to fail if you can't execute well and every single person down the company knows that. And we try to, you know, enable each person to be as autonomous as possible in their ability to execute their their portion of the business that allows us to move really, really, really fast. You know, we disseminate that responsibility quickly, and each leader and sort of each person knows what they have to do to execute. There's a high degree of accountability behind that, you know, I'd like to say there's some. There's some magic recipe that's, um, secret sauce, but it's a lot of just great people doing great work everyday. Well, Greg, you know it's any your competitors that they look at, You know, Boston's been been doing pretty well in Draftkings era, you know, for the last few years. ES o Boston's been a great market for us. We've expanded Conover here on DH. The sports teams have been fantastic, although the Bruins it was a little bit sad about Game seven over there, but it happens. >> So his m o be the flagship news that no, I wouldn't say >> that MLB was first, primarily just of the time of the year when we launched. NFL is always going to go, are not always going to be, but for the for the foreseeable future is the dominant US sport on will remain the dominant US for >> no reason. I mean, kids there watch MLB anymore. Maybe the maybe the playoffs and the games. It was a game. I think I'm some Father's day was like almost five hours long, you know, gets called. You can come in and out. But you know what some of the trends. You see soccer. Is that growing NFL? Obviously huge. Do you see so niche sports like lax coming on. >> So, uh, you know, starting point NFL has been huge. We actually launched a new product Ah, little over a year ago called Showdown, which allowed you start to do fantasy for a single game as opposed to the combination of games that's taken off fantastically because that's tapping into more of the I'm going to sit down and watch this game, and I would love to have a fantasy team on that on this game. That's really expanded the audience like that. That >> was genius because, look, if you're >> out of the running, it doesn't matter because I'm weak. On top of that N b A and NHL on fire. The embassy put out a great product is an actual sport league. You know, the Finals were great. You hate to see the injuries, but it was a great final. Siri's very competitive. The NHL Finals has been very, very competitive. Golf is growing phenomenally as a sport, way farm or interesting golf than I ever anticipated when I first started with the company and it's one of the most exciting things. When the Masters comes each year, every screen has turned to it and we see a huge player. Player number is kind of coming into that one. Beyond that, you know NASCAR. What's been interesting? NASCAR's been having a tough couple years, but the Truck series for us? We launched it this year and the trucks have been great. I don't know if you've watched NASCAR Trucks. They're wildly entertaining. Uh, you know, Emma, you got the big fighter. So every sport sort of has its moments. It's a matter of like picking those moments and figuring out how to make >> the most of them. Do you see boxing at all making a comeback? >> So we have thought about how to get boxing into a into a fantasy. We don't have it at the moment. We're putting a lot of thought into it, so we are actually seeing through. We've seen, you know, we've been in the M M A space and we've seen the growth out from there where that sports doing great and you look at places like Bela Tor. The Professional Fighters league is other leagues, and then boxing is the next step. There's a lot of interest there. I don't think they have the right products yet to be able to kind of engage with that extra way. So that's one of things we're working on. Also, you need a marquee fighter. You always need a marquee fighter. Kind of helped bring in the interest over on that side. So, um, be interesting to see with Taki on sort of the downside of his career. At this point on DH, Mayweather hasn't been fighting much. Will be interesting to see. Who's that next meeting with Adam. But >> I grew up in an era >> of Marquis fighters. What? They would fight, you know, they literally fight 6 70 times a year, you know, and you had used huge names on DSO, and then mm comes along and he's really hurt, >> but it feels like it's tryingto so to resuscitate. Yeah. I mean, I think these things could >> be a little bit cyclical. Like you get one Marquis fighter out there like so my wife, this Filipino. So I'm a huge backing out fan now way watch every fight. Even when we were living in remote locations that forces watching at weird hours. He's a type of athlete that could bring popularity of the sport. So if there was a major U. S. Fighter that gains that degree of sort of, you know that that degree of fame people will be into it, I think >> Do do do your analytics sort of have a probe into the activity at the at the fan level at the sports level, not just the fantasy level or the betting level? Is that a sort of ah ah predictor for you? Yet we >> see a lot of correlations between how many people play our sport are fantasy game, and how many people actually follow the underlying sport. Way can also see trends in terms of If I'm from Boston, I probably pick more patriots in my fantasy lineups than, uh, normal on DH. You can actually see that as people play different sports that you know, the number one Q. Be drafted in in Boston is almost always gonna be Tom Brady. And once you leave that you start seeing Aaron Rodgers pop up. Let's really, really fast. So you see these little micro trends where it's like you are still a sports fan of your local team in your local environment, but it manifest itself in the fantasy. >> So what you think that is? Do you think it's fan affinity >> or do you think it's just the sort of lack of knowledge out inside? You're sort of a circle of trust. >> I think it's probably a combination. I mean, I could say is, you know, following the Celtics in the mid to thousands, I knew the depth of the Celtics pension, how they would use their rotation better than anybody else, Probably better than anybody else in the coaches would probably disagree. But it's like I knew that James Posey was a huge value play on Saturday nights. I knew. I kind of with I feel the Eddie House nights. Uh, so, you know, on your local team, you probably know those players at the not the top top echelon All Stars, but the guy's right beneath. You know them a little bit better and probably more comfortable using >> what's your favorite sport. >> So my favorite sport, from a fantasy perspective, is I play all the basket. I play all football, played basketball just during play offs, and I played baseball. But baseball I'm strictly a fantasy player. I don't really follow the sport to play. I'm just playing fantasy. Okay, >> That's great. So, what do you think? The conference. Here. >> You have you Have you had any timeto interact? I know you were swamped after coming off the stage. >> You know, it looks like a great turnout over here. There's a lot of enthusiasm amongst them from people. I was a little bit late to the late to show up this morning, so I got a bit Swanson eager to go and be able to catch up a bit more. >> Okay, Well, Greg, thanks so much for coming on. The Cuba's great to have your every pleasure meeting you. >> All right, people. Right there. Still, when I >> was back with our next guest, John for it is also in the house. You wanted The Cube from active field data driven 19. Right back

>> Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by IBM. >> Okay, welcome back, everyone. We're live here at the Mandalay Bay in Las Vegas for the wrap-up of IBM InterConnect 2017. I'm John Furrier. My co-host this week, my partner in crime, co-CEO, co-founder of SiliconANGLE Media Inc. with myself, Dave Vellante. Dave, it's been a great week. I just feel like I have been Watsonized and Blockchained and cloud all week. As we wrap up InterConnect, I want to get your thoughts on IBM, the cloud business, the big data marketplace, some of the things that we're seeing at the 100 of events we go to. We've got our events coming up, we're going to be in Munich next month, we got DockerCon, but a lot of developer events coming up, but in general, we get to see the landscape, in some cases, that others don't see. Let's talk about that, so before we get into the landscape, let's about IBM, IBM's prospects. This show, just quick stat, almost double the online traffic we're seeing on IBMGO than World of Watson, which was the biggest show we've ever done with theCUBE that we've seen. So, an interest, it's a data point. Unpack the data, you can see that there's a lot of global interest in what IBM is doing right now with the cloud and with Watson, and certainly with Blockchain you add another disruptive enabler potentially to what will either be a brilliant IBM strategy or a complete crash and burn. I think this is an IBM go big or go home moment with Ginni Rometty. I love her messaging, I love her three pillars, enterprise strong, data first, cognitive to the core. That is solid messaging, all three pillars. To me, it's clear. IBM is at a reinvention moment, it's all coming together, but it's a go big or go home moment for them. >> Well, you know, John, I mean, Ginni when she took over, sorry, she was running strategy before she became CEO, I mean, IBM had a choice, they could go double down on infrastructure and go knock it out with Dell and EMC and HP, or they could go up the value chain. And my ongoing joke is Dell bought EMC, IBM buys some other company, and that to me underscores the differentiation in thinking. Oracle, I think, is a little different, but Oracle and IBM are somewhat similar, I think you'd agree, in that they've got a big SaaS portfolio, they're trying to vertically integrate, they're trying to drive high value margin businesses. The difference is IBM's much more services oriented than, say, an Oracle, and that's still, as I say, a big challenge for IBM. But I'm more, I'm a bull on IBM. >> Why is that? >> I think the strategy is, number one, they're relevant. We talked for years about how we weren't that excited about Microsoft because they weren't relevant. Satya Nadella came in, all of a sudden, they're relevant again. I think IBM is highly relevant in the minds of CEOs, CIOs, CCOs, CDOs, all the C-suite, IBM is super relevant there, just as are Accenture and Ernie Young and all the big SIs. But IBM's got tons of products beneath it, number one. Number two, despite the fact that, you called it out several years ago, they bought software for 2.4 billion, it was a bare metal hosting company, alright, but IBM's turning that into >> Bluemix. >> a cloud business with Bluemix, right. And they're building, bringing in acquisitions like Cleversafe, like Aspera, like Ustream, and others, where they're bringing services that are differentiated. You can only get Watson on IBM's cloud, you can only get IBM's Blockchain on IBM's cloud, so they're bringing in value-added services, and there's only one place you can get them, and I think that's a viable strategy that's going to throw off a lot of cash, and it's going to lead to success. >> And by the way, they're also continuing to invest in open source. So, again, that's-- >> That's the other piece. I wanted to talk to you, and this is your wheelhouse. IBM's open source mojo is not just lip service, alright. They have deep-rooted DNA in open source and their strategy around it, and they've proven that they can monetize open source. What's their model, I mean, explain the model because I think it's instructive. >> I mean, open source, there's a lot of different models. Red Hat-- >> For IBM, I mean. >> IBM's model of open source is very clear. If you look at what they've done with just Blockchain as a great example, they have mobilized their company, and they did it with Bluemix as well with the cloud, once they said, "We want to get in the cloud game," once, "We want to do Blockchain," they go open source at the core, then they get their entire brain trust workin' on it. It's not just a hand wave, some division, they're kind of reorganizing on the fly, they're kind of agile organization, which some may read as chaotic, but to me, I think that's just good management practice in this day and age. They get an open source project, and they drive that home, and they have people contributing and giving that to the community, and then adding value on top and differentiating. It's just classic 101, create some value, and create some differentiation with your products, and by the way, if you don't want to use our products, build your own, or hey, use the open source code. That's pretty much an over-simplified version of open source. >> But Blockchain's a great example of this, right? So, they see the leverage in open source project, they put all these resources in, and they say, okay, now let's build our product on top of that, let's get the open source community leverage and this is, let me ask you this, does IBM, so several years ago when IBM announced Bluemix, you were pretty critical. >> John: I was very critical. >> IBM has to win the developer audience or it's cooked in this game. >> That's what I said. >> How is it done, how would you grade them? >> I think they're doing very well. I think IBM is, again, to use your word, they're not putting lip service in it. So, I was joking with Meg Swanson last night, I saw Adam Gunther when they interviewed on theCUBE, and I was critical. I didn't say that their cloud was bad, I was just saying it's just not as, just got a lot of work to do, Amazon's kickin' ass, which we now know that happened, right. But they've done well. They've done well, they've ran hard, they've gone the table stakes on the enterprise. I still think they got some more work to do, we can analyze, I'm putting out my cloud ratings matrix, I'm going to put IBM on that list, I have Google and Amazon done. I'm going to add Microsoft Azure and IBM onto the mix in the comparison matrix. But IBM has done good with the developers. They've just invested 10 million in this announcement, and they're ramping up. I wouldn't say they're throwing just money at it, they got people, so I would give them, I'd give them a B-plus, A-minus score because they're hustlin', they're doing it. Are they totally blowing it out of the water? No, I don't think they're pushing hard enough there. I think they could give it some more gas, I think they could do more with it, personally thinking. But you know, Dr. Angel Diaz was on earlier today. They're going at their own pace. >> But you agree they're in the game. >> Oh, totally. >> Making good progress. >> They're totally, IBM is totally in the cloud game, and they don't get a lot of credit for it. Either does Oracle, by the way. Somehow, people seem to talk about Azure and Google. Google is so far behind, in my opinion, they're not even close. I think it's Amazon, Azure, IBM and Oracle and Google all kind of in that-- >> Juxtapose Oracle's developer cred, even though it owns Java, with IBM's. How would you compare the two? >> Very similar, I think. Different approaches, but again, to your point, IBM's relevant, Oracle's relevant. We had this question about VMware when they did the deal with AWS. They have customers and they have cash, so they're not going anywhere. It's not like IBM's a sinking ship. It's not like Oracle's a sinking ship. Now, that being said, there's a huge shift in the business, and I would say in that scenario, Google is in a very good position, so I've been very critical on Google only because they're trying to be acting like they're an enterprise flag. They're not, I mean, Google's got great tech, TensorFlow, machine learning. Google has great cloud tech, but in that game, they're up in the number one, two spot. But in the enterprise side, they're not close. They're workin' on that. So, that's my critique of Google. Microsoft has got the DNA for the enterprise, so Microsoft and Oracle to me are more similar than comparing IBM and Oracle. I'd say IBM is a lot more like Google and Amazon, kind of in-between, but Oracle and Microsoft look the same to me. Big install base, highly differentiated, stacks aren't perfect, but it looks good on paper, and they're gettin' business. And Oracle's earnings, by the way, were very explosive due to the cloud growth. >> Another question I like to ask sometimes is, okay, what would you have done differently if you had a choice? Like when Gerstner was running IBM, he chose to consolidate the company, essentially, not consolidate, but focus on services, one throat to choke, single-faced IBM. Great customer service and build the services business, buy-in, PWC, et cetera, that was the key. What could you have done differently that could've said, well-- >> John: For IBM? >> Yeah, at the time, you could have said, "We're spin out different product groups. "We're going to be the best at microprocessors, "or disk drives, or database, or software." >> I think IBM moved too slow. >> That's a historical example. Given what IBM's doing today, what would you have done differently if you were Ginni Rometty five or six years ago? >> I would've done what they're doing now three years ago. We were, when we started working with them with CUBE, IOD events, and Pulse. >> Dave: Information on Demand. >> You had a lot of silence. I think, if I had to go back and get a mulligan, if I was Ginni Rometty, I would've moved faster. >> Dave: Done that faster. >> Hindsight's 20-20 on that, but it wasn't that clear. But again, it's the big aircraft carrier, it can only move so fast. I think what they're doing now is good strategy, and they're price strong, data force, cognitive to the core is a good strategy. Now, cognitive is words for AI, and that's their word, cognitive 'cause of Watson, but essentially, machine learning and AI is going to be a big pillar there, and then, the data first is more of an architectural component that's very good. But in general, Dave, the cloud is, this is what's going on in my find. It's so obvious to me. The big data marketplace that was we defined by Cloudera and Hadoop and Hortonworks just never panned out. It morphed into a bigger picture, and so, Hadoop is part of, now, a bigger ecosystem. Cloud was growing very fast. Those two worlds are coming together and growing very rapidly independent with big data, with machine learning, AI, and IOT. They're coming together. The intersection of the big data and the cloud. >> Cloud-mapping data. That was Yuri Burton from 2005. >> But it's coming together really fast, and the IOT is the real business driver. I know there's not a lot of stuff shipping yet in the sim stuff out there, but merging IOT into IT into business process and into developer mindset, whether it's an Indiegogo up to full-on developers is the accelerant that's going to fuel the AI value. To me, that's the intersection point of big data and cloud, and that is the home run, that's the holy grail, and that's going to be disrupting some preexisting decisions by big vendors who made bets, and I'm talkin' about bets made in the past five years, not like bets made 20 years ago or 10 years ago. I think the IOT is going to really shape the game. The other thing I worry about now, in my opinion, is a lot of AI-washing. People say, "Oh, AI." You see people on the stage, "Oh, we did this with AI." There's no AI, it's augmented intelligence, which is basically predictive analytics. You know, true AI is not yet here, it's a little bit hyped up, not that I mind that. I think that the machine learning is the real meat on the bone right now, I think that's the core enabler. Machine learning is by far the most important trend in the computer science world today as it relates to integrating that capability into cloud native, microservices, and overall application. >> I agree, I mean, AI is still a heavy lift, but to me, the key, I go back to something you were saying, is developers. That's the lever that's going to give you the ability to move large mountains. If you don't have that developer community, and you don't have open source chops, you're going to struggle a little bit. You're going to be either in a swim lane like Oracle with its database and its red stack, and maybe you can break out of that, but I'm not sure it wants to. Or you're going to be stuck in infrastructure lane. >> Yeah, but the developers are driving all the action right now. My point about machine learning, if you look at the shows just recently, and certainly we have the history of the past year, machine learning is the sexiest trend in every show. Last show was Google Next, machine learning with TensorFlow, both open source. Machine learning's not new, it's just now accelerating the developer. The developers want to move faster, and I think things like machine learning, things like cognitive that IBM puts out there, are great catalysts. That's going to be a big thing we're going to watch, obviously, we have a big developer community at SiliconANGLE, so something to watch. >> What's next? We've got a chief data scientist summit next week in Silicon Valley, we're going to be at the-- >> Let's look at my Friday show this week. Every Friday I do the Silicon Valley Friday show with me and guests, we got that goin' on, so always check that out on soundcloud.com/johnfurrier, or check out my Facebook feed, facebook.com/johnfurrier. But in terms of CUBE events, we've got DataWorks in Munich on April 2nd, DockerCon in Austin, Oracle Marketing Sum Experience, Red Hat, Dell EMC World, Service Now, Open Stack, Big Data in London. >> It's going to be a busy spring. >> Lot of stuff going on. Great stuff. >> Deb, we'll see you in July. >> In bumper sticker, Dave, this show, encapsulate your thoughts. >> Well, I think it's all about cloud, data, and cognitive coming together in a way that allows business value and differentiation through the end customer. That's what this show is about to me. It's not about infrastructure, cloud and infrastructure, that's kind of table stakes. It's all about differentiation up the stack, creating, enabling new business models. >> My encapsulation is the enterprise strong, data first, cognitive to the core message that Ginni said, that translates into IBM's shoring up their base products and putting an innovation strategy around Blockchain and soon to be cognitive computing at a whole 'nother level, and I think they're going to have a real innovation strategy and continue to use what they did with Watson, the winning formula. Put something out there that's a guiding principle and draft the company behind it. I think that, to me, is my big walk away, and I think Blockchain will potentially level, has game-changing capabilities, and if that plays out like Watson's playing out, then IBM could be in great shape on both shoring up the base in cloud and their business and having an innovation strategy that extends them out. That to me is the reason why I'm bullish on them. So, great show, Dave Vellante. Thanks to the guys, thanks for everyone watching. That's it for us here in theCUBE. I'm John Furrier, Dave Vellante wrapping up IBM InterConnect 2017. Thanks for watching, stay with us, and follow us at theCUBE on Twitter and siliconangle.tv on the web. Thanks for watching. (electronic keyboard music)