>>Hi from Las Vegas, extracting the signal from the noise. It's the cube covering IBM insight 2015 brought to you by IBM. Now your host, Dave Vellante and Paul Gillin. >>Welcome back to IBM insight everybody. This is the cube. The cube goes out to the events. We extract the signal from the noise. This is I think our fourth year at IBM insight, IBM's big, big data show. IBM doesn't use that term, they call it analytics and it's been done a tremendous job of taking this giant portfolio and then building a leading the leading actually analytics business in the industry. Harriet Fryman is here, she's the vice president of marketing at IBM analytics. Harriet, welcome to the cube. Good to see you. Thanks for having me back. Yes, so the show here is big, I think bigger than anyone, you know, we've been to a lot of great energy. The solutions expo is tremendous. The, the keynote this morning were packed the general session, so you must be thrilled. >>Yeah, it's fantastic audience. And we just came off our advanced analytics keynote this afternoon. We were talking about the advances in Watson analytics. So the smart data discovery tool as well as our new release of Cognos. >>So Watson analytics is just permeating all parts of the business in the healthcare business, the cloud business, the analytics business. Talk about the impact that that little sort of experimental program with jeopardy has had on the company as a whole. >>Yeah, it's really delivering on the promise of, we talk about around the cognitive business and where Watson analytics comes in. It's really looking to bring that smart data discovery to an individual on their, um, on their PC to get instant insights into data. Whereas before they're really, um, could get access to the data, but how do they find the causation between data points versus just take a look at sales data, finance data. So Watson analytics really allows them to have that natural language question and um, have the processing behind the scenes find the interesting stuff in the data. >>Big idea is a, is it a marketing executive? You've got to love the, the fact that you can actually produce such a capability, you know, it's not like a little point product that's a platform that can touch every part of your business that can change lives. What are your, can you comment on that as again, from a marketing perspective, >>it's always fun in marketing to have a great portfolio to be able to market and something that really makes a difference to people's business. So with the, with Watson analytics and with what we're doing with Cognos around our business intelligence, it's great to market. Um, what has always been promised, I think in the BI market for many years, which is self service analytics for all. So, uh, as we're marketing both the capabilities around Watson as well as the capabilities and Cognos, it's kind of a delight to say, you know, what we were talking about give insight to everybody to make better decisions. It's really coming to fruition. >>If IBM has grown its analytics business largely through acquisition, I think you'd have 25 acquisitions. You've got a of different great brands, SPSS, core metrics, Cognos and the like is Watson, they're going to evolve and do a kind of a simulation point for all of those? >>Well, yeah. What we look at is, um, as we talked about the cognitive business and Watson really been the cognitive computing engines of, of that business. We're looking at how our analytics business really expands a company's business companies, company's ability to really understand what the data is, turning them, learn from experience of working with the data and put that into practice. So we can do that with dashboards, with reports as well, which is help people understand there's insight to be gained from data. There's value to be gained from data. And so you can apply it through being a learning company with or without having a cognitive system itself. It's, I'm going to take data, I'm going to apply analytics to understand patterns and I'm going to apply that to my business. And then I'm going to learn from the feedback loop and just keep learning, learning, learning. And that's what a cognitive business is about. >>So the BI business historically, you know, it's been interesting to watch. I mean I remember when it was called, you know, decision support, right? And, and it's put on a lot of promises, 360 degree view of the business, you know, predictive analytics and it didn't live up to those promises. And then you have this whole Hadoop movement come in and they're going to live up to those promises and then you realize, wow, they actually can't live up to those promises without the traditional data sets. And are those two worlds coming together? Is that the way that we should be thinking about this to actually fulfill on those promises? The last 15 to 20 years? >>Yeah, I think we always had the chicken and the egg, right? You can't have great analytics without great data. And what's the use of great data and as you have great analytics, so you really need both together. And then the promise has always been a great three 60 degree view of customer actually requires being able to get your arms around the data itself, reconcile it, make sense of it. And then it requires great analytics and a way to deliver it to the people who can use it in their business, be they in call center and service and sales. So the promise has always been there is the fact that we need to put it all together. We need to put together the data, as you said, Hadoop and relational data altogether inside and outside the firewall. We need able to make sense of it. So bring those entities together, do master data management, make the data, make sense as you pull it together and then have a great way for people to understand it. Consumer apply it in their business. >>So Cognos was obviously huge acquisition don't, Paul wasn't mentioning many of them. I think we used to tell you it's one of his favorite and I think it was rather large. It was with $5 billion acquisition, I believe. And so, and then IBM has sort of supercharged that entire business. So how has Cognos evolved and where are we today? >>Yeah. So as, as I came in through the Cognos acquisition many years ago when IBM acquired us, I really have seen it just develop and expand from the day that we, uh, we came on board with IBM. It's really expanded in a couple of ways. One is that we have expanded, um, cognitive capability to get at all types of data. So you mentioned Hadoop. So now we've, we know that in order to deliver a rich understanding of what's happening in the business called the Cognos reporting capabilities need to access all of that data. And so it does, it can access relational data, data and appliances, Hadoop data, data on the cloud. So really expanding the Corpus of data that can be put into a report and consumed by business. The second, a big investment has been, um, where BI was always thought of as an it only tool. Now I ask it for a report. They have a report backlog. Some months later they may give me a report. It's not quite what I wanted. That whole world has changed now, which is really bringing BI, we imagined into business people's hands because they want the right to be able to model data to be able to author reports, distributed, shared among their colleagues. So it's been an exciting journey as we've really taken business intelligence really to the next level. >>It's all about the, the role. What's the role of the spark, the big spark initiative that IBM announced a couple of months ago vis-a-vis all of the analytics products, the spark act as kind of a preprocessor for the, the capable of the value of those, uh, those point products add or how does spark fit in with them? >>Yeah, so, um, so with our spark investment, we announced our commitment to spark back in June and since then we're really looking at as well what we coined the term, the analytics operating system. So we see it as that foundational layer that's really going to speed up the speed of analytics as well as be able to apply algorithms to a much bigger, um, Corpus of data than you traditionally would have in a statistics tool, for example. So since then, actually today we announced that we now have 15 solutions built on spark across our analytics and our commerce portfolio. A great example is we replatformed DataWorks, which is our ability for business to do data wrangling as part of the Watson analytics work process. So we see spark is really an enabling technology for ourselves and then we've committed a significant investment back into the spark community to keep it enhancing the core fundamental capabilities of spark so that everybody in the ecosystem can take advantage of that. >>He said something just a minute ago, VI re-imagined. I want to pick up on that theme because again, the BI world used to be insights for a few and then they were very productive, very productive few, right? They had a huge impact potentially on the company. But you now hear things like we heard this morning about you know, citizens and analytics and the likes. So, and you have the, you know, the BI for Hadoop vendor does your sort of attacking the old, you got the vis guys attacking that business. As we said before, it's still critical. But so what is BI re-imagined? You know mean that means more agile. It means simpler, it means embedded into the workflow or the organization. I wonder if you could describe that in some more detail. >>Of course. So when we look at business intelligence, I totally agree with you. It's really a tool that it use to develop reports or dashboards that were then delivered to the corner office, the suite for them to understand how my sales trending, what are my financials looking like, what's my production yield sort of reporting like. And that's great. Um, but that's kind of left a, a population that was not served, which was really the, uh, the business users who wanted to find insights for themselves. And that's really where the desktop discovery tools kind of were born, which was to satisfy that need out there that was not being satisfied by BI. When we're looking at re-imagining BI, we're looking at serving that community too, which means we have re redesigned the user experience of business intelligence so that those people out in the business can author their own insights, can distributed, distribute their own insights. >>And we've taken the learnings of how we designed Watson analytics and that user experience into the BI portfolio too. So let me give you an example. So for example, um, I'm looking for data. I want to report sales by product and by region. Um, I would have had to in the past have it build a model for me of that data. Now with re-imagined BI, I can be in the business, I can simply type in sales product, region. It's got to propose the data. So I don't need to know where the data's stored. It could be in Hadoop, it could be in relational. It's going to propose what data might be the most relevant to me. I can hit hit a button that says proposed model. It's going to model it for me in a way I go. So I didn't need to be a data modeler. I didn't need to know where the data was stored. So now I'm much more empowered as a business person. I don't need to offload that data into a desktop tool, worry about data silos, fragmentation of the decision process. I've now bought to that underserved population. >>So you've said what you've described, you've got a library of models and the system chooses the right one and fits for me. Is that right? Did I, >>you actually have a light. Yeah, close. You actually have a library of data sources and then you can build different models across those data sources. So you mentioned that there's a, a, uh, a dashboard tool right over here for Hadoop over here for maybe if another file system, etc. Well, that's great if all your data sits there. What we've done with BIS, we said, let's make that invisible and then you can pick data from any data source and bring it together into a single report. >>We had a routine of gunner on this morning talking about, uh, talking about governance. And what you're talking about was sort of democratization of, of analytics and, and everybody having their own, uh, their own tools, ability to manipulate data, I mean that has to proceed from a solid foundation of data governance. How well prepared our clients in your experience to proceed in that direction you're talking about they have that data really well hardened and bullets. >>So there's, there's a couple of steps I believe that um, clients understand that there's need to have integration and governance over the data sets, the challenges, the kind of Maverick use of data that happens in a company. So it's both tooling and technology as well as a corporate culture of how you're going to treat the data that you have in your, in your company. So where Ritika talks about the fact that you need to have a data reservoir, you need to have data warehouse, you need to have governance over that. We also need all of that governance to go all the way through to the end consumption of data. So where we've re imagined BI is to say you need that trusted source. It may sit on a server or many servers and need to make that available to everybody to self-serve and their first call to be, I shouldn't be, can I download that data into a tool myself? Cause the minute you cut that cord, your governance is gone. Now clients are starting to understand that because they're hitting that as the data discovery tools, um, start getting hold in the business, which is there's as many copies of data as people in the organization. And so one way to tackle that is to say no, I need to bring them back into the fold on the govern data and do that in a way that doesn't compromise their self service. >>So the big data meme sort of exploded around 2012 my, at the time, my 13 year old would joke and say good morning Polara and she'd say, morning daddy hashtag big data. And so I remember in 2012 when we came to insight, it was interesting to observe, but what IBM had done with this sort of bespoke portfolio of assets is put them together. And I said at the time, super glued it to the big data meme, changed the language around analytics and business outcomes and is now dominating that business or will dominate that business was kind of my prediction and it's exactly what you did in my, my version. Um, so let's talk about your portfolio. You've got purview over, so there's information management that's BI, the predictive analytics database is, is in there as well, and data integration, is that right? So there's that. What were once sort of these bespoke toolings talk about how you bring those together and bring them to market and message them? >>Yeah, yeah. It feels like there was, um, an evolution that happened in the marketplace, which is, as you said, it was almost like it had a shopping list. I'm going to go shop for BI now. I'm going to go and shop for predictive analytics and I'm going to go shop for a database and I'm going to go shop for integration. And really that's, um, great to have capability coverage. But in order to actually get insight from data, you need to be able to be in all the types of data, wherever it resides. You need to be able to put that data into context, which requires integration, master data management, and then you need to be able to deliver that, that, um, analytics and insight capability to everybody who needs it both through a dashboard as well as embedded into applications. So we really saw the opportunity to help our clients get value was to put them together and integrate them in such a way that you actually look for what business questions you want to answer. You don't shop by capability anymore. So the great thing when we look at how we market that is we can start with the business outcome or the client value and work back from there because different types of business problems require different combinations of the capabilities. >>And, and you find, I, you know, there's an old saying it's better to have overlaps than, than gaps. Do you find that you have more overlaps than gaps or do you find that you still got big gaps that you need to fill? >>Um, I think the language, we need some more English words and we need more words in the English language because when we say I need to get it data, I need to integrate it together and I need to deliver it. You could say that about Hadoop, right? Cause it does that. You could say that about a relational database. You could say that about our business intelligence tools. So sometimes people get, it appears like there's overlap because there's only so many limited words that we have to describe what we do. But it's the use cases that will prescribe which part of the portfolio we use. >>So at the, at the strata Hadoop world show this year, there were three or four big themes that emerge. You know, one was really about the data in motion in real time. You know, we talked about spark earlier. Uh, the second was the data, the database, the file system, you know, that sort of plumbing. Um, and the third was sort of complexity. Uh, everybody sort of choking on Hadoop complexity, spark helps but sparks complex too. So it seems like you guys are trying to take all that stuff and just make it invisible. Um, start with the business outcome and say, okay, you need real time. We, you know, to service this business or crime fraud, you know, is going to require some real time nature or maybe it's micro batching and whatever technology you use. Um, is that the right way to think about it that you're trying to hide that complexity and how do you hide that complexity? >>Yeah, exactly. We um, if you take the analogy of a car, everybody drives a car, but we don't necessarily have to understand how the engine works and you know, when we buy the car, we don't open up the hood and take a look and have everybody explain every single piece part and how they all work together. And that's sort of our destiny for what we're doing with insight, what we're doing with the solutions we build, which is yes, it has all those capabilities inside it, but you don't have to be technically savvy enough to understand what that is. You just need to know that it does what you want it to do for your business. So our is with data management, the hide, all the complexity of different data containers behind the scenes using big sequel or ways to access and make that transparent. Then with the analytics, we're looking to make the analytics transparent. So whether you're using an algorithm written in spark, you use an algorithm written in R, it doesn't matter. You're looking to have an algorithm apply to, to find patterns. >>But the way you would hide that complexity over the last 15 years is a big services engagement. And that's changing. Am I, am I understanding that right? I mean you're, you're changing that. You're driving more software into the platform and you're doing it with API APIs and, and, and less of an emphasis on leading with services, more of an emphasis on leading with business outcomes. And then mapping the technology to that. Is that, is that fair or is it still very heavily services led? >>Yeah, we definitely live the lead with the business outcomes. Um, as we look to support hybrid cloud environments, some of that technical complexity is, is made invisible because of the way that we use cloud. So you don't have to worry about deployment and enter production. The other thing we do with our services is we're much more focused on how are you going to apply the data that you have. How you get to apply analytics to actually change your business or services is much more in discussion of how are you going to make this impactful for your business versus the bits and bites of how do you install it, configure it and deploy it. >>But who, who is, who on the back end is going to do that dirty work. And who do you see in the companies you work with? Is there a specialized data function emerging within the CEO's organization? Is it, is it independent? Is it a set of independent of it is too important to the business or who who, who do you recommend do that backend plumbing work? >>Because we always used to talk about two populations in a client business and then it and how business and it would work together. We actually see a third leg of the stool happening, which is around the data professionals, so that's all the way from a chief data officer to achieve data scientists, data engineers, to application developers to implement those insights. So we see this third profession emerging in our clients. Now what's interesting is when they report into the it organization, they're more centered on data management, integration, governance. When they report into the business, they're much more focused on applying analytics for business outcomes, but you're absolutely right. There's this third data savvy PR profession that's really rising in importance and you see a lot more appetite in clients to get that data savviness as a population in the company. >>At this point, you don't see any pattern emerging for where that function lives in the organization. Does that so? >>Correct. We see two, two distinct patterns in it. To better manage the data in the business to better drive an outcome from analytics. >>Do you see this, is the CDO a coming role? Is that, is that a high growth function within the big corporations you work with? >>It's definitely a function that is pretty much becoming established. They're called chief data officers or chief analytics officers sitting at the table helping with the business strategy of how to apply data for a difference in. >>And is that something CIO should worry about? >>Um, I don't, I don't know if they were, I'd have to ask a CIO that question, but definitely the CIO world is shifting much more to how do I provide the it infrastructure as a service provider. And then the CDO is C D O is taking that role with the data and analytics. We'll wait to see how it falls. >>Well, one of the, one of the sort of sea level question I think was about two years ago, the garden forecast, the chief marketing officers would spend more than CEOs by 2017 on it. Are you seeing that really happen? >>We're definitely seeing that. Um, the business side, the CMOs, the VP of sales, the chief operations officers driving much more of the decisions around analytics and data. The other thing that we're seeing is, um, and I think IDC actually quoted this is the rise of the profession of data science. It's outpacing the rise of it. >>Yeah. I mean in terms of growth rate we presume interesting or Harriet really appreciate you coming on the cube. We gotta we gotta leave it there. But last question is sort of, when you think about insight 2015, think about all the, the developments that have occurred over the last say four or five years. So how would you sort of summarize where we are today? What's the bumper sticker on insight 2015 >>the bumper sticker on insight 2015 is as its name in first insights to outcomes. You talked about big data five years ago. We're really shifting from being data hoarders and worrying about what the, how much data we have and what type it is to being insight hunters, which is how can I get the insights I need to make a difference to the, >>and that's where the business value is. Harry, thanks very much for coming on the queue. It's great to see you. All right, keep right there, buddy. We'll be back with our next guest right after this. This is the cube. We're live from insight 2015 in Las Vegas. We'll be right back.

>>Live from the Mandalay convention center in Las Vegas, Nevada it's doc cube at IBM insight, 2014. Here are your hosts, John furrier and Dave Volante. >>Okay. Welcome back everyone. We are here. Live in Las Vegas for IBM impact. This is the cube special presentation at IBM insight inside the digital experience. IBM insight go. Social media lounge. Uh, the social media gurus are here. John furry with David. Um, that's playing off the joke. We're just sharing on Twitter, but seriously, we're here. If I didn't see this on the noise, my coast, Dave latte, next guest Marsha Cola year. Who's the managing director of impact ingenuity at Marsha Marsha. Yes, that's your Twitter handle is awesome. Welcome. Welcome back. Welcome back. >>Well, thanks. It's thrilled to be here. >>So we were just joking about Halloween and we're going to be a social media guru. It's a little bit of a meme going around the internet. I mean, there is no social media guru. I mean, you can't really be a guru with developing technology. You can be a practitioner. I mean, I mean, guru, what is a social media? What is a social media guru? This, >>This is where, because I offered that. I would answer any question you ask me, you can ask me those things. Sure. Well, I think that's the problem. I think that's why it'd be a fabulous Halloween costume. I'm going to think about doing that one too, because people seem to be know to these folks. So following them to the ends of the earth, because of something that they sit on, social media, I mean that, that's a kind of a scary concept, but Google glass >>As well. I mean, I mean, I'm not going to go there. Um, but let's talk, let's go in into that, that theme. I mean, honestly, you know, Jeff Jonas was just on he's awesome. We always get in the weeds. He's a fun character to talk to, but he's super smart as we're on this G2 thing, observation space, but we're all internet of things, right? I mean, it reminds me of that book is to read to my kids thing one and thing two, you know, we, all things we're all in another thing. So what do you see as that impact to, uh, this digital transformation where not only are the humans connected to the machines, the data that they're exhausting or sharing or streaming, but the machines are connected and collecting as well. How is that going to change? What's your view on all this? >>While I have been in the technology sector, most of my, uh, most of my life, uh, and I appreciate and enjoy the technology. I never lose sight of the fact that this is about the people it's about us actually working together of actually learning together, doing whatever the hell it is we're needing to do. So if all of my appliances are actually then taking care of the mundane, if my water softener system is actually getting the water put in and getting delivered on the right day, you know, all, all the better. If the, if the toaster is alerting me to some sort of news, I'm thrilled. I love the idea of the technology. Actually being able to take care of all that stuff that we never wanted to do in the first place, but the technology has been so lousy over the last couple of years, actually forever, uh, that we've had to do this stuff because the technology isn't doing it for us. >>Sure. I was a patient out in the customer space because that's, you know, that's more of the home example, but even business now seems to be early innings. I mean, people are kicking the tires. You know, we've talked to all the gurus coming up here who are the tech side, IBM and customers. And the reality is we're all pro data, which we all kind of see that obvious social data and, you know, big data analytics, certainly helpful, but this transformation people are now really changing how to operate, operationalize their business with it. It's a huge daunting task and it's scary. Um, some people are like, whoa, I don't want to do it. Or, Hey, I'm jumping in. I'm cool. Is there a cool factor? Is there a scared factor? What's your, what's your observation from mountain talking to everyone out in the, in the marketplace? >>Well, first I would, I'll totally bash the, the idea that this is only a consumer play or that it doesn't apply to businesses. Think of all the, uh, the mundane and ridiculous things we have to do at work because they're not being taken care of us. We aren't taken care of for us by our desks. If you want to look at that way or our computers, I loved hearing about the, the new, uh, uh, pairing of, uh Wayblazer and, you know, Watson and the idea of the travel being taken care of us, what we discover because of the data that we're putting off each and every moment is their systems around us all the time that actually know our preferences, know how we would be handling this, but yet they don't do anything about it. So the idea that we can actually move forward in that way should be just as applicable to our business. Uh, a manager should not have to actually be asking some of the questions that they're asking the HR department is need to be asking how you're doing. It's evident by all the things that you put out into the world. And by just actually attending to what's going on, we have a huge opportunity to get back all that time that we've been wasting all these years. I'm just a stupid >>And just to what's. So what's the bottleneck is a fear security, oh, we don't want privacy. Marcia will get offended. If we tweet her, she knows that we know that she tweeted that. I mean, that's, that's a concern. People have, it seems to be, is it? Yeah. Well, look, go back up, >>But why is it a concern? It's because the people who've been doing it early are doing it horribly. I mean, they're doing it in not respectful ways. There isn't actually a real thought about how would I be okay with this doing? And then those are we're. So ahead of the curve, maybe because of the guru status, some of these social media, maybe that maybe that's the reason, >>Just look at the government, they were big data gurus and they screwed up that that whole Snowden thing was all like, Hey, just ask us, we'll give you our email addresses. You can search my email, have a nice day. >>It's a very different message. It's a very different conversation. It's a very different question. It's a very different level of respect that we have from one person working with another. I'm actually talking with people as opposed to at them. And instead of just making assumptions of actually participating, I mean, the idea that engagement is goal just implies that we haven't been engaged all these years. We haven't been thinking we haven't been doing, I haven't met. I personally, haven't met a really dumb person. It, you know, and years, and yet everything I do at would imply that we're, we're too stupid to be able to really think and act and, and be thoughtful about it. >>So you're an influencer. Um, you're out here in the digital sphere and you are, you're hearing influencer. Um, I mean, whatever you define it. Well, it's, I guess if they say so, if you are a VIP influencer, we'll go with that. Um, >>Digging on your Twitter stream here. Fantastic. >>Working on it. So share this law, you know, we'd love, we'd love to hear your stories cause you last year you were awesome with the cube. We'd love, love JV. Give us the update. What's going on with, sorry. We started together Ted at IBM conference. You super busy. Um, what's going on share with the folks out there. Some of the things you've been even into what your what's working show some, you know, some stuff that didn't work, what's going on, what's happening? What are you, what are you doing? What are you worried? All right, >>John, if you're going to ask them, I'm telling you you're really, if you're really ready, Don Damian, probably a little after I saw you last time after I was visiting here that, uh, our world's falling apart. And if all of us actually don't get on that. If we don't actually start figuring out how to use the precious time we have the, the precious money we have, the, the roles we have in our organizations, the resources at our disposal, our brains for good, not evil. I'm not so sure about the world that my son is going to be inheriting for example. And, uh, I'm, I'm at a point in my life where I realize, I, I know a heck of a lot in the world. I have a lot of skills, everybody. I know. I look at these people around me having tremendous skills. And instead of us just sort of churning out the butter one more year, uh, we best, we best be thinking about what can I do given what I have of my time and my resources, my skills, or whatever that is and apply that to what I have influence over and be able to make as much difference. >>Are we talking about God's last offer here, the sustainable world, or what's actually on all? >>Oh, you're not at the time that the timing is perfect too. If you think about it, don't seriously. >>What are we talking about? The deterioration of our planet? We're talking about social condition. Yes, >>I, well, I mean, I can go on and >>On about money return. I can, I can entertain for hours. You just made. The comment >>I made is that no matter where we look, that that scientists have pointed out that we're past the point of no return with our climate. We, uh, we look at the, uh, at the deterioration of the planet around us. I happen to live in the woods and I mean, deep in the woods and you can, you can see the change of how much rain is coming down. That didn't, I mean, I, I'm not, my intent here is not to talk about all the, that the problems around us. We all actually feel them, even if we're not acknowledging them, what I see is the wasted opportunity of us, not actually, re-examining what we're choosing to do and figure out how, whatever it is we're capable of doing could actually be helping instead of bringing it up. So how should people, let's say, people want to know that's good, but I just wanted to frame it. So let's >>Take people want to, so let's say that resonates to somebody in the audience. What should they do? How should they start pick a passion? And they >>Have, um, I mean, I, my, my approach to all the change work I do and have been doing with corporations for the last 20 years is actually not additive. It's not asking the question. What more could I do? Because that's usually what keeps people from doing it. I asked the question, what's keeping me from doing what I've always known needed to be done. So in, in our communities, you know, my experience is everybody knows who it is that could use some assistance, not in a handout sort of way in a reaching out and caring way of asking of, of having a conversation, a participating, and to be able to step back and ask that question. What's keeping me from doing that. We know what needs to be done, but we're not doing it. So how can I say, oh, well, what's keeping me from doing it. I don't have time to do it. Okay. Well, what can I do to actually just get a little bit more time to do something that matters in the world? So that that's the most, very, >>Very basic level. It could be slowly be that it's, >>It's less Twitter. It could also be a re-evaluating how much time I'm spending at work on stuff that could be automated. I mean, going back to this whole conversation about automation, it is to ask those questions. What I can do. That's just about time. Um, >>I, yeah, that is one of the biggest objections I don't have time. Right? >>Yeah. So what I find is when I talk about, uh, global health actually, is that when we look at the idea of health, not as in just exercising more or just eating, right, we're talking about fiscal health, we're talking about, uh, creating a world that is just, uh, a healthier place. When I ask people those questions, most of them can say, well, yeah, this isn't, this is important to me, but I don't know what to do about it. So one is, as you absolutely said, is finding, finding those passions and be able to figure out what you're going to do. But more importantly, to ask yourself that question, when am I going to do this? If not now, I feel like I'm, I'm falling. Like I, uh, I'm Mike is falling out. Let me, let me get that. >>Well, we chit chat a lot of hair. Yeah. Yeah. So I think, okay. So we're talking about different ways to find time. >>Um, Dave, I mean, I think it's a great time. I mean, the passionate thing, passionate thing is where the keyword is contributing, right? So like, I think it's a good time because I have, we, I, we both Dave and I both have four kids. So we see the new generation in their minds all the time because we're driving around, but they're impressionable right now is the old expression is you can grab the play though, and you can shape it. You can act, we can actually, as leaders and mature experience, instant people that have some skills in computing, we can influence like stem. We can influence women in tech. We can influence computer science curriculums or get influenced modern society because the new generation is coming in and they're natives, they're adopting and they're thirsty for leadership, but I don't think that they're seeing it. So I think there's really a good time. You've seen the Kickstarter crowdsourcing stuff is really becoming a part of this new tribe. So I believe the gravity around making things happen is participation, collaboration and data. Data is knowledge, endorsement, social proof. These are concepts that are easily transferable. If you can just, if you just wake up and do it. So I think, you know, >>If you just wake up and do it everywhere about, so Y Y if you wake up every day, why aren't you doing it today? >>We have Craig brown on earlier, he's doing $25,000 investments for kids to start companies, you know, whether the inner city kids. And that's pretty cool. I mean, so, you know, this is, this is the democratization piece, but in a connected network, it's frictionless communication. I mean, hell Twitter, overthrew governments. So you can have solidarity, peaceful solidarity as well as other rev revolution. So I think that's a very doable thing versus just checking the Basel. I volunteer to do something. And I think that has been more of like a peace Corps. I helped people. >>Uh, and I'm personally, I asked this question of everybody that I asked her, actually asked two questions of everybody I work with now. Uh, one of them is what can you not do? What can you not, not do actually. So if you, if you think to yourself, if I look back on my life, if I look back on my life, what is it that I thought to myself, oh, I didn't have time for that. Or I couldn't do it. You we've all heard that, you know, what do you want on your tombstone? However, that works. But I find that everybody, I know, think it has a burning need to be doing something useful in their lives. It's not just mission driven. It absolutely. It's a purpose. It's a connecting with, with connecting with people who are helping to move the world forward. And I just stopped. And I said, even in a business context, I say, you know, now it's time. We're kind of out of time. Get on with it, >>Please. The clock is ticking. Well, Jeff Jones was talking about the asteroid thing to geospatial smart geeky conversation. But the key thing out of that was better focus of finite resources. And that really comes down to the fundamental better decision-making. I mean, we, my wife says, so our kids will make better decisions. I mean, that's a mother talking to the kids, but that's our life now. So like, if we can make better decisions, that ultimately is the big data opportunity from social change to play to business. >>And then the second question absolutely, absolutely agree. Everything you said. I, the next big question I asked is what are you doing to improve the world? Now? I would say 50% of the people I say, just give me this completely deer in the headlights. Look, what do you mean to save the world or to improve the world, to change world? However you want to frame that. But I haven't met anybody in years that isn't interested in truly contributing, leaving the world a better place than they came into. And that's no matter what their, their demographic makeup is. That's no matter the community they live in, no matter what they're doing, people have a fundamental desire to do better. And so I asked that of every business person, every corporation I work with. And that's one of the things I love about this whole idea of, you know, building a smarter planet that should tie to every single thing we do. And, and when we lose sight of that, we see that, no, I think >>This is a really great conversation to have because it's, it's something that's emerging. And, you know, again, there's some obvious examples, oh, pebble watch crowdfunding. But if you look at really impactful things like open source software, you are seeing the playbook. I mean, the playbook is, you know, people can participate at any level. So the, the fear of getting this kind of group going is that I'm too busy or, you know, you can, the contribution doesn't have to be game changing for an individual could be one small piece of the puzzle. It could be small contribution. Someone might do more heavy lifting than the other. That's an open source concept. We've seen that work huge. A lot of leverage, a lot of participation. Um, so I think that's something that I really haven't seen get applied to at a large scale. I mean, you see the protest in Hong Kong are interesting. That's an indicator. What does that mean? Right. So what's your take on all? What do you think needs to happen to get more people tied into these shared missions? >>It's a little little over there off >>The ranch. A little bit more honesty. More honesty. Yeah. Yeah. I mean, not, not something that we talk about these sorts of events is that I I've gotten to the point where I do these large talks in front of thousands of people. And I ask everybody to turn to the person next to them and introduce themselves, honestly, like, why are you here? And why do you care? We've all gotten so wrapped up in the >>Who we are as well. And that's why I say, I love the idea of you being >>A social media guru for Halloween. It's just become, so it's so about the role that we've lost the connection with our humanity. And so I just, I asked people just to step back. So it's as simple. So yeah, I am all for the large initiatives. >>Yes. Self-aware is a really interesting concept. And that really what you're talking about here is, I mean, I make fun of myself. I put that out there. Probably gonna get some hate mail for that tweet, but no, it is what it is. I mean, I'm making fun of myself and us because we have to, because it's really not moving fast enough in the writer in my mind, at least I think, I mean, I think social media is a real, real game changer. I'm pro pro social media, but I mean, come on, if you can't make fun of yourself then, >>But what is social media do you mean? What is our untapped desire that why we're all participating in social media, where we've missed the opportunity for all these years to be human in everything that we're doing? Yeah. I mean, the idea that you can be, you know, wherever you are and be able to reach the people who have answers to be able to help you make better decisions is something that we've had that desire for a very long time. We've just been, not able to do that for so long that it's now it's time we get on >>With that. I would do the cube to Dave and I talk all the time. We want to broadcast out the data because I think people want to be part of something. And I think at the end of the day, it's human psychology is that being part of something makes psychology of the soul work better. It's like, okay, I want to be part of a group. I want to belong. It's a yearning, it's a tribe. Whatever that kind of collective group is, whether you know, the clown or the, or the guru or whatever, I think that's a people are yearning for that collectiveness of Griff groups. And I think the data gap is gravity. Like how do you a joke? It could be a serious conversation. It could be something provocative. I think content is a nice piece of gravity to kind of bring people together versus, you know, tweeting, Hey, look, how big I am. I got a zillion followers. >>Okay. So let's back up though. So content, so we can talk about the, the, the, the, the concept that has content. That's a lovely thing to do at a data conference, talking about the content it's about things we care about. That's what content is. So if we take that a step further and we actually extrapolate and say, how does this impact me? It's not because it's content it's because we're talking about topics that matter to each of us. And so the more we get back to that sort of conversation, the more we get back to that sort of point, I think we have a bigger opportunity to have conversations that matter and not be able to be. We are wasting our time doing the silly stuff. >>Okay. I'm getting the hook here, Marcia conversations that matter. That's really what it's all about. Changing the world. Thanks for calling the cube. Great to see you again. And, uh, we'll be right back after this short break live in Las Vegas date, you continues wall-to-wall coverage here, inside the cube, inside the digital experience in psycho with IBM social lounge. We right back after this short break,

>>From the Mandalay convention center in Las Vegas, Nevada. It's the queue at IBM. Insight 2014 here is your host, Dave Vellante. >>Hi, welcome back to IBM insight everybody. This is Dave Volante with John furrier. We're here with the cube. The cube is our live mobile studio. We go out to the events, we extract the signal from the noise. Carla Gentry is here otherwise known as at data nerd. Carla, great to see you. Welcome to the cube. You are a data scientists. Do you have your own company? Um, we were just talking to, uh, to dr Ahmed Bouloud from a university in um, Istanbul and he said, well, it's data science. It really, really isn't a such thing as a data scientist. And so he and I are arguing a little about it. So I said, come back and see Carla, right? You're a data scientist, right? >>Well, you know, right out of college I started with a RJ criminal associates up in Chicago. And um, that that's what we all were a bunch of data nerds in there playing around with terabytes of data before anybody even knew what a terabyte one terabyte was really big. Right? Right back when the terabyte was big data, but a, you know, gleaning insight for a discover financial services. And then, you know, I've worked with consumer packaged goods, the education, I mean it's, it's been a wonderful, wonderful career. And what's so great about this is to be able to walk around and see how much data is a part of more people's lives now than it was 20 years ago. I mean, 20 years ago you couldn't have, you know, gotten thousands of people together talking about data analytics. Well, you know, the interesting thing about what you're saying without you, you CPG education, financial services, John and I talk about this a lot, how the data layer is becoming a transport mechanism to connect the dots across different industries and data scientists. >>You guys don't like to get locked into one little industry niche. Do you you'd like to gather data from all types of different sources? Talk about that. Well, that's the thing. Uh, unfortunately, uh, we get bored very easily because, you know, we like to have our fingers in a lot of different pies. But, you know, you wouldn't want to be necessarily siloed with just one kind of information because curiosity makes you think about everything. Education, risk, you know, I'm that way. I have no walls. You know, I can, I can glean insight from any type of data. If you've got a database, uh, we can jump in with both feet. Is data is data and why is the data more transformative today in this day and age, you know, circa 2014 versus say, when you came out of college, why is it that everybody's talking about data that data is able to, to change industries, transform industries. >>What's different? Well, now the, you know, data can actually give you, you know, an insight into your customer mean, you know, what is your customer buying, you know? Um, so when you go to, you know, run a campaign or something like that, you, you're not shooting in the dark. You know, you're actually, you have a face to your customer. So you know, you can make decisions and it's not just marketing, you know, which is what I started out in, you know, trying to do increase and lift, you know, sales. But now you know, you have risk, you have, you know, data breaches. You have, you know, what keeps CEOs up at night, you know, it's not only the cash flow, you know, it's the mitigated risk that's involved. And when you're looking at your, your data and you're collecting this information that gives you a view into what's really going on so you can sleep at night and have a little bit of comfort mostly, >>well not sleeping at night, it's a couple hours of sleep. The notification when I opened CEO's and CIO's, CFO's, chief data officer, you've seen much more formal roles around data where data is real key asset. And this is awesome because it brings to the forefront the role of data. And so I want to get your perspective on this. You brought into the kind of the, kind of the trajectory of where we've come from, um, and talking about the role of software because really what this highlights here at IBM insight is okay, it's not just data per se, you know, how software that's a key part of it. So it's now also an integral part of the platforms. You have a developer angle, you have the data asset, and now you've got this real time in the moment experience. And IBM is talking about engagement a ton here. And so what's your take on all that? I mean it's, it's exciting. Certainly if you're in the data business. >>Well definitely, I mean, real time data, of course it's very expensive. Um, but it's, it's more attainable now than it ever was. Um, the thing is now is you don't necessarily have to be a data scientist to be able to go and get at your data. I mean, thanks to software tools, you know, like IBM, they give you that benchmark, you know, the, these tools, uh, where you can use BI and things like that. To be able to get a view into your business. And you know, it's not just for, you know, your analytical department anymore. Um, so I think it's what it's done is it's actually made it more attainable now. You know, it was like people looked at data wagon back then, Oh, and it was so scary, you know, but now it's, it's bringing it to the forefront to where we can make decisions. We can want our bitter, our business better. And like I joined forces with a repo software years ago to look at the supply chain. Now when you talk about that, that's what keeps the lights on. But you're only as strong as your weakest link. So when you're working with third parties, you have to make sure that everything is going smoothly. So >>I want to get your take on a couple of things in. He chose SA was on earlier and she's an awesome guest. She's been on many times. She's dynamic and articulate and super smart, brilliant and beautiful. We love talking with her. She said, I asked her what are the top three customer issues? And kind of a double edged question. She said three things, customer experience, operational assets, AKA the supply chain, and then risk security and governance. And then we weaved in context computing and then cognitive. So let's break that down. So customer experience, internet of things is a data play, you know, probes and sensors and machines certainly get that >>analogies. People are things. Yeah, well you know, here's the thing that you think about. Data. Data is a person that record that you have in that database equates to a real live person and you want to, you know, you're not going to be friends with your, your customers, but you want to know more about them so that you can serve them better. Um, you know, for me the biggest thing is, you know, people will go out and spend millions of dollars on a database but not necessarily know what to do with it. So it comes down to what question are you trying to answer? >>Yeah. And the infrastructure piece is interesting because you want to have that agile flexibility, which is kind of a buzz word amongst vendors. Hey, be flexible. But there is meaning behind it. Right. So context computing is relationships across entities. The streaming stuff is very, very interesting to me because now you have streaming data coming off of devices and again brings up the real time piece. So making sense of all this means it puts it in the forefront. >>And what you can do with that data is if you do have a client or a customer and you let them link in socially, like log in through Twitter or LinkedIn or Google, Facebook, now you can append that social data. So now you, you've got an ideal, you know sediment and you know when you're positive you it's first party data. Yeah, exactly. The Holy grail of active data is first party data. Exactly. >>Cause we'd love the crowd chatting and love people. The logging in and, and thanks for, by the way, for hosting the crowd chat with Brian the other day. It was really fantastic conversation. My pleasure. Let's talk about cognitive because this brings a human element of it. And one of the things we've been teasing out of the past couple of shows we've been at around big data is the role of the developer where the developers in the old days from even going back to the mainframe days, cold ball, they were adding in these rooms, almost like almost an image of coders in the back room coding away. But now with the customer experience front and center with mobile infrastructure, the developers are getting closer to the customer experience. And so you're seeing more creativity on the developers side with the use of data. Could you share just observation, anecdotes, things you've been involved in that can tease out where this is going and how people should be thinking about it? >>Oh, do you know 20 years ago if he tried to show someone and graft with, you know, 16 different things at one time going on, they were like, that's messy. Now you can actually find the sweet spot or where everything interacts. So you know, when you're talking to an artist, a digital artist who's working with data and giving that picture, that's exciting for me. And going back when we were talking about cognitive computing, when you're talking about the Watson on ecology, that's exciting. Yeah, that's the highlight of it's almost magic. It's almost like black magic, this Watson stuff and people are really just now getting their arms around that and that is essentially making sense of the data, but that's the thing. See, it's no longer magic now. That's what they thought 20 years ago. Poof. People like me, they kept in a little closet, you know, and then our office and they only came to Moses when they needed something. >>Now we're an integral part and we actually are in the business development meetings and we're a liaison between the it department and the C suite. One of the, one of the things that it's interesting about your role as not only you out in the field doing some great work, you're also an influencer here at the IBM influencer program, so I want to get your take on this balance between organic data and kind of structural data. Organic data means free forming unstructured data and then existing data that comes in that's rigid and structured because of business processes. And I get that is data warehousing business has been around for years, right? It's intelligence, it's all fenced in, all structured. But now you have this new inbound data sources coming in, being ingested by these large systems, data changes the data. So you now have a new dynamic where latency, real time insights, these are the new verbs, right? >>So talk about that role, the balance being organic data and the structure data and what the opportunities are. Well, the wonderful thing about, you know, now that unstructured data was scary way back in the day. So now it's not so scary, you know, now we can actually take this data and make business decisions, but uh, you know, like social data and things like that. When you can add that in a pin that and get to, you know, what we all want is a better view of our customer and to be able to, you know, do better business with them. Like, um, like supply chain management and things like that. I mean you're, you're looking at open people, you know, collecting information from varying sources and this all has to be put together. So I think they mentioned earlier this morning how 80% of it is we're data janitors cleaning up this, that and the other. >>Whereas what we really want to do is, you know, glean the insight from it. But I think, uh, the tools these days are making that much more easier no matter what the source is that we can actually put it all together, what we used to call the merge Burj back in the old days. It takes weeks to do the merge purge and yeah, who all here knows what a DLT is trying to solve this problem for a while with traditional technology 17 years. So let's talk about, you know, the, the promise of BI and the traditional data warehouse 360 degree view of my customer, real time information. And that's what it's about. It's about drilling down predictive analytics, all these promises. Did the data warehouse live up to those promises in your view? Well, initially, maybe not, but you know, things are, it just seems in the last few years that people have had an epiphany of how this is really adding value to their company. >>Now back in the old days, they all knew that, you know, insight is wonderful, but now you can see it visibly showing signs actually making a difference in company so they can keep an eye on everything that's going on. Now, going back to what keeps CFOs, you know, up at night with the risk and stuff, there's still always the risk, but at least now you can get a little better handle on it. And thanks to the age of technology and the data that we have accessible to us today and the tools we have available to us today. It's, it's made a dramatic change. What are the technology catalyst? Is it do? Is it no sequel? Is it, what are the, what are the tools that are sort of the foundation of that change? Well, I think always the, you know, the new tools and making it so that you don't have to go out and learn SQL. >>You don't have to be a programmer, you don't have to, you know, go to college for four years and learn mathematics and engineering to actually be able to work with this data. So thanks to, you know, tools like had it been other tools. I mean you can really sit down and glean insight without having to write one single line of code. So the things we're getting some questions in the crowd chats, um, um, at furry, at data nerd, what are the key things that are messy, scary right now for CEOs and CFOs? So things are becoming less scary. What is the scary things right now? Oh, the scary thing is the breaches. You know, when you hear about target and these big names, you know, people getting access to your, your credit card data. That's, that's scary. So, you know, we've got to really try to lock down that risk, you know, and I know everybody's scrambling scratching their head, figuring out how we're going to keep these breaches from happening again. >>Yeah. Big data solves that. I mean you have big data technology, which is a combination of machine learning, streaming where you're getting massive surges of data coming in to these ingest systems where you can apply some reasoning to it, some cognitive, some insights to look for the patterns and that's where machine learning shines. Um, how do you see that aspect of machine learning and these new tools affecting that kind of analysis? Will I see it opening up a lot of different doors for a lot of different people and making a difference because, uh, you know, everybody knows that data is important, but not a lot of people know how to deal with it, especially when it gets into the zettabytes of data. When you have tools, you know, like the IBM tools that can handle this type of load and be able to, to give you, you know, instantaneous information. >>And, and like what we saw this morning where, uh, like risk, I mean an oil and gas industry, you know, you, you have to worry about, you know, as someone going to get injured on the job and they showed the the center, whereas she walked toward it, it went off. I mean the internet of things, being able to let us know in real time if there's a danger, you know, to personal life or to your database and then predictive to be able to say, well this is what we think is going to happen in the future and to be able to move and act on that. It's a very exciting time. You mentioned IBM, so obviously is a leader in here, >>Jeff Kelly's report shows IBM is the number one big data player. But big part of that is IBM. So big, right? >>Well and you guys were around a long, you've been around a long time. You guys were playing with big data way back before. Big data was big data. So yeah, we guys, us guys, yeah, well social, social data, >>those guys, right? So we're not all right, but so, but, but so you bring up IBM, a lot of people have a perception IBM big, hard to work with, but you're, >>but that's changing. So talk about that change. What I'm excited about is the Watson's analytics. I mean that in itself right there and made me sit up and, you know, get excited about the data world all over again. You know, to be able to excite you about Watson analytics platform? Well, I really like, uh, the, uh, the oncology, uh, Watson, um, they had the, the one for the, uh, not necessarily for the police, but for the, uh, the crimes. I mean, in real time, if you can see that a crime is about to happen and you can prevent it, or if you see someone's health is failing and you're able to step in. And that's why over there, earlier I was talking about IBM cognitive abilities can save lives, you know, so I mean, my, my mom passed away from cancer, so, you know, the, the, um, oncology Watson was very exciting to me, but it's gonna make a difference. And I think the thing is now is that how it's changed is to make them user friendly where you don't have to have a data scientist or an analyst to come in. You know, they talk about how expensive data scientists are. Now the reason I opened my business was to make it affordable to small businesses, you know, so although you know, people look at IBM and think it's scary, I think they're going to see now that the, the direction that they're moving is becoming more user friendly and more available. >>So Carla, I wonder if you could talk about how you engage with clients. So you mentioned small business, right? Cause you have a lot of, a lot of businesses, small midsize companies don't have the resources. Right? Um, so where did they start? Did they start with a call to you and, >>well, uh, most of the time it's a call where, you know, we spent all this money on this database and we still can't get what we want out of it. So it comes down to what question are you trying to answer? I think that's the most important thing because that directly deals with what data that you need. And if you don't have it internally, can we get it externally? You know, can we go through open source, can we get census data? Can we get, you know, work with hospitals and doctors and things like that and use this to be able to feed this information into them to make a difference. >>So what do you do? I mean, are you so CEO calls up small companies, is that got all this data? It's unstructured. I get some social data. I get my customer data trying to make sense out of. I'm trying to figure out, you know, who's >>ready to buy, where I should be, you know, focus my products. Uh, and I got all this, this, this date. I don't know what to do with it, but I know there's some gold in there. I know there's a signal in that data mining, right? So how do I get it? How can you help me? Well, it's gap analysis. First off, I would come in and I would sit down and first of all, I need to see what variables you're collecting. Uh, if you're telling me you you're collecting your name, address and phone number, but you want to do a predictive model, we can't get that. So, um, you know, the question that you want to answer is, is most important? Are you wanting to increase your sales? Are you wanting to get your, to know your customers better, to be able to service them better? >>Like in the healthcare industry, you know, you really want to know what's going on health wise, you know, so, uh, I sat down with them when we do a gap analysis, what are you missing? What do you have? How can we get it? What do you want? Where are you at? Yeah. And here's, here's what you have, here's what you're missing. How do we get at that? And that's oftentimes starts with data sources. Exactly. So then you go get the data sources and then more than what you do, well then we merge it back in. And here's the thing, you have to have that way to connect them. You know, the relational databases will always exist to where you have, you know, client information here and you've got other information over here and you have to always bring that back together. So, um, you know, it's a wonderful time. >>You're a data hacker in a sense, right? Is that fair data nerd in a complimentary way? I mean hacking is about exploration. Yeah, exactly right. So I mean, so you have the skillsets as a data scientist to pull all this data together, analyze it and well, you're going to bring in an external source and then when you bring it externally, you want to make sure that you can match it back up. And now that's the important and without a unique quantify or how do you do that? And that's why when you see databases with all these little arrows and everything pointing to where things belong, I mean we have to be able to pull that in to make decisions. >>Yeah. We were talking with frons yesterday to another influencer. We were talking about this particular point. He was ex P and G back in the day, which is very data-driven. Of course, they're well known for their brand work and certainly on the advertising side, but they're, they're quant jocks over there. They love data. Their data nerds over there, they're kicking out on data. And he used to say that the software would cut off data points that were skewing way outside the median. And so they would essentially throw away what are now exploratory points. So this kind of brings up this long tail distribution concept where, okay, you can get the meat of what you want in the head of the tail and distribution, but out into the long tail is all these skew data points that were once skew standard off the standard deviation that are now doorway. So, you know, we're old enough to know that that movie with Jodie foster with contact where they, they find that little white space, they open it up and there's a, a huge puzzle. That's the kind of things that's happening right now. So exactly >>the same thing. Well, yes, yes. I mean, you know, the thing is, uh, you know, a lot of people don't necessarily have the information that they need. So they're seeking it, you know, when they're going to what Avenue, where, where do I go to get this data? You know, and thanks to open source and things like that. You, you know, we've been able to get more information and bring it together than we've ever been able to do before. And I think people now are more open to analysis where it's not necessarily a dirty word. It doesn't necessarily mean you have to go out and spend $300,000 a year to hire a data scientist. You can sit down, you know, and look at what you have and uh, someone else mentioned that. Take the people that you have that know what's going on with your company. You know, they may not be data scientists, they may not be analytical, but they have insights they have. >>There's more of a cultural issue now around playing with data and an experimental sandbox way where you don't need to have the upfront prove the case. And then pre prefabricated systems you can say, I'm going to do some stuff in jest, for instance, bringing in data sources and play with the data. >>Well, and you mentioned, you know, outliners I mean everything when, when you look graphically at data, you expect everything to fall within this little bubble, this, you know, this thing. But when you see, you know, all these outliners going on for me, usually that means a mistake. Okay. So, and if it's not a mistake, it's something that calls attention. So it's definitely not something you just want to toss aside >>talking about creativity because creativity now becomes, you know, uh, uh, an aspect of the job where you gotta be creative, where it's not just being the math geek or being super analytical and you have to kind of think outside the box or outside the query, if you will, to do the exploration. What's the role of creativity in the new model? >>Well before, I think that we always thought of ourself as just being, you know, matter of fact, you know, just the facts please, you know, but now, you know, you can look at things visually and see, you know, and it is an art form to be able to find that sweet spot in the data. And um, you know, before, you know, years and years and years ago when you would take something like that to a CEO, he would say it was messy, you know, so now you get that creative side where you can actually make things visually attractive. And I think that's important to people too because it's not just data, it's the way you present it. >>It's also the mindset of understanding MSCI is a good start, start with messy and then versus getting the perfect answer. As we were saying, using it with pop-up Jana earlier about, don't try it at the home run right away. Hit a few singles. He's in the baseball metaphor given the world series going on. So totally awesome. Um, but I want to get your final thoughts as we wrap up the segment here on the practitioners out there. What's, what should they do? So there's an approach to the job now, right? So there is a shift and inflection point happening at the same time. What advice would you give to folks out there who say, Oh, I love Carla's interview. I want to do that. I just don't know where to start, what to do. How do I convince management I want to be, I want to get going. What do you, what would you share for advice? >>Well, I'm sure it's the platform. I mean, you know, think about the foundation of a house. Now if you have a strong data foundation, you can build on that. It's just like your house. If you have a weak foundation, your house is going to tumble down. So if you have a strong, you have a strong foundation or with your data and everything is built right now. When I say built right means, what are you trying to do? What are you trying to accomplish? You know, if it's risk, then you need to be, you know, looking at those, those factors. You know, how many people have been hurt? How many of you people been injured? You know, how many people died? You know, I mean, how many breaches do we have? You know, so it starts with the question, what is it that you're trying to accomplish? And then you go from there and collect the right variables. So don't wait, you know, a year later and call a data scientist and going, I've spent, you know, millions of dollars on this. I'm still not getting what I want. So think about an initially in the setup and you know, be involved, involved your analyst, involve your data scientists, make sure that they're in your business meetings because we're the liaisons between it and the Csuite. >>Yeah, and that's the key roles team as a team, that person really is collaborative. We heard from a med earlier pair programming pair, not pay eggs in an accent, pair programming, work in pairs, buddy system. This is really a true team effort. >>Well, I always said, you know, I am a team of data. Scientists can write programs, we can glean insight, but the team part has to come from working with it and working with your C suite. So very much agree. It's definitely a team sport. >>Carla Gentry, owner and data science analytical solutions influencer here at the IBM special presentation and second experience, second screen here in the social media lounge. Really doing a real innovative social business. Again, activated audience, you're an influencer, but also you're really a subject matter expert. Thanks for coming on the cube. Really appreciate and thanks for hosting the crowd. Chat with Brian Fonzo is really good content now. This is the cube. We are live here in Las Vegas. Extracting the ceiling from the noise, getting the data and sharing it with you. I'm John Frey with Dave a lot there. We'll be right back after this short break.

>>Live from the Mandalay convention center in Las Vegas, Nevada. It's not cue at IBM insight 2014 >>you're all your hosts. John furrier and Dave Volante.. >>Okay. Welcome back everyone. We're here live inside the cube at IBM insight. I'm Sean with Dave Volante. We go after the events, extract the signal and noise. We go wall to wall covers what we do here. I don't, of course we're excited to have awesome gas. We talked to the executives, entrepreneurs, but we get the media stars in here. Uh, Katie Lyndon doll. Welcome to the cube. You are with CNN, the today show. You're the tech correspondent and you get a lot of energy. I could just tell this is going to be fun. It's been fun to hear the last few days. So I mean, Watson is the geeky story of any what, what are you seeing? Let me get the wife in a second. But outside of Watson, what's the coolest thing you've seen? >>I'm constantly on the hunt for the latest innovations in technology and I think that's probably the best part about my job. And always chasing down high level stories. I recently just came back for a dive with NASA. I learned that NASA astronauts actually train underwater to simulate microgravity and I'm like, Oh my gosh, no way. And they're like, do you want to come down to the world's only Marine underwater habitat? I was like, yes, please. So went down to the Florida keys, it's an hour off the coast and was diving literally with NASA European space agency and the Canadian space agency underwater. And again, it's the world's only underwater Marine habitat and seeing how they train in everything from asteroid mining to um, underwater surgery to actually seeing how the body responds to exercise. I guess water simulates one sixth of gravity. So it was a pretty dynamic shoot. >>I was doing that for NBC news and it's just I, those are the types of stories. I, I am a diver. I actually was doing a story on big data last year and it required me to get my dive certs and the Island of Bermuda feel very bad. It was a presentation that I was speaking on here at insight a, there was all this crowdsourced information about how the lion fish, if you've ever heard of the lion fish has been, it's an invasion in the Atlantic ocean. I took all of this information and metrics and made a story for CNN and it required me to get my advanced dive certs. So now I'm getting all these dive stories cause there's not a lot of us dive reporters. So the lion fish story for CNN too. Another good example of a piece that I go after. >>So you, you bring a lot of energy. What do you see here? I mean you see a lot of stories and you get pitched stories. I can imagine that your email box flux, I mean it's like, Oh >>I have 78,000 unread emails right now. I'm not proud of that. But yes, constantly being pitched. >>I had 40,000 I'm a little bit blind. I'm going to give that to you in the today show. Not too shabby. But what do you do? You get pitched all the time and so you got the vet stories. What's your formula for vetting stories? I mean, what gets your attention and how do you go outside your comfort zone to select good stories? What your attention. It's funny, >>you know, so I've been in television for the last 10 years and I feel like now I have this internal barometer and knowing when something's very good and the scope of the things that I cover from, you know, in the past month alone when I was talking about the NASA piece and then I'll flip the next day and do top Halloween gadgets on today's show. So it's, it's very vast, but I can instantly tell and it's, it's come through experience and being in a background in technology and knowing what's gonna work for the consumer and knowing a hot product. When I see it and I I T I gotten pretty good I think at it spotting a product that a consumer is going to love but also finding a story that is, maybe it's super nerdy, but my job is to take it and to bring it down to a level that's entertaining for any kind of audience, whether it be CNN or whether it be today. >>So it says your Guinness book of world record holder, share that in little nugget with the folks in. Yes, that is a true story. I have a Guinness world record holder in the most high fives and one minute. Okay, so this probably solicit some like how the heck did that happen? I've always been fascinated with Guinness world records and I always wanted one and I've always been obsessed with a high five like I am paranoid of huggers, there's nothing that scares me more or good high five just go for the five. I don't want to bring it in and okay, it's a little OCD. I will completely aware. So anyways, I found that this Guinness world record was held by a clown in England for the most high fives and one minute. So I convinced I was hosting a show on spike TV and I convinced them to allow me to break this record. >>So we had all these people line up in the MTV cafeteria and you have a Guinness world record adjudicator come onsite, you get two tries and if you win you get a plaque in a formal ceremony. The cube before we should do the most consecutive interviews to having a drink of water. We want to just come here and we could break something able to break something or like you said, it's his official. Yeah, we started to get like real nervous and like hot and yeah, so I had two tribes. Oh I was, I was giving him a big ass big fitness person. So I was like ready. And if clown beats me at this point, it's over your careers. division. You'll never work again because I beat it on the first try and then I advanced it on a single hand or you go, there's a whole process as you can imagine with the adjudicator's she's like real intense. >>She's like counting with her clicker on the high five so I go down this line of people and it has to be over there can't be like a mailed in like you know like a high five you go for the five names and then I got a couple that were disqualified, you know like a couple didn't count because it wasn't like a full on five four so like a film replay. Super slow motion. I like argued a few. I was like no, I was for sure up on that one. The flag, it was sponsored by PRL. It wasn't but it should have been but it was fun. So I have a plaque how many? 107 heard rumors that it's been broken but I didn't care as long as I've got a plan to that plan at one point. Okay. Let's cut to about IBM because Watson is the coolest thing I'll say is pretty mainstream. >>It hits your wheelhouse. I'll see for the day I've seen jeopardy. Absolutely. Now how does that translate into a story for sure. Stuff going on here. What do you, so what's very cool about Watson? I called my boyfriend because I've had a relationship with him now over the last few years, a few years ago on CVS. I actually got to challenge Watson on a full game of jeopardy and I think that was of course the most, the most memorable part of Watson when he took on the two, you know, jeopardy champions. But so this is like a lifetime moment for me. I got a full game of jeopardy, me Watson and another individual smoked me and actually I was doing okay and then it was like tennis vocab. I was like, Oh, I got this. You know, like I've been in sports my whole life. I've been worked at ESPN for seven years. >>I got this in the bag, I was doing good. And then they were like, Oh, we had them on the low setting. I was like, all right, really? Like really? Like I was just feeling good about myself. I finished with $2, two bucks. Um, and I thought it was so cool how gimmicky it was, you know, in a healthy beach in the tennis category. Oh, you smoking, you never in the low setting for sure. I got a few of those, a few. I actually got set in Tennessee vocab. You're going to have it right. Even watching tennis your whole life. Right. ESPN is embarrassing and disappointing. And then I weighed you too much and then the double jeopardy. Anyways, I digress. So how cool is it that I got to play Watson but then now years later seeing the power in it in many different developments and most notably I work over at as a volunteer at Sloan Memorial Kettering cancer center for a small group called Candlelighters that works with individuals that come in from around the world for cancer treatments. >>Now Sloan is one of those powerful cancer centers in the world is actually using it as predictive analysis. So here and I work with these kids and I, it's very complex. When they go in for a diagnosis, there's lots of different problems that they have and really it's, it's, it's, it's, it's guesswork for a doctor now. They can put all of these things that are happening with it, with a child into a machine, and they can pump out a hypotheses. Of course, you're going to have to have the human interaction tailored with that to have the emotional side, but I had been fascinated, especially on the medical side, watching your boyfriend at this point. That's interesting. We'll get that to the world of Facebook. It's complicated. I heard rumors that he's talks back and we'll listen to this a true statement. He's a lot smarter than I am. >>I'm intimidated by that, but what's the coolest demo with Watson that you've seen besides jeopardy? Yeah, that would have, well I actually learned something new from a few developers that I met yesterday about the new chef app. So being able to go into your pantry and to do some recipe from what you have, the ingredients you have insider, I think that's a little more consumer friendly. So I was kind of like, um, I'm excited to check that one out. Looking at the tech landscape, what are you most excited about? I mean, what's the coolest kind of consumer meats like gadget, short door, tech cloud. If you could pull a few favorites at what's, what's drawing your attention? Uh, one that we actually had here that's probably popped into mind. There's so many to choose from, but in the world of Oculus rift, and the reason I say that is not for the gaming aspect, but more for the potential in the landscape of physical therapy. >>The first time I got on Oculus raft, I was actually training on a Navy boat and I was doing a segment where all my camera men were all around me. I lost track of reality and I got so immersed into virtual reality and being there and even as a huge diver, I get very motion sick and I got motion sick on the boat. Being in this physical, this augmented reality world, we're actually shooting this at the birthplace of Oculus rift. So we really diving behind the scenes into the actual, uh, software and hardware and it was such a cool, immersive experience and realize that what this could do for physical therapy or even at the dentist at a lower end, I think the capabilities for augmented reality and taking yourself out of that moment are huge. So I think that's very exciting. How about drones? >>Oh my gosh. So yes, let's talk to, and my nephew the other day and he said, do you want to see the drone that I built? And I said, yeah, it's got this four or five quadcopter. It's a quadcopter. Yup. I said, where'd you get the software for? He goes, I'll download it. It's all open source. I hacked it a little bit. I actually have several drones. Okay. Nominal. Because this blew me away. I probably have what I consider is the best prosumer drone. It's a DGI Phantom, a DJI Phantom two and I have got some incredible aerial footage over the mountains of Montana and also over a Bermuda, the Island of Bermuda. I sent it up, put it over a shipwreck, gorgeous. And for me as a flake, being in photo and video and going out and getting my own video and not having to rely on a cop, a copter for, you know, that would be thousands of dollars worth of footage or relying on a cameraman. >>I just sent that baby up. I'm like, please don't hit anybody. It's a little hard to operate when you get the one, the higher end models. I have a couple of the parents too. There are a lot easier to operate and do it right from my iPhone, but I am just like, I'm so into it now. I think it's a little gimmicky when we talk about Amazon and pizza deliveries and taco deliveries and beer deliveries with a drone shooting surprises. Texas man, what am, I don't know about that. But uh, I think it's fascinating. I think it's a really cool technology. And again, I've personally saved tens and thousands of dollars using my drones. So you, when you flew over these sites yet proximate, so you had visual concepts. So the Phantom Jerome that I have, that's my favorite one. I actually attach a GoPro to it so I can send it up and I use the gyroscope or just kind of move my GoPro around in mid air. It goes hundreds of feet high. I mean, you've really got to get a grasp on it and know what you're doing. I had it out in a field well before I took it out to an Island on a beach. But I'm not, a drive is not something you really, it's not a remote control car. Now did you build it? Oh no. Goodness. Aww, that's totally on the market. Yeah, I got it at B and H photo >>sending them out. So in San Francisco off their balconies and then they're going out to, you know, angel Island, Alcatraz, and literally they're flying out then unregulated. It's like someday there'll be drone collisions, let's say this is unregulated. This is a huge, people are geeking out with the drones. It's super exciting. Dave camera's shooting down him sending him into football venues or you know, the world series delivering packages. But mom's a streaker. I mean Amazon. I like that. Okay. So what else is new for you? Tell us more about some, some cool behind the scenes at a today's show. Any sad night live, uh, opportunities for you next been >>to Saturday night live. Oh my gosh. By the way, that's like the hottest ticket in New York to get. I've had the opportunity to go to two shows cause my friend's a cameraman over there. The rehearsal for it is like amazing. I know that's a huge digression, but talking about something to see in person, that's one of my bucket lists. Phenomenal. Yeah. Phenomenal. What else is new in New York and the scene there? Uh, Oh, we constantly covering a lot of different pieces. Uh, one, I just came back from Africa a little bit ago. I was doing a number of pieces over there from an elephant orphanage to one of my favorite pieces that we'll be rolling out soon. I did it for cnn.com and also working on a video piece of it. I went in embedded myself in the second poorest part of the entire world in the slums of Kibera, Kenya, and it was amazing to see that in these very poor areas, 70 to 80% cell penetration. A lot of people don't think that a smartphone would be prevalent. It sure is. And these kids, yeah, absolutely. There's cell towers everywhere. These kids were, you know, they don't have much, but they have e-reader devices and they can have thousands of books when they're walking 10 miles to school. You walk into the school that doesn't have any electricity, it's a hundred degrees, but they all have e-readers, Kindles right on their desk. I was blown away. I went to several different schools around Eastern Kenya. Fascinating story to be able to cover. So >>yeah, that's a really good point. In mobile penetration. If I was talking to this startup that where their business plan is to build, sell a solar battery recharging stations because they have the exact points, like they have all these devices but it's not, they don't have the traditional electricity and the parks >>one outlet in the entire school. So fortunately for, you know, with wifi off it's about a week charge on a Kindle. So it is, >>yeah, I think, I think that's a great market opportunity. Certainly in emerging countries, the mobile penetration, I'm so suites about the IBM show here. Is this your first time here or, >>I have had the luxury and the opportunity to be a part of several IBM events and everyone is so uniquely different. And this one all about developers obviously. So something I get to nerd out in myself in that is an it girl and also a developer. It's fun to be able to learn. I picked up so much new information so I just kind of like, they're like, you can, you're done with, I'm like, I'm going to hang out for a little bit longer. >>You know, you know you're a, you know, you're a geek when you're geeking out, when you're off the clock, you know Steve and I the same way. We're like we should stop rookies now let's keep going. So CES, UFC, yes, >>yes, every year for sure. And for anyone that hasn't been to CF, it's kind of on the bucket list for anybody that's attending technology, 35 football fields full of gadgets. Amazing. Yeah, it's always one of my biggest times of the year. So we'll be back here. >>now do you enjoy CES or is it a hard slog for you because you must have to really get down and dirty for CS, I mean a lot of stuff to cover. >>I did and I tried to make it to like the most random boosts. I find someone of my best technology products and like the ma and PA type shops that don't have the million dollar booth and like you know that are really back in a corner and I'm like zero in, >>you go on to cover, by the way, do you go into cover? You kind of sneak in there and you go into the camera guys. No, I go for it. You go for it. Okay. Time. Okay. All right guys. Um, that's awesome. Well can. Thanks for coming on the cube. We really appreciate spending the time. We'd love the personality. I love the energy. I mean Dave and I think you know, we're, first of all we're huge fans of your work. Especially the ESPN part. No, we're, we're big sports fans. In fact we call this the ESPN of tech cause it's our kind of version of like trying to be like ESPN. But we think technology is going mainstream. People at this new generation are geeks and even too, you alluded to ESPN, even sports and technology, I can't tell you how many pieces I've covered in pro athletes and how tech is entering in that space. Everywhere. Disruption in the data, the social media, you know, limiting have agents that go direct to the audience. Just super exciting. I mean I'm real big fan of media, tech, sports and entertainment. Thanks for coming on the cube. We appreciate it. We'll be right back with this after the short break here inside the cube live in Las Vegas. I'm John and Dave. We write back.

>> Announcer: Live from Las Vegas, it's TheCUBE! Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to Las Vegas, everybody. IBM Think, the inaugural IBM Think. This is TheCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm here with Ed Walsh, the general manager of IBM Storage. Ed, always a pleasure, my friend. Good to see you again. >> As always, great. >> Wow, what a show! >> It's amazing, it's fantastic. >> 30,000, 40,000, I don't know. I said to John, too many people to count! >> Hard to get through places, right? Just to get here, it was hard to get here. >> We're going to get into your business. You're not a newbie anymore. >> Ed: 18 months, right? >> Second time at IBM, so you really know the ropes. But let's start off with Ginni's talk. You heard our riff, John and myself at the talk. I really like her style. I was poking at some things, but what was your take on her message to the audience? >> Well, just consistency. As an outsider from IBM, the power of IBM to actually change the environment's pretty good, but putting smarter to work and really focusing on business is where we're core. I think it's powerful, but also it allows you to have the overall message of IBM come in, innovative technology. Now, we're going to talk about data and cloud, but innovative technology, an industry split on things, and then, really, the trust and security piece, that comes together. Now, when we talk about it, how do we in the data area move people forward? I think it's a powerful message of, I heard your earlier statement about that, the power of the incumbent. If you look at this, global 2,000 clients that we deal with are looking to user data and to more aggressively advance themselves, and that's where we're perfectly positioned. Even as storage, and we'll get back to storage in a second. But it all comes back to data, which I can include storage, but it's leveraging the data for the competitive advantage and doing what they maybe were slow to do. The early phase one of the data era was really the consumer companies really taking over. We'll talk about good tech versus bad tech. Really, now, we believe it's the rise of the incumbent, which you messaged pretty well, because they do have all this data. Maybe they're slow to adopt how to use that data. With the right partnership at IBM, we can do that. And that's where we're getting the most traction for the clients is telling them, "How do you actually get data-driven in your business?" "It's not as easy as you want it to be." It is about technology, but it's also about human capital as well. >> You obviously talk to a lot of customers. You have for years on both sides of the fence. You've been talking to customers about disrupting companies like IBM, and now you're a part of IBM, and you're helping the incumbents not get disrupted, and maybe be the disruptors, as Ginni was saying. The reason why I was poking at that a little bit is because it is all about the data, and if you, I mentioned yesterday, look at the five top companies in the US in terms of market cap. $600 billion, $700 billion companies. We know who they are. They're the Amazons, the Facebooks, the Googles, et cetera. The premise that I have is they have data at the core of their business, and they've organized human, human expertise around that data, whereas historically, I was talking to Peter Burris about this the other day, he said, "Historically, people have organized humans "around their assets," which might be plant equipment, it might be the bottling factory or whatever it is. So, how do companies go from that distributed, bespoke, siloed data model into this core data model? That's a cultural change, it's a technology change, it's a people and process change. What are you seeing, now, we saw some examples today. RBC, we saw Maersk, we saw Verizon, I'm a little more skeptical on Verizon. Big telcos have a lot of infrastructure that's unchanged, but what are you seeing with companies, how receptive are they? Are they sort of sidecaring their digital transformation, or are they jamming it right through the center, the heart of the company? >> Everyone's on a different maturity curve for sure. We see the leaders and the laggers, right, and the people in between. But everyone desperately wants to do it, so we spend a lot of time saying with our clients, "Let me show you how others are getting more data-driven." On-prem, we focus a lot on private clouds in my division, but also how that's multi-cloud in nature. Because you do have to look at the overall environment and how to look at it, and everyone has their own vision about how they're going to go from where they are to where they need to get to. To get them there in the right steps takes, actually, the girth of an IBM with our technology, with our consultant, our capability to do that. It does take innovative technology, but to get clients is really sharing, really, we see three patterns on-premises are people leveraging to get to multi-cloud. But really, how do they modernize and transform their current environment to do it? We spend a lot of time explaining what other people are doing so that they're, 'cause some of 'em are laggers. Everyone wants to be data-driven. They've tried different areas, and now, how do we make it easier to do that? We're also making investments to make it easier to do that. Little things like machine learning, deep learning. That can be hard stuff. You can wrestle with a lot of the tools and building models. We're doing simple things like, Power AI would be example, in the environment where we bring these open-source tools and make it very easy for you to get your team to start focusing on business value, not the technology components. That's just making it easier, allowing, maybe you'd say the slower, right? Phase one is largely consumer disruptors disrupting it, 'cause they're moving just much faster than maybe the incumbent was. But we can make the incumbent get nimble, which they can with the right technology, but also, it's human capital as well, we can get there. We're doing a lot, not only in the infrastructure side, but you can do in public cloud, by private cloud, but leveraging that system record data is kind of hard, so it's all about tools and being more agile. But also, it's about making it really simple to do some complex things. I gave you the AI. I'll give you another one. People want to do app modernization there on native cloud apps. They want to refactor applications. They want to go to containers and microservices. Yeah, so, and how's that going? And they'll say it's pretty hard. So what do we do? We come out with IBM Cloud Private. What is that? Well, we've taken the challenge out of putting all these tools together. They said Docker, Kubernetes, Cloud Foundry, but also our operational layer to make it easy for you to deploy that, and then now you have complete portability between different clouds, multi-clouds, including IBM's cloud. But you can do it on-prem as well. But now what you can do is you're not focusing on getting all the components together. You're driving your value, which is where, typically, all these things, they focus so much on building a data lake and actually getting, how do I get the data lake up and running, compared to, how do I actually make sure I'm doing the right data, the right business? That's where I think you're seeing IBM focus a lot of innovation. It might not seem like, you know, that doesn't sound like storage to me, right? But it allows us to help our clients move forward, and those are the things holding them back. Storage is about having API-based automation, which, you're not thinking about storage that way, but you need to do it to fit in to this new world. You're going to see us do more and more. When you talk about putting smarter to work, we're trying to make it dramatically easier to get value, even for the incumbent. Which, maybe you could say they were slower, they don't have the right skills, or they have to do some things. I think we're going out of our way to build the right things. >> Well, my takeaway is, you're allowing the incumbents to get value out of their existing advantages, and their existing, I've talked about app modernization. They're making a lot of money on those apps, and if they can modernize, they can use that as a competitive weapon. I want to talk about your business. People that don't know you, you've done a bunch of startups, you kind of had the Midas touch. You're a technologist. You really understand deep technology. I'm told you're a tough boss, but a fair boss, so you're demanding. You know what it takes to win. IBM Storage, four consecutive quarters of growth, and not just 0.05 % growth, you're talking about substantial, meaningful, high single digits, mid single digits, and the market's growing at whatever, 2%, 3%. You're gaining share in a very large market. Give us the update on your business. How are you doing it? >> You nailed it. A lot of people highlight after years of not keeping with market, we went for not only growing, but we grow in all four quarters. But more importantly, we grow 7% year to year, which the market's grown about 0.9%. But it's really, it's also broad-based. It wasn't a particular product. If you look at our portfolio, every report segment we have internally, externally, grew for the year. If you look at geographies, six out of seven geographies grew. The only geography that didn't grow for us was China, and it's growing in software, it's just not growing in hardware because of some of the unique instances dealing with business in China. But if you look at broad-based, it's not a particular thing. Our portfolio's doing well. It's really how we're approaching the customer, and it's resonating with clients. Then it pulls together the whole portfolio. We have the broadest portfolio, which, you know, we talked about early on. Are you going to simplify that, or is it too much? I actually think it's an advantage, 'cause if you're trying to help people, and this is where the advantage is. All our clients are challenged. We talk about being data-driven. Now, that's a big challenge. But also, they're challenged with budgets and other things for efficiency. How do you get from where you are, where you need to get to, and then make the right steps? You need a broad portfolio to do that. I think the biggest value is we help people get more data-driven. A lot of that is showing what other people are doing walking forward, and it's very into modernizing and having the right agility in the infrastructure. But that's where it's really resonating with the market. And then we're focusing on offerings. We probably have the most competitive offerings. We have hardware and software, but also, the right go-to-market. How do you have the right messaging? We talked more about modernizing, transforming, helping clients free up critical dollars for resources so they can transform and do that in a concrete way. That's what you need to do so that you connect, you transform. And then we help 'em with the data, how to be truly data-driven. That message really plays because all of our clients, big and small, are just challenged that way. What our competitors are, to be honest, more pure storage players, I think I've told you a couple times, the reason I'm happy to be here is, you think of what IBM, when it shows up, can do to help you. I think storage and helping people into the next data-driven era is a big boy/big girl game. You have to bring a lot to bear. We're going to talk about analytics, machine learning, different tool sets. It's not about the next array, but underneath my portfolio, we'll go toe-to-toe with everyone product by product. That was just a lot of offering-by-offering work that had to be done, but we're in much better shape now, and then you're going to see continued innovation through this year. >> Well, I have to bring in the competition, 'cause you're stealing share from the competition. If I'm hearing you correctly, you're saying, Joe Tucci used to say, "We'd rather have overlap than gaps." That's a philosophy that you seem to be taking. EMC now under Dell's ownership taking a different philosophy. They seem to be consolidating their portfolios, they seem to be going for more volume plays, which is consistent with how Dell would operate. I wonder if you could compare and contrast those two philosophies. Am I right that you'd rather have a broad portfolio with no gaps than have gaps and not being able to meet market demand? Is that fair? >> Yeah, I think you'll see us be disciplined in portfolio. But my point is, someone's really trying to, you're trying to really help someone get from A to B in their environment. One product doesn't do it. A couple products don't do it. You do need the full solution set to do it. I also think it's not only what we can do with storage, what we can do with systems. You talk about data-driven. I bring in the overall group. Analytics, we're number one in analytics, et cetera. That's where you start to get, where we show up, it's a different value proposition. That's where we're winning. Now, we also still get involved with, hey, I'm going to, it's U-verse, EMC, array-by-array, winner takes all. We do that all the time, and we'll stand by every product. But you said it, well, you used Tucci. Conversation with Tucci has been reported, but he said to me, which was, "What do you fear most is, "if IBM ever got their act together," he said, "It'd be scary." All we're basically doing is getting IBM's act together, and then from clients are responding to it because they're actually getting a bigger value. That's changing some of our relationship with the clients because they still want to focus on this product and that product. But I think that's really what's affecting the change and the overall business direction. >> Well, getting your act together involved a lot of blocking and tackling, and still does, I'm sure, but it also involved a focused effort on taking R&D, pinpointing that on what the clients needed, getting products out. I mean, when we first did TheCUBE with you guys years ago, it was hard to see a rapid cycle of new product innovation coming out. My sense is that that's changed. I see more announcements, I see a lot more announcements. That makes products that people can buy, it drives revenue, it drives transactions. It brings partnerships. Is that a fair assessment of what you guys have done? >> It comes back to team. We'll go to the high-level team offering at go-to-market, but if you don't have the right team, so, basically, the first thing you do, you have to get the right team. The right team will make the right call. I built Insight IBM. The team I have now is not the team I started with, but it's really getting the right people that are knowing their business cold, inside, outside, that know storage, that can really drive that. The decisions become pretty easy. You got to have the right vision. The vision's all about having a dynamic vision that people understand and can give feedback to, and it does outside-in. It's what's going on with the customers that really matter to us. But get everyone around that, you have an open culture that that feedback loop down to every IBMer, right? You need to ignite the IBMer, I'm talking about, like, a third party, but it really, it's an amazing culture that if you give them the right direction, they'll drive for walls. It was probably my easiest turnaround I've ever done with the right vision. Also, at this-sized companies, a lot about having very agile operation. I spent a lot of time on things that you're not going to talk about on TheCUBE, but what we're doing with costs and quality, all the different things we're doing in serviceability that really do show up as far as NPS. We do a lot of things on a net promoter score, or every time we sell something or service something, we're getting feedback from clients, and they're filling in these verbatims. Boy, that is rich information that is going directly in a, I can give you a couple examples, goes directly into it. What we did is, one of our products is Spectrum Protect. Again, I'm not going to try to go to, but might as well. One particular offering that I have is a great offering, but it's been around for a long time. TSM turned to Spectrum Protect. Verbatims from clients, "I just need and it was simplicity, agent, listen," and they came up with three or four different things that had to be done on a particular environment. So, guess what? We deliver that, and literally, do this, get that. You listen to clients, we deliver that with quality. You put it as part of the overall Spectrum Protect, all of a sudden, transaction revenue goes up by 6%, which is a big revenue stream to just pop in a very single quarter. We're going to do that, but that's like an offering by offering work that has to be done, and you have to have the right team to do it. I would say the credit goes to the team, and the IBM team that really responded to it and lifted it. >> I mean, 10 years ago, that would've taken a year and a half or more to actually get into the product flow, right? >> It's fast. >> Okay, but the other thing I would observe, I've been hearing from companies like yours for decades that, "Well, we're going to use the adjacencies in our other business "to compete with the leaders." And it's never happened. It's starting to happen now, and presumably because people don't care as much about the speeds and feeds as they do about transforming their business and digital business and all that stuff. It seems like you're able to leverage that, so let's talk about some of those other trends. Cloud, that's the other big competitor, the public cloud. You've got a cloud option, but private cloud, we've talked about true private cloud. I think you're familiar with our research, there. How is that going, is it a tailwind for you guys? Is it working? >> Your research on true private cloud, I use it a lot, by the way. That's the idea, and I'll play it back, is having all the agility, flexibility, but also cost models of in the public cloud, but they want to do it on-premises with any time we don't leverage the public cloud resources, APIs, resources, as business demands. That's where my clients are looking to drive it. They want to have all the flexibility. They want to be able to go to the cloud for particular things. But it's lift and shift. We spend a lot of time, that is where we're getting the most traction. We spend a lot of time saying, "This is what we're seeing on-premises "with true private cloud, "and this is how they're going to "multi-cloud." We do show 'em all of our solution sets are now available in, not only IBM, but some of the other major clouds, because we do believe it's truly multi-cloud. But the biggest thing is helping clients understand what they can do along that maturity curve, and I think that's where clients really get the benefit of engaging. And always, the conversation does always come to something outside just storage. It comes into what you can do with server, or machine learning, deep learning, how to be data-driven, what we're doing as far as containers. We're not just saying our storage works for containers. Hey, are you wrestling with that? Let me give you, I'll give you IBM Cloud Private, which is a distribution that allows you to do, literally, in a matter of 40 minutes, be up and running, and then focus on getting a value. That's my storage message. You're saying it's not storage, but that's exactly how the clients are responding, and they need a partner to help them do that. It's not only having the vision of where they are and where they need to get to, data and cloud vision, but then they need someone to actually help them get there. Some things that don't seem like hard storage things really make a difference if our clients get the value out of the data. >> Infrastructure, as Tom Rosamilia says, "Infrastructure matters." It's interesting to see IBM's financials, the Z, Power and Storage driving a lot of the momentum. >> It's hitting the market where it needs, as far as the capabilities. You think about security and what we're doing the mainframe, it's amazing the capability you can accomplish there. Same thing on Power, the ability to do what we're doing on AI. You can do things on our infrastructure you just simply can't do. And then, analytic speed actually really does matter. Bandwidth does matter. And of course, storage fits in all that. >> Well, for 30 years, I've been hearing how hardware's dead, infrastructure's dead, and it just keeps bumping along. Sometimes you see a little spike. You have to have infrastructure for AI and this cognitive world, as you guys call it. So, Ed, great talking to you. Thanks so much for coming to TheCUBE. I wish you continued success. >> Thank you very much. >> Appreciate the time. >> Keep it right there, buddy. We'll be back with our next guest right after this short break. You're watching TheCUBE live from IBM Think 2018. We'll be right back. (fast electronic music)