(upbeat music) >> Hello everyone and welcome to the special Cube remote conversation. I'm John Furrier, the host of theCUBE. We're here in our Palo Alto studio. We do all of our digital events. We do all of our content, original content here in studio. Of course, we can reach anyone around the world through our remote technology. And we like to bring experts in, to talk about some of the cutting edge issues and one of the most important things that I've been really doing a lot of thinking on lately and putting it into practice is, the role of individuals in groups in digital and since we're using software, this is becoming a really critical dynamic for the concept of engagement. Which is the holy grail of digital marketing. And now with the Coronavirus you're going to see a lot of events being canceled. You're going to see new norms being formed around how people engage, how they bond and ultimately, how they get work done. So we got a great guest J Metz, who has got a Ph.D in Communications Technology. Dr. Jay Metz, thank you for taking the time to jump on our remote interview. >> Hello. >> So I got to ask you, you know, we were talking before you came on you've got your doctorate and going back thirty years ago, you were doing a lot of pioneering work with others in academic circles around group behavior, software and you know, for us old guys but you rolled back the clock back then, you're talking message groups, you're talking about, you know, online tech systems. But the world is pretty similar evolved evolution in terms of those same concepts. Now more than ever, you're seeing Facebook breaking democracy, the government wants to try and create an e-democracy model. How do you do voting? All these things now are cutting edge issues and certainly with the Coronavirus, you're looking at people wanting to take content and posting it on the internet. It sounds so easy but it's now, it's going to be different. So, I got to ask you, you know, how do you see this world because you've done a lot of thinking on this? You know networks, you know technology and digital. How do you see the role of content and people and groups forming on the internet? >> Well I think that the role of technology hasn't really changed all that much when it comes to slowest moving piece, which is human nature. When we were, as you pointed out we were talking about this a long time ago way back before there were pretty pictures to look at on computers, you know. We had, we had IRC Chat, we had Bitnet Relay, we had Minitel in France, we've had different places had different forms of communicating through the use of computer. And at the time, they were really curious as to what was going to wind up happening. Were you going to get, you know, a bunch of freaks running things? Or are you going to get people you know, effectively isolated from society? All these questions that we're kind of asking nowadays. We still had them back then and we don't have a new answer. The same problem exists, even if there are prettier pictures to look at on the screen. >> David Vellante put and I put out a post, he actually did an interview, an article, where we talk about digital events and his advice was, "Don't just think about the software, "think about the outcome." So I have to ask you, when you start looking at digital interactions and human behavior, you're looking at stuff from whether it's visualization, Sigchi did a ton of work going back to the 80s to today. You're seeing, you're getting group theory coming in. The outcome is just people either getting something done, finding what they're looking for, making new friends and connecting. Digital is not just the software, there's a human component. Can you share your view about you know, the role of engagement, how content in groups, group social formation, social capital, social organizations can emerge from this new dynamic that is going to be forced upon us as we start thinking about virtual and work remotely and everything else. >> Well, I always felt that engagement was sort of a misnomer, to be honest. I always felt that engagement really had to do with the way that participation was counted. And participation is not necessarily an indication of how closely somebody feels to somebody else. How much of a part of the group they actually feel. And we start to look at group dynamics, as we start to look at the communication part, we look at the actual points on the graph as individual elements of participation, as if that's a good thing or tells us something. It doesn't tell us where the vector spin is going, right? Is it going in a positive way? Is it going in a negative way? And the reality as I've been able to find out over the last several decades and I can't believe I said that out loud. But the reality over time and this was always back to you know, before the radio even, I mean. This is a common theme in human nature. How people form groups through the use of technology is relatively consistent. And it has to go through the nature of the medium as it pertains to making our conversations either delayed by time or increased by time. So that synchronicity makes a huge difference as to what we call engagement and what kind of meaning we can apply to it. >> I want to get with you on asynchronous versus synchronous. Now that's an important concept and you know, the cloud native technologies are all asynchronous and horizontally scalable. These are the benefits of large scale systems now. But i get to your point about participation, you mentioned about engagement. Conventional wisdom says that, "Hey I need a lot of "people in the funnel. "I want more people, "what are the numbers? "We have a million views?." You're kind of saying it's kind of going the other way. That's actually not good engagement in digital or in these kind of group formations. Can you explain that? >> Well I mean, we just don't know. So when I was, when I was doing way back when I was doing my dissertation, I thought the same thing. I thought that if I could find out how much somebody participated in a group, I would be able to determine how closely affiliated they feel to that group. And it turns out, that's just not the case. What I found out especially in the short term, was the participation inside of a group usually was indicating that they disagree with the group, not agree. So if you only stop there, you won't get the full story. And what we'll find out is over time, there is an evolutionary approach to this, more about a fractal way of recursively coming in and an iterative approach to being part of a group, bringing yourself into it, letting the group accept you, that kind of a thing. And it simply isn't true that because I have X number of views or this level of rewatches on my videos, that that means that they were either each participating or even affiliated with what I got. Are they part of my group or not? I can't tell simply by the number of views. That's what I mean. >> Yeah, great great stuff. I want to get your thoughts on, and we, I saw your comments on my LinkedIn post, I just posted on my plane ride back from Washington, D.C. But I want to get your reaction to a couple edits here. So I wrote, "In the age of digitals, "not the individual that makes a change, "it's the group or mob. "Often groups are where "individuals voices are processed, "refined, and validated as a collective. "And then, "New social constructs "emerge in digital, "where we interact as "individuals within groups." With digital now pervasive, and certainly everyone working at home, this is going to be highlighted a lot. Can you comment and your reaction to those statements? What's your thoughts? >> Well think about the way we start conversations digitally versus in person, right? So, our idea and this goes to what you said you want to get to regarding synchronicity. So, when we have conversations in a group, in a face to face environment, it is a lot more dynamic, it is a lot more chaotic. There's a lot more complexity and the adaptive system of the group emerges in it's own particular pattern. That same adaptive system does exist inside of the digital world but it is highly regulated. It's regulated by the kind of software and platform that we use. So we will get different types of that group evolution based upon what the actual software will allow us to do. Just like Twitter has a different engagement level. And I use that in a sense of how we interact. It has a different interaction level than the way LinkedIn does. So for example, I could not have responded to you on LinkedIn the way we did because you couldn't have even posted the message on Twitter the way you did on LinkedIn. And the way that we handle the individualism is going to be handled in such a way that we have a more paced turn taking approach to doing things. So, it's not going to be a complete collective and it's not going to be complete individualistic approach depending upon which platform we're using for communication. >> Yeah, one of the beautiful things about the internet is you've seen the evolution, there has been pros and cons. A lot of value has been created. You got the website, you can self-serve yourself. Social networks, you meet some friends, you get some connections. But as we start to see more digital connection, people being connected together or individually if you will, the progression of learning has been somewhat nonlinear. You go to Google type something in, you pop to a webpage or you and I see each other on Twitter, I jump into Discord, talk to my gaming friends, next thing I'm on LinkedIn. I'm kind of popping around in a very nonlinear way. Creates for a very asynchronous kind of consumption or communication pattern. Could you talk about the difference between or the value or the pros and cons between asynchronous communication and consumption of that content and synchronous. >> Well, I think that ultimately, the concept of time is an underrated approach to evaluating how successful something is or is not. So, the time between the way that we communicate and our expectations of it makes a huge difference. If I were to have a, even a slice of a five second delay between your question and my answer, like we are doing some sort of satellite messaging, it would be very disruptive to our flow, right? We would not be able to bond in quite a way. And yet, if I write something that's five seconds after you posted, wow, that's amazing, right? So, our expectations for how time plays a role in the development of our relationship makes a huge difference. But you also sort of talking about the idea of multitasking and the content switching that we do from place to place whether it be gaming in Discord and whether it be in storage or it's, you know, my background or whether it be networking or whether it be medicine or whatever the concept that we have to involve, that probability to content switch even with the same people in the room, the "digital room", that still winds up being a place inside of our head because we've conceptualized those time elements quite differently based upon where we're actually having the conversation. And so ultimately, at the very end of the day, it's a complex system that we tend to forget that we're even doing naturally. We just, we just do. >> It's interesting. You may talk earlier about adaptive and what not. I was talking with a friend this past weekend, we're talking about the difference in organism and a mechanism. You know, organisms are self healing, they repair. You don't have, if people act as a group, there's kind of that, kind of group feel like a social organism versus a mechanism. Software today feels like a mechanism. I got a chat window open, you can't see me. You're like "Hey you're there?", and I'm like, I could be making coffee, doing whatever. I'm not really present. So, you start to see what organism and mechanism concepts and then the notion of presence and commitment. If I'm face to face, that's value and time matters, and presence matters. I'm looking over there, talking to you. So presence and commitment are also concepts. So talk about those two things. You got being an organism, a social organism, social being versus a mechanism, it's like a software and then, you know, the commitment and presence dynamic. What's your view of those things? >> So you brought up the idea of linearity earlier and non-linearity. And when you look at something called, Complex Adaptive Systems, we take very static rules and they don't have to be a lot of rules, just a couple rules and just like the mechanisms that you're talking about. They can be very simple but, you know, in a stasis way and the human nature is to work around it. So our organistic, (laughs), you know what I mean. >> Yeah. >> That element that we bring to the table, tends to wind up working within that rule set or without that rule set and depending on what our particular needs are. But what happens in that parlance is called emergence. In other words, the process is called, autopoiesis, a technical term that means a pattern self-emerges from the mixture of a static mechanical element, those rules of communication and the way that we dynamically as organisms tend to work within and without those rules. And a pattern will emerge as a result. >> I want to get your thoughts on a digital event building out with the next generation kind of constructs for, how people can actually use the digital network, Zoom, Keynotes, Breakouts and then the other community aspect of it. But I want to get your thoughts on the role within groups, online groups. One is a group that self forms, has roles and responsibilities, there's decision making, there's group interaction, there's a dynamic kind of organism feel to it. Versus a mob, people just kind of gather up, grass roots Where it's just more free and loose. Can you talk about how you see those differences 'cuz you, you know, people could just gather publicly and chat. It could be self governed in some way but there's no real roles, no decision making, it's more mob like. And then, social constructs around decision making and group formation and decision making. >> In reality, it doesn't, if all things were being equal in terms of amount of time they had spent, the human element of forming groups does not change. The social development of groups has been something that's been studied since the 1840s in academia. And when you look back at that, those as basic ground rules of how groups form, they really haven't changed all that much. The facilitation of that may have changed. But have you ever gone to a group where the first meeting will have all whole bunch of people show up, and the second, people a lot less and by the third time it's already dead? You know, that game of life that we're familiar with with the whole, you know, software program, well that's very true. That's a good metaphor for the way that humans form groups in the first place. Just because it doesn't necessarily form in a digital way, it doesn't mean that was the nature of that particular way. It means that, that particular group itself, that participation, that affiliation, didn't happen in the timeframe necessary to keep it going. And I really think and I really believe that understanding the nature of the people involved, the marriage with the content that they are for and the medium that provides that facilitation is what will provide the idea of whether or not the entire group digital or other wise lives or dies. >> That's great insight J. I really appreciate that. You know, final question on this whole digital shift. The Coronavirus is forcing people to stay at home, events are being canceled. And you've been following theCUBE, you kind of know what SiliconANGLE and theCUBE have been doing. We would go to events where people would be there, physical spaces, and we would interview people in our authentic way and face to face and bond and but gather the data from the guests and distribute it digitally to our audiences. We've been doing that for 10 years. Now what's interesting though is the worlds now changed. There's no more venue. But the people running these events still want to take content value but now they got to digitally distribute it to where the people are in digital streams or digital space. Okay, or cyber space. So, this has been a real challenge for us people that are used to relying on the venue to handle a lot of the structural things. Decisions, stage, boom, breakouts, areas for hallway tracks, happy hour, networking. So, the venue handled all that. Now you have a flip of the script where it's still content value but the distribution to digital is chaotic and distributed. There's a group challenge, right? So, the question I have for you based on your expertise, how should people be thinking about the complexity to do a digital event 'cuz you got to have content, you have a digital stage, you need distribution, but you need to have the humans involved because they are the consumers and the actors. What your view of this and if we run a team together trying to figure this out, what we would say to people to help them along? >> I think, so there's a short game and there's long game here. And the long game is that, there are elements to digital forms of communication in asynchronous method just to use the terminology we've been doing. There are realities that cannot be met, the same way that you met in a face to face. And those are ages ago they used to be called, social context cues. But effectively the richness of a face to face just simply cannot be held in an asynchronous format for long. So, the long term game here, the long game is that, this is temporary setback because you still need to be able to do things that you can't normally do just through you know, watch pre-recorded content. Even if it winds up being a recorded content that will be a pre-recorded at some point. You're watching it live, you're still going to view it that way, right? If I watch a webinar live, hell, I have produced dozens and dozens of these things. I'm always aware that this is basically being viewed as if it were a, you know, pre-recorded content. On the short term now to answer your question, what has to happen is that, we have to look at a multi-pronged communication approach. How do I get that synchronicity of communication? How do I get people to feel like they've been heard? That's the problem. When your in a face to face situation in conferences you know you've been heard. In the hallways, in the walkways you would stand up and you would do a question. You know that. That's is one of the biggest problems we have to solve digitally because ultimately, I'm broadcasting something to you and it's a very different communication style than if we're having a interpersonal communication. >> Yeah, and you know one of the things over the years with the internet, the content acquisition which was the primary use case of an event. You go and learn. That can be done online. So, we've seen the progression of the networking peaks, the face to face value, meeting new people. My friends is there, I haven't seen him in a while. Or we work remotely and we see each other and we have beers together or we're bonding. So, is that's just really hard to replicate in software. It really really is. It can be a big challenge. >> Oh, without question. I mean, but at the same time think about reality of how much time you spend with people that you don't normally spend time with at the conferences. Entire friendships had been based on 30 minute conversations spread out over three conferences, right? I mean, you'll go and you'll dinner with one group of people, one conference and then you won't see them again for another three conferences. You go back to that fourth conference and, "Hey we're back "to where we left off "and we're good friends and "that'll never really change." So, we're able to kind of fill in the blanks mentally and emotionally in that sense. The question is, can we do that through the use of a digital technology or to your other point that you mentioned earlier, do other forms whether it be the politics that come out on Twitter or the you know, the other groups we're associated with, but they are worthy, God help us the cancel culture that's coming up. Will that affect everything digitally, that you can skip over when you're actually in a face to face situation. Those are questions that I don't have an answer to. >> Yeah I mean, we're looking at it hard. We think content is key, content value. And again, timing is critical. I like your perspective on timing. There's a time series involved. And there's asynchronous, right? So, it being there. You know, content with, you know, people who are heard or participating, contribution, forming bonds, and interacting. The digital venue that has to facilitate a community loop in, right? So, it's a really complicated but new emerging trend. We're really watching this closely and we really appreciate your insight. Thanks for taking the time. >> My best. >> J Metz, Dr. J Metz here, helping me unpack and sitting back in looking at the philosophy but really the practice of 30 years of internet and online research and sociology around the role of people, individuals in context to groups, this is a big discussion as people start to figure out and operationalize what is the right mix for digital and virtual with physical of spaces. And certainly, we think events will come back soon. But J, thanks for giving us the time and we'll talk to you later. >> Thanks for the invite. >> I'm John Furrier here at theCUBE studios for remote interview with Dr. J Metz talking about the social theory around digital groups. Thanks for watching. (upbeat music)

>> Narrator: Live from Washington D.C. It's theCUBE. Covering Boomi World '19. Brought to you by Boomi. >> Welcome to theCUBE. Lisa Martin with John Ferrier. We are in Washington D.C., at Boomi World '19. John and I have been here now for two days, and we're pleased welcome another CUBE alumni back to our program, Michael Morton, the CTO of Boomi, Michael J. Morton. >> Thank you! It's so great to be back with you guys. >> Great to see you. >> I love this. This is great. >> So we were geeking out the last day and a half, John and I were, with all of our guests and realized Booomi World 2018 was only 11 months ago. >> John: Yup. >> So here we are in D.C. Lots of news around fed rant marketplace certification. But in such a short period of time, Boomi has scaled to 9,000 plus customers in over 80 countries. Your partner ecosystem is now over 580. All in 11 months. And 11 months ago, one of the things that was very clear from all of the Boomi execs is we're going to redefine the i in iPaaS to be intelligence. Now here we are, fast track a few months later, we're going to be talking about, Boomi is talking about, redefining that i to be intelligent insights. Cool stuff. Talk to us about the insights. >> Okay, so let's talk about intelligence first. So everybody's intelligence happy of course, but we've been very disciplined of actually being articulate about what does intelligence mean, not just the label. So we have a history of intelligence being how can you facilitate customers building solutions on Boomi faster. That's our legacy. And so we'll always continue to add new features to the product, but we had an opportunity that we realized we kept in our back pocket for a little while, right? And that's around insights. So we knew that the way the world uses Boomi is to integrate data. They connect the things. They move data. But now we're kind of shifting a little bit and saying it defines what your business is doing, not what your data's doing. Right? So now comes insights, the first for any iPaaS to do, is now we can intelligently tell you what is your business doing. So now we had to make a decision. We can't just advertise it and say we do this, right? And hey, wave our hands. So we said we're going to pick a business challenge, not a very common one. Just kidding, of course. What's a business challenge that every business has? Data privacy. So we chose the insights to say we want to help customers address a business challenge of data privacy. It makes perfect sense. If Boomi is the traffic to running your business about moving data, what's data privacy? It's about getting your arms around the movement of your data. So it just was a perfect fit, for an integration platform as a service, to expose, in a much different way, where is the data about your business actually coming and going? >> Is it going to be part of the product, chargeable, free? How're you guys thinking about these insights? Is it going to be a module? Is it going to be a connector? How do you guys think about the insights piece of it from a consumption stand point, from a customer stand point. >> Okay, so I'll take it one step at a time. I will just be honest and say we have yet to decide is it a charge for feature? We're still evolving it, but consumption's a very important question, so today what we're doing is we have this capability working today. We talked about it on stage, very comfortable about speaking about it, because we're working with a set of customers that gave us real feedback about what's important and what's not important. The consumption's a very interesting question, because depending on the role, right? If you are a chief security officer, what do you want to see? Do you want to see PDFs? Do you want to see reports? Or do you want APIs to get the data to consume into something else? So, one of our to do's is consumption. How do you want to receive this information? So this is actually in the works. >> So, I can see policy and AI being helpful there. You mentioned privacy. I want to get to that in a second. But why not security? That's the number one problem, too. Data, privacy, and security. Is it just too elusive? Or is it too hard? >> Michael: To me, they go together. >> Okay, so explain. What's going on, how does security fit in to this? >> Yep. I mean, I think there's many aspects of security obviously. But I mean security from an access standpoint, all right? So I'll take the position of access. One of the reasons why customers buy Boomi today is they want to expose a certain amount of data to consumers, either from monetization or to an application or to a consumer or to a website, right? And so one type of security is how do you limit the data that you get access to? And so today I'll go back to intelligence or insights. >> (chuckling) Exactly, same. >> It is not out of the realm of possibility that we actually show you who's accessing the data. >> Yeah, I mean we've seen this moving around. That's when the thieves are also moving around, too, and the bad actors. That's a good observation opportunity. And that's kind of where this comes from, right? This whole ability to observe, observability. >> That's right. Observe access. I mean, impersonations is a very popular thing, you can impersonate people, but the whole ability to observe inbound requests, right? I mean, there's always traffic controls on API gateways and things like that, which we'll fully support. But security? I mean, it comes with access. >> I want to get your thoughts on a couple things while you're here. Observability remind me of this cloud 2.0 conversation we've been having on theCUBE. And we're kind of goofing on web 2.0, cloud 2.0. Cloud 1.0, Amazon storage, computes, scale up, everyone's born there, loves it, no problem, no issues, just grow and buy as you go. It's great stuff. At some point when you're an enterprise, it's not that easy. >> Michael: Right. >> So, from cloud 2.0, observability has really taken network management to a whole 'nother level. And it's a data problem. So people going public, SignalFx got acquired, it's a whole industry now. Automation is evolving out of the configuration management area. RPA has got some AI in it. So if you connect the dots here, I can see you guys know where I'm going with this. >> Yep, yep. >> Observability is data. Automation is about making things easier. >> Michael: Yep. >> How do you see those components fitting into the Boomi world? Because architecturally they're now building blocks for either conversational AI or some sort of insights and intelligence. What is, what's the framework, what's the building blocks to make all this data value come to life? How would you talk about that? >> Well, I mean, you're asking, I broke down your whole tirade there into many sections already. >> John: Tirade, good word. That's a great word. >> So let's talk about, in relationship to Boomi, you used the word infrastructure. You used the word network. You threw a lot of things in there. >> John: Tirade, that's for sure. >> And it's like, okay, now I have a soup. So I'll just try to pick pieces out of the soup that I think are relevant. So, again I'll tie back to intelligence a little bit. Boomi, when you use the product, there's an engine that you run. It's a container, right? So you build in the cloud and Boomi, and then you choose where you want to run, right? And part of our efforts around intelligence is to keep that run time environment healthy and maybe scaling, all right? So automation for Boomi will be, let me look at the workloads that you are using to run on Boomi, and predict when I need to scale your environment. Automation. You'll see slowly even more automation capabilities to make it easier for scaling, sizing. So that's one aspect of hopefully answering what you're asking and trying to dissect a little bit about automation. So one will be automation for ourselves. I mean to help basic, just don't think about your moving around time anymore. It's just going to work. It's just going to scale. So we are planning to get to that point where it's fully automated. >> And that's efficiency for you. Creates value. >> Michael: Yeah, correct. >> Deploy resources to other areas. >> Yes, but here's something else to consider is it also saves our support organization the call. That's the most important thing, is the company when you scale, is you have to put in your company cultures. You build the product. What can you do to avoid that service call coming in? So I do want to talk about culture a little bit, even for intelligence. And I like to give a very simple example about how does a product like Boomi change their culture about building in intelligence into the product. And I have a great example. So let's say I'm a developer that's been assigned to put a new feature in Boomi. And it has five configuration parameters that you need to ask the customer to configure before you can use it. Why? Why five? Can't I just tell the customer what they need for three of those? And now there's only two? And it gets people thinking, oh yeah, I guess I could have gone back into their metadata. They already did this once. So why don't I grab that value that they already did? And that's an interesting mindshift when you think about it is instead of five, I challenge you to get down to two. Get it down to two. So, intelligence is not just an outward facing customer feature. It's a development culture. >> You talk about operating systems. It's really a great conversation, because you know when you look at data, and then and what you're talking about, back to the demo and the privacy conversation that you guys are talking about, is if you think about data holistically, as a system, not as a isolated thing, 'cause that's what you're getting at. It's a systems approach. >> Michael: It is. >> The data's somewhere. Why you have another form? You get it, pull it in, automation. But as you did the demo, people were buzzing about mind blowing, whoa! Look what's flying around! What was the purpose behind the demo? What was your main point? What were you trying to get across in that demo that you wanted people to walk away with? Was it that there's threats out there that's an issue or their problems are going to be solved? Or is this cool? What was the main driver behind the demo and the privacy as the first step? >> That's a very good question. And so I'll give you the first thing that comes to mind. The company and data is a living ecosystem. It never stops. It's always in motion. It's harder to manage. It's harder to observe. Boomi is meant to basically build the engine of your living ecosystem. All right? How can you possibly as a human get insight into that ecosystem? It's impossible. But with a product like Boomi, we're giving you insights into the living part of your business. That's the really the theme. Now applying to, you said threats. Good word. Threats to what? In this case, it's threats to being fined by GDPR. It's not necessarily a security breach. But fines are real now. I mean there's monetary loss. And so that's the message. >> What have some of the, you mentioned the word mindshift in your demo this morning, you mentioned it a minute ago, when you've been working with some of these customers helping you evaluate this intelligent insight capability, what has been the mindshift there, in terms of exposing this information? What are some of the things these customers have been really like whoa, really surprised that this intelligent insights can show them, that they just have no idea about with respect to their business? >> Yep, great question. Because I gauge success on the reaction, all right? And in this case the human reaction is actually seeing a map between countries with lines. It's actually that simple, to visually be able to see as a human, the flow of data. Then on top of that, the flow of private data. >> It's like an x-ray. It's like looking at the bloodstream. >> Ah, that's a good analogy. >> Yeah, I mean the blood's flowing, all aspects. >> Right, you can't see your blood. I can't see it, right? I know it's there. >> John: (laughing) Yeah, I think so. It's red. >> I hope so. >> That's like Superman. You can see through the data points to get into what you want because the data's flowing. You guys make that observable. Now what about the data that's not in the Boomi platform? Connectors, how would people, I mean so obviously not, Boomi's not everywhere, you've got 9,000 customers, not 900,000 customers. So there's a lot of other businesses that aren't using Boomi. Can I leverage it with other platforms? How do you think about that? >> Again I'm going to interpret what you're asking. There's many other sources of data of course that people are not using Boomi to access. But if, this may be a bit of a salesman opinion, the more you use Boomi, the more insights you're going to get. So why wouldn't you connect to those things? >> So but connecting means I can just connect to those things. I'll give you a hypothetical, real world example. We have so much data on these CUBE interviews. In fact, after this CUBE interview's done, your words will be transcribed into a transcript, will be linked to the video. We can make clips out of it. It's a big data set. When people will share those clips, we know who's sharing the data. So we are there, a lot of good data. So I would be like hey, I'd like to tap into that Boomi. Why build it? I can just connect. So do I connect all my applications into Boomi or just my data? >> That's actually interesting. Now, of course, I'm the CTO of the business. I'm going to invent stuff on the fly 'cause that's what I do, right? You have metadata about, you have metadata about these files? >> We have APIs, metadata, all kinds of stuff, yeah. >> What we would expect would be this. You would need to, if you're looking for other insights, all right, you're going to now see start combining data. So analytics is really about taking multiple sources of data, putting it in one place, and mining it for new insights because of correlating things together. >> And that validates your point about being that sales rep, because more data, the better data. Look it, we just did a master class here. Master and student. Real time, on the fly. >> This is the second master class you guys have done. At Dell Technologies World, there was a master class on block chain I sat in between you two. >> I got to say, that's a new format we should look at, this real time invention. >> Michael: I love it. >> Well, Michael, thank you so much for joining John and me on theCUBE. It's been really exciting to see, in 11 months, what's transpired for Boomi. We can't wait for next Boomi World. I can't wait to hear how this double i intelligent-- >> Maybe another i? >> Insights. I cubed? I three? All right, all right. Won't quote you on that, but we appreciate it. >> Great to see you. >> Very cool stuff. For John Ferrier, I'm Lisa Martin. You're watching theCUBE from Boomi World '19. Thanks for watching. (upbeat music)

>> Announcer: Live from Miami Beach, Florida, it's theCUBE. Covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to the Fontainebleau, Miami, everybody. My name is Dave Vellante, I'm here with my co-host for this segment, Justin Warren. Justin it's great to see you. This is theCUBE, the leader in live tech coverage, day two of our coverage of VeeamON 2019 here in Miami. Jason Buffington, @Jbuff is here, he's the vice president of solution strategy congratulations on the promotion and great to see you again, my friend. >> Thank you very much. >> Dave: And Nathan Hughes who is the IT director at Flex-N-Gate. Great to see you, thanks for coming on. We love to get the customer's perspective, so welcome. >> Great to be here. >> Okay, so, Jason let me start with you. Former analyst, you've been at Veeam now for long enough to A, get promoted, but also, get the Kool-Aid injection, you're wearing the green, and, what are the big trends that you're seeing in the market that are really driving this next era, what do guys call it? Act two of data protection? >> Sure. So, I preached on this even before I joined Veeam that every 10 years or so, when the industry shifts the platform of choice, the data protection vendors almost always reset, right? The people that lead in NetWare don't lead in Windows. The people that lead in Windows didn't lead in Vert. The next wave is we're moving from servers to services. Right, we're going from on prem into cloud and so, and every time the problem is the secret sauce doesn't line up, right? So you got to reinvent yourself each time. And what we saw in the past generations, what we learned from, is, you can't be so busy taking care of your install base that you forget to keep innovating on what that next platform is and so for us, act two is all about cloud. We're going to take everything we know about reliability but we're moving into cloud. The difference is, that in virtualization there was one hero scenario. VMs, right? This time around it's IaaS, it's SaaS, it's PaaS, it's using cloud storage, it's BaaS and DRaaS, there's not a single hero scenario which means we have a lot more innovation to do. That's round two. >> And you made that point today, you used the Archimedes quote, give me a lever and a fulcrum and I'll change the world. You used the analogy of backup as now becoming much more than just backup, it's data protection, it's data management, we're going to get into that. And test some of that with Nathan. So, Nathan, tell us about Flex-N-Gate what does the company do and what does your role as IT director entail? >> Okay, so Flex-N-Gate is a tier one automotive supplier. Which means that we provide parts, most of the things that go into a car besides electronics and glass, to the final automotive makers. So most of the companies that you're familiar with when you go to buy one. >> Okay, so you guys are global, I think you've got what, 24,000 associates worldwide, 64 locations. So what're some of the things that are, fundamental drivers of your business, that are rippling through to your IT strategy? >> Well, our business is varied in the sense that we do a lot of different things in house so, we do, obviously, manufacturing, that's a big part of what we do. And then, even that is broken down into different kinds and then beyond manufacturing we have advanced product development and engineering so we do a lot of that in house. >> Dave: You support it all? >> Yes. >> So you've got diverse lines of business, you've got different roles and personas, you know, engineers versus business people versus finance people. And you got to make 'em all happy. >> We've got to make 'em all happy. >> So, one of the things I love about manufacturing examples, is if you think about it it's the two extremes of high tech and low tech, right? On the low tech side of things you've got this manufacturing floor and it's just producing real stuff, not the zeros and ones that we live with, but real things come off this line. And then you have the engineering and R and D side. Where they're absolutely focused on stuff that comes out of some engineer's head into a computer, which is truly unique data, so, one of the things I love about the story is, talk about the downtime challenges you have around the manufacturing floor. Because I learned some things when we first met, that I think is phenomenal when it comes to manufacturing things that I didn't realize. >> Sure. So, we have a lot of different kinds of manufacturing environments. Some of them are more passive and some of them are more active. The most active environments are, a form of manufacturing known as sequencing. And it's sort of where you bring final assembly of parts together right before they go to the customer. The way that customers order up parts these days, it's not like they used to back in the 70s and 80s. Where they would warehouse huge volumes of everything on their site and then just draw it down if they needed it. And you just kept the queue full. Now they want everything just in time delivery. So they basically want parts to come to the line right when they're needed and actually in the order they're needed. So, a final car maker, they're not necessarily making, 300 of the same thing in a row, they're going to make one of this in blue and one of that in red and they're all going to be sequenced behind each other, one right after the other on the assembly line. And they want the parts from the suppliers to come in the exact right order for that environment. So, the challenge with that from our perspective is that we have trucking windows that are between 30, maybe 60 minutes on the high end, and if anything goes badly, you can put the customer down. And now you're talking about stopping production at Ford, Chrysler, GM, whatever. And that's a lot of money and a lot of other suppliers impacted. >> Dave: So this is a data problem isn't it? >> Yeah, it definitely is. And it's an interesting point, 'cause, you talk about sequencing. Veeam has their own sequence about how customers use the product and they start with backup, everything starts with backup, and then they move further to the right so that you get, ideally, to fully automated data protection. So, what are you actually using Veeam for today? And where do you see yourself going with Veeam? >> So, right now, we're using Veeam primarily as backup and recovery. It's how we started with it. We came from another product that was, great conceptually, but in the real world it had terrible reliability and its performance was very poor as time went on and so, when Veeam came on the scene it was a breath of fresh air because we got to the place where we knew that what we had was dependable, it was reliable. We got to understand how the product worked and to improve the way that we'd implemented it. And so, one of the key features in Veeam that really actually excited us, especially in those sequencing environments are these instant recovery options, right? So, we were used to the idea of having to write down a VM out of snapshot storage. And then being put in a position where it might take an hour, two hours, three hours before you could get that thing back online now, or again, to be able to launch that right out of snapshot storage was a blessing in the industry we're in. >> Yeah, did you see the tech demo yesterday where they were showing off how you could do an instant recovery directly from cloud storage? >> Yes, yeah. >> Did that get you excited? >> Yes. That is exciting. >> Are you using cloud at the moment or is this something that you're looking to move towards? >> Cloud is something we're sort of investigating but it's not something that we're actively utilizing right now. >> So this instance recovery, you guys obviously make a big deal out of that, I was talking to Danny Allan yesterday offline about it. He claims it's unique in the industry. And I asked him a question, I said specifically, if you lose the catalog, can I actually get the data back? And he said yes. And I'm like, that sounds like magic. So, so I guess my question to maybe both of you is, instant, how instant? And how does it actually work? (he laughs) >> It just works, isn't that? >> It just works! >> It's just magic, new tagline? >> I guess we don't have to get into the weeds but when you say, when I hear instant recovery, we're talking like, (fingers clicking) instantaneous recovery with, very short RTOs? >> To us what that means is that in practice, we can expect to have a VM from snapshot data back into production in about a five minute window. >> Dave: Five minutes? Okay. >> And that is sufficient for our needs in any environment. >> Okay, so now we're talking RTO, right? And then, what about, so we said 64 sites across the world, 24,000 associates, is Veeam your enterprise wide data protection strategy or are you rolling it out now? Where are you at? >> Yes, no. Veeam, we started with it in a handful of key sites. And we were using it to specifically back up SharePoint and a few other platforms. But once we understood what the product was capable of, and we were sort of reaching the end of our rope with this former product, yeah, we began an active roll out and we've now had Veeam in our facilities for five, six years. >> So you swept the floor of that previous product. And how complicated was it for you to move from the legacy product to Veeam? >> It was a challenge just rethinking the way that we do things, the previous product, one thing that it really had going for it, if this could be considered a positive, I guess, is that it was very very simple to set up. So, you could take an entry level IT administrator and they just next, next, next, next, next. And it would do all the things that they needed it to do. But the problem was that in the real world, that was sort of the Achilles' Heel, because, it meant that it wasn't very well customized and it meant also that, the way that they've developed that product, it became performance, it had poor performance. >> So the reason I ask that question is because, so many times customers are stuck. And it's like they don't want to move, because it's a pain. But the longer they go, the more costly it is, down the road. So I'm always looking to IT practitioners like, advice that you would give in terms of others, things that you might do differently if you had a mulligan, I don't know, maybe you would've started sooner, or maybe there were some things that you'd do differently. What would you advise? >> Yeah, I mean, if we'd understood, the whole context of what was happening with that other product, we would've moved sooner. And the one thing that I will say about Veeam is, it's not click and point. It does involve a little more setup. But the Veeam team is excellent when it comes to support. So there's nothing to fear in that category because they stand behind their product and it's very easy to get qualified technicians to help you out. >> Is that by design? >> I don't know if it's. Well, the being great to work with, yes, that's by design. >> Yeah, but I mean. >> I was talking to Danny yesterday and asked about the interface thing. Because there is always that tension between making it really really simple to use but then it doesn't have any knobs to change when you need to. >> That's what I'm asking. >> But it can't be too complex either. >> Our gap actually comes a little bit later in the process, right? So, you asked earlier about, in what ways do you use Veeam? And we think about Veeam as a progression, right? So, everybody if they're using Veeam at all, they're using it for Veeam backup and replication and because foundationally, until you can protect your stuff, right? Until you can reliably do that, all the other stuff that you'd like to do around data management is aspirational and unattainable at best, right? So, we think the journey comes in at yeah, it is pretty easy, to go next, next, next, finish. Just a few tweaks, right? To get backup going. But then when you go beyond that, now there's a whole range of other things you can do, right? So Danny, I'm sure, talked about DataLabs yesterday. The orchestration engine, those are not, next, next, next, finish. But anything that's worthwhile takes a little bit of effort, right? So as we pivot from, now that you've solved backup, then you can do those other things and that's where we really start going back into something which is really more expertise driven. >> Well, and it's early days too and as you get more data and more experience you can begin to automate things. >> Yeah, absolutely. So Justin was asking, Nathan, where the direction is. Today it's really backup. You've seen the stages where, talking about full automation. Is that something that, is on the horizon, it is sort of near term, midterm, longterm? >> I mean, coming to the conference, our experience with backup, or Veeam, is primarily backup and recovery operations but, I've seen a lot of things in the last few days that have piqued my interest. Particularly when it comes to the cloud integration. That's being actively baked into the product now. And, some of the automated, API stuff, that's being built into the product. Any place where I can get to where we simplify our procedures for recovery, that's a plus. So I'm really excited about the idea of the virtual labs, being able to actively test backup on a regular basis without human intervention and have reporting out of that. Those are things that I don't see in any other product that's out there. >> You know, there's another piece of the innovation that we should think through, and, so we've talked about the sequencing side which is where we focus on RTO, how fast can you get back and running again? And when you and I talked earlier, the example that we worked on was think of a zipper, right? You've got the bumpers coming in to a line of cars and if either side slows down, everything breaks, and at the end, by the way, is the truck, right? And everything has to come at the same time at the same rate, if there's downtime on either side of the source, you're done. But that's an RTO problem. The engineering side, for high tech, is an RPO problem, right? You have unique stuff coming out of somebody's brain into a PC and it'll never come out that way again. And so, when we look at backup and replication, that should be the next pieces to go on. And then as you mentioned, DataLabs becomes really interesting and orchestration, so. >> Well speaking of human brains, and you kind of touched on it, Nathan, that you came here to learn some things and you've learned things from different sessions. So, what is it about coming to VeeamON that is worth the time for IT practitioners like yourself? >> I think it's all those, I mean we were talking about Veeam, doing backup and recovery operations, fairly straightforwardly, in terms of getting in, but once you see some of this stuff here at a conference like this, you get a better sense of all the more, elaborate aspects of the product. And, you wouldn't get that >> See the possibilities. >> I think, if you were just sitting in front of it using it conventionally, this is a good place to really learn the depth and the level that you can go with it. >> And you're like most of your peers here, is that right, highly virtualized, is that right? Lot of Microsoft apps. And, they say, mid-sized global organization, actually kind of bumping up into big. >> Nathan: Sure. >> Yeah, cool. I asked about the data problem before, it sounds like the zipper's coming together, that's some funky math that you got to figure out to make sure everything's there. So, talk about the data angle. How important data is to your organization, we know much data's growing, data's the new oil, all those promides but, what about your organization specifically as it relates to a digital strategy? It's a buzzword that we hear a lot but, does it have meaning for you, and what does it mean? >> Data is vital in any organization. I mean, we were referencing earlier, how you've got low tech in manufacturing, or at least people think of it as lower tech. And then high tech in R and D, and how those things merge together in a single company. But the reality is all of that is data driven, right? Even when you go to the shop floor, all your scheduling, all your automation equipment, all this stuff is talking and it's all laying down data. You're putting rivets in the parts, you're probably taking pictures of that now with imagers when you're in manufacturing. And you do that so that if you get 300 bad ones you can see exactly when that started and what happened at the machine level, right? So, >> That's a good one. >> We're just constantly collecting massive volumes of new data, and being able to store that reliably is everything. >> Well, and the reason I'm asking is you guys have been around for a while and your a highly distributed organization so, in the old days, even still today, you'd build, you'd get a server for an application, you'd harden that application, you'd secure that box and the application running on it, you'd lock the data inside and, my question is, can, the backup approach, the data protection approach, the data management, or whatever we want to call it, can it help solve that data silo problem? Is that part of the strategy or is it just too early for that? >> I'm, sorry, I'm going to get you to repeat that question in a slightly different way. >> Yeah so, am I correct that you've got data in silos from all the years and years and years of building up applications and-- >> I mean, we have-- >> And can you use something like Veeam to help unify that data model? >> Draw that all together? Yeah. I think a lot of that has, it's more on the hosting side, right? So it depends on how those systems were rolled out originally and all that kind of thing. But yeah, as we've moved towards Veeam, we've necessarily rebuilt some of those systems in such a way that they are more aggregated and that Veeam can pick them up in an integrated kind of way. >> You see that as a common theme? Veeam as one of the levers of the fulcrum to new data architecture? >> We're getting there, so here's the trick. So, first you got to solve for basic protection, right? But the next thing along the way to really get towards data management is you got to know what you got, right? You got to know what's actually in those zeros and ones. And so, some of the things that you've already seen from us are around what we do around GDPR compliance, some of the things we do around sanitization of data for DevOps scenarios and reuse scenarios. All of that opens up a box of, okay, now that the data is curated. Now that it's ingested into our system, what else can you do with it? You know, when I talk to C-level execs, what I tell them is, data protection, no matter who it comes from, including Veeam, is really expensive if the only thing you do is put that data in a box and wait for bad things to happen, right? Now the good news is, bad things are going to happen, so you're going to get ROI. But better is don't just leave your data in a box, right? Do other stuff with that data, unlock the value of it and some of that value comes in, now that I'm more aware of it, let's reduce some of the copies, let's reduce some of the compliance mandates. Let's only put data that has sovereignty requirements where it goes, but to do all of that, you got to know what you got. >> Go ahead, please. >> There was some impressive demo yesterday about exactly that, so, we have the data. You can use the API to script it and you can do all kinds of, basically, you're limited by your imagination. So it's going to be fascinating to see what customers do with it once they've put it in place, they've got their data protected. And then they start playing with things, come to a conference like this and learn, ooh, I might just give that a try on my data when I get back home. >> That's right. >> We'll give the customer the last word, Nathan. Impressions of VeeamON 2019? >> It's been great. And like I say, if you're a company that's been using Veeam even for a while, and you have your entry level setup for backup and recovery and I think there's a lot of, probably, companies out there that use Veeam in that kind of way, this is a great place to have a better understanding of all that's available to you in that product. And there's a lot more than just meets the eye. >> And it's fun, good food, fun people. Thanks you guys for coming on, really appreciate it. >> Yeah, thank you. >> Alright, keep it right there, buddy, we'll be back with our next guest, you're watching theCUBE, Dave Vellante, Justin Warren, and Peter Burris is also here. VeeamON 2019, we'll be right back. (electronic music)

why from Las Vegas it's the cube covering informatica world 2018 bacio by inform Attica hey welcome back it runs the cubes exclusive coverage of informatica world 2018 we're here at the Venetian in Las Vegas live I'm John for your co-host with Peterborough's coasting and head of analyst said we keep on insulating all the cube our next guest is jammed the dalla who's the enterprise analytics architecture engineer sire pharmaceutical and some named director of the enterprise analytic solutions lead at sire as well great to have you guys thanks for joining us thank you so love getting the practitioner view of kind of the reality right of what's going on off see dramatic has their show you guys are a customer you're looking at some of their products take a minute first to talk about what you guys do first see Pharma got some stuff going on Davies involved privacy's involves you're in Europe in the u.s. GDP ours here think I'm gonna talk about what you guys do sure so char Pharmaceuticals is a global leader in rare diseases so there's about 350 million patients who are effective remedies is today and so art group with NIT enterprise analytics so we're focused on making sure we bring the right technologies and capabilities around bi and analytics to the organization so we look at products tools figure out how they fit into our our ecosystem of bi stack of tools and make that available to our RIT colleagues as well as our business colleagues so rare disease can you just explain kind of categorically what that is cuz I'm assuming this fits rare is not a lot of data on it or there's data you got to figure out what is that how do you guys categorize that so rare disease you know majority the rare disease affected by affected children so that's a kind of a critical aspect of what we do you know rare disease could be in immunology it could be in oncology GI I mean there's very disease typically you know people who are affected affected probably less than a thousand or 2,000 I think one of our drugs the population is around 5,000 people and these are chronic diseases typically their chronic diseases so they're they're they're diseases that affect the quality of life of an individual so what you guys are doing is identifying what is it about the genealogy etc the genome associated with the disease but then providing treatments that will allow especially kids an opportunity to have live a better life over extensive time yeah and what do you guys do there in terms the data side can you explain what your roles are yeah so like I said we're you're in the enterprise analytics so we're focused on bringing technologies and capabilities around bi and analytics spaces so how do we bring data in and ingest it how do we curate the data how do we do if data visualizations how do we do data discovery advanced analytics so all of those kind of capabilities and we're responsible for so what's your architecture today you have some on premises their cloud involved you just kind of lay out kind of the environment as much as you can share I know maybe some confidential information but for the most part what's the current landscape internally for you guys what are you dealing with the data sure so we fill out a new a new next generation analytics we called it our marketplace or the analytics marketplace we're leveraging both on Prem as well as cloud technologies so we're leveraging Microsoft Azure hdinsight for Hadoop the Big Data technologies as well as informatica for data ingestion and bringing data and transform or transforming yet but there are many tools involved in that one so it's like the whole ecosystem we call does marketplace which is backbone for shared enterprise analytics strategy and future you guys put a policy around what tools people can bring to work so to speak and we're seeing a proliferation of tools there's a tool vendor everywhere we look around the big data it's right I got a tool for this I got a tool for wrangling I've seen everything how do you guys deal with that onslaught of tools coming in do you guys look at it more from a platform respective how are you guys handling that right so look at a platform perspective and we try to bring tools in and make that a standard within the organization we look at you know the security is it enterprise grade technology and yeah it's a challenge I mean they're basically certified you kick the tires give it a pace test through its paces and then we have our own operations team so we can support that that tool set the platform itself so and what are your customers do with the data they doing self service or they data scientists are they like just business analysts what's the profile of the users of your customers of your we have all set of users they have like a technical folks which they want to use the data like traditional ETL reality so there are folks from the business they want to do like self-serve and unless they want to do analysis on the data so we have all the capabilities in our marketplace so some tools enable those guys to get the data for the selves or like the tools we have and dalibor does their own stuff like the eld talk a little bit about the one of the key challenges associated with pharmaceuticals especially in the types of rare disease chronic young people types of things that you guys are mainly focused on a big challenge has always been that people when they start taking a drug that can significantly improve their lives they start to feel better and when they start to feel better they stop taking it so how are you using big data to or using analytics to identify people help describe potential treatments for them help keep them on the regimen how do you do are you first of all are you doing those things and as you do it how are you ensuring that you are compliant with basic ethical and privacy laws and what types of tools are you using to do that it's a big question yeah yeah so we are doing some of that you know we have looked at things around persistence and adherence and understanding kind of you know what what combination of drugs may work best for certain individuals or groups of people yeah and definitely you know some compliance is a big factor in that so when I'm working close with a compliance group understanding how we're allowed to use that data in between which parts of the organization do you anticipate that you'll have a direct relationship as some of these customers or is there an optimist in other words does analytics provide you an opportunity to start to alter the way that you engage the core users of your products and services like I believe so you know I think one thing that we're looking at which strategic standpoint is um how do we diagnose people sooner a lot of these chronic diseases you know they go through 2-3 years of undiagnosed so they'll jump around from you know doctor a doctor if I understand what you know what the issue is so I think one thing we're looking at is how do we use data and AI to to more quickly be able to diagnose patients has a 360 view helped you guys of data you guys have a 360 view how do you cuz we'll look at that in terms of a channel selling a product and serving because we have a different perspective what's the 360 view benefit that you guys are getting yeah so we have a kind of a customer care model which is kind of a 360 for our customer so understanding you know around just drug manufacturing to making sure they have the right you know they have the right supply to understand is it working for the patient's so we've always been talking about the role a big day you mentioned had to do that Hadoop supposed to be this whole industry now it's a feature of data right so there's a variety of you know infrastructure as a service platform as a service some say I pass and Big Data how are you guys looking at that as as as builders of IT next-generation IT the role of I pass and Big Data we see it as a role in a blur you know I think what cloud brings us in the past type solutions is agility you know we as the market is so evolving so quickly and there's new versions of new software coming out so quickly that you wanna be able to embrace that and leverage that give it benefit of like give it some sort of a comparison old way versus a cloud like is there been some immediate benefits that just pop out yeah that a lot more benefits with doing the world way and the cloud way because with the cloud that brings a lot more scalability in in all India's to get like 10 servers you need to work with the infrastructure team I get it like it takes three months or two months again it with the cloud based one you've worked out you can scale up or scale down so that's one thing because it's so you're talking about Big Data yeah you're getting the volume of data you're getting you need to scale up your storage or your any compute you either JMS and compute bring data to the table and then you gotta have the custom tooling for the visualization yeah how that kind of together right you talk about them from your perspective the balance that you have to have guys have to deal with every day like you got to deal with the current situation NIT you got cloud you got an electrical customers personas of people using the product but you got to stay in the cutting edge it's like what's next cuz we going down the cloud road you're looking at containers kubernetes service meshes you need a lot more stuff coming down the pike if you will coming down the road for you guys how are you guys looking at that and how are you managing it you have some greenfield projects do you do a little you know Rd you integrated in how are you dealing with this new cloud native set of technologies yeah definitely a balancing act you know I think we do a lot of pocs and we actually work with our business and IT counterparts to see hey if there's a new use case that is coming down you know how do we solve that use case with some of the newer technologies and we try a POC may bring in a product to just see if it works and then see how do we then do we then take that to the enterprise so I got one final question for you guys and maybe you do as well John but but in life and death businesses like pharmaceuticals is a life and death business the quality of the data is really really important getting it wrong has major implications the fidelity of the system is really crucial you say using informatica for for example ingest and other types of services how has that choice made the business feel more certain about the quality of their data that you're using in your analytic systems into standardization so you know if between MDM round mastering our data - ingesting data transforming our data just having that data lineage having that standard around how that data gets transformed is that fundamentally a feature of the services that you're providing is you not only were you you know the ability to do visualization on data but actually providing your scientists and your businesspeople and your legal staff explicit knowledge about where this data came from and how trustworthy it is and whether they should be making these kind of free complex very real hardcore human level decisions on is that is that all helping yes because it seems like it would be a really crucial determination of what tools you guys would use right it is yeah and absolutely I think also as we move more towards self-service and having these people having data scientists do their things on their own being able to have the tools that can do that kind of audit and data lineage is crucial great to have you guys on we had a wrap I want to ask one more question here you guys were an innovation award e informática congratulations any advice for your peers out there want to unleash the power data and be on the cutting edge and potentially be an honoree yeah I would say just definitely think outside the box seem to try new things try puce you know do POCs is there so much new technologies coming down so quickly that it's hard to keep up Jam cuz it's like a moving target you need to chase your movie target and based on B was it that gets you like what you want it to do you know siding yeah get out front don't keep your eye on the prize yeah focus on task at hand bring in the new technologies guys thanks so much for coming on great to hear the practitioners reality from the trenches certainly front lines you know life-or-death situations of quality of the data matter scaling is important cloud era of data I'm John for a Peterborough's more live coverage after the short break

>> Announcer: Live from Madrid Spain. It's theCUBE covering HPE Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid Spain everybody. This is theCUBE, the leader in live tech coverage. We're here covering HPE Discover Madrid. I'm Dave Vellante with my co-host Peter Burris. Vaibhav Parmar is here. He's a partner with PwC. Good to see you again. >> Good afternoon thank you for having me here. >> Yeah you're welcome. So PwC obviously people know it as top consultancy, global capabilities, deep industry expertise but give us the update on sort of your role and where you're focused. >> Sure so I represent our technology consulting organization at PwC. And basically we work with our clients and our business partners in bridging the gap between the business solution and the business outcome that are intended and all of the enabling technologies that get to the outcome. And so our role is to design solutions, help implement and get them deployed, and make sure they work properly all with the objective of this technology has to be aligned to the outcome, the business results that are being intended. So we provide that traceability from the beginning to the end and we are the part of the consulting organization that focuses on the use of these new and emerging technologies for bringing that business realization. >> So anybody who's followed the tech business obviously has been following cloud and the impact that cloud has had on customers, on industry competition, on how companies partner, go to market, et cetera. And get and achieve outcomes. So hybrid cloud is all the rage. Hybrid IT, what does that mean to you? You hear it from Hewlett Packard Enterprise. What does it mean to PwC? >> Sure so I think the word hybrid has become very pervasive now as we think about technology, as we think about IT and there's several definitions to the word hybrid or the terminology hybrid IT. First it's the use of multiple types of technology environments to deliver the outcome. It could be a public cloud provided by one of the major cloud providers. It could be all of the on premise traditional data center technologies and infrastructure. It could be a combination of both using some third party intermediary in a co-location or in a hosted manner. But that's one part of the hybrid definition. The second part of it is actually being able to access services and capabilities that are built and innovated by the providers. So if you look at where Microsoft is going with Azure and all of the platform as a service capabilities that they've introduced into the marketplace, how do we take advantage of that so that we're not building individual lego blocks we're actually taking lego blocks that have been built and assembling them for some type of a business outcome. So hybrid is also taking advantage of the services that have been prebuilt and predefined so that we can fuse them together to get the result that we're looking for. And the third part of hybrid is what we're now starting to take advantage of with the public cloud providers which is we use what we need and only pay for what we need. In the traditional model, we buy this much and we may be used to using this much at some point in time, this much at some point in time. I think in the new and emerging model it's... We only want to pay for what we need and what we use whether it's in a public cloud manner or it's in our own data center manner. So hybrid is also that flexible consumption and economic model associated with all of this technology and the infrastructure. >> So what's the predominant conversation going on with customers today? Are they saying Vaibhav help me get to the public cloud. I don't want to have all this infrastructure in house or are they saying look I can't move everything to the cloud, but I want that cloud experience in my own operations. >> Yeah. >> Hybrid, hybrid IT obviously is the latter, but what's the dominant discussion with customers? >> So I think it starts often as the first because customers hear that hey everybody's talking about the public cloud. Maybe I need to be there. But then very quickly we come to the conclusion that a public cloud by itself may not be enough or adequate and we actually need to think about the hybrid model for a number of reasons. It could be for data governance and compliance reasons. There are jurisdictions and municipalities that have data residency requirements which make public cloud more difficult to use. It could be for performance reasons where a lot of the applications and the use cases are of a nature that an on premise environment will continue to make more sense. So very quickly we move to the point of view that a hybrid model is the more probable and practical model. But the conversation also is not so much that I want to be in the public cloud or I need a hybrid cloud, it's more so around here's the outcome and the business result that I'm looking to achieve. It could be that I want to get more features out to the market faster. It could be that I want to take advantage of innovation that's available to me so that I don't have to invest in that myself. It could be that my developers are antsy for all of this new technology that's available and they don't want to you know be encumbered by more traditional life cycle activities. All of that then leads to the decision or the discussion on okay well this sounds like a cloud oriented mindset. Let's talk about what is available to us to get more flexibility, to get more agility, to get the developers all the tools that they're looking for. And that's where we quickly start saying okay the public cloud has all of these offerings but again it may not be adequate enough and we need to complement that with an on premise environment and the hybrid model becomes a natural landing point. >> So the technologies and means to that outcome end. Okay so in thinking about the realities of hybrid cloud, hybrid IT whatever you want to call it, how do you actually... You named some attributes and some parameters. How do you actually bring those to the clients? How do you make it real? >> Sure. So I think we have to think about what is it that we need to make it real? Again if we think about it from a developer point of view they want quick access to environments so they can do testing. They can do code reviews, right. And the environment has to be stood up in a very timely manner. Today it takes time to request the environment, to do all of the configurations, make sure all the security processes are in place. But the developers want quick access because they want to turn that code over very quickly. So that's one part of what is needed to make this real. Let's think about the developers. The second part of it is around operations. We want this to be safe, we want this to be secure. We want this to be aligned to our corporate policies on regulation, on use, whatever it might be. And so we have to think about okay well what are all of those elements that make this compliant? That make this highly aligned to our security policies? The third part is the economic part of the equation. Again it's we want to only pay for what we want to use. How do we make that a reality in an on premise world where we're used to traditionally spending a lot of money at one time and then we're just amortizing that over time. Well in this new world we need that economic model as well. The ability to only pay for what we need yet still have the capacity that we're looking for. So when we think about what is needed to make this a reality, I think it's the infrastructure in an on premise environment has to look and feel very much like the infrastructure that's in the public cloud. Highly accessible, you can turn it on and turn it off when you need it. You can spin up these environments when you need it. And then you turn 'em off when you don't need them. It's the consumption model and the economic model. Again I'm only going to pay for what I need and not for excess capacity. So that capability has to be there as well. And then the third is the fact that developers are highly motivated by these innovative capabilities that are available in the public cloud model. So you know firewall as a service, storage as a service, how do we make that equally available in an on premise environment? The on premise world and the cloud world have to look very much alike from an infrastructure point of view, from an application and services point of view, and from an economic and sourcing point of view. That's what's needed to make it a reality. >> Is the delta so... That all sounds great and it's kind of consistent with what we see in our research. But when you start to peel the onion on what exactly goes in on prem, it isn't exactly like the cloud, but maybe it doesn't have to be. Does it just have to be substantially better than what was there before? And substantially mimic the cloud? With some other attributes that the cloud can't deliver. For instance data residency. >> Correct. >> And other locality stuff. Maybe governance, maybe not. I mean that's one you've got to really think through. >> Vaibhav: Sure. >> Some of the cloud guys would say hey we've got great security and great governance. >> Vaibhav: Sure. >> But does it map to my edicts as an organization? So there's some nuance there. But I guess my question is how close do you actually have to get to satisfy this sort of customer demand? How close to that cloud model? >> So again I think I would say we can try to match it from a... A CPU to CPU point of view or from a storage terabytes petabytes point of view. But again our observation and our experience in working with our clients is it's not so much at that level, it's more so at the, the behavior level. Again if I'm a developer, I don't want to wait two, three weeks for somebody to stand up an environment. I want to be able to stand it up in 30 minutes or an hour because my code is a microcode. It's not a big monolithic, waterfall oriented code anymore. So if I have a microcode that I want to quickly test, I want to be able to have the environment that's quickly accessible and when I'm done with it, it can go away. So it's those functional attributes that we have to match. How we technically match them, you know we can go in many different directions. I think one of the things that we're excited about in where HPE is going as an example, is with Azure Stack, right. The availability of Azure Stack in collaboration with Microsoft in an on premise environment looks and feels very much like the public cloud environment. With the ability to get the microservices that we're looking for. With the ability to spin up and spin down the environments in the timely manners that we're looking for. Those are the attributes that I think are what we see as our clients looking for. And behind the scenes, how we technologically enable them, it doesn't have to be a like for like match. >> Dave: Right. >> So the exciting thing is we're seeing the evolution take place. We're seeing the availability now. And it's time to start taking advantage of it. >> So we talked about hybrid cloud, but in many respects we're really talking about multi-cloud. That's really going to be the challenge. So I want to take you back a few years. And build a scenario and you tell me if you think this is where things are going to be. So a number of years ago, we had a lot of mini computer companies with a lot of specialized networks. And if you were running a plant, you would have all these little mini computers. And you'd say I want a single network for everything. And they'd say yeah, bridge my network, gateway my network, all this other stuff. And along came TCP/IP and flattened everything. >> Vaibhav: Sure. >> And that drove a lot of the mini computer companies into... I mean HP survived because they were one of the first ones to address and adopt TCP/IP in a big way. >> Vaibhav: Right. >> So here's the question. We're going to have hybrid cloud. But it's inevitable we're going to have multi-cloud. >> Correct. >> Because we're going to have Saas, we're going to have Iaas, we're going to have on premise, we're going to have Edge. And all these have to share attributes as you're saying of the cloud experience. >> Vaibhav: Right. >> How are companies going to start thinking about flattening all those different cloud options so they are not recreating the legacy of having to manage all this stuff but adding the transaction cost of having to do that through a contractual arrangement? >> Vaibhav: Sure. >> Where's this going to end up? >> Sure. So I think there's a couple of ways to think about that. If we think about the cloud model, you mentioned those terms infrastructure as a service, you have platform as a service, and you have software as a service. I think we're making a lot of progress on the infrastructure as a service layer becoming more and more flatter. And more and more consistent across the different providers. Consistent across your private cloud providers. Consistent across your public cloud providers. And what I mean by that. >> Give us an example. >> So an example would be as we look at where technologies like Open Stack and Open Shift are going. >> Peter: Okay. >> You know you're essentially turning all of this infrastructure into virtual elements, right. I want a computing resource whether it's this company's CPU or this company's CPU, it shouldn't matter. I'm looking for storage. Whether it's this company's storage or that company's storage, it shouldn't matter. I just need high speed storage, which might be flash, or I need more traditional storage because it's all static data which may be more disc based storage. We're becoming more and more flatter from that point of view. And behind the scenes, again, it could be a white box. It could be a branded box. It doesn't really matter to us anymore. So we're making good progress at the infrastructure layer and on top of it we've got good control mechanisms to be able to access that infrastructure function. Again through Open Stack type technologies that provide this control mechanism so you can provision, you can source, and you can manage and operate. As you get to the next level which is platform as a service, this becomes a little tricky because this is where you're getting into the application layer that's taking advantage of that infrastructure. And here you do have differences between the cloud providers. You know one cloud provider may choose to offer a set of platform services that are built one way whereas somebody else may do it a little bit differently. And so that does require some contemplation, right. Are we going to go down this path or go down this path? Because getting a firewall function from this provider... It still gives us a firewall function that this provider provides, but it's done a little bit differently. And that may not be always... You may not be able to make it flat. Because that's the nature of how the application layer is being built up. As you move to the software as a service layer, this is purely at the application layer now right? And there you will always have differences. Software as a service coming from one CRM provider or HR services provider will be different than another one. But what they've done is completely abstracted all of the underlying requirements. You don't need to worry about infrastructure. You don't need to worry about platform. You're purely sourcing the software function. So I think as, going back to your question of where will we get to when it comes to flattening all of these things, I think at the infrastructure layer we will get there because it's happening. At the platform layer, we may not get there because it's the nature of the business and the functions that these providers are developing and making available. And at the software layer, we won't get there because it doesn't make sense, right? We're going to focus on the business outcome and not necessarily the software itself. >> Well how about at the governance layer? My last question, at the governance layer across all these multi-clouds, the Saas, the platform as a service, the infrastructure, can we get to a common governance model? And why is your approach, you know talk to me as a customer, how can you help me get to that common governance model? Why is that approach better than sort of doing it on my own or doing it with a cloud provider? >> Sure so you bring up a great point. That despite the fact that we will have variances in the cloud providers and the cloud capabilities, yeah we do need some way to properly manage, run, orchestrate, operate, and govern all of these different multi-cloud scenarios that we will be in as a large enterprise. And so governance becomes a key tenant of how do we make this successful? And governance has a number of different definitions behind it. It's the operating model and the policies by why you provide access to the cloud services. So how do we make sure that a developer isn't just clicking a button, and then spinning up environments without the right controls behind it? Whether it's in this cloud provider or in this cloud provider. So putting in the policies and controls in place is one element of governance. The second part is having a consistent mechanism for connecting into those cloud providers through the right APIs and interfaces so that when somebody says I need additional storage, you're not having to create bespoke processes and technical interfaces between one provider and a different provider. You almost need an abstraction layer that provides all of the transparency in the back end so you can plug to provider A, provider B, but on the front end to the developers, to the architects it looks like I want more storage, right. And the machine will do all of the translation behind the scenes. So that's the second part of governance. The third part is on the operating model, on the operations itself. How do we make sure that the cloud provider is holding up to their commitments in terms of reliability, availability, throughput, all of these commitments that they've made so that we can get the performance results that we're looking for. Well provider A is going to have a different set of mechanisms to run and operate their environment compared to provider B. So governance also includes this element of looking at all of those different mechanisms by which the environments are being monitored and operated and giving us that consistent view so we know that yep, we're getting the services and the performance and the throughput that we're looking for and we've got a common set of processes and tools that allow us to interface into each of those providers on the back end. So we're not having to do all of this bespoke tools development, we can do it in a common way. And the fourth part to governance is ongoing controls. So how do we make sure that what we're expecting to use, what we're expecting to consume is aligned to the forecast. And that we're not deviating. If we are deviating, there's a good rationale behind it. Right, if the developers say over the next six to 12 months I'm expecting to use this much storage and this much compute because it's aligned to these business objectives, how do we make sure that's what ends up happening and that the developers aren't spinning up extra environments without the right discipline behind it? So that's a part of governance as well. >> Excellent. Well great framework Vaibhav. Thanks very much we've got to leave it there. We appreciate you coming on theCUBE and sharing your thoughts. >> Absolutely. It was my pleasure thank you David. Thank you Peter. >> You're welcome. Alright keep it right there everybody we'll be back with our next guest. We're live from HPE Discover Madrid 2017. This is theCUBE. (upbeat music)

(upbeat music) >> Voiceover: Live from Las Vegas, it's The Cube, covering VMworld 2017. Brought to you by VMware and its ecosystem partners. >> Hey, welcome back to The Cube's continuing coverage of VMworld 2017. Day 2, lots of stuff going on. I'm Lisa Martin with my esteemed colleague Dave Vellante. >> Hey hey. >> Hey hey! I'm excited to welcome an old friend, Eric Herzog, the CMO of IBM, as well as Sam Warner offering management IBM software-defined storage. Welcome, guys! >> Well thanks, we always love to be on The Cube, always. >> Dave: Love the shirt. >> Thank you, I'm glad I'm wearing a Hawaiian shirt again. >> Dave: Thank you for making sure you wore that, yeah. >> I think it's like my 25th time on The Cube with a Hawaiian shirt. >> Lisa: Oh you're like the Alec Baldwin of The Cube. (laughs) >> Lisa: Alright guys, so here we are- >> Dave: If we have the record, that is the same shirt you wore last year, isn't it? >> Yes, but I did clean it, Dave. (laughs) >> He wears it once a year. >> I've never had to ask anyone about dry cleaning on The Cube but there's a first time for everything. Alright guys, so here we are at VMworld. What's new with IBM and VMware? Kind of talk to us, Eric, from a marketing perspective. What's going on there? >> Sure, well the big thing is IBM and VMware have a very strong alliance across our entire portfolio. The Cloud Division has a big agreement with VMware that was announced with Pat Gelsinger and the head of the division last year, the Storage Division has all kinds of heavy duty integration with our VersaStack product, as well as in all of our all-flash arrays, and then Sam's team brought out a new backup and recovery product, Spectrum Tech Plus, which is optimized for VMware and hypervisor and cloud environments. >> Excellent. And that's one of the things actually thematically that we heard yesterday is that, you know, backup is hot. So tell us a little bit more about that hotness and how you guys are working with VMware to dial that- >> Dial that heat. >> Yeah, dial that heat up. >> Sam: Well it's actually, it's more than backup, right, it's about data availability, and ensuring your data's safe, data's the bloodline of your company now, right? Everything's moving toward cognitive and AI, you can't do that without data. Most of your data's trapped as a backup. And what we're trying to do now is make it really easy for people to get at that data and use it for other purposes. So first of all, making sure you're safe from things like ransomware, but also making sure you can get some value out of that data. Make it very easy to recover that data. >> So, lots of topics that we could cover there, I wonder, did you have one more and I want to jump in. >> I did. Just, Eric from a, as the CMO, from a messaging perspective now we've heard backup is hot, you've just kind of articulated that a little bit more, same with storage. From a conversation perspective, and you talked about the importance of data, Michael Dell talked about that this morning, that the data conversation is a CEO agenda. How is the conversation changing, and the position of IBM changing when you guys are talking to customers that, is backup, is storage a conversation around data that you're having with the C-suite of your customers? >> So, a couple things, and I've done storage for 32 years. EMC, IBM twice, seven startups, and the C-suite hates storage, including the CIO, but they do love their data. So they all know they need storage but when you talk about data, data availability, the resiliency of the data, the data always needs to be there, you don't even use things like data resiliency 'cause the CEO doesn't know what that is, so you need to say, so how'd you like it if you were in Star Trek, and Bones wanded you with a new healthcare wand, and it came back with no answer? (laughs) That's 'cause your storage is not resilient and it's not fast enough. So the data has to be available and it has to be fast. So we're moving to this world where everything is AI and everything is immediate. If your storage goes down and you're in dark trading, you just lost ten million bucks per second. So, but it's all about the data. So basically what we're doing is getting out of the storage conversation and talking about the data conversation. How data is used to optimize their business, and then you weave the storage in underneath as, well as you know if you've got a bad foundation to your building and the earthquake hits, boom. You building falls down. So data is that building, and storage is the foundation on which your data rests. >> I love this conversation, and I think you're right on. The C-suite, they hate storage because it's to them, it's just an expense, but I want to pick up on something that was one of my favorite interviews thus far this year. Believe it or not, it was the interview that you and Burris and Ed Walsh did in our studio in Palo Alto. And I wonder if you could add some color, and then Sam I want you to chime in. What I loved about that interview is you guys talked about digital business and digital business being all about data and how you leverage data. And you said something there, and I want to unpack it a little bit. Storage should not be just a dumb target that is unintelligent. it should be an active element of your data and digital strategy. >> Eric: Right. >> So what did you mean by that and how does IBM make it, storage, an active element of a data strategy? >> So the first thing you want to do is you want to make it all automated. You want to make it transparent to the user. So, whether it's in the healthcare space, I don't care what your business, Herzog's bar and grill? My storage is transparent. Okay I'm running a bar and grill, I don't have time to fool around with the storage. I need it automated, I need it fast, I need to see who's drinking what, how many cigars I can sell, I don't have time to fart around. Right? Storage can make that happen. So you've got certain CPU that's done on the server level or in the virtual machines, and then you've got to have storage that's intelligent. So, we're working on some products we're not ready to announce yet, but we've got some products that have built-in AI into the storage themselves. So things like, you can search in the storage instead of search on the server. How do like, be able to look at metadata and have the storage actually fetch the data not the server fetch the data, so the server's crunching, crunching, crunching, and the storage is smart enough to go grab the data on its own and then bring it to the server. Versus the server having to do that work. So all that's about making data more available, more resilient, and again, having smart storage not dumb storage. >> So Sam, when we were talking about backup it's how you say, it's not just backup, it's more than that. >> Sam: Right. >> Pick up on what Eric just said. How is Spectrum Protect more than just backup and playing into what Eric just talked about? >> Well a lot of things Eric was just talking about you don't necessarily, you're not necessarily going to be able to do all this analysis reporting, analytics on your production data, you don't want to get in the way of your critical workloads, so how can we make copies off to the side where you can do things like analytics, where you can do dev test, quickly build new applications, so we give the ability to have access to that data in a way that's not going to jeopardize your core applications as well. And of course, that data, you can't lose it, right? I mean, you've got to make sure it's protected. So we also offer you a very simple way to protect it, and very rapidly restore it. >> So, let's go through an example or use case. You mentioned ransomware before. >> Yeah. >> So a lot of people think okay I'll create an air gap, but air gap, in and of itself, you know, you watch these Black Hat shows, and they go, "Air gap is a joke. It's easy for me to get through an air gap." >> Sam: Right. >> So how do you deal with that problem? Presumably, you have insights and analytics that can help you identify anomalies, but I wonder if you can address what's the conversation like with your customers and how are you solving a problem like that? >> Well I think there's a lot of stages that would solve it. First of all, there's simple things you can do like have copies that are immutable, so they can't be changed, encryption can't go and encrypt a read-only volume, there is air gapping, which like you said there are ways around that, but then there's also, Eric touched on some of the metadata analysis. If you can find anomalies and changes in the metadata that are unexpected, you can take action and alert an administrator and let them know that something doesn't seem right, so there's a lot more work we're doing to introduce cognitive capabilities that can also detect that. >> One of the things actually that Pat Gelsinger said this morning, and this may have put a smile on your face when you said there's something you can't quite talk to yet is, companies have to integrate AI into their products. And machine learning. >> Eric: So, that's the plan at IBM, and we've already done some of that, we have some products that we've hinted at, that's product code name Harmony, and we've already done a public blog on that, a statement of direction, and that is our first step in implementing AI technology directly into the storage, again it's part of what I talked about a couple weeks ago when I filmed at your Palo Alto office, storage is not dumb anymore. I may be dumb, but storage is not. Storage is smart, storage is intelligent, storage is active not passive, and in the old worlds, when I started doing storage a long time ago, storage was just passive. Just a big brick. It's no longer a brick. It's a brain, and it thinks and it acts, and it relieves the CPU, and the other areas of your IT infrastructure from having to do the work, which is part of the metadata action that Sam talked about that we're working on and also this project Harmony that we talked about, is adding AI intelligence, things like Watson for example, maybe, but I can't quote me on that yet, but maybe we might put Watson inside of our storage, since we happen to own Watson, the dominant AI platform on the planet, we could probably put that into our storage. Maybe we will. >> So there's still a... okay why not? There's still a lot of dumb storage out there though. >> Yes. >> Huge install base. You actually probably sold a lot of it back in the day, so fixing the problem that you created, that's smart marketing. (laughs) But when you talk about the technical debt that exists, how do you go from point A to point B, going from that dumb storage to that active element? What's that conversation like with customers? >> So, it's actually pretty easy. First of all, storage refreshes every three to five years anyway. So now you can say, "Well you know the storage you had only did this, how about if we could do this, this, this or this, and really raise the bar?" The other thing of course is that IBM is the number one storage software company in the world, so anything we do is going to be integrated into the software side of our business, not just embedded in the storage systems we sell. And that software works with everyone's arrays. So that, if you will, artificial intelligence that we can bring to bear in an IBM Storwize or flash systems would also work on an EMC VNX2, would also work on a Dell Compellent, would also work on an HP 3PAR, would also work on this guy, that guy, and the other guy, because we are the number one storage software company in the world, for the guys that track the numbers, and all of this is being implemented into the software layer, which means it'll work with the other guys' gear. So we can take the old stuff I used to do at the evil machine company and make that stuff smart. >> What do you mean when you say you're the number one software company, because when you worked for that company you guys would always tell me, us as analysts, "Look, we don't really have any hardware engineers any more, we spend all our time on software, so we're a software company." You're talking about something different today, you guys leaned in to software to find, you've put your chips in, you did your billion dollar Steve Mills bet, what does it mean today to be a software company in storage? >> So for us, let's take all of our storage systems for example, FlashSystem V9 comes with Spectrum virtualized software, which works with over 400 arrays that aren't IBM logo. That software comes on that system. FlashSystem A9000 comes with Spectrum Accelerate, which is a scale-out block infrastructure that works both on-premise and in the cloud. Again, not just with our own gear. So we basically decided that, do we want to sell the full system solution? Sure we do. But if we sell the software only, that's fine with us, and remember, most of the big shops in IBM is exceedingly strong, enterprise to the Global Fortune 1000, and the Global Fortune 1000 down to those sort of, you know, one billion dollar company and up, most of them are heterogeneous anyway, so you're, if you're smart, and we think we are at IBM, to this effect, we made sure our software works with everybody else's gear. Spectrum Protect and Spectrum Protect Plus will back up any storage from any vendor, old or new, will go to any tape drive, will go to any cloud, we can automatically back up to the cloud, will automatically go to an object store, not just to our own object store, but other object stores. Will automatically go to disk or flash, so we've made it completely heterogeneous and, if you will, media and technology independent. And we're doing that across the board with all the IBM storage software. >> So that compatibility matrix, if I can call it that, is very important, has always been important in the storage business, but I feel like it's insufficient in today's cloud world. And let me tell you, explain what I mean and get your reaction. I'll start with Sam. So we've been talking all week about the imperative to not try to reform your business and bring it to the cloud, but rather to shape the cloud and bring cloud services to your data. And that's the right model, and now part of that, a big part of that, a huge part of that is simplicity. So we're here at VMworld, we're talking about backup and data protection, simplicity is fundamental. What are you guys doing in that regard, generally and specifically with regard to Spectrum Protect? >> Yeah, I think what you want is a very simple way to do data protection, and a methodology to do data protection that's consistent between your applications that you're running in your own data center and what you're running in the cloud. So you don't want to find out that, yeah your traditional applications that you've been you know, running in your data center for years are all protected, but it turns out all the new applications being built out on the cloud don't have the same rigor, aren't following the same standards, you're breaking your governance models, and you're at risk. So what you want is a simple way to manage both sides, you want a simple dashboard that gives you visibility to the entire environment in one space, so you know I've got 2,000 VMs, 1,800 of them are backed up, two of them aren't backed up, oh those are in the cloud, somebody didn't set it up correctly. You want to be able to see it very easily on a simple dashboard, and that's what we're bringing with Spectrum Protect Plus. >> Speaking of simple, Eric, last question to you, as the CMO, how do you make this message simple for a C-suite to comprehend and understand and help take them to the next level for them? >> Well for us, we don't even talk storage anymore. We just talk data, applications, their workloads and their use cases. That's it, and then you bring storage up underneath it, again it's the foundation of your data infrastructure, your data is the primary building, but if you don't have a solid foundation and, being from Silicon Valley and being from the '89 earthquake, when the earthquake hits, if you have a solid foundation, the building stays up, if you don't the building falls down. So, we lead with data, data, data, ease of use, simplicity, but really focus on what's your application, what's the workload you're trying to accomplish, what's the use case you need. And when you do it that way, you take the discussion away from being, "You're a storage guy." It's, "You're the data guy. You're the business guy." And that's how you have to pitch it. >> I like that. Hashtag data data data you heard it here first. (laughs) Eric and Sam, thank you so much for joining us on The Cube, I wish you best of luck and we'll be keeping our eyes and ears open for what's coming with AI and machine learning. Thank you for watching The Cube, continuing coverage live from VMworld 2017 Day 2, I'm Lisa Martin for Dave Vellante. Stick around, we've got more great conversations coming right back up. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering VMworld 2017. Brought to you by VMware and its ecosystem partners. (electronic music) >> Chad: Thank you. >> Welcome back to VMworld 2017 here in Las Vegas. I'm Dave Vellante with my co-host Peter Burris. This is Day 2. Chad Sakac is here. He's the president of Dell EMC, long-time CUBE guest, CUBE alumn. Chad, we were talking about eight years >> Yeah, it's crazy, man, it's been great. >> Dave: And you were one of the first. >> It's been great. I was thinking about it. What I love is it's always a great events where there's great things happening. And you guys ask killer, right to the point questions, and I always try to give killer, right to the point answers. >> Dave: All right, well let's get into it. Your ascendancy, personally, kind of coincided with VMware's explosion. You are down and dirty with the customers. So, first of all, congratulations on-- >> Thanks, dude. >> Dave: that role and being the president at Dell EMC. Awesome. >> I have a passion for it, Dave. Passion is the key, right? >> Okay, so we're all talking about cloud, right? Cloud first is something that you hear from customers all the time. I want to be cloud first. What does that mean to you, to Dell EMC, VMware? >> I think the first thing is is that to all of us, cloud is much more about an operating model than a place. And people have started to internalize that it's about changing the way that they operate their business, both for some of their traditional apps, as well as how they build cloud-native apps. That's the first thing. Operating model, not place. The second thing is, I think I'm seeing the customers in the market get a little more, I don't how to say this without sounding pejorative, but a little more mature in their view that the answer is going to have to be a hybrid model based on data and data gravity, based on elasticity of workloads, based on governance factors, that lead to hybrid being the answer. And if you think about what we've seen just in the last two days, VMware on AWS, Google partnering with VMware and Pivotal around Pivotal Container Services. Those are all about hybridizing both traditional IT and how people build new cloud applications. So operating model, not place. Hybrid is the answer. And the third thing is that it's multi. I still occasionally encounter somebody that says, "It's all going to be one cloud." And I'm like, "Okay, just out of curiosity, "does your definition of cloud include SalesForce.com?" "Well, yeah." "Does it include Office 365?" "Well, yeah." "Does it include AWS?" "Well, yeah." "Does it include your own private cloud?" "Well, yeah." "So, what are you talking about?" >> Peter: Where's the one? (laughs) >> Where's the one, right? And I think that there's a... Things start to matter once they move out of hyperbole and into pragmatism. >> Well, and when you paid attention, let's say four or five years ago, when you listened to Andy Jassy speak, the notion of hybrid cloud, or hybrid IT, or private cloud was not in his lexicon. And then yesterday, we saw him up on stage with Pat Gelsinger. They were talking about hybrid and private cloud. >> Chad: Well, by the way, I don't want to throw the dart at Andy. I think if you talked to Vmware or Dell EMC four or five years ago, public cloud wasn't in our-- >> Dave: Absolutely. >> (laughs) in our vernacular either. >> Dave: Absolutely, so those worlds have come together with the customer reality that says, "Well there isn't just one cloud. "And I can't just bring my business, "reform my business for the cloud." So what do you make of the fact that we've evolved as an industry and as a vendor community? >> I think it's time to get on to the brass tacks of solving the problems for the customers, ma'am. And I see actually that happening in the industry more and more. People are solving problems that they can't solve in their private clouds using public clouds. They're figuring out that the best place to put a dollar is to rebuild their applications using cloud-native principles. But they're also realizing that sometimes that it's not even a legitimate choice or option. And they're trying to figure out also, at the same time, "How do I support some of those "more traditional application stacks "and make them more automated and cloud-like, "even if they're not going to be cloud-native maybe ever." >> Peter: Let me jump in here for a minute. >> Dave: So this gets to the promise that you've got to make. And please jump in. >> Yeah, because in many respects, what we're really saying, let me test this with you, Pat, is that, ultimately, it may be one cloud, but that one cloud is going to be defined by the business and not by a particular vendor. >> Chad: It's a higher-order function. >> Peter: That's right. So what we like to say is we like to say, "You're not going to take your business to the cloud. "You're going to bring the cloud to your business." And your business attributes and your business characteristics, where you operate, how you operate, how you use data, who your customers are, how are you going to reach them, all those different things, the physical realities, the legal realities, the IP realities, all that's going to shape the architectural choices that you make regarding cloud. And you have to have a strategy for that becoming consistent and coherent for your business. So a lot of piece parts, but it becomes your cloud. Does that make sense to you? >> It makes sense to me. It means that it's an answer that involves a little more sophistication and nuance for the customer, because they've got to think about what it means for them. And the answer is not the same for every single customer. However, there are common base elements in that formula. Number one, digital transformation always starts with applications that are written using cloud-native principles, often using data fabrics that are modern distributed data fabrics. That's one piece. There's a consistent piece that says, "I'm going to leverage public and private cloud models." And the definition of which workload goes to one or another, like you said, is very much driven by data gravity. Compute tends to co-locate with the data against which it's computing. Governance rules, which is not security. Public and private clouds are equivalent. In some cases, one or the other is more secure than the other. But those are common elements. There's one other common element that I've learned over the last four years of being on the journey myself with many of our customers, which is that the only way that the on-premises part of cloud stacks work is through radical simplification and deploying their on-premises infrastructure using design and automation principles that look a lot more like the public cloud than they look like their most traditional IT. >> No, you're absolutely right. And I think that's a crucial point, that ultimately the physics of all this. >> Chad: Mm-hmm. >> And I agree, cloud is not a We like to say the cloud is not a place, it's a time. >> Chad: Yeah. >> Because at the end of the day, all this is defined by the realities of your data. >> Chad: Yep. >> And if your data can't If you don't have time to move the data or it's too expensive to move the data, that's going to dictate where the process actually runs. And I like the way you've redefined, I'll say redefined data gravity. Most people think data gravity, "Oh, once you put data in place, "it's going to accrete more gravity." And you're saying, "No, that's not the way to think about it. "It's going to accrete more function." >> Chad: Right. >> 100% agreement. And I don't think a lot of people are talking about things that way. >> By the way, the linkage to physics, I don't know how many of the viewers basically were physics majors, but it's actually related to quantum physics and mechanics. Information inherently can't simultaneously be in two places at once. That's a law of physics, right? >> Data, okay, keep going, keep going. >> If any bit, any information, basically, is connected between two points at the speed of light, that's not a function of vendor technology until someone-- >> Well, let me we get into quantum entanglement, nano >> Yeah. >> But I think where you are, where you're absolutely correct is that ultimately, that there is a cost to moving data. >> Chad: Bingo. Bingo >> And we have to start When we think about digital transformation, our approach is the difference between a digital business and a business is a digital business treats data as an asset and builds strategic capabilities to treat data as an asset and apply data as an asset. And one of the beauties of what you were saying earlier with simplification, is for example, the idea that if I build around data, >> Chad: Yup. >> then I can use hyper-converged, I can use converged, I can use Flash, I can use VC, and I can use all these different things to treat my data differently. >> And do it as simple as possible. The thing that I think I'll give you an example from this morning. I was meeting with a customer that's in the finance and insurance vertical, right? And they're pretty advanced down there, use of both public and private clouds. They've got a software-defined data center. And they're trying to basically redefine how they're using mobile apps and customer intelligence. They provide a ton of services. They're a great, great customer and a partner. But again, to highlight that cloud is a place, or a time, to use your vernacular, as they build their mobile app, sets of assets are running in a public cloud, the data was born in the public cloud, the compute is running in the public cloud, it's built around a cloud-native app principle using PCF and Kubernetes. Great! When that person is using that application, there's a moment when they go in and do a transaction where literally it's hitting a mainframe running DB2 in their core data center. >> And there's nothing wrong with that. >> And there's nothing wrong with that. In fact, that pattern is universal, right? And so it highlights basically that you've got to be a little practical about how you do this stuff. >> Okay, so in the limited time we have remaining, give us the the quick why Dell EMC, Dell EMC, VMware, why you guys Maybe talk a little bit about the portfolio. >> So if you look at this week, the one thing that jumps out, at least to me, I'm probably a little close to it, Dave, but I hope it jumps out to the viewers, right, is while we maintain an open ecosystem, Dell EMC has its open ecosystem, VMware has its ecosystem, Pivotal has its ecosystem, we're becoming much more opinionated, right? And that matters because customers want clarity. So I'll give you clarity. Clarity that jumped out on stage and it came out of the mouth of Pat, not me, was the easiest way to deploy VSAN is on VxRail. The easiest way to deploy VMware Cloud Foundation is on VxRack SDDC. Period, full stop. Now, why are we saying that so emphatically? It's because if you don't have a good foundation for an SDS and SDC, or SDC, SDS, and SDN, so software-defined network and compute and storage, in the case of VMware Cloud Foundation and VxRack SDDC, then your whole underpinning is just way too complex, right? So there's a very clear opinionated point of view that says hyper-converged infrastructure that's being built by the combined team is the way forward for customers who have standardized on vSphere. >> Well, and you nailed it earlier. If you're going to bring the cloud model to on-prem, to the data, it's got to be simple. >> Chad: Mm-hmm. >> Peter: That's the cloud model. >> That is the cloud model, right? And and without it, you can't fulfill that promise. With it, you can. >> I'll give you a second example. For the last four years, we've been supporting our customers with the Enterprise Hybrid Cloud. We've learned more about what does it take to lifecycle, manage, and deploy vRealize Suite on top of HCI, where we own the lifecycle, right? At the same time, VMware has been learning about, "What does it take to take vRealize and run it "in the VMware cloud on AWS, not as software, "but as a service?" And that's all about simplification and lifecycle management. What we're doing between VMware and Dell EMC is taking that knowledge and saying, "HCI is the foundation, and on top of that, "here's how you build your IaaS "for your traditional applications, "and the foundation for what's coming next." And then the last part that we saw today loud and clear is a strongly opinionated point of view that says PCF, Pivotal Cloud Foundry, is the best structured PaaS in the market, and a full embrace of Kubernetes, Pivotal Kubernetes Services, Pivotal Container Services using Kubernetes, is going to be the best way to build container as a service. How do you deploy it best? On vRealize. How do you deploy it best? On top of VxRack SDDC. It's pretty clear. >> Covered all the bases, we could go all day with you, but we're out of time. >> Yeah. >> Chad, thanks very much for coming on theCUBE yet again. Really appreciate it. >> It's my pleasure, guys, thank you. >> All right, keep it right there, everybody. We'll be back with our next guest right after this short break. This is theCUBE. (electronic music)

>> Announcer: Live from the Javits Center in New York City It's theCube covering Inforum 2017. Brought to you by Inforum. >> Welcome back to theCube's coverage of Inforum 2017 here in New York City. I'm your host Rebecca Knight along with my co-host Dave Ballante. We're joined by Mike Rodgers. He is the CSIO of Pilot Flying J. Thanks so much for coming on theCube. >> Thanks for having me. >> So tell our viewers a little bit about Pilot Flying J and your relationship with Inforum. >> So Pilot Flying J is a travel center. We cater to basically over the road truckers and we do have a big gas business too. We operate about 700 locations. Most of them are owned fully by Pilot Flying J. Some of them are dealers where they have a relationship with us. They're in our network but we don't know them. So we run the majority of the locations and we own about 40% of the overall road diesel market. >> Rebecca: In the US and Canada? >> In the US and Canada. >> Okay and talk about your relationship with Inforum. >> So our relationship with Inforum really goes back to Lawson. I've been with the company for about two years. We run Lawson. David Clo-thy will tell you probably 25 years. The company has very rapidly. Started off as a small little Tennessee company. Well now it's a rather large company and we felt we knew we had to make a change relative to our human capital management and our financial systems is because we basically outgrew it. And we like to write a lot of things so we wrote a lot of applications out of our desperate sylo. And of course it's a lot of technical debt that goes along with them. So when I start with the company. We started on valuation process and picked for as the partner to replace all of our financial systems, and all of our human capital management systems. >> And so you migrating from traditional legacy lawson to the cloud suite. >> Pretty much, I would characterize it as a migration but we had very little in the vein of human capital management. And what we did have, we wrote ourselves. For example, we wrote our own applicant tracking system, which we'll of course have to integrate into lawson. So we have an integration layer that we have to support there and that's just one. There was a slide put up this morning that showed that we're going to eliminate 26 systems that we either bought as the best of breed type of application or we wrote ourselves. >> So how painful is that? Is that why you-- >> It's extremely painful. >> They brought you in for this task and you obviously knew this coming in or just-- >> Oh I knew this coming in. >> Dave: No surprise. >> No surprise and by the way, pilot is no different than a lot of other retailers in other companies out there. We've got a lot of technical there and I will tell you the more I see about Inforum. The more I think we made the right decision. I really like the cloud strategy. I'd like the integration associated with all the different functions specifically within the HCM suite. It's not a roll up like some of the other guys have rolled up. They bought but whether it's PeopleSoft or whatever and they many talk about it being integrated, bit it's not as integrated as the Inforum suite. >> So if I may, sorry. We want to stay on the migrations for a second because it's non-trivial and people. The conundrum of migrations is nobody wants to do them because it's just such a heavy lift. But the longer you wait, the more technical debt you accrue. >> I use to say you have to get off the treadmill. You have to stop and say we're not going to keep digging ourself in this ditch and it's going to be painful. It's going to be expensive. It's going to be disruptive and I use to say the (indistinct speaking) usually get fired. That really is, I might say that laughingly but-- >> Dave: You got a got attitude about-- >> It's hard, okay. It's a hard thing not just for the IT guys. It's a hard thing for the organization with respect to change management. >> So incredible amount of planning obviously. You knew your freezing code. >> Pretty much because why would we continue to develop something. I wouldn't say we were 100% frozen. Things come out especially in HR where there's a regulation thing. >> Dave: Compliance, right. >> Right compliance and you got to do it so we got pretty good at saying we're not going to, we're going to wait for Inforum. And we've got a lot of it implemented. We're continuing. We got a nice plan. An iterative plan, we're not trying to blow the ocean and convert everything all at once. Very good engagement from the business. We have a lot of business partners here with us. Like the IT representation at this conference. It's the smallest compared to the business. >> So I would think a key there though is because when you freeze code. It slows your business down, but then when you actually go to the new platform. You want to be able to move faster and leap frog your competition. >> I would argue that really, because we really didn't have much. It really hasn't slow much down. Where we had to do something from a compliance perspective, we've done it. But it hasn't really slowed us down. The leap frog that we're going to do when we implement the whole cloud suite is going to be enormous. >> Sorry about. >> I wanted you to step back a little bit and tell our viewers about some of the specific HCM challenges you have and what you, talk about the pain, I guess is what I want you to describe. >> We run travel service. We're open 365 days a year, 24/7. They never close. They're all on food operations. >> Rebecca: Of the three quick services food operations. >> It could be up to three. If we don't have three in every stores someone said that. We may have one in every store plus a deli operation that we run ourselves and we actually create the food. Whether it's pizza, meatloaf whatever the truck drivers really want with respect to our food offering. They want something different, more variety. So yeah, it's a very complex business. It's hard and we're very spread out throughout the country. We're not necessarily in a big cities like New York. you're not going to see a pilot in New York City. You're going to see a pilot or a flying J on major interstates throughout the country. So there were spread out. So connecting with our team members has been a challenge for us. And our owner Jimmy Haslam will tell you that we probably have not any give himself a vibe. And we are connecting with the team member so we're doing a lot to facilitate that connection. We'd actually partner with the Disney Institute to help us with that. And we've actually called Inforum for project connect. So it's going to provide that connection platform to those team members that are spread throughout the country and Canada for that matter. That we don't get to see that very often, if ever. >> We're hearing a lot at the keynote retail has been highlighted a lot and Pilot J is a form of retail in that sense. And talking about how important it is for the customer experience. The trucker themselves who come in to apply at Pilot Flying J. >> Our strategy is focused on making it a great place to work. In other words, doing the right things for our team member and the investment at Inforum is really going to provide that platform. The other part is making it a great place to shop, and we want our customer to come back. Okay we sell a commodity, let's face it. We sell diesel. You can buy it down the road. We want the experience when they come into our store. We want to take care of our guest like nobody else takes care of them. We got a truck driver. There was an article written in New York Times but you don't throw away people. These guys, you got it, you're wearing it. Your tie, your shirt, whatever came on a truck, and these guys, they're great people. I've talked to a million of them. We want to be the place where they come that feels like home and we want to make a better day for the truck or the driver. It's a tough job. They work hard. They're waking their families. When they come into a pilot. It should feel like somewhat of an oasis. >> Right so, it's super clean I understand. >> Yeah, we try to make them clean. Remember If you're a truck driver and you're away for week's on end. You're going to shower at our locations and so the showers are cleaned and maintained after every shower. Nobody gets in a dirty shower. The rest it's challenging. We have 3000 people come through our doors every day at every location so it's challenging to keep the rest rooms in particular clean. But the showers are cleaned before anybody gets in them. >> And you own the real estate or you lease it? >> We own. >> Dave: Really. >> I'm sure we lease some of this. I've got a question for Dave. We own most of our-- >> But your in the real estate business too. >> Oh yeah. We're definitely in the real estate business. >> What about the data? How is the way in which you use data evolving? >> It's evolving very rapidly and we are a data rich company especially with respect to the professional driver which is the majority of our profitable business. They scan their loyalty card whenever they come. We have a 92% swipe rate and that's because they use those points to buy food, buy showers. >> Rebecca: They're rewarded. >> They're rewarded and it's lucrative to them. They're managing a business so they use that as currency. So that data provides us with the ability to solve. We needed utility along the customer journey. For example, we may know when a guy needs a shower and we may have a fuel buying advantage at a certain location. Offer them a free shower if he fuels at location X because it's beneficial for him and us. Okay we're going to give him a free shower or a free slice of pizza if we feel we have an advantage with respect to purchasing petroleum. >> You're building loyalty. >> Right and builds loyalty so that's on the customer side. >> Rebecca: That's the nudge they need to walk in-- >> To be able to use our digital platforms, our digital properties to take the data and drive behavior, and loyalty. It's really about loyalty. We want to give good things to our loyal customers, take good care of them and solve the problems they have. 'Cause they'll come back. And Jimmy says we want them to come back. He says it and we do things that are going to solve the problem they have. They're going to come back because it's the least friction. >> Are you using data for the logistics in any way, for these truckers in other ways? >> Yeah, that's not Inforum, however well for the truckers. We're using logistics with respect to how we procure petroleum. And I'm probably not going to get into a lot of that because we feel it's a competitive thing there with respect to how we do it. And we are investing a good bit of money into how we procure and manage how we distribute petroleum to our various locations. >> That's a data lever. You got advantage better than-- >> That's where a lot of data reach and we can use data very effectively. >> So data literally is oil. We had a guest on. >> Well data is abundant insights aren't necessarily so that's where you're making money. You've mentioned before Mike that you said you are more confident after you go through this migration, but Inforum was the right decision. What gives you that confidence? Can you double click on that? >> Yeah, it's a couple of things. Number one, and we talked about the technical debt right. So lifting everything to the cloud give me a unique opportunity to eliminate the technical debt 'cause we're not going to write it. We're going to stay current on the latest release of the software. Whereas if you looked around here, everybody will tell you they're behind releases, releases, releases on enterprise software that they've purchased from somebody else that's not in the cloud. So number one elimination of technical debt and staying current on the existing platforms. You really can't customize it. You can customize it within the tool so with the customization or configuration or extensibility carries along as they operate the software. That's the biggest events and I think being in the cloud. I was showing some data to my boss the other day regarding how our infrastructure investment has gone up. Really been able to manage the actual investment with the number of servers, VMware and all that we're running has grown exponentially. That's 'cause we hadn't retire anything. We're going to, with Inforum we're retire 26 platforms. They're going away. They'll be out of the infrastructure and it will be in the cloud. I don't have to manage anymore. >> You're getting rid of stuff, wow. >> Mike: Getting rid of it. >> GRS recall, that never happens in IT. >> I took personal responsibility for the decommissioning aspect of the project. >> I'm going to ask you another IT question is that latest release because you're in the cloud and you're multi-tenet, you have to go essentially into the next release. Does that create down stream problems for you. How do you plan for that? >> Well we're new into it, okay. We're working with Inforum on that and it's perfect now but they get it. We got to be careful when we make the release so we can be prepared for it. So far there have been upgrades and it's been nerve racking. A new release of code that we hadn't really tested or whatever but I think we'll get that route resolved. I said it's new, we got to become efficient in how that happens. We need a little bit of prior notice. >> Dave: Forced agile. >> Yeah, forced agile. Here it comes. (laughing) >> There's a lot of buzz about artificial intelligence here at Inforum. Where would you say Pilot Flying J is with regard to using artificial intelligence as part of your workforce. Giving your workers access to it and also more tools to make the right decision at the right time. >> I think it's at the stage now where it's really cool and it's somewhat of a buzz thing. AI when machine learning. I think it's going to be very relevant and probably not the too distant future. It's not on my immediate road map to worry about artificial intelligence. We thought about doing a project with IBM on fuel procurement and pricing with Lawson. It's just really not quite ready yet. What we can develop is deep insights with the data we have to make better decisions, and put power in the hands of our pricing team or our logistics team to make really good decisions. I think that's for us. Let's get that perfected and then we talked about the voice recognition that we heard yesterday. That I think is imminent and I think it's important for us and it's going to be on our road map because as a truck driver. I'm driving and if I can have the ability to ask questions of our app and purvey information back to that driver, without him having to touch his phone. There's a value of that. Most that has to be architected through the right type of data. How we structure our data to be able to access via natural speech but it is something that is on our road map. >> How large is your IT organization? Roughly. >> In number of people? >> Dave: Yeah. We have about 250 people in our IT organization but we do have a significant use of partners. >> And they're distributed or? >> No, they're in Tennessee. And for the notes popping now we use offshore resources with certain integration partners. We have a couple primary integration partners that we're using. >> So reason I'm asking so as you move to this cloud sass platform. How are you thinking about protecting your data and is it changing. >> It's a good question. And all of a sudden, for awhile there I think we do a great as securing it. We invested a significant amount of money protecting our data. I think I'd be naive to say that we could do a better job than Amazon web services. >> Dave: I would agree, no offense. >> And I think one of the gentleman was speaking yesterday said the same thing. And one of my guys looked at me says that's what we've been saying. I think there's always a risk. Security is a big deal especially with what's happened with one-acry and the subsequent problem. There's going to be more. I think that Amazon could be on top of it. I think together we can do a good job on security. It doesn't worry me anymore than it worries me everyday with respect to my own infrastructure. And it does worry me just not anymore. >> Great, well Mike, thanks so much for joining us. It's been a really enlightening conversation. >> Okay, thank you. >> I'm Rebecca Knight for Dave Ballante. We'll have more from Inforum in a little bit. (uptempo piano music)

>> Announcer: Live from the Javits Center in New York City, it's the theCUBE, covering Inforum 2017. Brought to you by Infor. (bright electronic music) >> We are back with theCUBE's coverage of Inforum 2017. I'm your host, Rebecca Knight, along with my cohost, Dave Vellante. We're joined by Barig Siraj and Nasser Bayram. They are both of the Zahid Group, out of Saudi Arabia. Thank you both so much for joining us. >> Good to be here, thank you for having us. >> So I want you to start out by just explaining to our viewers a little bit about what Zahid Group and Zahid Tractor, what you do. >> We are a large group based in Saudi Arabia. We're very diversified. We are mainly in heavy equipment, capital equipment business. We are the importer of Caterpillar machinery and Volvo trucks, Renault trucks, and many other products. More than 40 franchises. We have locations in more than 40 locations, or branches, more than 40 locations for their area, and we have about 4,000 employees, and we mainly focus on providing sales and after-sales services in the kingdom, with a big focus on after-sales. We pride ourselves to be the second to none when it comes down to after-sales services, and we strongly believe in technology and in digital transformation that is sweeping the world of business, and thus far, we embarked on this journey five years ago. >> So what does that digital transformation mean for your business, and generally, and then specifically for IT. Maybe you can start, Nasser. >> Well, first, we have to agree. The business model has changed. There are new business models that has disrupted every single industry landscape out there, and you have to be ready to change and accept that transformation, otherwise, you'll be left behind. The digital transformation takes you beyond managing an organization introducing an IT platform or technology. You have to change the way you think and your readiness to be able to manage where the future is going. If we look, we just attended this session, 52% of Fortune 500 companies in year 2000 no longer exist. They went out of business. In 2015, 55% of Fortune 500 companies lost money. There was no economic crisis or downfall. It simply missed the boat, or they did not, they were not very innovative in their digital strategy or thinking ahead, allowing their industry to be disrupted by people like Uber, Amazon, Alibaba, Souq, an other new entrants with very great innovative ideas and technologies. The old business model of cutting cost or restructuring an organization no longer works. You need to think differently and act differently, and hence, digital transformation becomes critical for your organization, and implementing an ERP platform, standardizing rationalization of your ERP platform, if you have more than one, like in our case, we have more than one, you have to have one standardized platform, one standardized processes, business processes, so that we have one source of data in order to be ready for the future where you can mine that data, have it be by analytics or business intelligence, in order to be able to better serve your customers and learning on about their behavior, about their trends, and how you can better position production services for them in the future to buy, and for you to remain profitable. >> So Barig, okay so now, that's, what Nasser just described, I'm inferring, is much more real-time, much faster, and more data. Your ability to analyze that data wherever it is, how do you, and the processes and people behind that as we talked about technology's the easy part even though some technology's even more complicated than ever. So what does that mean for the IT organization? >> Well for IT organization, we had, and we still have a legacy application built over 30 years. Now, and there we could not reap the benefits of the data mining, the standardization, even that just from AI capabilities on top of that. We cannot reap that until we have that standardized ERP Platform across all our companies. So basically, that's the tall order that was put on our plate, and what we have done, we started the journey. We're partly through it. We went live with two of our companies. We still have three more to go, and we've done it with lesser volume, allowing us to learn and therefore, once we reach our biggest volume company, we would have learned as an organization, not just applying the technology that even the personnel, the change management, the resistant pockets have to deal with all of that. >> Can you give an example of what you've learned along the way, becoming, as we said, it is so much about change management, and it's about getting people over this fear of change. Can you give an example of what you've learned, of what you're doing differently for the companies that have yet to have the rollout? >> The biggest learning experience we had, we just went live with one of our companies, called EJAR, which is a rental company. The success there of the learning, the success is a learning experience. We have a long journey for to go live with five companies, and this is the first one to go live. What we learned by doing that company first is the challenges of change management, how to support on live, challenge of data migration, data cleansing, readiness of the organization, not simply from change management perspective, but also from IT, legal, readiness of your documentation, the contracts, et cetera. It's a vast learning curve to overcome, and we're very happy that we took the strategic decision to go live once more company, so that we gain that experience, and that is the real success we got out of this project now. Now we better we feel we are in better position for the new companies to go forward with, when we go live, we learn so much about change management, where we failed and where we succeeded, we learn better about our readiness, whether it is Zahid Tractor, or Infor, or our IT, our infrastructure, our training program, our after go-live support, the war room was set up to support the go-live, and go in production. We've been two month in production. We're still having some challenges, but nothing that, there are no showstoppers, however, more and more every day, we learn more and more, and we are better positioned to go live with a bing bang on the big company. >> Nasser, as the executive in sort of leading this transformation, do you look for and demand new metrics, new types of KPIs that you want to see? >> Well, definitely, you do the whole thing because of the new metrics. The new metrics have to have built into it, not simply the traditional KPIs of your GPs and revenue and discount and so on, you need to look at customer behavior, customer analytics, pricing positioning, where you are going forward. In the old days, everybody would sit down around the table, say, "Hey, we're number one, okay?" That doesn't hold water anymore. You're number one in what? It's about number one in responding to customer requirements on that customer behavior. Today, with Amazon.com, many retail businesses are challenged, they're going out of business. How do you stop that business model? You can't. So how do you compete? You can. To do that, you have to have the right data in place, the right organization in place, and the right mindset to be able to lead your organization to compete in the new market space. >> Can you give our viewers some examples of the kind of data that you are deriving, in terms of this business analytics, in terms of understanding and deepening your understanding of customer behavior, and what customers want, and how it's changing, how you approach your customers and what you do for them. >> I'll give you a comparison. When we have a legacy systems, what you do at end of day, you extract your data, you transform it and you load it up to your data mart or data warehouse, and then you run your report, and if you're lucky, you have savvy users who can create their own reports on the fly, but with the way we're going with an integrated ERP solution and one standardized platform, we do hope we have the right analytics in place, and business intelligence in place, that we give our management the right data to make decisions, ready to make decisions. Not filtered data, not reports designed, and that takes me straight into your question on IT and ability to IT to deliver. There is no way for any IT organization to cope with the changes. Nowadays, when Amazon went live recently with Whole Food, it took them three to six, three to four months to deal with legal, to deal with retail, with pricing, with the announcement, the whole nine yards of marketing. How did they have their IT ready? That's a challenge. How can you do that in four to six month? That is the challenge in the future. If you don't have the right platform to do that, you will never be able to compete, and data analytics are critical for you to respond or predict the behavior of customer, so before a customer comes next time to the counter, you already have certain statistics that tell you what that person is ready for, and that takes you straight also into IoT. Your products, or our products now, are connected to the Internet. If you don't have IoT in place, connected to your back end, and your analytics, you won't be able to compete, and that would be the differentiator in the future. Those who could do that versus those who will continue to follow the old brick and mortar business model, restructuring and cost-cutting and whatnot. >> So your instrumenting your heavy equipment in the field, presumably, and that's, you're well down the road with that. That changes the data model, it changes the analytics model so I wonder if you could describe that a little bit. I mean, obviously you're processing data at the edge. How much data stays at the edge versus comes back to your central location, maybe you could add some color to that whole equation. >> Well the devices that are put on the machines, there are several ways of putting. The older models, you have, actually the PSSR has to actually go with his laptop, hook it up, suck the data, and bring it back for analytics. The newer models are more, are sending it to, directly to us, and enabling our, what I call tower, to do equipment monitoring, and be able to anticipate, we call up the customer and saying, "By the way." Actually tell the salesmen to call up the customer and saying, "You need to bring your machine in "because it's, you might face a failure "in so amount of time." So improving the customer side, that is, that is that part, but coming back to the organization change issue, we went from a legacy application that the branch managers waited until the end of the month to get the truth, to now being able to, seeing the performance on a daily basis, because they're seeing the truth because everything is connected, whereas before, whatever they did, they don't, their piece of the puzzle, they have a lot missing, and they, information that they waited until it show, send them back there, a report. >> And none of this takes place in the public cloud, is that right? >> No, it does, to add to that, the data is stored in the cloud. Customers have access to it, along with our SOS lab, which is oil sampling lab. They have access to the data to see what is happening, like predictive analysis of their machine performance, and as a result of analyzing the oil, plus any data collected from these machines. We do have cloud implementation. We just went live with our treasury management system. It is on the cloud, and it was our first deployment on the cloud, though the implementation of Infor today is still on-premise. Long-term, down the road, we may be looking at the cloud. >> I got to ask you, we hear Infor messaging about microspecialization, that last mile, all the hard stuff that nobody else wants to do. Is that something that you take advantage of in your industry, or is it? >> I'll give you an example. We utilize the implementation accelerator from Infor for the rental, and it's 77% of our processes map directly into that, so we, that enabled us, that, to have EJAR, which is a rental company, go much smoother. Now, we're working with Infor to enhance their equipment implementation accelerator, and it will be partly the same ratio, around 70% of the processes that we're going to go live with, are the standard processes in the product, out of the box, for the equipment rental, for the equipment business space. >> Our objective is to reduce customization as much as possible, go out of the box, or native, out of the box, as much as possible, but you have to accept the fact, depending on your business environment and some localization requirement, you have to do some customization. However we do have a governance in place, to make sure it's to the minimal. Otherwise, long-term, you'll be challenged with release management and change management and so on, and when you speak of the cloud, if you ever elect to go to the cloud, you can kiss customization goodbye. (Dave laughs) You have to be ready to adopt and adapt. >> And how about your security regime, as a result of the edge and IoT and now, cloud, how is that evolving? >> That's close to my heart. (laughs) >> Yeah, I'll bet, and probably the board's. >> Actually, well, (laughs) actually, interesting enough, many organization, like ourselves included, we invested so much money in building firewalls and security systems to protect what's behind the wall. Now with the cloud, well your most important data is no longer behind the wall. >> Rebecca: It's right there. >> It's outside the wall, so you have to have some kind of a hybrid security system, and you really have to pick the right partner who is hosting your cloud application, leasing your cloud application to you, so the challenge or the perspective of security, cybersecurity, changes drastically and totally, and your understanding of it has to change, otherwise, you just stay behind your own wall and guess what? You can end up locking yourself behind the wall, and you're going to miss the boat, but this does not mean that you'll let down your guard. You have to maintain your security awareness, you have to maintain your security diligence, and you should not underestimate the threats out there, because even if you are on the cloud, the biggest threat nowadays is through phishing. That's what we call the human firewall. Relegating the right awareness, the right education to your organization from within, to understand the threats and the danger of such a threat, otherwise, your password, that's how you access the cloud, you'll end up be compromised and guess what? So will be your data. >> Yes, so, Barig, Nasser, thank you so much for joining us. It's been great to have you on the program. >> Our pleasure. >> Thank you. >> Nasser: Thank you for hosting us, thank you. >> See you guys again, great, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from Inforum after this. 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(upbeat music) >> Live from Las Vegas it's theCUBE. Covering Oracle modern customer experience 2017. Brought to you by Oracle. (electronic music fades away) Welcome back everyone. We are here live in Las Vegas at the Mandalay Bay for Oracle's Modern Customer Experience Conference. I'm John Furrier with my co-host Peter Burris with theCUBE and our next guest is Brian Curran, Vice President of Strategy and Design with Oracle Cloud. Great to have you on theCUBE. Welcome to theCUBE. >> Thanks for having me. >> So you're a design and strategy person you've been the art and science of designing experiences. Not so much in the technology, Vasas Port, Vasas Server and yet innovation is the number one thing people talk about in the digital transformation certainly that's happening. But it's hard when you have all those Legacy stuff process, people, well that guy does that, that's his job over there and this guy runs it over there, so that's all coming together as we were talking about on our intro, Peter and I were talking about that. How do you get at the innovation when you engage with customers? When you walk in the door? >> It's funny. It's still a dirty word in companies innovation, right? I mean people are scared of it because the fancy word is innovation. The real word is change. And now you want to make changes in an organization and it's scary for people. And what I really do is I try to spend time with them trying to get them to understand that this is an art and a science. The science part is usually where you start first because I'm trying to get them to kind of go through the discipline of what it takes to do that. And it's really about getting the right people involved in that. And so I really try to spend my time saying look, let's find something really small to go work on, let's find a little problem that maybe you have and let me show you the art and science of getting from that understanding of the customer need all the way to hey I've got to wait to actually solve that will drive results for your business. >> It's interesting, the psychology of the customer is under a lot of stress, because as you said, it's a dirty word, innovation, because it means change but now it's interesting with Cloud you're seeing some of these technologies out there there's more pressure on top of that, it'speed they have to do it faster, so now you have a speed game going on and then agility and all these things people are seeing as use cases that okay, people are getting things right, but what do I do? And this is a lot of pressure for them. How does that add to the complication when you get to come in and say okay, we've got to change we've got to do it fast. You're roles might change. How do you take that? How do you walk through that? >> Well, first of all when you talk about the trends and the changes, what it's driving is these increased expectations so customers are dealing with an Amazon then they're coming back to another brand saying hey, how come you're experience is not like Amazon? So companies feel that pressure right now and they realize they can't wait six months, 12 months to go make the change, they've got to make it in six weeks or 12 weeks and so one of the things I'm a big believer is in rapid prototyping, get your point to a test where you can actually get it out in the market. So how do you frame something to really understand it in a couple days? How do you ideate in a couple days? How do you get everyone to understand what you're trying to do in a couple days and eventually get to a point where maybe five or six weeks, boy you're driving at that point. But the old days of going, hey, let's have a big strategy session and then we'll come through stuff in three to six months and nine months from now by then you're out of business. So we're really focused on trying to get people to understand it is about speed, it is about understanding and get to that point. >> But it comes back to the customer. Ultimately the design point is what experience do you want the customer to have with you. >> Correct. So in many respects the challenge is the customer does things and in a B2B setting they do things with a lot of other folks in their organization and they do things with the seller. In a B2C sense it's by themselves but they do things and they move through different context, what they do together. How do you help companies get focused on that singular element, it's what the customer is trying to do and how you want them to invite you to do it with them? >> To me, there's adjurity, right? There's a step-by-step process that the customer goes through in order to fulfill their need. And so it is about understanding that interaction that engagement and determining whether you're actually meeting the customer's need at that moment. Do you understand the context, do you understand the expectations, do you have all of the things that you need in order to understand that moment? But once you've chosen that moment, now what you're really focused on is the value equation. How do I fulfill that need in a way, drive that experience, that perception, that changes the customer's attitude so they think differently. That ultimately drives a different behavior from the customer that leads to a result that's different for the business. So businesses need to understand that value equation. Your job, number one job, is to fulfill customers needs. And I'm not talking about just the end need, but the need at every single moment along that life-cycle. And if you can understand and fulfill that need you can understand how to deliver results. Then it's just about plugging that formula in to get that done. >> So the question that I have for a lot of design folks, and it's kind of a big question but it ties back into some of the trends we're talking about. The Cloud, which is this thing that presumably allows companies to be in a lot of different places with at least a digital presence has been instrumental in presenting services to the communities to a lot of communities in new ways. >> Brian: Yes. >> To what degree do you think The Cloud and design thinking are reinforcing each other. By that I mean design thinking gets the business to focus on what's the value in use and The Cloud is presented as a service, not as a product. So is the design thinking The Cloud helping to move us from thinking about products to the services that they provide overall? >> Yeah, I would say design thinking first came out to actually drive product design but now it's starting to drive experiential design. The thing about The Cloud is that I can quickly go from rapid prototyping to putting it right in front of customers where before, using Legacy, armed premise capability, it would take me months to stand up something that I wanted to go do. So I think we're at the beautiful time for design, right? Is that all the disciplines around design the ability to really understand the customer to have that empathetic understanding to actually design experiences that are very relevant to that customer. But now to be able to actually take that experience and go multi-variant, AB tested immediately, not months from now but days from now and to get that learning, because part of great design thinking is not just the first generation, when I think design thinking I'm also thinking service design, lean, agile so I get the ability to take my minimal viable experience, not minimal viable product, get it in the market very quickly, get the learning from that, come back and make that iteration, put it back out on the market again So The Cloud allows you to do that on the fly where before you couldn't drive at that kind of speed. >> Talk about the commitment level, because that's a commit they have to make organizationally to iterate >> To fail? Well, to be ready for the iteration because you're throwing something out there that's also, I mean some people just got to get over, hey, the parachute will open. >> Brian: Yes. Kind of get over that fear and then once they're there they have to commit, they can't just leave it there. How do you walk through that with the customer because that to me, I think, is the trend that I see. Maybe it's different across different customers but the same organizational commitment. >> You've got to stop thinking about projects and you've got to start thinking about learning and engaging and so for me the process is really about going, hey, can I design something, can I actually test it very quickly, can I learn, and learn to me is fail. I mean I was involved in building the first Apple store. I will tell you the first Apple store was a complete failure (laughing) and it was the best learning that Apple could ever get in order to be able to use to build the next store, which was a much more successful piece. You have to build that in your DNA that says, if I'm fast then I can actually reduce my risk I can get to a point where I actually, be able to >> Yeah. learn very quickly and that I can go make that change come into place. >> That's great. I've got to ask you a question in terms of the customers because this is awesome you have a lot of experience with the customers. What's the pattern that emerges as you go out and look at the transformational heroes out there that are taking the transformation from the evolution of that? Is there a pattern that emerges, they kind of get nervous at first, then they snap in line here, and then things kind of happen. Can you share what you've seen as a pattern? >> So the pattern for innovators is usually they're just a little off-center and they have a little less fear than the rest of us about losing their job the next day and they're so passionate about what they want to do, they're willing to actually kind of push the envelope. What I find is that's the innovator. That's the guy. And by the way, usually not up high, usually down around the middle of the company. Now when they run into someone who will, on high also, is passionate about the change but not sure how to do it when the two of them come into combination, that innovator whose passionate, and that leader who understands they need to build that DNA, what I find is when those two come together, that is the pattern for success. So bottom's up, top's down innovation is really what works the best. I also find that the people who actually embrace discipline, embrace design thinking, embrace all of those aspects, but also have the arty kind of, hey, let's try some new things, let's be willing to kind of put our nose out there >> Yeah. I find the stodgy people who are not willing to make the change are the ones who actually just get stuck and we've seen those companies all go out of business, right? So the people who are willing to be leading-edge what's great is, though, if you see really great leaders, >> John: Yeah. they're also willing to be credible and authentic and get in front of audiences to say, "I designed this, it was a failure. >> Yeah. "I'm willing to actually now go do the next thing." And we see this from great leaders >> Yeah. from Starbucks on, that way I tried to do a bar in Starbucks and actually it didn't work, so we're going to go on to something else. >> Doesn't it also, I mean I agree with you totally, Brian having studied this a lot myself over the years. But it also means data. That you have to build measurement into everything >> Yes. Because the innovator doesn't get acknowledged or recognized by the leader if there isn't some data that >> Correct transmits message. You don't realize you're failing if you don't have data that alerts you early, before you double-down and triple-down, and quadruple-down on a bad idea. So how does the science of design thinking come into play here, because it's the designing-in, the measurements, the changes that become so crucial to actually moving us from just a good idea into something that actually manifests change. >> To me, the value equation is the first thing you work on, right? Which is the math. I need to understand the customer's needs and I need to understand the results that you're getting to. So I need to understand the attitudinal, the behavioral, the operational, the executional, all of those measurements so financial measurements, customer measurements, all those pieces. That data's crucial. I don't start, by the way, on any innovation projects until we have current-state understanding of that. The design is actually about how do I get that moving? How do I get that attitudinal, behavioral, operational, executional, financial movement by the design of what I'm doing. So data actually becomes more crucial. What's great too, about The Cloud, is that I actually have more access to data that I didn't have access to before and the data's in the hands of the innovator, not some other group I don't have to wait >> Right. a long time for analysis so I can literally go, here's our current state, let me go do A, B, multi-variant testing, wow, I got this change right here. Look at the pattern of behavior that I'm getting from customers. Now I say, okay, that's working, we will eventually get the results. And the fear for businesses in some cases, they need the financial result immediately, but now what we can say is actually, if you watch this track of behavior, you'll eventually get to the results. So if you're getting the behavioral change, you're actually >> With risk management to headed in the right direction. >> To your other point so there's also a piece of don't just jump to where's the ROI? >> Correct. (laughs) >> To, no, you're going to get there. >> Well we're talking about things like advocacy and retention and loyalty, well these are long-term behavioral things so you actually have to even go even further up and start measuring attitudinal, am I getting the movement for customers of how they talk about our brand and how they talk about engagement. That will eventually lead to the behaviors that I want, will eventually lead to results. So there is a leap of faith here >> Yes. that says if you understand the formula you should be able to actually drive the outcome by understanding the pieces across the formula. >> Well the good news is that by doing a better job of measurement, by having a discipline approach and think about design, how it leads innovation and getting leadership in place, you actually look at risk management as a way of thinking about what options am I going to buy in the future by failing now. >> Brian: Right. So I've learned something that says, well so now that group of options we're pairing-off. We still have this group of options. Let's pursue this group of options and when something didn't work, let's pair these options off >> Brian: Correct. And each time the risk of movement, of action goes down. >> Well the speed of it does too. >> Peter: Exactly. So time actually costs money, right? >> Right. And so if I can make quick bets, I can test them very quickly and I can determine what I should scale and what I should not scale. It's actually cheaper to de-risk that piece that way. >> Yeah, this is an interesting point you guys bring up the psychology and the DNA of the innovator. Whether it's the person in the trenches, who gets the data and makes the discovery and the innovation to the executive. But one area that we've seen is, and certainly this is always talked about at the conferences and stages, the No Manager. They're looking for ways to say no. >> Brian: Right. Then there's the guy who's looking to get to the yes. >> Brian: Yes. Take me through your experience on that, because you have to get to yes. >> Correct You have to find that person that's looking for yes. >> Correct. (laughs) In our process, by the way, we go from framing to ideating to share. And in share we believe that showcasing is really important. The ability to actually put your idea in front of someone the right way. But when people say, "No." They spell it N-O and I always spell it K-N-O-W, right? Most cases a leader is saying no because they don't actually have enough information. >> Yes. So if you framed, you really understand the customer and you've done a really good job of ideating, and you're really putting some proof of concepts together and getting them validated internally and externally and you've done the disciplined work >> John: Yeah. by the time you get to a decision, you should be able to give enough of that K-N-O-W >> Yeah to get that leader to move in the direction. >> John: Yeah, because they're looking for information, they're looking to learn. >> Peter: Which means you want an informed yes. >> Brian: Correct. Because if you don't get the informed yes, you're not getting the leader. You're really not getting the leader >> Brian: Correct. You're getting rubber-stamping >> But leaders ask great questions, right? >> and that's not what you want. >> Peter: That's right. >> And they're looking for other people to have the answers and they want to make sure that they went through the process, so when you bring me and ROI model, I want to say, well how did you put this together? How do you know that actually is going to get increased? And I back them up to well, wait a minute, here's the customer's attitude and here's the behavior and here's how I measured them. Okay, how do you know it's going to cost this much? I went through every activity, resource, partner, I've determined what I believe it's going to take. If you're doing the disciplined work, along with the artwork, you have a much better chance of actually getting things done. The other piece too, is that by the time you go to execute, even if you were wrong, you had so many measurements in place, that you're able to make those tweaks and iterations or decide to kill the innovation quick enough. So for leaders I'm saying don't make scale-decisions. Make test-decisions. Make very small, little bets, very quick, rapid prototyping and then make scale-decisions based-off of those tests. Now you've de-risked the whole process. >> Well you get clear visibility on what will the fly-wheel be for the scale, get the visibility on the metrics and unit economics or whatever >> Exactly. Alright, so final question since we have to wrap-up is what's the coolest thing that you've seen or been involved with of a customer? It could be an ah-ha moment, it could be you walked into a train wreck and you cleaned it up, or a big discovery or a big innovation. >> So I try not to share too many of the individual customers that I'm working with but I'll give you a story, it was in the Middle East, a customer that I'm working with, they were looking at, it's a communications company, they were looking at their bundling process of how do I sell wireless and broadband at the same time. So after going through the whole customer ethnography work and framing it, they realized that what they were doing is actually selling two silos that didn't make any sense. The customer just wanted connectivity. They didn't care whether it was broadband or wireless or anything, so they started thinking differently, which was maybe we should step back from this and actually stop trying to bundle or special-pricing based-off of the bundle, let's just sell connectivity. Let's just do away with the whole thought process, that it's actually two different things. >> John: And it worked? >> They're in the process of actually >> so they simplify it. going through that design. >> I thought you might say, "Well, here's how the American companies do it. Do it the exact opposite." (laughter) >> Yeah, because let's face it the process is not right but they actually got to the point, and by the way, we didn't come in with, okay, here's the idea that you should go do >> yeah they came to a conclusion that said, it's not unified billing, it's unified delivery of fulfilling the need. The customer's need is not broadband and wireless. The customer's need is connectivity. >> John: Yeah. If that's the need, we should be fulfilling that and not thinking about the duck below the water, whether that's broadband or this and that. >> That's a great point. A lot of companies just stay in their product lanes and say, "Buy the products." not what they want. >> Brian: Correct. >> Peter: Focus on the service. Alright. >> Brian: Correct. Alright, Brian Curran here inside theCUBE really laying-out some great insight into the design thinking, the role of the innovator, the role of organization. Congratulations on all your work, great insight here on theCUBE, appreciate it. Thanks for sharing the data, we learned a lot >> thanks for having me. We're going to iterate more with great interviews coming up from Oracle Modern Customer Experience after this short break. (electronic music)

>> Hey welcome back everybody, Jeff Frick here with theCUBE we're at the data privacy day at Twitter's world headquarters in downtown San Fransciso and we're really excited to get into it with our next guest Dr. Andreas Weigend, he is now at the Social Data Lab, used to be at Amazon, recently published author. Welcome. >> Good to be here, morning. >> Absolutely, so give us a little about what is Social Data Lab for people who aren't that familiar with it and what are you doing over at Berkeley? >> Alright, so let's start with what is social data? Social data is a data people create and share whether they know it or not and what that means is Twitter is explicit but also a geo location or maybe even just having photos about you. I was in Russia all day during the election day in the United States with Putin, and I have to say that people now share on Facebook what the KGB wouldn't have gotten out of them under torture. >> So did you ever see the Saturday Night Live sketch where they had a congressional hearing and the guy the CIA guy says, Facebook is the most successful project that we've ever launched, people tell us where they are who they're with and what they're going to do, share pictures, location, it's a pretty interesting sketch. >> Only be taught by Black Mirror, some of these episodes are absolutely amazing. >> People can't even watch is it what I have not seen I have to see but they're like that's just too crazy. Too real, too close to home. >> Yeah, so what was the question? >> So let's talk about your new book. >> Oh that was social data. >> Yeah social data >> Yeah, and so I call it actually social data revolution. Because if you think back, 10, 20 years ago we absolutely we doesn't mean just you and me, it means a billion people. They think about who they are, differently from 20 years ago, think Facebook as you mentioned. How we buy things, we buy things based on social data we buy things based on what other people say. Not on what some marketing department says. And even you know, the way we think about information I mean could you do a day without Google? >> No >> No. >> Could you go an hour without Google? >> An hour, yes, when I sleep. But some people actually they Google in their sleep. >> Well and they have their health tracker turned on while they sleep to tell them if they slept well. >> I actually find this super interesting. How dependent I am to know in the morning when I wake up before I can push a smiley face or the okay face or the frowny face, to first see how did I sleep? And if the cycles were nice up and down, then it must have been a good night. >> So it's interesting because the concept from all of these kind of biometric feedback loops is if you have the data, you can change your behavior based on the data, but on the other hand there is so much data and do we really change our behaivor based on the data? >> I think the question is a different one. The question is alright, we have all this data but how can we make sure that this data is used for us, not against us. Within a few hundred meters of here there's a company where employees were asked to wear a fit bit or tracking devices which retain more generally. And then one morning one employee came in after you know not having had an exactly solid night of sleep shall we say and his boss said I'm sorry but I just looked at your fit bit you know this is an important meeting, we can't have you at that meeting. Sorry about that. >> True story? >> Yeah >> Now that's interesting. So I think the fit bit angle is interesting when that is a requirement to have company issued health insurance and they see you've been sitting on your couch too much. Now how does that then run into the HIPPA regulations. >> You know, they have dog walkers here. I'm not sure where you live in San Francisco. But in the area many people have dogs. And I know that a couple of my neighbors they give when the dog walker comes to take the dog, they also give their phone to the dog walker so now it looks like they are taking regular walks and they're waiting for the discount from health insurance. >> Yeah, it's interesting. Works great for the person that does walk or gives their phone to the dog walker. But what about the person that doesn't, what about the person that doesn't stop at stop signs. What happens in a world on business models based on aggregated risk pooling when you can segment the individual? >> That is a very very very biased question. It's a question of fairness. So if we know everything about everybody what would it mean to be fair? As you said, insurance is built on pooling risk and that means by nature that there are things that we don't know about people. So maybe, we should propose lbotomy data lobotomy. So people actually have some part chopped off out of the data chopped off. So now we can pool again. >> Interesting >> Of course not, the answer is that we as society should come up with ways of coming up with objective functions, how do we weigh the person you know taking a walk and then it's easy to agree on the function then get the data and rank whatever insurance premium whatever you're talking about here rank that accordingly. So I really think it's a really important concept which actually goes back to my time at Amazon. Where we came up with fitness functions as we call it. And it takes a lot of work to have probably spent 50 hours on that with me going through groups and groups and groups figuring out, what do we want the fitness function to be like? You have to have the buy in of the groups you know it they just think you know that is some random management thing imposed on us, it's not going to happen. But if they understand that's the output they're managing for, then not bad. >> So I want to follow up on the Amazon piece because we're big fans of Jeff Hamilton and Jeff Bezzos who we go to AWS and it's interesting excuse me, James Hamilton when he talks about the resources that EWS can bring to bear around privacy and security and networking and all this massive infrastructure being built in terms of being able to protect privacy once you're in the quote un-quote public cloud versus people trying to execute that at the individual company level and you know RSA is in a couple of weeks the amount of crazy scary stuff that is coming in for people that want interviews around some of this crazy security stuff. When you look at kind of public cloud versus private cloud and privacy you know supported by a big heavy infrastructure like what EWS has versus a Joe Blow company you know trying to implement them themselves, how do you see that challenge. I mean I don't know how the person can compete with having the resourses again the aggregated resources pool that James Hamilton has to bring to barrel this problem. >> So I think we really need to distinguish two things. Which is security versus privacy. So for security there's no question in my mind that Joe Blow, with this little PC has not a chance against our Chinese or Russian friends. Is no question for me that Amazon or Google have way better security teams than anybody else can afford. Because it is really their bread and butter. And if there's a breach on that level then I think it is terrible for them. Just think about the Sony breach on a much smaller scale. That's a very different point from the point of privacy. And from the point about companies deliberately giving the data about you for targeting purposes for instance. And targeting purposes to other companies So I think for the cloud there I trust, I trust Google, I trust Amazon that they are doing hopefully a better job than the Russian hackers. I am more interested in the discussion on the value of data. Over the privacy discussion after all this is the world privacy day and there the question is what do people understand as the trade off they have, what they give in order to get something. People have talked about Google having this impossible irresistible value proposition that for all of those little data you get for instance I took Google Maps to get here, of course Google needs to know where I am to tell me to turn left at the intersection. And of course Google has to know where I want to be going. And Google knows that a bunch of other people are going there today, and you probably figure out that something interesting is happening here. >> Right >> And so those are the interesting questions from me. What do we do with data? What is the value of data? >> But A I don't really think people understand the amount of data that they're giving over and B I really don't think that they understand I mean now maybe they're starting to understand the value because of the value of companies like Google and Facebook that have the data. But do you see a shifting in A the awareness, and I think it's even worse with younger kids who just have lived on their mobile phones since the day they were conscious practically these days. Or will there be a value to >> Or will they even mobile before they were born? Children now come pre-loaded, because the parents take pictures of their children before they are born >> That's true. And you're right and the sonogram et cetera. But and then how has mobile changed this whole conversation because when I was on Facebook on my PC at home very different set of information than when it's connected to all the sensors in my mobile phone when Facebook is on my mobile phone really changes where I am how fast I'm moving, who I'm in proximity to it completely changed the privacy game. >> Yes so geo location and the ACLU here in Northern California chapter has a very good quote on that. "Geo location is really extremely powerful variable" Now what was the question? >> How has this whole privacy thing changed now with the proliferation of the mobile, and the other thing I would say, when you have kids that grew up with mobile and sharing on the young ones don't use Facebook anymore, Instagram, Snap Chat just kind of the notion of sharing and privacy relative to folks that you know wouldn't even give their credit card over the telephone not that long ago, much less type it into a keyboard, um do they really know the value do they really understand the value do they really get the implications when that's the world in which they've lived in. Most of them, you know they're just starting to enter the work force and haven't really felt the implications of that. >> So for me the value of data is how much the data impacts a decision. So for the side of the individual, if I have data about the restaurant, and that makes me decide whether to go there or to not go there. That is having an impact on my decision thus the data is valuable. For a company a decision whether to show me this offer or that offer that is how data is valued from the company. So that kind of should be quantified The value of the picture of my dog when I was a child. That is you know so valuable, I'm not talking about this. I'm very sort of rational here in terms of value of data as the impact is has on decisions. >> Do you see companies giving back more of that value to the providers of that data? Instead of you know just simple access to useful applications but obviously the value exceeds the value of the application they're giving you. >> So you use the term giving back and before you talked about kids giving up data. So I don't think that it is quite the right metaphor. So I know that metaphor come from the physical world. That sometimes has been data is in your oil and that indeed is a good metaphor when it comes to it needs to be refined to have value. But there are other elements where data is very different from oil and that is that I don't really give up data when I share and the company doesn't really give something back to me but it is much interesting exchange like a refinery that I put things in and now I get something not necessarily back I typically get something which is very different from what I gave because it has been combined with the data of a billion other people. And that is where the value lies, that my data gets combined with other peoples data in some cases it's impossible to actually take it out it's like a drop of ink, a drop in the ocean and it spreads out and you cannot say, oh I want my ink back. No, it's too late for that. But it's now spread out and that is a metaphor I think I have for data. So people say, you know I want to be in control of my data. I often think they don't have deep enough thought of what they mean by that. I want to change the conversation of people saying You what can I get by giving you the data? How can you help me make better decisions? How can I be empowered by the data which you are grabbing or which you are listening to that I produce. That is a conversation which I want to ask here at the Privacy Day. >> And that's happening with like Google Maps obviously you're exchanging the information, you're walking down the street, you're headed here they're telling you that there's a Starbucks on the corner if you want to pick up a coffee on the way. So that is already kind of happening right and that's why obviously Google has been so successful. Because they're giving you enough and you're giving them more and you get in this kind of virtuous cycle in terms of the information flow but clearly they're getting a lot more value than you are in terms of their you know based on their market capitalization you know, it's a very valuable thing in the aggregation. So it's almost like a one plus one makes three >> Yes. >> On their side. >> Yes, but it's a one trick pony ultimately. All of the money we make is rats. >> Right, right that's true. But in-- >> It's a good one to point out-- >> But then it begs the question too when we no longer ask but are just delivered that information. >> Yes, I have a friend Gam Dias and he runs a company called First Retail, and he makes the point that there will be no search anymore in a couple of years from now. What are you talking about? I search every day, but is it. Yes. But You know, you will get the things before you even think about it and with Google now a few years ago when other things, I think he is quite right. >> We're starting to see that, right where the cards come to you with a guess as to-- >> And it's not so complicated If let's see you go to the symphony you know, my phone knows that I'm at the symphony even if I turn it off, it know where I turned it off. And it knows when the symphony ends because there are like a thousand other people, so why not get Ubers, Lyfts closer there and amaze people by wow, your car is there already. You know that is always a joke what we have in Germany. In Germany we have a joke that says, Hey go for vacation in Poland your car is there already. But maybe I shouldn't tell those jokes. >> Let's talk about your book. So you've got a new book that came out >> Yeah >> Just recently released, it's called Data for the People. What's in it what should people expect, what motivated you to write the book? >> Well, I'm actually excited yesterday I got my first free copies not from the publisher and not from Amazon. Because they are going by the embargo by which is out next week. But Barnes and Noble-- >> They broke the embargo-- Barnes and Noble. Breaking news >> But three years of work and basically it is about trying to get people to embrace the data they create and to be empowered by the data they create. Lots of stories from companies I've worked with Lots of stories also from China, I have a house in China I spend a month or two months there every year for the last 15 years and the Chinese ecosystem is quite different from the US ecosystem and you of course know that the EU regulations are quite different from the US regulations. So, I wrote on what I think is interesting and I'm looking forward to actually rereading it because they told me I should reread it before I talk about it. >> Because when did you submit it? You probably submitted it-- >> Half a year >> Half a year ago, so yeah. Yeah. So it's available at Barnes and Noble and now Amazon >> It is available. I mean if you order it now, you'll get it by Monday. >> Alright, well Dr. Andreas Weigin thanks for taking a few minutes, we could go forever and ever but I think we've got to let you go back to the rest of the sessions. >> Thank you for having me. >> Alright, pleasure Jeff Frick, you're watching theCUBE see you next time.

>> Narrator: Live from Las Vegas, it's The Cube. Covering IBM Think 2018. Brought to you by IBM. >> Hello everyone and welcome to The Cube here at IBM Think in Las Vegas, the Mandalay Bay. I'm John Furrier, the host of The Cube. We're here in this Cube studio as a set for IBM Think. My next guest is Jennifer Shiin who's the founder of 8 Path Solutions. Twitter handle Jenn, J-S-H-I-N. Great to see you. Thanks for joining me. >> Yeah, happy to be here. >> I'm glad you stopped by. I wanted to get your thoughts. You're thought leader in the industry. You've been on multiple Cube panels. Thank you very much. And also Cube alumni. You know, IBM with the data center of the value proposition. The CEO's up on the stage today saying you got data, you got blockchain and you got AI, which is such the infrastructure of the future. And AI is the software of the future, data's at the middle. Dave and I were talking about that as the innovation sandwich. The data is being sandwiched between blockchain and AI, two super important things. And she also mentioned Moore's law. Faster, smaller, cheaper. Every 6 months doubling in speed and performance. And then Metcalfe's law, which is more of a network effect. Kind of teasing out token economics. You see kind of where the world's going. This is an interesting position from IBM. I like it. Is it real? >> Well it sounds very data sciency, right? You have the economics part, you have the networking. You have all these things in your plane. So I think it's very much in line with what you would expect if data science actually sustains (mumbles), which thankfully it has. >> Yeah. >> And I think the reality is you know, we like to boil things down into nice, simple concepts but in the real world when you're actually figuring it all out its going to be multiple effects. It's going to be, you know a lot of different things that interact. >> And they kind of really tease out their cloud strategy in a very elegant way. I mean they essentially said, 'Look we're into the cloud and we're not going to try to.' They didn't say it directly, but they basically said it. We're not going to compete with Amazon head-to-head. We're going to let our offerings to do the talking. We're going to use data and give customers choice with multi cloud. How does that jive for you? How does that work because at the end of the day I got to have business logics. I need applications. >> Yes. >> You know whether its blockchains, cryptocurrency or apps. The killer app's now money. >> Yep. >> If no one's making any money. >> Sure. >> No commerce is being done. >> Right. I mean I think it makes sense. You know, Amazon has such a strong hold in the infrastructure part, right? Being able to store your data elsewhere and have it be cloud. I don't think that was really IBM's core business. You know, a lot of I think their business model was built around business and business relationships and these days, one of the great things about all these data technologies is that one company doesn't have to do all of it, right? You have partnerships and actually partners so that you know, one company does AI. You partner with another company that has data. And that way you can actually both make money, right? There's more than enough work to go around and that much you can say having worked in data science teams right? If I can offload some of my work to different divisions, fantastic. That'd be great. Saves us time. You get to market faster. You can build things quicker. So I think that's one of the great things about what's happening with data these days, right? There's enough work to get around. >> And it's beautiful too because if you think about the concept that made cloud great is DevOps. Blockchain is an opportunity to use desensualization to take away a lot of inefficiencies. AI is also an automation opportunity to create value. So you got inefficiencies on block chains side and AI to create value, your thoughts and reaction to where that's going to go. You know, in light of the first death on a Uber self-driving car. Again, historic yesterday right? And so you know, the reality is right there. We're not perfect. >> Yeah. >> But there's a path. >> Well so most of its inefficiency out there. It's not the technology. It's all the people using technology, right? You broke the logic by putting in something you shouldn't have put in that data set, you know? The data's now dirty because you put in things that you know, the developer didn't think you'd put in there. So the reality is we're going to keep making mistakes and there will be more and more opportunities for new technologies to help you know, cheer that up. >> So I was talking to Rob Thomas, GM of the analytics team. You know Rob, great guy. He's smart. He's also an executive but he knows the tech. He and I were talking about this notion of data containers. So with Kubernetes now front and center as an orchestration layer for cloud and application workloads, IBM has an interesting announcement with this cloud private approach. Where data is the central thing in this. Because you've got things like GDPR out there and the regulatory environment not going to get any easier. You got blockchain crypto. That's a regulatory nightmare. We know a GDBR. That's a total nightmare. So this is happening, right? So what should customers be doing, in your experience? Customers are scratching their head. They don't want to make a wrong bet, but they need good data, good strategy. They need to do things differently. How do they get the best out of their data architecture knowing that there's hurdles and potential blockers in front of them? >> Well so I think you want to be careful of what you select. and how much are you going to be indebted to that one service that you selected, right? So if you're not sure yet maybe you don't want to invest all of your budget into this one thing you're not sure is going to be what you really want to be paying for a year or two, right? So I think being really open to how you're going to plan for things long term and thinking about where you can have some flexibility, whereas certain things you can't. For instance, if you're going to be in an industry that is going to be you know, strict on regulatory requirements right? Then you have less wiggle room than let's say an industry where that's not going to be an absolute necessary part of your technology. >> Let me ask you a question and being kind of a historian you know, what say one year is seven dog years or whatever the expression is in the data space. It just seems like yesterday that Hadoop was going to save the world. So that as kind of context, what is some technologies that just didn't pan out? Is the data link working? You know, what didn't work and what replaced it if you can make an observation? >> Well, so I think that's hard because I think the way I understood technology is probably not the way everyone else did right? I mean, you know at the end of the day it just is being a way to store data right? And just being able to use you know, more information store faster, but I'll tell you what I think is hilarious. I've seen people using Hadoop and then writing sequel queries the same way we did like ten plus years ago, same inefficiencies and they're not leveling the fact that it's Hadoop. Right? They're treating it like I want to create eight million tables and then use joins. So they're not really using the technology. I think that's probably the biggest disappointment is that without that knowledge sharing, without education you have people making the same mistakes you made when technology wasn't as efficient. >> I mean if you're a hammer, everything else is like a nail I guess if that's the expression. >> Right. >> On the exciting side, what are you excited about in technology right now? What are you looking at that's a you know, next 20 mile stare of potential goodness that could be coming out of the industry? >> So I think anytime you have better science, better measurements. So measurement's huge, right? If you think about media industry, right? Everyone's trying to measure. I think there was an article that came out about some of YouTube's failure about measurement, right? And I think in general like Facebook is you know, very well known for measurement. That's going to be really interesting to see, right? What methodologies come out in terms of how well can we measure? I think another one will be say, target advertising right? That's another huge market that you know, a lot of companies are going after. I think what's really going to be cool in the next few years is to see what people come up with, right? It's really the human ingenuity of it, right? We have the technology now. We have data engineers. What can we actually build? And how are we going to be able to partner to be able to do that? >> And there's new stacks that are developing. You think about the ecommerce stack. It's a 30 year old stack. AdTech and DNS and cookiing, now you've got social and network effects going on. You mentioned you know, the Metcalfe's law. So with all that, I want to get just your personal thoughts on blockchain. Beyond blockchain, token economics because there are a lot people who are doing stuff with crypto. But what's really kind of pointing as a mega trands standpoint is a new class of desensualized application developers are coming in. >> Right. >> Okay. They're dealing with data now on a desensualized basis. At the heart of that is the token economics, which is changing some of the business model dynamics. Have you seen anything? Your thoughts on token economics? >> So I haven't seen it from the economics standpoint. I've seen it from more of the algorithms and that standpoint. I actually have a good friend of mine, she's at Yale. And she actually runs the, she's executive director of their corporate law center. So I hear some from her on the legal side. I think what's really interesting is there's all these different arenas. Legal being a very important component in blockchain. As well as, from the mathematical standpoint. You know when I was in school way back when, we studied things like hash keys and you know, RSA keys and so from a math standpoint that's also a really cool aspect of it. So I think it's probably too early to say for sure what the economics part is going to actually look like. I think that's going to be a little more longterm. But what is exciting about this, is you actually see different parts of businesses, right? Not just the financial sector but also the legal sector and then you know say, the math and algorithms and you know. Having that integration of being able to build cooler things for that reason. >> Yeah the math's certainly exciting. Machine learning, obviously that's well documented. The growth and success of what, and certainly the interests are there. You seeing Amazon celebrating all the time. I just saw Werner Vogels, the CTO. Talking about another SageMaker, a success. They're looking at machine learning that way. You got Google with TensorFlow. You've got this goodness in these libraries now that are in the community. It's kind of a perfect storm of innovation. What's new in the ML world that developers are getting excited about that companies are harnessing for value? You seeing anything there? Can you share some commentary on the current machine learning trends? >> So I think a lot of companies have gotten a little more adjusted to the idea of ML. At the beginning everyone was like, 'Oh this is all new.' They loved the idea of it but they didn't really know what they were doing, right? Right now they know a little bit more. I think in general everyone thinks deep learning is really cool, neural networks. I think what's interesting though is everyone's trying to figure out where's the line. What's the different between AI versus machine learning versus deep learning versus neural networks. I think it's a little bit fun for me just to see everyone kind of struggle a little bit and actually even know the terminology so we can have a conversation. So I think all of that, right? Just anything related to that you know, when do you TensorFlow? What do you use it for? And then also say, from Google right? Which parts do you actually send through an API? I mean that's some of the conversations I've been having with people in the business industry, like which parts do you send through an API. Which parts do you actually have in house versus you know, having to outsource out? >> And that's really kind of your thinking there is what, around core competencies where people need to kind of own it and really build a core competency and then outsource where its more a femoral invalue. Is there a formula, I guess to know when to bring it in house and build around? >> Right. >> What's your thoughts there? >> Well part of it, I think is scalability. If you don't have the resources or the time, right? Sometimes time. If you don't have the time to build it in house, it does make sense actually to outsource it out. Also if you don't think that's part of your core business, developing that within house do you're spending all that money and resources to hire the best data scientists, may not be worth it because in fact the majority of your actual sales is with the sale department. I mean they're the ones that actually bring in that revenue. So I think it's finding a balance of what investment's actually worth it. >> And sometimes personnel could leave and you could be a big problem, you know. Someone walks about the door, gets another job because its a hot commodity to be. >> That's actually one of the big complaints I've heard is that we spend all this time investing in certain young people and then they leave. I think part of this is actually that human factor. How do you encourage them to stay? >> Let's talk about you. How did you get here? School? Interests? Did you go off the path? Did you come in from another vector? How did you get into what you're doing now and share a little bit about who you are? >> Yeah so I studied economics, mathematics, creative writing as an undergrad and statistics as a grad student. So you know, kind of perfect storm. >> Natural math, bring it all together. >> Yeah but you know its funny because I actually wrote about and talked about how data is going to be this big thing. This is like 2009, 2010 and people didn't think it was that important, you know? I was like next three to five years mathematicians are going to be a hot hire. No one believed me. So I ended up going, 'Okay well, the economy crashed.' I was in management consulting in finance, private equity hedge funds. Everyone swore like, if you do this you're going to be set for life, right? You're on the path. You'll make money and then the economy crashed. All the jobs went away. And I went, 'Maybe not the best career choice for me.' So I did what I did at companies. I looked at the market and I went, 'Where's their growth?' I saw tech had growth and decided I'm going to pick up some skills I've never had before, learn to develop more. I mean in the beginning I had no idea what an application development process was, right? I'm like, 'What does that mean to actually develop an application?' So the last few years I've really just been spending, just learning these things. What's really cool though is last year when my patents went through and I was able to actually able to launch something with Box at their keynote. That was really awesome. >> Awesome. >> So I became a long way from I think, have the academic knowledge to being able to apply it and then learn the technologies and then developing the technologies, which is a cool thing. >> Yeah and that's a good path because you came in with a clean sheet of paper. You didn't have any dogma of waterfall and all the technologies. So you kind of jumped in. Did you use like a cloud to build on? Was it Amazon? Was it? >> Oh that's funny too. Actually I do know Legacy's technology quite well because I was in corporate America before. Yeah, so like Sequel. For instance like when I started working data science, funny enough we didn't call it data science. We just called it like whatever you call it, you know. There was no data science term at that point. You know we didn't have that idea of whether to use R or Python. I mean I've used R over ten years, but it was for statistics. It was never for like actual data science work. And then we used Sequel in corporate America. When I was taking data it was like in 2012. Around then, everyone swore that no, no. They're going to programmers. Got to know programming. To which, I'm like really? In corporate America, we're going to have programmers? I mean think about how long it's going to take to get someone to learn any language and of course, now everyone's learning. It's on Sequel again right? So. >> Isn't it fun to like, when you see someone on Facebook or Linkdin, 'Oh man data's a new oil.' And then you say, 'Yeah here's a blog post I wrote in 2009.' >> Right. Yeah, exactly. Well so funny enough Ginni Rometty today was saying about exponential versus linear and that's one of the things I've been saying over the last year about because you know, you want exponential growth. Because linear anyone can do. That's a tweet. That's not really growth. >> Well we value your opinion. You've been great on The Cube. Great to help us out on those panels, got a great view. What's going on with your company? What are you working on now? What's exciting you these days? >> Yeah so one of the cool things we worked on, it's very much in line with what the IBM announcement was, so being smarter, right? So I developed some technology in the photo industry, digital assent management as well as being able to automate the renaming of files, right? So you think you probably a picture on your digital camera you never moved over because you, I remember the process. You open it, you rename it, you saved it. You open the next one. Takes forever. >> Sometimes its the same number. I got same version files. It's a nightmare. >> Exactly. So I basically automated that process of having all of that automatically renamed. So the demo that I did I had 120 photos renamed in less than two minutes, right? Just making it faster and smarter. So really developing technologies that you can actually use every day and leverage for things like photography and some cooler stuff with OCR, which is the long term goal. To be able to allow photographers to never touch the computer and have all of their clients photos automatically uploaded, renamed and sent to the right locations instantly. >> How did you get to start that app? Are you into photography or? >> No >> More of, I got a picture problem and I got to fix it? >> Well actually its funny. I had a photographer taking my picture and she showed me what she does, the process. And I went, 'This is not okay. You can do better than this.' So I can code so I basically went to Python and went, 'Alright I think this could work,' built a proof of concept and then decided to patent it. >> Awesome. Well congratulations on the patent. Final thoughts here about IBM Think? Overall sentiment of the show? Ginni's keynote. Did you get a chance to check anything out? What's the hallway conversations like? What are some of the things that you're hearing? >> So I think there's a general excitement about what might be coming, right? So a lot of the people who are here are actually here to, I think share notes. They want to know what everyone else is doing, so that's actually great. You get to see more people here who are actually interested in this technology. I think there's probably some questions about alignment, about where does everything fit. That seems to be a lot of the conversation here. It's much bigger this year as I'm sure you've noticed, right? It's a lot bigger so that's probably the biggest thing I've heard like there's so many more people than we expected there to be so. >> I like the big tent events. I'm a big fan of it. I think if I was going to be critical I would say, they should do a business event and do a technical one under the same kind of theme and bring more alpha geeks to the technical one and make this much more of a business conversation because the business transformation seems to be the hottest thing here but I want to get down in the weeds, you know? Get down and dirty so I would like to see two. That's my take. >> I think its really hard to cater to both. Like whenever I give a talk, I don't give a really nerdy talk to say a business crowd. I don't give a really business talk to a nerdy crowd, you know? >> It's hard. >> You just have to know, right? I think they both have a very different sensibility, so really if you want to have a successful talk. Generally you want both. >> Jennifer thanks so much for coming by and spending some time with The Cube. Great to see you. Thanks for sharing your insights. Jennifer Shin here inside The Cube at IBM Think 2018. I'm John Furrier, host of The Cube. We'll be back with more coverage after this short break.