(upbeat techno music) >> Narrator: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2019. Brought to you buy Amazon Web Services and Intel, along with its equal system partners. >> Welcome back everyone. CUBE's live coverage here in Las Vegas for AWS, re:Invent 2019. I'm John Furrier and my cohost Dave Vellante. We're here extracting the signal from the noise with theCube covers for three days. Our next two guests, Mark Lohmeyer, Senior Vice President, General Manager, Cloud platform, business unit for VMWare. Ben Tanner, Director of Cloud Enable for IHS Market. Guys, thank you for coming on theCube. Good to see you again. >> Yeah, great to be here again. >> You got a customer here, customer at Momentum Store, but before we get into that I just want to get your quick take on the key note from Andy Jassy. Clearly, the VMWare relationship with AWS, really paying off well. >> Mark Lohmeyer: Right. >> Dave's going to dig into some customer spending data in the marketplace. Great momentum, I mean, looking back a few years when you guys launched this, I mean, come on. You got to be happy. (gentlemen laughing) >> Yeah, we're pleased. I mean, I think, as you said the partnership has never been stronger and I think the foundation of that is really the tremendous customer demand we're seeing for the service. And this initial idea that Pat and Andy had together of how do we create the best of both worlds here, right? The enterprise class capabilities of VMWare are combined with everything customers love about the AWS Cloud. I think that's really come to fruition and, you know, what's been great to sort of see over the last two years is, really the customer momentum and the use cases and the way they're able to take advantage of that service to really solve some really big challenges for their business, right? And for it to become a platform for them for innovation. So really pleased to see that momentum. >> John Furrier: Ben, talk about your use case. You obviously, the story here to reinvent is don't tire kick the Cloud, you got to kind of go all in as Chastity would say, but you've got to leverage the transformational aspects of the scale, but when you get in the reality, which you live, talk about what's real about the Cloud. >> Ben Tanner: We're an information company. Data is king to us so, you know, it's real hard for us to be part in on the Cloud. You know, we have a data gravity problem, so how do we get our workload to there without necessarily having to refactor them. How do we do it with a way that we can minimize the risks? So for me, you know, getting all in on the Cloud means getting the data to the Cloud and enabling the developers to work in a way that's going to deliver business value quicker to our customers. So, that's really where VMC kind of helps bridge that gap for us, I think. Originally, we were looking at it as like a short-term capacity first venue, but then we look under the covers. Actually, you know, we can go build a brace to VMC and really get to the Cloud quicker. >> John Furrier: VMC, VMWare Cloud? >> VMWare Cloud, sorry. >> I want to make sure I get it out there. >> I want to dive in on some of the spending data that we have access to from ETR, Enterprise Technology Research. And essentially, they do these these quarterly surveys. And a survey, the most recent one, there was 1,300 people who responded. 708 of U.S. customers, of which 150 said we are spending heavily on VMWare Cloud on AWS. So my first question is, to what do you attribute, sort of the momentum, maybe you can give us the update there. And then I want to follow up on the customer point of view. >> Mark Lohmeyer: Yeah, absolutely not. I'll sort of build on some of Ben's comments, because I think what he articulated is one of the killer use cases of VMWare Cloud on AWS that I think is driving that momentum, right, which is we think it's one of the best uses in the marketplace and customers have told us this, to enable them to migrate and modernize, right? So let's talk about the migrate piece first, right? I mean, you have customers that have these tremendous enterprise-class applications, running on vSphere in their data centers. They're built on top of that platform. They depend upon it for performance availability, everything else. With VMWare Cloud in AWS, we can migrate those applications with zero downtime, no refactoring, no additional costs, in a matter of weeks or months, as opposed to if you had to refactor everything, could take years and millions of dollars, right? So that Cloud migration use case I would say is the killer for us and that's, you know, exactly what Ben was referring to. >> John Furrier: We've got a special report on siliconangle.com called The Great Migration and it's about Cloud. Talk about this particular issue because this is like top of mind of everybody. How do you do it right if you're a VMWare customer, what do you pay attention to? What are some of the things that you learned and what are the things to watch out for? >> Ben Tanner: That's a great question. I think ultimately you have to listen to your customers. So for me, that sort of element community and then within IHS Market and then ultimately, their customers. So we cover like three broad sectors. Oil and gas, the energy division, we have transportation division and then we have our financial services division. So each one of those division's got a different risk appetite. So depending on that appetite, we'll very much govern how we take the approach of moving to the Cloud. We've done the classic lift and shift using tools like VMWare's HCX. We actually, as a kick the tires, we moved a thousand workloads in six weeks into VMC, which was kind of exciting. >> Mark Lohmeyer: Yeah, pretty impressive. >> We enjoyed that. And then in other areas we're looking at, well we don't want to take all that tentacle debt that lives in our data center with us, so can we do what we call a lift and fix approach, where we'll leverage sort of private Cloud ultimation tool and build over VMC to rapidly spin up new workloads there but without changing our operating model. And then that's one of the big things I call out about VMC, it allows you to get into that public Cloud space without having to drastically change how IT operates. And then you can start to shift to more of a public Cloud focus. So there's really that lift and shift, lift and fix, and then where we're developing new capabilities, or where there is definite business value, and that's the key thing, refactor of a Cloud native. So it's a spectrum. >> So you ultimately want to change your operating model- >> Ben Tanner: Absolutely. >> Just not today. >> Ben Tanner: Well no, I don't want to do it in a big bang. You know, that's very disruptive while we're doing that we're, you know, it takes our focus off away from delivering business value. So we're trying to find a way to do it in a more incremental manner. VMC's, VMWare Cloud Native is one of the things that's going to help us do that. >> John Furrier: Are you guys looking at Amazon's other services because you now, in AWS- >> Ben Tanner: Well we're heavy Amazon customers as it stands so we have a lot of Cloud Native Apps going out there. It was really interesting today, seeing where they're going with the HPC workloads, particularly where we're starting to look at ML and AI. We have a data late program that's at an AWS. So for our new developments, we're definitely embracing Cloud Native, but very much in the sort of hybrid Cloud methodology with the MC. >> John Furrier: Well Ben, I want to get your take on a meme that we've been kicking around all week around Cloud Native. The T, if we take the T out, which stands for trust, it's Cloud Naive. (laughter) So a lot of customers, they're trying, I think they're doing Cloud, they've got to factor into all these operational disruptions. >> Ben Tanner: Yep. >> You have staff issues, you have cost and inefficiencies that kick in. Disruption. Development choices. So where's the naivety, where's the native, savvy, where should people start thinking about when they start moving in the Cloud? >> Ben Tanner: It's a maturity conversation ultimately. I think if we look at, certainly within IHS Market, we've very much grown by acquisition. We have different sort of cultures within the firm. We have 650, 700 products, 700 different ways of doing things sometimes and they've all gone to the public Cloud at different rates and in different ways. So for us, it was assuming that we could do that in a manageable, controlled-cost, safely-governed way. And really understanding that, you know, you can't go out there as individual Dev teams and expect it all to be perfect. We need to start building almost a collabed community within the company and then starting to layer in governance. But again, that's if you say take the T out, trust. We within IT, we have to build up trust with our products teams because I think why they go to the Cloud is sometimes because IT hasn't been able to deliver on it. You know, it's customer's expectations. >> John Furrier: You can't move fast enough. >> Yeah, exactly. Yeah. And you know, we're never going to be able to compete with the likes of Amazon or VMWare in security and functionality and scalability. Why would we try to compete? Let's embrace that. Extend, enable it, and really try to give our customers a consistent, delightful experience. >> So Ben, where are you placing your bets? Obviously Cloud, Hybrid, those are two things. Any other places where you're really trying to focus? >> Ben Tanner: So I think that's interesting. Again, my job is to make life easy for my developers. So what do they need? And this is something that we're going through, again, internal transformation, starting to run IT more like a product management organization and actively listening and soliciting feedback and really delivering what they need. You know, we're getting a lot of talk around containers, what are our plays going to be in that space. Some of the development teams are on that. Some of them want to go and embrace the new stuff like Fargate and EKS and that's great as well, but ultimately, I want to get out of tickets and weight states and get out of the way of the developers. >> John Furrier: I want to ask you a question around developers, cause one of the trends we're seeing and we're kind of picking out of the announcements is when you look at the DevOps movement that started roughly around 2007-2008, '09 timeframe, that early wave of pioneers created infrastructure as code. >> Ben Tanner: Yeah. >> That essentially became, "I don't want to configure the software. Operating models like VMWare, make it easy." Things are just running under the covers. Now with the data modeling you're seeing, if you've got large scale infrastructure, you're seeing now all these data toolings. So there's almost a data as code kind of theme going on here where developers just want to access the data, they don't to have to get into the wrangling. >> Ben Tanner: I think that's where we're sort of seeing things like data late coming to the forefront. You know, again, IHS Market Information Company. How do we pool all that information together in a way that, you know, creates new business value, creates new ideas. You know, broad ease of access for our developers and our customers, but at the same time, how do we protect things like data sovereignty. If we've got PII data out there, you know, we have to think about that. Whether they're alter motive customers. You know, you've got different state legislation so again, it's how do we as the IT and sort of the develop community facilitate broad safe access to data. Data is a service. Yeah. >> John Furrier: Yeah. 100%. >> Absolutely. >> So Mark, as customers move to the Cloud and they want to change their operating model, what role is VMWare playing in terms of facilitating that? >> Mark Lohmeyer: Yeah, you know, I think essentially you said you wanted to make life as easy as possible for the developers, right? And I think we want to make life as easy as possible for Ben and IT so he can make it easy for developers. And I think we know one of the ways that we love to do that is, and the way I think about is, we want to provide him and customers like him the broadest, most powerful tool kit that they can choose from, right, as they're enabling their developers. If you think about VMWare Cloud and AWS, it can actually enable that, right? Because you have access to all of the VMWare tools and capabilities, not just your existing workloads, but also for modernized applications with things like Kubernetes and some of the capabilities we're bringing to bear there. So we provide all of those services in the VMWare environment, but then we also allow their IT teams and their development teams to also have access to all the Native AWS services and some of the data tools that they might want to leverage from AWS- >> So is it- >> All in a single environment. >> So you've got core VMWare, now you have pivotal- >> Mark Lohmeyer: That's right. >> For the developer angle and you've got all the security acquisitions you've made, not the least which is carbon black so that's the package that you're delivering to your customers. >> Mark Lohmeyer: Absolutely. Right. And we want to do all of that, obviously, as a service on top of AWS, right, bringing that same sort of simplicity of operations for all of those capabilities. >> John Furrier: Mark, talk about what's coming next for you guys at VMWare and the Cloud platform. Obviously, we saw that Outpost, Native Outpost, which is Amazon shipping, available now. >> Mark Lohmeyer: Yeah. >> 2020 we're going to see VMWare on AWS, VMWare Cloud and AWS roughly shipping behind it. So that's looking like good news too. Architectural shifts are happening, can you share any insight into what's next for you and your team? >> Mark Lohmeyer: Yeah, I mean, it's a really exciting time. I think, look at this point, I think the customer's have spoken, its a hybrid Cloud world, right? They want to have the flexibility to run apps across their own data centers, across public Clouds, across edge environments. It's a hybrid Cloud world. >> John Furrier: AWS agrees. >> Yeah, I mean, even AWS agrees. You know, as VMWare as a company, we're looking to really enable the most seamless, most consistent hybrid Cloud experience. Obviously, we're the standard in most enterprise customer's data centers today. With VMWare Cloud and AWS, we're bringing that capability to AWS. And then we're really excited, of course, about VMWare Cloud and AWS Outpost because we can now bring that same Cloud delivered model back, you know, on-prem and into edge environments, right? And so we think that full set of services, right, what you have in your data center today, what you can do on AWS with VMC and now back on-prem, it opens up a lot of possibilities for customers like IHS. >> John Furrier: And Chastity kind of hinted at it, well he talked specifically about networking- >> Mark Lohmeyer: Right. >> In context of 5G latency, different use cases around latency. So networking is going to be a big thing. >> Mark Lohmeyer: I mean networking, if you think about a hybrid Cloud world, right? I mean, networking is kind of at the heart of it, right? And if you look at technologies like NSX, right, that gives you a consistent software networking layer that can work across any hardware on-prem. Obviously, it's the heart of VMWare Cloud and AWS, also in Outpost, it's a really important construct that fundamentally enables things like the seamless migration of workloads between these different environments. >> John Furrier: On Open Source as well. Guys, thanks for coming on. Final word, your thoughts on the keynote, the presence here at AWS. What's your takeaway from the day one. >> Ben Tanner: I think for me for day one, it's really exciting to see the development in things like the HPCP's. How that's going to enable us as a customer to do more with things like AI and ML. I think, for me, Outpost is really fascinating. We were talking about this earlier, where we've got regulatory requirements, performance requirements. We can still deliver that consistent experience in the Cloud, in the data center. So those for me are going to be, potentially, really transformative. >> John Furrier: And this really highlights what we've been debating. I challenged Gelsinger, Pat Gelsinger, CEO of VMWare in 2013 about hybrid being a halfway house to the public Cloud. He's like, "What are you talking about? It is the model." Pat if you're watching, you were right, I was wrong. I admit it. (laughter) But hybrid Cloud is certainly a visibility, but the Cloud as an operating model and what Chastity's saying and what Microsoft and other's are saying is, "Hey, the Cloud is the operating model, not the old way." So center of gravity is Cloud, but the on-premise for these specific things like governance, compliance, use cases. This is the new normal. This is very clear, no one debates this. >> John Furrier: Congratulations. Congratulations on your success, so say hello to Ragu and the team. >> Will do. >> John Furrier: Thanks for coming on. VMWare and custom momentum. I'm John Furrier with Dave Vellante. AWS re:Invent. Be back with more coverage after the short break. (upbeat techno music)

>>Hey everybody. Welcome back. Good afternoon. Lisa Martin here with John Feer live in Detroit, Michigan. We are at Coon Cloud Native Con 2020s North America. John Thank is who. This is nearing the end of our second day of coverage and one of the things that has been breaking all day on this show is news. News. We have more news to >>Break next. Yeah, this next segment is a company we've been following. They got some news we're gonna get into. Managing Kubernetes life cycle has been a huge challenge when you've got large organizations, whether you're spinning up and scaling scale is the big story. Kubernetes is the center of the conversation. This next segment's gonna be great. It >>Is. We've got two guests from Specter Cloud here. Please welcome. It's CEO Chenery Fu and co-founder and it's c g a co-founder Sta Mallek. Guys, great to have you on the program. Thank >>You for having us. My pleasure. >>So Timary, what's going on? What's the big news? >>Yeah, so we just announced our Palace three this morning. So we add a bunch, a new functionality. So first of all we have a Nest cluster. So enable enterprise to easily provide Kubernete service even on top of their existing clusters. And secondly, we also support seamlessly migration for their existing cluster. We enable them to be able to migrate their cluster into our CNC for upstream Kubernete distro called Pallet extended Kubernetes, GX K without any downtime. And lastly, we also add a lot of focus on developer experience. Those additional capability enable developer to easily onboard and and deploy the application for. They have test and troubleshooting without, they have to have a steep Kubernetes lending curve. >>So big breaking news this morning, pallet 3.0. So you got the, you got the product. This is a big theme here. Developer productivity, ease of use is the top story here. As developers are gonna increase their code velocity cuz they're under a lot of pressure. This infrastructure's getting smarter. This is a big part of managing it. So the toil is now moving to the ops. Steves are now dev teams. Security, you gotta enable faster deployment of apps and code. This is what you guys solve while you getting this right. Is that, take us through that specific value proposition. What's the, what are the key things on in this news release? Yeah, >>You're exactly right. Right. So we basically provide our solution to platform engineering ship so that they can use our platform to enable Kubernetes service to serve their developers and their application ship. And then in the meantime, the developers will be able to easily use Kubernetes or without, They have to learn a lot of what Kubernetes specific things like. So maybe you can get in some >>Detail. Yeah. And absolutely the detail about it is there's a big separation between what operations team does and the development teams that are using the actual capabilities. The development teams don't necessarily to know the internals of Kubernetes. There's so much complexity when it comes, comes into it. How do I do things like deployment pause manifests just too much. So what our platform does, it makes it really simple for them to say, I have a containerized application, I wanna be able to model it. It's a really simple profile and from there, being able to say, I have a database service. I wanna attach to it. I have a specific service. Go run it behind the scenes. Does it run inside of a Nest cluster? Which we'll talk into a little bit. Does it run into a host cluster? Those are happen transparently for >>The developer. You know what I love about this? What you guys are doing in the news, it really points out what I love about DevOps. Because cloud, let's face a cloud early adopters, we're all the hardcore cloud folks as it goes mainstream. With Kubernetes, you start to see like words like platform engineering. I mean I love that term. That means as a platform, it's been around for a while. For people who are building their own stuff, that means it's gonna scale and enable people to enable value, build on top of it, move faster. This platform engineering is becoming now standard in enterprises. It wasn't like that before. What's your eyes reactions that, How do you see that evolving faster? Or do you believe that or what's your take on >>It? Yeah, so I think it's starting from the DevOps op team, right? That every application team, they all try to deploy and manage their application under their own ING infrastructure. But very soon all these each application team, they start realize they have to repeatedly do the same thing. So these will need to have a platform engineering team to basically bring some of common practice to >>That. >>And some people call them SREs like and that's really platform >>Engineering. It is, it is. I mean, you think about like Esther ability to deploy your applications at scale and monitoring and observability. I think what platform engineering does is codify all those best practices. Everything when it comes about how you monitor the actual applications. How do you do c i CD your backups? Instead of not having every single individual development team figuring how to do it themselves. Platform engineer is saying, why don't we actually build policy that we can provide as a service to different development teams so that they can operate their own applications at scale. >>So launching Pellet 3.0 today, you also had a launch in September, so just a few weeks ago. Talk about what these two announcements mean from Specter Cloud's perspective in terms of proof points, what you're delivering to the end users and the value that they're getting from that. >>Yeah, so our goal is really to help enterprise to deploy and around Kubernetes anywhere, right? Whether it's in cloud data center or even at Edge locations. So in September we also announce our HV two capabilities, which enable very easy deployment of Edge Kubernetes, right at at at any any location, like a retail stores restaurant, so on and so forth. So as you know, at Edge location, there's no cloud endpoint there. It's not easy to directly deploy and manage Kubernetes. And also at Edge location there's not, it's not as secure as as cloud or data center environment. So how to make the end to end system more secure, right? That it's temper proof, that is also very, very important. >>Right. Great, great take there. Thanks for explaining that. I gotta ask cuz I'm curious, what's the secret sauce? Is it nested clusters? What's, what's the core under the hood here on 3.0 that people should know about it's news? It's what's, what's the, what's that post important >>To? To be honest, it's about enabling developer velocity. Now how do you enable developer velocity? It's gonna be able for them to think about deploying applications without worrying about Kubernetes being able to build this application profiles. This NEA cluster that we're talking about enables them, they get access to it in complete cluster within seconds. They're essentially having access to be able to add any operations, any capabilities without having the ability to provision a cluster on inside of infrastructure. Whether it's Amazon, Google, or OnPrem. >>So, and you get the dev engine too, right? That that, that's a self-service provisioning in for environments. Is that, Yeah, >>So the dev engine itself are the capabilities that we offer to developers so that they can build these application profiles. What the application profiles, again they define aspects about, my application is gonna be a container, it's gonna be a database service, it's gonna be a helm chart. They define that entire structure inside of it. From there they can choose to say, I wanna deploy this. The target environment, whether it becomes an actual host cluster or a cluster itself is irrelevant to them. For them it's complete transparent. >>So transparency, enabling developer velocity. What's been some of the feedback so far? >>Oh, all developer love that. And also same for all >>The ops team. If it's easy and goods faster and the steps >>Win-win team. Yeah, Ops team, they need a consistency. They need a governance, they need visibility, but in the meantime, developers, they need the flexibility then theys or without a steep learning curve. So this really, >>So So I hear a lot of people say, I got a lot of sprawl, cluster sprawl. Yeah, let's get outta hand does, let's solve that. How do you guys solve that problem? Yeah, >>So the Neste cluster is a profit answer for that. So before you nest cluster, for a lot of enterprise to serving developers, they have to either create a very large TED cluster and then isolated by namespace, which not ideal for a lot of situation because name stay namespace is not a hard isolation and also a lot of global resource like CID and operator does not work in space. But the other way is you give each developer a separate, a separate ADE cluster, but that very quickly become too costly. Cause not every developer is working for four, seven, and half of the time your, your cluster is is a sit there idol and that costs a lot of money. So you cluster, you'll be able to basically do all these inside the your wholesale cluster, bring the >>Efficiency there. That is huge. Yeah. Saves a lot of time. Reduces the steps it takes. So I take, take a minute, my last question to you to explain what's in it for the developer, if they work with Spec Cloud, what is your value? What's the pitch? Not the sales pitch, but like what's the value pitch that >>You give them? Yeah, yeah. And the value for us is again, develop their number of different services and teams people are using today are so many, there are so many different languages or so many different libraries there so many different capabilities. It's too hard for developers to have to understand not only the internal development tools, but also the Kubernetes, the containers of technologies. There's too much for it. Our value prop is making it really easy for them to get access to all these different integrations and tooling without having to learn it. Right? And then being able to very easily say, I wanna deploy this into a cluster. Again, whether it's a Nest cluster or a host cluster. But the next layer on top of that is how do we also share those abilities with other teams. If I build my application profile, I'm developing an application, I should be able to share it with my team members. But Henry saying, Hey Tanner, why don't you also take a look at my app profile and let's build and collaborate together on that. So it's about collaboration and be able to move >>Really fast. I mean, more develops gotta be more productive. That's number one. Number one hit here. Great job. >>Exactly. Last question before we run out Time. Is this ga now? Can folks get their hands on it where >>Yes. Yeah. It is GA and available both as a, as a SaaS and also the store. >>Awesome guys, thank you so much for joining us. Congratulations on the announcement and the momentum that Specter Cloud is empowering itself with. We appreciate your insights on your time. >>Thank you. Thank you so much. Right, pleasure. >>Thanks for having us. For our guest and John Furrier, Lisa Martin here live in Michigan at Co con Cloud native PON 22. Our next guests join us in just a minute. So stick around.

I from Las Vegas Nevada it's the cube covering IBM world of Watson 2016 brought to you by IBM now here are your hosts John furrier and Dave vellante hey welcome back everyone we're here live in Las Vegas for IBM's world of Watson at the mandalay bay here this is the cube SiliconANGLE media's flagship program we go out to the events and extract the signal-to-noise I'm John Ford SiliconANGLE i'm here with dave vellante my co-host chief researcher red Wikibon calm and our next guest is inderpal bhandari who's the chief global chief data officer for IBM welcome to the cube welcome back thank you thank you meet you you have in common with Dave at the last event 10 years Papa John was just honest we just talked about the ten year anniversary of I OD information on demand and Dave's joke why thought was telling we'll set up the says that ten years ago different data conversation how do you get rid of it is I don't want the compliance and liability now it shifted to a much more organic innovative exciting yeah I need a value add what's the shift what's the big change in 10 years what besides the obvious of the Watson vision how did what it move so fast or too slow what's your take on this ya know so David used to be viewed as exhaust right the tribe is something to get rid of like you pointed out and now it's much more to an asset and in fact you know people are even talking about about quantifying it as an asset so that you can reflect it on the balance sheet and stuff like that so it certainly moved a long long way and I think part of it has to do with the fact that we are inundated with data and data does contain valuable information and to the extent that you're able to glean it and act on it efficiently and quickly and accurately it leads to a competitive advantage what's the landscape for architects out there because a lot of things that we hear is that ok i buy the day they I got a digital transformation ok but now I got to get put the data to work so I need to have it all categorized what's the setup is there a general architecture philosophy that you could share with companies that are trying to set themselves up for some baseline foundational sets of building blocks I mean I think they buy the Watson dream that's a little Headroom I just want to start in kindergarten or in little league or whatever metaphor we want to use any to baseline what's today what's the building blocks approach the building blocks approach I mean from a if you're talking about a pure technical architectural that kind of approach that's one thing if you're really going after a methodology that's going to allow you to create value from data I would back you up further I would say that you want to start with the business itself and gaining an understanding of how the business is going to go about monetizing itself not its data but you know what is the businesses monetization strategy how does the business plan to make money over the next few years not how it makes money today but over the next few years how it plans to make money that's the right starting point once you've understood that then it's basically reflecting on how data is best used in service of that and then that leads you down to the architecture the technologies the people you need the skills makes the process Tanner intuitive the way it used to be the ivory tower or we would convene and dictate policy and schemas on databases and say this is how you do it you're saying the opposite business you is going to go in and own the road map if you will the business it's a business roadmap and then figure it out yeah go back then go back well that's that's really the better way to address it than my way so the framework that we talked about in in Boston and now and just you're like the professor I'm the student so and I've been out speaking to other cheap date officers about it it's spot on this framework so let me briefly summarize it and we can I heard you not rebuilding it to me babe I'm saying this is Allah Falls framework I've stolen it but with no shame no kidding and so again we're doing a live TV it's you know he can source your head I will give him credit so but you have said they're there are two parallel and three sequential activities that have to take place for data opposite of chief data officer the two parallel our partnership with the line of business and get the skill sets right the three sequential are the thing you just mentioned how you going to monetize data access to data data sources and Trust trust the data okay so great framework and I'd say I've tested it some CEOs have said to me well I geeza that's actually better than the framework I had so they've sort of evolved as I said you're welcome and oh okay but now so let's drill into that a little bit maybe starting with the monetization piece in the early days Jonna when people are talking about Big Data it was the the mistake people made was I got to sell the data monetize the data itself not necessarily it's what you're saying yes yes I think that's the common pitfall with that when you start thinking about monetization and you're the chief data officer your brain naturally goes to well how do I monetize the data that's the wrong question the question really is how is the business planning to monetize itself what is the monetization strategy for the overall business and once you understand that then you kind of back into what data is needed to support it and that's really kind of the sets the staff the strategy in place and then the next two steps off well then how do you govern that data so it's fit for the purpose of that business lead that you just identified and finally what data is so critical that you want to centralize it and make sure that it's completely trusted so you back into those three those three steps so thinking about data sources you know people always say well should you start with internal should you start with external and the answer presumably is it depends it depends on the business so how do you how do you actually go through that decision tree what's that process like yeah I mean if you know you start with the monetization strategy of the company so for example I'll use IBM a banana and the case of IBM took me the first few months to understand that our monetization strategy was around cognitive business specifically making enterprises into cognitive businesses and so then the strategy that we have internally for IBM's data is to enable cognition within within IBM the enterprise and move forward with that and then that becomes a showcase for our customers because it is after all such a good example of a complex enterprise and so backing you know backing in from that strategy it becomes clear what are some of the critical data elements that you need to master that you need to trust that you need to centralize and you need to govern very very rigorously so that's basically how I approached it did I answer your question daivam do you get so so you touched on the on the second part I want to drill into the the third sequential activities which which is sources so i did so you did we just talk about this well the sources i mean if you had something add to that yes in terms of the i think you mentioned the internal versus external so one thing else i'll mention especially if you kind of take that 10-year outlook that we were talking about 10 years ago serials had very internal outlook in terms of the data was all internal business data today it's much more external as well there's a lot more exogenous data that we have to handle and validity and that's because we're making use of a lot more unstructured data so things like news feeds press releases articles that have just been written all our fair game to amplify the view that you have about some entity so for example if we're dealing with a new supplier you know previously we might gather some information by talking with them now we'd also be able to look at essentially everything that's out there about them and factor that in so it is a there's an element of the exogenous data that's brought to bear and then that obviously becomes part of the realm of the CDO as well to make sure that that data is available and you unusable by the business is John Kelly said something go ahead sorry well Jeff Jonas would say that's the observation space right that you want to have the news feeds it's extra metadata that could change the alchemy if you will of whatever the mix of the data is that kind of well yeah I would say you might even go further than just metadata i would say that in some some sense it's part of your intrinsic data set because you know it gives you additional information about the entities that you're collecting data on and that measuring the John Kelly in the keynote this morning he made two statements he said one is in three to five years every health care practitioners going to going to want to consult Watson and then he also said same thing for MA because watch is going to know every public piece of data about every single company right so it's would seem that within the three to five year time frame that the shift is going to be increasingly toward external data sources not necessarily the value in the lever points but in terms of the volume certainly of data is that fair I think it's a it's a fair statement I mean I think if you think of it in the healthcare context if you know a patient comes in and there's a doctor or a practitioner that's examining the patient right there they're generating some data based on their interaction but then if you think about the exogenous data that's relevant and pertinent to that case that could involve you know thousands of journals and articles and so you know your example of essentially saying that the external data could be far greater than the internal data out say we're already there okay and then the third sequential piece is trust are you gonna be able to trust the trust we talk a lot about we were down to Big Data NYC the same week you guys made your big announcement the data works everybody talks about data Lakes we joke gets the data swamp and can't really trust the data yeah we further away from a single version of the truth than we ever were so how are you dealing with that problem internally at IBM and what's the focus is it more on reporting is it more on supporting lines of business in product yeah the focus internal within IBM is in terms of driving cognition at the way I would describe it is at points where today we have significant human judgment being exercised to make decisions and that's you know thousands of points in our enterprise or complicated enterprise like IBM's and each of those decision points is actually an opportunity to inject cognitive technology and play and then bring to bear and augmented intelligence to those decisions that you know a factors in the exogenous data so leaving a much better informed decision but also them a much more accurate decision okay the two parallel activities let's start with the first one line of business you know relationships sounds like bromide why is it not just sort of a trite throwaway statement what where's the detail behind that so the detail behind that if you go back to the very first and the most important step and this whole thing with regard to the monetization strategy of the company understanding that if you don't have those deep relationships with the lines of business there's no way that you'll be able to understand the monetization strategy of the business so that's why that's a concurrent activity that has to start on day one otherwise you won't even get past the you know that that very first first base in terms of understanding what the monetization strategies are for the business and that can only really come by working directly with the business units meeting with their leadership understanding their business so you have to do that due diligence and that's where that partnership becomes critical then as you move on as you progress to that sequence you need them again so for instance once you understood the strategy and now you understood what data you need to follow that strategy and to govern it you need their help in governing the business because in many cases the businesses may be the ones collecting the data or at least controlling the source systems for that data so that partnership then just gets deeper and deeper and deeper as you move forward in that program I love the conscience of monetizing earlier and this some tweets going around you know what's holding it back cost of building it obviously and manageability but I want to bring that back and bring a developer perspective here because a lot of emphasis is on developing apps where the data is now part of the development process I wrote a blog post in 2008 saying that dated some new development kit radical at the time but reality it came out to be true and that they're looking at data as library of value to tap into so if stuffs annandale they could be sitting there for years but I could pull something out and be very relevant in context in real time and change the game on some insight and the insight economy is bob was saying so what is your strategy for IBM 21 on board more developer goodness and to how do you talk to customers were really trying to figure out a developer strategy so they can build apps and not to go back and rewrite it make it certainly mobile first etc but what's how does a date of first appt get built and I should developers be programming with you I'll give you a way to think about it right i mean and going back again to that ten-year paradigm shift right so ten years ago if somebody wanted to write an application and put it on the internet and it was based on data the hardest part was getting hold of the data because it was just very very difficult for them to get all of it to access the data and then those who did manage to get all of the data they were very successful in being able to utilize it so now with the the paradigm shift that's happened now is the approaches that you make the data available to developers and so they don't have to go through that work both in terms of accessing collecting finding that data then cleaning it it's also significant and so time consuming that it could put put back there their whole process of eventually getting to the app so to the extent that you have large stores of data that are ready to go and you can then make that available to a body of developers it just unleashes it's like having a library of code available is it all the hard work and I think that's a good way to look at it I mean that's think that's a very good way to look at it because you've also got technologies like the deep learning technologies where you can essentially train them with data so you don't need to write the code they get trained to later so I see a DevOps of data means like an agile meets I'm again you're right a lot of the cleaning and this is where you no more noise we all know that problem or data creates more noise better cleaning tools so however you can automate that yes seems to be the secret differentiator it's an accelerator it's amazing accelerator for development if you have good sets of data that are available for them to used so I want to round out my my little framework here your frame working with my my learnings for the fifth one being skills yes so this is complicated because it involves organization skills changes as pepper going through the lava here we try to get her on the cube Dave home to think the pamper okay babe yeah so should I take over pepper you want to go see pepper I want to see pepper on the cube hey sorry exact dress but so a lot of issues there there's reporting structures so what do you mean when you talk about sort of the skill sets and rescaling so and I'll describe to you a little bit about the organization that I have at IBM as an example some of that carries over and some of that doesn't the reason I say that is again I mean the skills piece there are some generic skill sets that you need for to be achieved data officer to be a successful chief data officer in an enterprise there is one pillar that I have in my organization is around data science data engineering DevOps deep learning and these are the folks who are adept at those technologies and approaches and methodologies and they can take those and apply them to the enterprise so in a sense these are the more technical people then another pillar that's again pretty generic and you have to have it is the information and data governance pillow so that anything that's flowing any data that's flowing through the data platform that I spoke off in the first pillar that those that that data is governed and fit for purpose so they have to worry about that as soon as any data is you even think of introducing that into the platform these folks have to be on that and they're essentially governing it making sure that people have the right access security the quality is good its improving there's a path to improving it and so forth I think those are some fairly generic you know skill sets that we have to get in the case of the first pillar what's difficult is that there aren't that many people with those skills and so it's hard to find that talent and so the sooner you get on it so that would that's the biggest barrier in the case of the second pillar what's the most difficult piece there is you need people who can walk the balance between monetization and governance too much governance and you essentially slow everything down and nothing moved a cuff and you're handcuffed and then you know if it's too much monetization you might run aground because you you ignored some major regulation so walking that loss of market value yeah that's what you have to really get ahead of your skis as they say and have a faceplant you'll try too hard to live boost mobile web startups like Twitter that's big cock rock concert with Twitter Facebook if you try to monetize too early yes you lose the flywheel effect of value absolutely so walking that balance is critical so that's that that's really finding the skill set to be able to do that that's that's what what's at play in that second or the third one is if you are applying it to an enterprise you have to integrate these you know this platform into the workflow off the enterprise itself otherwise you're not going to create any impact because that's where the impact gets created right that's basically where the data is that the tip of the spear to so to speak so you it's going to create value and in a large enterprise which has legacy systems which are silos which is acquiring companies and so on and so forth that's enough itself a significant job and that skill set is that's a handicapped because if you have that kind of siloed mentality you don't get the benefits of the data sharing right so what's that what's said how much how much effort would it take I'm just kind of painting that picture kind of like out there like well a lot of massively hard ya know that that's you know a lot of you know a lot of people think that data mining is all about my data you know this is my data I'm not going to give it to you the one of the functions of the chief data office is to change that mindset yeah and to stop making use of the data in a broader context than just a departmental siloed type of approach and now some data can legitimately be used only departmentally but the moment you need two or more department start using that data I mean it's essentially corporate data so are those roles a shared service everybody see that works it maybe varies but is it a shared service that reports into the chief data officer or is it embedded into the business those those skill sets that you talked about I think those skill sets are definitely part of the chief data officer you know organization now it's interesting you mentioned that about embedding them and the business units now in a in a large enterprise a complicated enterprise like IBM the different business units and that potentially have different business objectives and so forth you know you you do need a chief data officer role for each of these business units and that's something that I've been advocating that's my fault pillar and we are setting that up and then within the context of IBM so that they serve the business unit but they essentially reporting to me so that they can make use of the overall corporate structure you do their performance review the performance review is done by the business unit it is ok but the functional direction is given by me ok so I get back to still go either way oh yes that's a balance loon yeah absolutely under a lot of time for sure i'll get back to this data mining because you bring up a good point we can maybe continue on our next time we talk but data monies were all the cutting edge kind of best practices are were arsed work what we're relations are still there technically if you're here but that the dynamic of data mining is is that you're assuming no new data so with if you have a lot of data coming in most of the best data mining techniques are like a corpus you attack it and learned but if the pile of data is getting bigger faster that you could date a mine it what good is against or initial circular hole I'm going to again you know just take you back 10 years from now and now right and the differences between the two so it's very interesting points that you bring up I'll give you an example from 10 years ago this data mining example not ten years ago actually my first go-around at IBM so it's like 94 yeah one of the things I've done was we had a program a computer program that every team in the National Basketball Association started using and this was a classic data mining program it would look at the data and find insights and present them and one of the insights that it came up with and this was for a critical playoff game it told the coach you got to play your backup point guard and your backup forward now think about that which same coach would actually go with that so it's very hard for them to believe that they don't know if it's right or wrong in my own insurance and the way we got around that was we essentially pointed back to the snippets of video where those circumstances occurred and now the coach could see what is going on make a you know an informed decision flash forward to now the systems we have now can actually look at all that context all at once what's happening in the video what's happening in the audio also the data can piece together the context so data mining is very different today than what it was them now it's all about weaving the context and the story together and serving it up yeah what happened what's happening and what's going to happen kinda is the theaters of yes there are in sight writing what happened it's easy just yeah look at the data and spit out some insight what's happening now is a bit harder in memory I think that's the difference between cognition as it away versus data mining as you know we understood a few years ago great cartridge we can go for another hour but do we ever get enough love to follow up on some of the deep learning maybe come down to armonk next time we're in this certainly on the sports data we have a whole program on sports data so we love the sports with the ESPN of tech and bringing you all the action right here yes I did Doug before Moneyball you know my mistake was letting right yeah yeah right the next algorithm but that's okay you know we put a little foot mark on the cube notes for that thank you very much thank you appreciate okay live in Mandalay Bay we're right back with more live coverage I'm Sean for a table on thing great back today I am helping people