(upbeat music) >> We're back with Steve McDowell, the Principal Analyst for Data & Storage at Moor Insights and Strategy. Hey Steve, great to have you on. Tell us a little bit about yourself. You've got a really interesting background and kind of a blend of engineering and strategy and what's your research focus? >> Yeah, so my research, my focus area is data and storage and all the things around that, whether it's On-Prem or Cloud or, you know, software as a service. My background, as you said, is a blend, right? I grew up as an engineer. I started off as an OS developer at IBM. I came up through the ranks and shifted over into corporate strategy and product marketing and product management, and I have been doing working as an industry analyst now for about five years at Moor Insights and Strategy. >> Steve, how do you see this playing out in the next three to five years? I mean, cloud got it all started, it's going to snowballing. You know, however you look at it percent of spending on storage that you think is going to land in as a service. How do you see the evolution here? >> IT buyers are looking at as a service and consumption base is, you know, a natural model. It extends the data center, brings all of the flexibility all of the goodness that I get from public cloud, but without all of the downside and uncertainty on cost and security and things like that, right, that also come with the public cloud and it's delivered by technology providers that I trust and that I know, and that I worked with, you know, for, in some cases, decades. So, I don't know that we have hard data on how much adoption there is of the model, but we do know that it's trending up, you know and every infrastructure provider at this point has some flavor of offering in the space. So, it's clearly popular with CIOs and IT practitioners alike. >> So Steve, organizations are at a they're different levels of maturity in their, their transformation journeys, and of course, as a result, they're going to have different storage needs that are aligned with their bottom line business objectives. From an IT buyer perspective, you may have data on this, even if it's anecdotal, where does storage as a service actually fit in and can it be a growth lever? >> It can absolutely be a growth leader. It gives me the flexibility as an IT architect to scale my business over time without worrying about how much money I have to invest in storage hardware. Right? So I, I get kind of, again, that cloud like flexibility in terms of procurement and deployment, but it gives me that control by oftentimes being on site within my premise, and then I manage it like a storage array that I own. So, you know, it's beautiful for for organizations that are scaling and it's equally nice for organizations that just want to manage and control cost over time. So, it's a model that makes a lot of sense and fits and certainly growing in adoption and in popularity. >> How about from a technology vendor perspective? You've worked for in the tech industry for companies? What do you think is going to define the winners and losers in this space? If you running strategy for a storage company, what would you say? >> I think the days of of a storage administrator managing, you know, rate levels and recovering and things of that sort are over, right? What these organizations like Pure delivering but they're offering is simplicity. It's a push button approach to deploying storage to the applications and workloads that need it, right? It becomes storage as a utility. So, it's not just the, you know the consumption based economic model of as a service. It's also the manageability that comes with that or the flexibility of management that comes with that. I can push a button, deploy bites to you know a workload that needs it, and it just becomes very simple, right, for the storage administrator, in a way that, you know kind of old school On-Prem storage can't really deliver. >> You know, I want to, I want to ask you, I mean I've been thinking about this because again, a lot of companies are, are you know, moving, hopping on the as a service bandwagon. I feel like, okay, in and of itself, that's not where the innovation lives. The innovation is going to come from making that singular experience from On-Prem to the clouds across clouds maybe eventually out to the edge. Do you, where do you see the innovation in as a service? >> Well, there's two levels of innovation, right? One, is business model innovation, right? I now have an organizational flexibility to build the infrastructure to support my digital transformation efforts, but on the product side and the offering side, it really is as you said, it's about the integration of experience. Every enterprise today touches a cloud in some way, shape or form. Right, I have data spread, not just in my data center, but at the edge, oftentimes in a public cloud, maybe a private cloud. I don't know where my data is, and it really lands on the storage providers to help me manage that and deliver that manageability experience to to the IT administrators. So, when I look at innovation in this space, you know, it's not just a a storage array and rack that I'm leasing, right, this is not another lease model. It's really fully integrated, you know end to end management of my data and yeah and all of the things around that. >> Yeah, so to your point about a lease model is if you're doing a lease, you know, yeah. You can shift CapEx to OPEX, but you're still committed to you have to over provision, whereas here and I wanted to ask you about that. It's an interesting model, right, because you got to read the fine print. Of course the fine print says you got to commit to some level typically, and then if, you know, if you go over you you charge for what you use and you can scale that back down and that's got to be very attractive for folks. I wonder if you we'll ever see like true cloud like consumption pricing, that has two edges to it, right? You see consumption based pricing in some of the software models and you know yeah, people like it, the, the lines of business maybe because they're paying in by the drink, but then procurement hates it because they don't have predictability. How do you see the pricing models? Do you see that maturing or do you think we're sort of locked in on, on where we're at? >> No, I do see that maturing, right? And when you work with a company like Pure to understand their consumption base and as a service and you know, when you work with a company like Pure to understand their consumption base and as a service offerings, it really is sitting down and understanding where your data needs are going to scale. Right? You buy in at a certain level, you have capacity planning. You can expand if you need to. You can shrink if you need to. So, it really does put more control in the hands of the IT buyer than, well certainly then traditional CapEx based On-Prem, but also more control than you would get, you know working with an Amazon or an Azure. >> Well the next 10 years, it ain't going to be like the last 10 years. Thanks Steve! We'll leave it there for now. Love to have you back. Look at, keep it right there. You don't want to miss this next segment where we dig into the customer angle. You're watching theCube production of At Your Storage Service, brought to you by PureStorage. One more. Okay, thanks Steve! We'll leave it there for now. I'd love to have you back. Keep it right there, At Your Storage Service continues in a moment. You're watching theCube. (upbeat music)

>>it is time to take a look at what piers up to from a slightly different perspective to help us do that as scott Sinclair, who is a senior analyst at the enterprise strategy group and scott, thanks for joining us here on the cube. Good to see you today. >>Great to see you >>All right. So let's let's jump into this first. We'll get to the announcement just a little bit first off. In terms of pure strategy as you've been watching this company evolve over over years now. How has it evolved? And and and then we'll move to the announcements and how that fits into the strategy. First off, let's just take them from your point of view. Where have they been and how are they doing? >>Yeah. You know, you know many people know a pure, maybe they don't know of their history is an all flash array. I think Pure has always been ever since they entered the I. T. Industry as as a pioneer. They're one of the early ones that said look we're going all in on the all flash array business and a focus on flash technology. Then there were early pioneers and things like evergreen and things like storage as a service capabilities for on premises storage and the entire time they've had a really you know almost streamlined focus on ease of use, which you know from the outside. I think everyone talks about ease of use and making things simple for I. T. But Pure has really made that almost like core as part of not only their product and they're designed but also part of their culture and one of the things and we'll get into this a little bit as we talk about the announcements but you know if you look at these announcements of where Pure is going there trying to expand that culture that DNA around ease of use or simplicity and expanding it beyond just storage or I. T. Operations and really trying to see okay how do we make the entire digital initiative process or the larger I. T. Operations journey simpler. And I think that's part of where pure is going is not just storage but focusing more on operations and data and making it easier for the entire experience. >>So so how do the announcements we're talking about uh whether three phases here and again we'll unpack those separately but just in general how did the announcements and you think fit into that strategy and fit into their view and your view really of of the market trends. >>You know I think one of the big trends is you know I. T. In terms for most businesses is it's not just an enabler anymore. It is actually in the driver's seat. Uh You know we see in our research at TsG we just did this study and I'm going to glance over my notes as I'm kind of talking but we see one of the things is more than half of businesses are identifying some portion of the revenue is coming from digital products for digital services. So data is part of the revenue chain for a majority of organizations according to what we're seeing in our research and so what that does is it puts I. T. Right in that core you know that core delivery model of where the faster I can operate the faster organizations can realize these revenue opportunities. So what what is that doing to tighty organizations? Well first off it makes your life a lot harder. It makes demands continue to increase. But also this old this old adage or this old narrative that I thi is about availability it's about resiliency, it's about keeping the lights on and ensuring that the business doesn't go down. Well none of that goes away but now I. T. Organizations are being measured on their ability to accelerate operations and in this world where everything is becoming more and more complex they're more demands, organizations are becoming more distributed. Application demands are becoming more diverse and they're growing and breath all of this means that more pressure is falling not only on the I. T. Operations but also on the instructor providers like pure storage to step up and make things even simpler with things like automation and supplication which again we're going to talk about but to help accelerate those operations. >>Yeah I mean if your devops these days I mean and you're talking about kind of these quandaries that people are in. Um but I mean what are what are these specific challenges do you think? I mean on the enterprise level here that that that pure is addressing? >>Yeah well so for example you talked about developers and you know dr going into you know that in particular I want to say let's say you know glancing my notes here, about two thirds of organizations say they're they're under pressure to accelerate their I. T. Initiatives due to pressures from specifically from devops teams as well as line of business teams. So what does that mean? It means that as organizations build up and try to accelerate either their revenue creation via the creation of software or products or things that that drive that support a devops team maybe it's improving customer experience for example as well as other line of business teams such as analytics and and trying to provide better insights and better decision making off of data. What that means is this traditional process of I. T. Operations of where you submit a trouble ticket and then it takes you know after a few days something happens. And they started doing analysis in terms of basically what ends up being multiple days or multiple weeks to end up to basically provision storage just takes too long. And so in these announcements what we're seeing is pure delivering solutions that are all about automating the back end services and delivering storage in a way that is designed to be easily and quickly consumed by the new consumers of I. T. The developers the line of business teams via a. P. S. Where you can write to a standard api and it goes across basically lots of different technologies and happens very quickly where a lot of the back end processes are automated and essentially making the storage invisible uh to these to these new consumers and all of that just delivers value because what what these groups are doing is now they can access that get the resources that they need and they don't have to know about what's happening behind the scenes which candidly they don't really know much about right now and they don't really care >>right. You know what I what I don't see what I don't know won't hurt me. Exactly and as we know it can. Um All right so let's let's look at the announcements Pure fusion. Um I think we're hearing about that just a little bit before earlier in the interview that day was conducting. But let's talk about pure fusion and your thoughts on that. >>Yeah confusion is what I was talking about a little bit where they're they're abstracting a lot of the storage capabilities and presenting it as an A P. I a consistent api that allows developers to provision things very quickly and where a lot of the back end services are automated and you know essentially invisible to developer and that is I mean it's it addresses where you know I kind of talked about this with some of the data that we just you know, some of our research stats that we just discussed but it's where a lot of organizations are going. The bottom line is you know we used to you know in a world where it services weren't growing as fast and where everything had to be resilient available, you could put a lot of personnel power or personal hours focused on okay, making sure every box and everything was checked prior to doing a new implementation and all that was designed to reduce risk and possibly optimize the environment, reduced costs. Now in this world of acceleration, what we've seen is organizations um need faster responsiveness from their I. T. Organizations. Well that's all well and good. But the problem is it's difficult to do all those back end processes and make sure that data is fully being protected or making sure that everything is happening behind the scenes the way it should be. And so this is again just mounting more and more pressure so with things like pure fusion, what they're doing is they're essentially automating a lot of that on the back end and really simplifying it and making so storage or I. T. Administrators can provide access to um to their line of business to development teams to leverage infrastructure a lot faster while still ensuring that that all those back end services, all those operations still happen. >>Port works, data services also announced and hearing from Dave from that perspective, maybe a game changer in terms of storage. So your take on that import works. >>I really liked what works. I've been following them ever since prior to the acquisition. Um, you know, one of the things that they were very early on is understanding the impact of microservices on the industry and really the importance of designing infrastructure around for that for that environment. I think what they're doing around data services is really intriguing. I think it's really intriguing first off for Pure as a company because it elevates their visibility to a new audience in the new persona that may not have been familiar with them. Right? As organizations are looking at one of the things that they're doing with this um, with this data services is essentially delivering a database as a service platform where you can go provision, you know, and stand up databases very quickly and again, similar to, we talked about fusion a lot of those back end processes are automated um really fascinating, again aligns directly with this acceleration need that we talked about, so, you know, huge value but it's really fascinating for Pure because it opens them up to, you know, hey, there's this whole new world of possible consumers that where there's, you know, that where they can get experience to really the ease of use of Pure is known for a lot of the capability. Support works is known for, but also just, you know, increase, you know, really the value that pure is able to deliver to some of these modern enterprises >>and just did briefly on the enhancements to Pure one also being announced today. Your take on those >>um you know, I like that as well. I think one of the things if I kind of go through the through the list is a lot of insights and intelligence in terms of uh new app, you know, sizing applications for the environment if I remember correctly um and more, you know, better capabilities to help ensure that your environment is optimized, which candidly is a is a top challenge around the organizations we talked about again, I keep hitting on this need to move faster faster, faster. One of the big disconnect what we've seen and we saw it very early when organizations were moving to for example public cloud services is this disconnect towards for this individual app. How many resources do I really need? And I think that's something that you know, vendors like Pure need to start integrating more and more intelligence and that's what my understanding is they're doing with Pure One, which is really impressive. >>Well, solid takes scott, we appreciate the time, thank you for your insights and what has been a big day for pure storage but thank you again for the time scott some clarity and her enterprise strategy group senior analyst there, let's go back to day Volonte now with more on the cube. >>Thanks for watching this cube program made possible by pure storage? I want to say in summary. You know, sometimes it's hard to squint through all the vendor noise on cloud and as a service and all the buzz words and acronyms in the market place. But as we said at the top, the cloud is changing. It's evolving, it's expanding to new locations. The operating model is increasingly defining the cloud. There's so much opportunity to build value on top of the massive infrastructure build out from the hyper scale is $200 billion dollars in Capex last year alone. This is not just true for technology vendors but organizations are building their own layer to take advantage of the cloud? Now of course technology is critical. So when you're evaluating technology solutions, look for the following first the ability of the solution to simplify your life. Can it abstract the underlying complexity of a cloud multiple clouds connect to on prem workloads in an experience that is substantially identical irrespective of location. Does the solution leverage cloud native technologies and innovations and primitives and a P. I. S. Or is it just a hosted stack? That's really not on the latest technology curve whether that's processor technology or virtualization or machine learning streaming? Open source tech et cetera. 3rd, How Programmable is the infrastructure? Does it make developers more productive? Does it accelerate time to value? Does it minimize rework and increase the quality of your output for? What's the business impact? Will customers stand up and talk about the solution and how it contributed to their digital transformation? By flexibly supporting emerging emerging data intensive workloads and evolving as their business rapidly changed. These are some of the important markers that we would suggest you monitor pure is obviously driving hard to optimize these and other areas. So watch closely and make your own assessment as to how what they and others are building will fit into your business Now as always, this content is available on demand at the cube dot net. So definitely check that out. This is day Volonte for jOHN walls and the entire cube team. Thanks for watching everybody. We'll see you next time.

>>Hi, welcome to this cube conversation. I'm Lisa Martin and pleased to welcome back. One of our cube alumni, Christian rowdy, the VP of technology strategy at Citrix Christian. Welcome back to the program. >>Thank you, Lisa. And thanks for having me. Great to see you again, and we'll be virtually at this time. >>Great to see you too. It's been a couple of years and quite a few things have changed since we got to sit down at synergy a couple of years together together. Citrix has an exciting new announcement. Let's unpack that. Talk me to me about what you're announcing and what it's going to deliver. >>Sure. You know, as you said, actually, I can't believe it's been a couple of years since we last saw each other. And I think, you know, time's kind of just disappeared within the pandemic. So it actually, as a result of some of those things that we've seen, you know, people get so tired of being stuck in the same place and tired of being on this constant stream of video. And one of the things that we wanted to do was, was actually a vital Citrix launch part, which is kind of our new announcement series that will be delivered via LinkedIn live. But he's really intended to be kind of a short burst approach to providing updates to some of them really important things that we're working on at Citrix. So, uh, hopefully, uh, people would love to say a reason and get some rich information from them. >>And there's going to be a series of three launchpad programs. Now we've seen so much change since the rapid pivot to work from home. Now this worked from anywhere hybrid environment. We've seen the, the massive adoption of cloud and SAS. We've also seen the threat landscape, the attack surface, just expand and expand. Talk to me about why Citrix is doing the launch pad series and then we'll go through each of the three series. >>Yeah, absolutely. So maybe I think just to set a little bit of context, you know, we, we were working on some pretty interesting things, uh, pre pandemic, you know, uh, as a result of the, kind of the, the evolution of Citrix as an organization, but perhaps more importantly, the journey that our customers were on globally, you know, every customer that we had in, in any industry across the world, we're all at various stages of their own digital transformation. And I think what the pandemic has done apart from all the really bad things, actually, if you look at it as a, perhaps one gleaming bit of light in the whole thing was that we've given organizations, whether we realize it or not the opportunity to try this huge remote work experiment. And I think what it has done above anything else has shown that remote work actually works. >>And so as a result of that, what we've seen coming out of the pandemic is that organizations are really going to use that as a springboard. So implement some new strategies, new technologies, and really drive the next generation of that business. So with one eye on that, I think if you were to categorize the three big things that we're looking at from a Citrix perspective, it's really about how to help, we'll continue to help our customers with that accelerated it modernization to really help them understand what it takes to have secure, flexible work in this new post pandemic world. And then also to think about productivity, what does productivity mean in a world of ever more distributed teams? And so the events that we're talking about and specifically the cloud one, we'll focus on some of the new offerings from Citrix, some of the new technologies and talk about the trends that we've seen within our customers. >>So, you know, one of the big things that Citrix has always been very proud of is our market leading position in virtual application and virtual desktop delivery. And even that itself has now begun to emerge into what we call desktop as a service. And there's a ton of new innovations that we've been working on in that space as well. But also if you think about what's happening in cloud, as you talked about, you know, the evolution of applications being from traditional on premises, wills to SAS applications, what we're also seeing is things like the network services that use to support those applications when they looked slightly different, which from a deployment perspective, and now all moving to cloud services, the security that you alluded to in terms of how complicated that is, but how important it is for it, organizations, those services also moving to cloud as the applications begin to look very differently in the future. So extremely excited about the cloud launch. Patino, we're going to talk a lot about those things that we're doing both in the public cloud, in the hybrid cloud. And I think it will resonate well with customers around the world. >>I think it will as well. And you mentioned there are glimmers of hope that we've seen in the last 18 months. And one of the things that this has proved is that work from home can be productive, can be successful. Employees need to be empowered to be able to do that. Let's go ahead and talk through the first, um, program accelerating it monetization. This is Tuesday, September 28th. Let's talk about some of the, of the Citrix innovations that you're going to be announcing. >>Yeah, so I mean, as I mentioned know, we, we, we think about sort of ecstatic. I see modernization in various parts. You know, we tend to start with the classic infrastructure and we've seen over the years that lots of infrastructure, you know, he's leaving the building. And by that we mean the traditional realms of on-premise data centers or co-location facilities, this constant evolution and migration of those services, uh, to, to infrastructure as a service providers from the huge cloud companies that are out there. And we can continue to see that as a, as a huge trend. Of course. Um, one of the things that off the back of that of course is our move from the traditional world of virtual desktops, which was a very on-premise concept into desktop as a service. So really the key around desktop as a service, it's a simplification, some cost optimization and the things that it are looking at in terms of how they can really bring things to the party for their organizations going forward. >>And of course, as we move into that world of everything being delivered as a service know, things like network services, security services, they almost follow. So some of the things that you'll hear about that is really around our application, delivering security and also our move from VDI to DAS. And, you know, you'll hear a lot about what we're doing with the world's leading cloud providers to really add more Citrix value or build on what we've already done with them, but lots, lots more, uh, and really support the, the, the notion of the, every customer is on a journey to cloud one way or the other. And of course, districts will be ready to help at any stage of that journey. >>Every customer is on the journey to cloud. And we've seen that accelerate so much in the last 18 months. Talk to me a little bit about if we, if we think of desktop as a service, as an evolution of VDI, is that what you're saying? >>Yeah. You know, you think about sort of the traditional VDI scenario was that your virtual desktops, where we were using instead of physical desktops, you know, in inside the usual office location, but during the pandemic, you know, we saw so many customers rely on moving to VDI, to cloud, for reasons of scalability and reasons of security, but then also needing to still in many cases, provide access to those sort of traditional physical PCs. And of course, Citrix has had solutions for that for fundamentally many, many years. Um, but what we're also seeing is that organizations are striving for simplicity. You know, the kind of the value of the desktop is being able to deliver it on demand to the end user securely from wherever they are in the world on whatever device they're on. And as we see this sort of establishment of these new working norms, and I'm not a great fan of the phrase, the new normal, I think we have a new now and that now will evolve. You know, they almost daily as we come through the other side of the pandemic. So the real key drivers for us there obviously flexibility, reliability, security, and also cost optimization, which of course is the bread and butter of most conversations we have with CIO and CTO is around the world. >>That's critical. And I'm going to borrow that, um, the new, now, if you don't mind, I'll cite you credit. But I like that. I agree that I hope this is not the new normal, but one of the things that we've seen in the new now on the security front is we've seen this massive increase in ransomware. Everybody went to work from home almost overnight. Suddenly you have millions of devices, IOT devices connecting to corporate networks. Security became the acceleration of security, became a huge challenge for customers in any organization globally. Let's talk about now the second announcement. This is going to be Tuesday, October 5th, empowering a secure distributed workforce. >>Yeah. And I, and I think you you've hit the nail on the head there. I think the one thing that was perhaps completely staggering to everybody was the speed in which organizations were forced to lock their employees out of the physical office locations and by force. I mean, for all the right reasons that are around the health and wellbeing. I mean, if I think back to my earlier career, you know, before I joined Citrix, I was in a large organization and we would, you know, perform these fire drills every so often where we would go through our disaster recovery business continuity plans and really play scenarios out. Like the office in London was unavailable or the office in LA was unavailable, but never once do I remember is doing every office. And every location is offline from tomorrow. And there's no negotiability. If you have a device at home, please use it. >>You know, we can't provide laptops quick enough, especially with the global chip shortage now as well. So whatever device you have, we'll do our best to, to make that secure. And I think there was, uh, an expectation that the employees would sort of play nicely in that scenario. But of course, you know, if you have your home device, you probably don't update it as much as a work device. So it really does require a new set of thinking. And of course, Citrix has been at the forefront of the zero trust evolution. Now the technologies that we have in place do permit remote work and have them for many years. But I think what we're seeing now is a slightly different type of remote work, you know, with different types of, of applications and devices, as you said, different locations, you know, needing to knit all of that together in a sort of a more contextual way so that we can understand, you know, combinations of the end user, their location, the types of applications that they're using the state of their devices, and sort of bring it all that together to really understand, you know, just exactly how much security needs to be applied. >>I think the traditional challenges are still there, you know, too much security and end users will find a way around it because it's not a good user experience. And, you know, perhaps too much user experience without the security leaves, big holes and big problems for organizations. So, yeah, I think this balancing act is really key. And of course, uh, as we go through the launch funnel security, we'll talk about some of the great innovations and solutions that are coming from central. >>You're right with the fact that, uh, you know, this rapid pivot security, the changes, the things that people are saying, the workforce needs to be empowered. You know, we saw this sudden dependence on all these SAS applications to communicate and to collaborate. We also saw with that rapid PennDOT to work from home ransomware, I was doing some research recently, Christian, and that's it, it's up almost 11 X just in the first half of 2021 DDoSs is massively up. People are, are working from home in environments that are just suddenly a bit chaotic. And it's challenging from a security perspective when you have so many distractions to be able to make sure that you're following all the right steps as an employee, um, that you're not clicking on nefarious links and that you're really doing your own due diligence. So having that zero trust and help from folks like Citrix is really key to this new. Now, as you say, >>It is, you know, the unfortunate thing is that wildlife, uh, no end user, or certainly I would hope that no one user would willingly cause a problem from a security perspective. I think just by the very nature of the way that end users thing, can they interact with links in emails or the, uh, you know, interact with attachments in emails? Unfortunately, relying on the human is always going to be the weakest link in the chain. And I think that's why we have to have new approaches to how we address the use of behavior. You know, can we actually, uh, you know, guide people in different ways. There are plenty of technologies that are out there now. And then many, many from Citrix that actually allow us to what we've lovingly said is, is to save the users from themselves. You know, we can't simply rely on every user to be diligent for every single email or every single link that they see. So, you know, being able to actually understand, you know, where the threats are as it relates to the end user and the likely interaction they have, and then being able to combat those threats in the technology at a seamless way is really part of the excited evolution of, of what we're doing with Citrix. And again, lots of great things to come as we go through the security. >>And the third announcement is around worker boosting worker productivity. That's been a challenge that we've all faced in the last 18 months of having, like I said, a minute ago, you know, people that have suddenly kids learning from home spouses, working people competing for bandwidth. Talk to me about some of the things that Citrix is doing to help those workers be more engaged, be plugged in and really be able to get their jobs done from anywhere. >>Yeah, well, you know, I mean, I can give you the benefit of my experience, you know, being, uh, in a, in a home office for, for, for almost 20 months has been completely the antithesis of the opposite of the rest of my career. You know, I've, I've always been very mobile, um, you know, kind of picking up different devices and using them for different things, just purely from a, you know, the perspective of what's most convenient to me. And I think, you know, if you take that and extrapolate it to, to every employee and every organization around the world who has had to invite work into their home, you know, and another soundbite that I use quite often now is that, you know, for the last 20 months, we really haven't been working from home. We've been living at work, you know, and, and, and it's, it's a fact, you know, we've probably done more hours than ever before. >>We've run the risk of burnout more than ever before. And, you know, prior to the pandemic, I know, talked to you and I talked about this very thing, uh, at synergy, you know, w we talked about the notion of needing to focus on employee experience and employee productivity. You know, we saw plenty of examples in customers with huge initiatives around employee experience and employee productivity. You know, CIO is partnering with HR leads and really trying to figure out a map, the employee journey, you know, what is it that they do every day? You know, how can we make their life easier? And perhaps interestingly, how can we reduce some of the mundane overhead, you know, approvals or requests or things that we see in our everyday life, but actually give the employees more time to be valuable and, and do great cognitive work, which is of course, what, what humans do best. >>And so, you know, you remember, we talked about the micro apps back then. We, we we'd completed the acquisition of Sappho, uh, as you and I talked last time when we unveiled micro apps and micro workflows, as a way to really help end users interact within Citrix workspace. So the systems that they use every day, but provide a new way to do that. And just earlier this year, we completed the acquisition and integration of Reich, which was a fantastic addition to the Citrix portfolio. And so we've really begun to think about, you know, how can we actually help employees to do their best work? You know, w w what are the new capabilities that we need within Citrix workspace? What are the new capabilities that we need in Reich? How do we bring all that together with some of the other solutions that we have Citrix Podio is a really interesting suite of productivity applications that we have really aimed at that number one problem, which is how can I get people to be productive, to stay engaged, to lower the burnout and help them do their best work. And I'm really, really excited because there's some fantastic things. So we announced that the work version of the launch pod, which is on October 12th, >>All of those are so critical. You know, I I've always said employee productivity employee is directly related to the customer experience. I've used Wrike myself before, um, for different projects and being able to have productivity tools that allow the employee to engage, to be able to empower them to move projects forward, especially in a time that is still somewhat chaotic is, is critical as is to your point, ensuring that there are the proper tools to facilitate folks so that they get what they need when they need it to help reduce burnout. That's been a big challenge. You're right. That the living at work thing is real, it's persisting, and we're going to be in this hybrid environment for some TBD amount of time longer. So having the ability to be empowered and productive in a secure way, leveraging cloud capabilities is really key. And it's exciting to hear what Citrix launchpad is going to announce over those three days and deliver. >>Yeah. You know, I, I would just say, you know, in, in, in sort of summary where we're, we're really excited about the three areas now, and they really do sort of all come together in some of those challenges that we talked about, you know, specifically around how we can help organizations to address that accelerated it modernization to drive secure, flexible work in the new now, and also to really reach that goal of having extremely productive, distributed teams as we come out the other side of the pandemic. So, you know, lots going on a fantastic time to, to be here and to talk to you and to be at Citrix, of course, with so many, you know, huge customer issues that we, that we have to solve. And we're really excited for the challenge. >>Excellent. And we all are looking forward to that, the Citrix launchpad series, Christian, where can folks go to register for these different programs? >>Yeah, sure. So it's pretty simple. So if we just go to HTTP bit dot Lee, bit dot L Y forward slash Citrix launchpad, and we can sign up through that. >>Excellent. I've already signed up. I'm looking forward to these series, this series, to learn more about what you guys are doing and kind of dig in double click on some of the things that you spoke about Christian. Thank you for joining me today, talking about the launch pad series and letting folks know where they can go to register. >>Thank you. Great to be on the great to see you again. >>Likewise, for Christian Riley, I'm Lisa Martin, you're watching a cube conversation.

>>Hi everyone. And welcome to data citizens. Thank you for making the time to join me and the over 5,000 data citizens like you that are looking to become United by data. My name is Jim Cushman. I serve as the chief product officer at Collibra. I have the benefit of sharing with you, the product, vision, and strategy of Culebra. There's several sections to this presentation, and I can't wait to share them with you. The first is a story of how we're taking a business user and making it possible for him or her data, use data and gain. And if it and insight from that data, without relying on anyone in the organization to write code or do the work for them next I'll share with you how Collibra will make it possible to manage metadata at scales, into the billions of assets. And again, load this into our software without writing any code third, I will demonstrate to you the integration we have already achieved with our newest product release it's data quality that's powered by machine learning. >>Right? Finally, you're going to hear about how Colibra has become the most universally available solution in the market. Now, we all know that data is a critical asset that can make or break an organization. Yet organizations struggle to capture the power of their data and many remain afraid of how their data could be misused and or abused. We also observe that the understanding of and access to data remains in the hands of just a small few, three out of every four companies continue to struggle to use data, to drive meaningful insights, all forward looking companies, looking for an advantage, a differentiator that will set them apart from their peers and competitors. What if you could improve your organization's productivity by just 5%, even a modest 5% productivity improvement compounded over a five-year period will make your organization 28% more productive. This will leave you with an overwhelming advantage over your competition and uniting your data. >>Litter employees with data is the key to your success. And dare I say, sorry to unlock this potential for increased productivity, huge competitive advantage organizations need to enable self-service access to data for everyday to literate knowledge worker. Our ultimate goal at Cleaver has always been to enable this self-service for our customers to empower every knowledge worker to access the data they need when they need it. But with the peace of mind that your data is governed insecure. Just to imagine if you had a single integrated solution that could deliver a seamless governed, no code user experience of delivering the right data to the right person at the right time, just as simply as ordering a pair of shoes online would be quite a magic trick and one that would place you and your organization on the fast track for success. Let me introduce you to our character here. >>Cliff cliff is that business analyst. He doesn't write code. He doesn't know Julian or R or sequel, but is data literate. When cliff has presented with data of high quality and can actually help find that data of high-quality cliff knows what to do with it. Well, we're going to expose cliff to our software and see how he can find the best data to solve his problem of the day, which is customer churn. Cliff is going to go out and find this information is going to bring it back to him. And he's going to analyze it in his favorite BI reporting tool. Tableau, of course, that could be Looker, could be power BI or any other of your favorites, but let's go ahead and get started and see how cliff can do this without any help from anyone in the organization. So cliff is going to log into Cleaver and being a business user. >>The first thing he's going to do is look for a business term. He looks for customer churn rate. Now, when he brings back a churn rate, it shows him the definition of churn rate and various other things that have been attributed to it such as data domains like product and customer in order. Now, cliff says, okay, customer is really important. So let me click on that and see what makes up customer definition. Cliff will scroll through a customer and find out the various data concepts attributes that make up the definition of customer and cliff knows that customer identifier is a really important aspect to this. It helps link all the data together. And so cliff is going to want to make sure that whatever source he brings actually has customer identifier in it. And that it's of high quality cliff is also interested in things such as email address and credit activity and credit card. >>But he's now going to say, okay, what data sets actually have customer as a data domain in, and by the way, why I'm doing it, what else has product and order information? That's again, relevant to the concept of customer churn. Now, as he goes on, he can actually filter down because there's a lot of different results that could potentially come back. And again, customer identifier was very important to cliff. So cliff, further filters on customer identifier any further does it on customer churn rate as well. This results in two different datasets that are available to cliff for selection, which one to use? Well, he's first presented with some data quality information you can see for customer analytics. It has a data quality score of 76. You can see for sales data enrichment dataset. It has a data quality score of 68. Something that he can see right at the front of the box of things that he's looking for, but let's dig in deeper because the contents really matter. >>So we see again the score of 76, but we actually have the chance to find out that this is something that's actually certified. And this is something that has a check mark. And so he knows someone he trusts is actually certified. This is a dataset. You'll see that there's 91 columns that make up this data set. And rather than sifting through all of that information, cliff is going to go ahead and say, well, okay, customer identifier is very important to me. Let me search through and see if I can find what it's data quality scores very quickly. He finds that using a fuzzy search and brings back and sees, wow, that's a really high data quality score of 98. Well, what's the alternative? Well, the data set is only has 68, but how about, uh, the customer identifier and quickly, he discovers that the data quality for that is only 70. >>So all things being equal, customer analytics is the better data set for what cliff needs to achieve. But now he wants to look and say, other people have used this, what have they had to say about it? And you can see there are various reviews for different reviews from peers of his, in the organization that have given it five stars. So this is encourages cliffs, a confidence that this is great data set to use. Now cliff wants to look a little bit more detailed before he finally commits to using this dataset. Cliff has the opportunity to look at it in the broader set. What are the things can I learn about customer analytics, such as what else is it related to? Who else uses it? Where did it come from? Where does it go and what actually happens to it? And so within our graph of information, we're able to show you a diagram. >>You can see the customer analytics actually comes from the CRM cloud system. And from there you can inherit some wonderful information. We know exactly what CRM cloud is about as an overall system. It's related to other logical models. And here you're actually seeing that it's related to a policy policy about PII or personally identifiable information. This gets cliff almost the immediate knowledge that there's going to be some customer information in this PII information that he's not going to be able to see given his user role in the organization. But cliff says, Hey, that's okay. I actually don't need to see somebody's name and social security number to do my work. I can actually work with other information in the data file. That'll actually help me understand why our customers churning in, what can I actually do about it. If we dig in deeper, we can see what is personally identifiable information that actually could cause issues. >>And as we scroll down and take a little bit of a focus on what we call or what you'll see here is customer phone, because we'll show that to you a little bit later, but these show the various information that once cliff actually has it fulfilled and delivered to him, he will see that it's actually massed and or redacted from his use. Now cliff might drive in deeper and see more information. And he says, you know what? Another piece that's important to me in my analysis is something called is churned. This is basically suggesting that has a customer actually churned. It's an important flag, of course, because that's the analysis that he's performing cliff sees that the score is a mere 65. That's not exactly a great data quality score, but cliff has, is kind of in a hurry. His bosses is, has come back and said, we need to have this information so we can take action. >>So he's not going to wait around to see if they can go through some long day to quality project before he pursues, but he is going to come up and use it. The speed of thinking. He's going to create a suggestion, an issue. He's going to submit this as a work queue item that actually informs others that are responsible for the quality of data. That there's an opportunity for improvement to this dataset that is highly reviewed, but it may be, it has room for improvement as cliff is actually typing in his explanation that he'll pass along. We can also see that the data quality is made up of multiple components, such as integrity, duplication, accuracy, consistency, and conformity. Um, we see that we can submit this, uh, issue and pass it through. And this will go to somebody else who can actually work on this. >>And we'll show that to you a little bit later, but back to cliff, cliff says, okay, I'd like to, I'd like to work with this dataset. So he adds it to his data basket. And just like if he's shopping online, cliff wants that kind of ability to just say, I want to just click once and be done with it. Now it is data and there's some sensitivity about it. And again, there's an owner of this data who you need to get permission from. So cliff is going to provide information to the owner to say, here's why I need this data. And how long do I need this data for starting on a certain date and ending on a certain date and ultimately, what purpose am I going to have with this data? Now, there are other things that cliff can choose to run. This one is how do you want this day to deliver to you? >>Now, you'll see down below, there are three options. One is borrow the other's lease and others by what does that mean? Well, borrow is this idea of, I don't want to have the data that's currently in this CRM, uh, cloud database moved somewhere. I don't want it to be persistent anywhere else. I just want to borrow it very short term to use in my Tablo report and then poof be gone. Cause I don't want to create any problems in my organization. Now you also see lease. Lease is a situation where you actually do need to take possession of the data, but only for a time box period of time, you don't need it for an indefinite amount of time. And ultimately buy is your ability to take possession of the data and have it in perpetuity. So we're going to go forward with our bar use case and cliff is going to submit this and all the fun starts there. >>So cliff has actually submitted the order and the owner, Joanna is actually going to receive the request for the order. Joanna, uh, opens up her task, UCS there's work to perform. It says, oh, okay, here's this there's work for me to perform. Now, Joanna has the ability to automate this using incorporated workflow that we have in Colibra. But for this situation, she's going to manually review that. Cliff wants to borrow a specific data set for a certain period of time. And he actually wants to be using in a Tablo context. So she reviews. It makes an approval and submits it this in turn, flips it back to cliff who says, okay, what obligations did I just take on in order to work for this data? And he reviews each of these data sharing agreements that you, as an organization would set up and say, what am I, uh, what are my restrictions for using this data site? >>As cliff accepts his notices, he now has triggered the process of what we would call fulfillment or a service broker. And in this situation we're doing a virtualization, uh, access, uh, for the borrow use case. Cliff suggests Tablo is his preferred BI and reporting tool. And you can see the various options that are available from power BI Looker size on ThoughtSpot. There are others that can be added over time. And from there, cliff now will be alerted the minute this data is available to them. So now we're running out and doing a distributed query to get the information and you see it returns back for raw view. Now what's really interesting is you'll see, the customer phone has a bunch of X's in it. If you remember that's PII. So it's actually being massed. So cliff can't actually see the raw data. Now cliff also wants to look at it in a Tablo report and can see the visualization layer, but you also see an incorporation of something we call Collibra on the go. >>Not only do we bring the data to the report, but then we tell you the reader, how to interpret the report. It could be that there's someone else who wants to use the very same report that cliff helped create, but they don't understand exactly all the things that cliff went through. So now they have the ability to get a full interpretation of what was this data that was used, where did it come from? And how do I actually interpret some of the fields that I see on this report? Really a clever combination of bringing the data to you and showing you how to use it. Cliff can also see this as a registered asset within a Colibra. So the next shopper comes through might actually, instead of shopping for the dataset might actually shop for the report itself. And the report is connected with the data set he used. >>So now they have a full bill of materials to run a customer Shern report and schedule it anytime they want. So now we've turned cliff actually into a creator of data assets, and this is where intelligent, it gets more intelligence and that's really what we call data intelligence. So let's go back through that magic trick that we just did with cliff. So cliff went into the software, not knowing if the source of data that he was looking for for customer product sales was even available to him. He went in very quickly and searched and found his dataset, use facts and facets to filter down to exactly what was available. Compare to contrast the options that were there actually made an observation that there actually wasn't enough data quality around a certain thing was important to him, created an idea, or basically a suggestion for somebody to follow up on was able to put that into his shopping basket checkout and have it delivered to his front door. >>I mean, that's a bit of a magic trick, right? So, uh, cliff was successful in finding data that he wanted and having it, deliver it to him. And then in his preferred model, he was able to look at it into Tableau. All right. So let's talk about how we're going to make this vision a reality. So our first section here is about performance and scale, but it's also about codeless database registration. How did we get all that stuff into the data catalog and available for, uh, cliff to find? So allow us to introduce you to what we call the asset life cycle and some of the largest organizations in the world. They might have upwards of a billion data assets. These are columns and tables, reports, API, APIs, algorithms, et cetera. These are very high volume and quite technical and far more information than a business user like cliff might want to be engaged with those very same really large organizations may have upwards of say, 20 to 25 million that are critical data sources and data assets, things that they do need to highly curate and make available. >>But through that as a bit of a distillation, a lifecycle of different things you might want to do along that. And so we're going to share with you how you can actually automatically register these sources, deal with these very large volumes at speed and at scale, and actually make it available with just a level of information you need to govern and protect, but also make it available for opportunistic use cases, such as the one we presented with cliff. So as you recall, when cliff was actually trying to look for his dataset, he identified that the is churned, uh, data at your was of low quality. So he passed this over to Eliza, who's a data steward and she actually receives this work queue in a collaborative fashion. And she has to review, what is the request? If you recall, this was the request to improve the data quality for his churn. >>Now she needs to familiarize herself with what cliff was observing when he was doing his shopping experience. So she digs in and wants to look at the quality that he was observing and sure enough, as she goes down and it looks at his churn, she sees that it was a low 65% and now understands exactly what cliff was referring to. She says, aha, okay. I need to get help. I need to decide whether I have a data quality project to fix the data, or should I see if there's another data set in the organization that has better, uh, data for this. And so she creates a queue that can go over to one of her colleagues who really focuses on data quality. She submits this request and it goes over to, uh, her colleague, John who's really familiar with data quality. So John actually receives the request from Eliza and you'll see a task showing up in his queue. >>He opens up the request and finds out that Eliza's asking if there's another source out there that actually has good is churned, uh, data available. Now he actually knows quite a bit about the quality of information sturdiness. So he goes into the data quality console and does a quick look for a dataset that he's familiar with called customer product sales. He quickly scrolls down and finds out the one that's actually been published. That's the one he was looking for and he opens it up to find out more information. What data sets are, what columns are actually in there. And he goes down to find his churned is in fact, one of the attributes in there. It actually does have active rules that are associated with it to manage the quality. And so he says, well, let's look in more detail and find out what is the quality of this dataset? >>Oh, it's 86. This is a dramatic improvement over what we've seen before. So we can see again, it's trended quite nicely over time each day, it hasn't actually degraded in performance. So we actually responds back to realize and say, this data set, uh, is actually the data set that you want to bring in. It really will improve. And you'll see that he refers to the refined database within the CRM cloud solution. Once he actually submits this, it goes back to Eliza and she's able to continue her work. Now when Eliza actually brings this back open, she's able to very quickly go into the database registration process for her. She very quickly goes into the CRM cloud, selects the community, to which she wants to register this, uh, data set into the schemas community. And the CRM cloud is the system that she wants to load it in. >>And the refined is the database that John told her that she should bring in. After a quick description, she's able to click register. And this triggers that automatic codeless process of going out to the dataset and bringing back its metadata. Now metadata is great, but it's not the end all be all. There's a lot of other values that she really cares about as she's actually registering this dataset and synchronizing the metadata she's also then asked, would you like to bring in quality information? And so she'll go out and say, yes, of course, I want to enable the quality information from CRM refined. I also want to bring back lineage information to associate with this metadata. And I also want to select profiling and classification information. Now when she actually selects it, she can also say, how often do you want to synchronize this? This is a daily, weekly, monthly kind of update. >>That's part of the change data capture process. Again, all automated without the require of actually writing code. So she's actually run this process. Now, after this loads in, she can then open up this new registered, uh, dataset and actually look and see if it actually has achieved the problem that cliff set her out on, which was improved data quality. So looking into the data quality for the is churn capability shows her that she has fantastic quality. It's at a hundred, it's exactly what she was looking for. So she can with confidence actually, uh, suggest that it's done, but she did notice something and something that she wants to tell John, which is there's a couple of data quality checks that seem to be missing from this dataset. So again, in a collaborative fashion, she can pass that information, uh, for validity and completeness to say, you know what, check for NOLs and MPS and send that back. >>So she submits this onto John to work on. And John now has a work queue in his task force, but remember she's been working in this task forklift and because she actually has actually added a much better source for his churn information, she's going to update that test that was sent to her to notify cliff that the work has actually been done and that she actually has a really good data set in there. In fact, if you recall, it was 100% in terms of its data quality. So this will really make life a lot easier for cliff. Once he receives that data and processes, the churn report analysis next time. So let's talk about these audacious performance goals that we have in mind. Now today, we actually have really strong performance and amazing usability. Our customers continue to tell us how great our usability is, but they keep asking for more well, we've decided to present to you. >>Something you can start to bank on. This is the performance you can expect from us on the highly curated assets that are available for the business users, as well as the technical and lineage assets that are more available for the developer uses and for things that are more warehoused based, you'll see in Q1, uh, our Q2 of this year, we're making available 5 million curated assets. Now you might be out there saying, Hey, I'm already using the software and I've got over 20 million already. That's fair. We do. We have customers that are actually well over 20 million in terms of assets they're managing, but we wanted to present this to you with zero conditions, no limitations we wouldn't talk about, well, it depends, et cetera. This is without any conditions. That's what we can offer you without fail. And yes, it can go higher and higher. We're also talking about the speed with which you can ingest the data right now, we're ingesting somewhere around 50,000 to a hundred thousand records per and of course, yes, you've probably seen it go quite a bit faster, but we are assuring you that that's the case, but what's really impressive is right now, we can also, uh, help you manage 250 million technical assets and we can load it at a speed of 25 million for our, and you can see how over the next 18 months about every two quarters, we show you dramatic improvements, more than doubling of these. >>For most of them leading up to the end of 2022, we're actually handling over a billion technical lineage assets and we're loading at a hundred million per hour. That sets the mark for the industry. Earlier this year, we announced a recent acquisition Al DQ. LDQ brought to us machine learning based data quality. We're now able to introduce to you Collibra data quality, the first integrated approach to Al DQ and Culebra. We've got a demo to follow. I'm really excited to share it with you. Let's get started. So Eliza submitted a task for John to work on, remember to add checks for no and for empty. So John picks up this task very quickly and looks and sees what's what's the request. And from there says, ah, yes, we do have a quality check issue when we look at these churns. So he jumps over to the data quality console and says, I need to create a new data quality test. >>So cliff is able to go in, uh, to the solution and, uh, set up quick rules, automated rules. Uh, he could inherit rules from other things, but it starts with first identifying what is the data source that he needs to connect to, to perform this. And so he chooses the CRM refined data set that was most recently, uh, registered by Lysa. You'll see the same score of 86 was the quality score for the dataset. And you'll also see, there are four rules that are associated underneath this. Now there are various checks that, uh, that John can establish on this, but remember, this is a fairly easy request that he receives from Eliza. So he's going to go in and choose the actual field, uh, is churned. Uh, and from there identify quick rules of, uh, an empty check and that quickly sets up the rules for him. >>And also the null check equally fast. This one's established and analyzes all the data in there. And this sets up the baseline of data quality, uh, for this. Now this data, once it's captured then is periodically brought back to the catalog. So it's available to not only Eliza, but also to cliff next time he, uh, where to shop in the environment. As we look through the rules that were created through that very simple user experience, you can see the one for is empty and is no that we're set up. Now, these are various, uh, styles that can be set up either manually, or you can set them up through machine learning again, or you can inherit them. But the key is to track these, uh, rule creation in the metrics that are generated from these rules so that it can be brought back to the catalog and then used in meaningful context, by someone who's shopping and the confidence that this has neither empty nor no fields, at least most of them don't well now give a confidence as you go forward. >>And as you can see, those checks have now been entered in and you can see that it's a hundred percent quality score for the Knoll check. So with confidence now, John can actually respond back to Eliza and say, I've actually inserted them they're up and running. And, uh, you're in good status. So that was pretty amazing integration, right? And four months after our acquisition, we've already brought that level of integration between, uh, Colibra, uh, data intelligence, cloud, and data quality. Now it doesn't stop there. We have really impressive and high site set early next year. We're getting introduced a fully immersive experience where customers can work within Culebra and actually bring the data quality information all the way in as well as start to manipulate the rules and generate the machine learning rules. On top of it, all of that will be a deeply immersive experience. >>We also have something really clever coming, which we call continuous data profiling, where we bring the power of data quality all the way into the database. So it's continuously running and always making that data available for you. Now, I'd also like to share with you one of the reasons why we are the most universally available software solutions in data intelligence. We've already announced that we're available on AWS and Google cloud prior, but today we can announce to you in Q3, we're going to be, um, available on Microsoft Azure as well. Now it's not just these three cloud providers that were available on we've also become available on each of their marketplaces. So if you are buying our software, you can actually go out and achieve that same purchase from their marketplace and achieve your financial objectives as well. We're very excited about this. These are very important partners for, uh, for our, for us. >>Now, I'd also like to introduce you our system integrators, without them. There's no way we could actually achieve our objectives of growing so rapidly and dealing with the demand that you customers have had Accenture, Deloitte emphasis, and even others have been instrumental in making sure that we can serve your needs when you need them. Uh, and so it's been a big part of our growth and will be a continued part of our growth as well. And finally, I'd like to actually introduce you to our product showcases where we can go into absolute detail on many of the topics I talked about today, such as data governance with Arco or data privacy with Sergio or data quality with Brian and finally catalog with Peter. Again, I'd like to thank you all for joining us. Uh, and we really look forward to hearing your feedback. Thank you..

>>Hello, everyone. And welcome back to our wall to wall coverage of the data Cloud Summit. This is Dave a lot. And we're seeing the emergence of a next generation workload in the cloud were more facile access and governed. Sharing of data is accelerating. Time to insights and action. All right, allow me to introduce our next guest. Amy Irwin is here. She's the vice president of strategy for experience. And Matt Glickman is VP customer product strategy it snowflake with an emphasis on financial services. Folks, welcome to the Cube. Thanks so much for coming on. >>Thanks for >>having us >>nice to be here. Hey, >>So, Amy, I mean, obviously 2020 has been pretty unique and crazy and challenging time for a lot of people. I don't know why I've been checking my credit score a lot more for some reason. On the app I love the app I got hacked. I had a lock it the other day I locked my credit. Somebody tried to dio on and it worked. I was so happy. So thank you for that. But so we know experience, but there's a ton of data behind what you do. I wonder if you could share kind of where you sit in the data space and how you've seen organizations leverage data up to this point. And really, if you could address maybe some of the changes that you're seeing as a result of the pandemic, that would be great. >>Sure, sure. Well, Azaz, you mentioned experience Eyes best known as a credit bureau. Uh, I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions and better understand and connect with consumers. Eso we offer markers products around data identity activation measurement. We have a consumer view data file that's based on off line P I and contains demographic interest, transaction data and other attributes on about 300 million people in the U. S. Uh, and on the identity side, we've always been known for our safe haven or privacy friendly matching that allows marketers to connect their first party data to experience or other third parties. Uh, but in today's world, with the growth and importance of digital advertising and consumer behavior shifting to digital, uh, experience also is working to connect that offline data to the digital world for a complete view of the customer you mentioned co vid, um, we actually we serve many different verticals. And what we're seeing from our clients during co vid is that there's a bearing impact of the pandemic. The common theme is that those that have successfully pivoted their businesses to digital are doing much better. Uh, as we all know, Kobe accelerated very strong trends to digital both in the commerce and immediate viewing habits. We work with a lot of retailers. Retail is a tale of two cities with big box and grocery growing and apparel retail really struggling. We've helped our clients leveraging our data to better understand the shifts in these consumer behaviors and better segment their customers during this really challenging time. Eso think about there's there's a group of customers that is still staying home that is sheltered in place. There's a group of customers starting that significantly varied their consumer behavior, but it's starting to venture out a little. And then there's a group of customers that's doing largely what they did before and a somewhat modified fashion. So we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups. And we're also helping them with at risk audiences. Eso That's more on the financial side. Which of your customers air really struggling? Do the endemic And how do you respond? >>It's awesome, thank you. You know, it's it's funny. I mean somebody I saw Twitter poll today asking if we measure our screen time and I said, Oh my no eso Matt, let me ask you. You spend a ton of time in financial services. You really kind of cut your teeth there, and it's always been very data oriented. You've seen a lot of changes tell us about how your customers are bringing together data, the skills that people obviously a big part of the equation and applications to really put data at the center of their universe. What's new and different that these companies were getting out of the investments in data and skills. >>That's a great question. Um, the acceleration that Amy mentioned Israel, Um, we're seeing it particularly this year, but I think even in the past few years, the reluctance of customers to embrace the cloud is behind us. And now there's this massive acceleration to be able to go faster on, and in some ways the new entrance into this category. Have an advantage versus, you know, the companies that have been in the space within its financial services or beyond. Um, and in a lot of ways they are are seeing the cloud and services like snowflake as a way toe not only catch up but leapfrog your competitors and really deliver a differentiated experience to your customers to your business, internally or externally. Um, and this past, you know, however long this crisis has been going on, has really only accelerated that, because now there's a new demand. Understand your customer better your your business better with with your traditional data sources and also new alternative data sources, Um, and also be able to take a pulse. One of things that we learned which was you know, I opening experience was as the crisis unfolded, one of our data partners decided to take the data sets about where the cases where were happening from the Johns Hopkins and World Health Organization and put that on our platform, and it became a runaway hit where now with thousands of our customers overnight, we're using this data to understand how their business was doing versus how the crisis was unfolding in real time. On this has been a game changer, and I think it's only it's only scratching the surface of what now the world will be able to do when data is really at their fingertips. You're not hindered by your legacy platforms. >>I wrote about that back in the early days of the pandemic when you guys did that and talked about some of the changes that you guys enabled and and, you know you're right about Cloud. I mean, financial services. Cloud used to be an evil word, and now it's almost become a mandate. Amy, I >>wonder if you >>could tell us a little bit more about what? What, you know your customers they're having to work through in order to achieve some of these outcomes. I mean, I'm interested in the starting point. I've been talking a lot and writing a lot on talking to practitioners about what I call the data lifecycle. Sometimes people call it the data pipeline. It za complicated matter, but those customers and companies that can put data at the center and really treat that pipeline is the heart of their organization, If you will, really succeeding. What are you seeing and what really is the starting point there? >>Yes, yes, that's a good question. And as you mentioned, first party, I mean, we start with first party data. Right? First party data is critical to understanding consumers on been in different verticals, different companies. Different brands have varying levels of first party data. So retailers gonna have a lot more first party data financial services company, then say an auto manufacturer. Uh, while many marketers have that first party data to really have a 3 60 view of the customer, they need third party data as well. And that's where experience comes in. We help brands connect those disparate data sets both 1st and 3rd party baked data to better understand consumers and create a single customer view, which has a number of applications. I think the last that I heard was that there's about eight devices on average per person. I always joke that we're gonna have these enormous. I mean, that that number is growing. We're gonna have these enormous charging stations in our house, and I think we're because all the different devices and way seamlessly move from device to device along our customer journey. And, um, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience and way site that about 95% of companies are actually that they are looking to achieve that single customer view. They recognize, um, that they need that. And they've aligned various teams from e commerce to marketing to sales toe at a minimum in just their first party data and then connect that data to better understand, uh, consumers so consumers can interact with the brand through website and mobile app in store visits, um, by the phone, TV ads, etcetera. And a brand needs to use all of those touchpoints often collected by different parts of the organization and then adding that third party data to really understand the consumers in terms of specific use cases, Um, there's there's about three that come to mind, so there's first. There's relevant advertising and reaching the right customer. There's measurement s or being able to evaluate your advertising efforts. Uh, if you see an ad on the if I see it out of my mobile and then I by by visiting a desktop website understanding or get a direct mail piece, understanding that those connect those interactions are all connected to the same person is critical for measurement. And then there's, uh, there's personalization, um, which includes encourage customer experience amongst your own, um, touch points with that consumer personalized marketing communication and then, of course, um, analytics. So those are the use cases we're seeing? Great. >>Thank you, Amy. I'm out. You can't really talk about data without talking about, >>you know, >>governance and and and compliance. And I remember back in 2006, when the Federal Rules of Civil Procedure went in, it was easy. The lawyers just said, No, nobody can have access, but that's changed. One of things I like about what snowflakes doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic, what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >>No, it's another great question. Um, this is where I think the major disruption is happening. Um, and what Amy described being able to join together 1st and 3rd party data sets. Um, being able to do this was always a challenge because data had to be moved around, had a ship, my first party data to the other side. The third party data had to be shipped to me on being able to join those data sets together, um was problematic at best. And now, with the focus on privacy and protecting P, I, um, this is this is something that has to change. And the good news is with the data cloud data does not have to move. Data can stay where it belongs. Experiencing keep its data experience. Customers can hold on to their data. Yet the data can be joined together on this universal global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are gonna prevent data from being collected on either a mobile device or in wet warren as cookies and Web browsers, new approaches. And we're seeing this a lot in our space, both in financials and in media is to set up these data clean rooms where both sides can give access to one another, but not have to reveal any P i i to do that joint. Um, this is gonna be huge right now. You actually can protect your your customers, private your consumers, private identities, but still accomplish that. Join that Amy mentioned to be able to thio relate the cause and effect of these campaigns and really understand the signals. Um, that these data sets are trying to say about one another again without having to move data without having to reveal P. I We're seeing this happening now. This is this is the next big thing that we're gonna see explode over the next months and years to come. >>I totally agree. Massive changes coming in public policy in this area, and I wanted we only have a few minutes left. I wonder if for our audience members that you know, looking for some advice, what's the what's the one thing you'd recommend? They start doing differently or consider putting in place. That's going to set them up for success over the next decade. >>Yeah, that's a good question. Um, you know, I think e always say, you know, first harness all of your first party data across all touchpoints. Get that first party data in one place and working together Second back that data with trusted third parties and in mats, just in some ways to do that and then third, always with the customer first speak their language. Uh, where and when they want to be, uh, reached out thio on and use the information. You have to really create a better a better customer experience for your customers. >>Matt. What would you add to that? Bring us home if you would >>applications. Um, the idea that data can now be your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications again without data moving these personalized applications experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're gonna build? If you had all of your consumers, consumers had access to their data in the app and not having to think about things you know from scratch. Leverage the data cloud leverage these, you know, service providers like experience and build the applications of tomorrow. >>I'm super excited when I talked to practitioners like yourselves about the future of data Guys, Thanks so much for coming on. The Cube was really a pleasure having you and hope we can continue this conversation in the future. >>Thank you. >>All right. Thank you for watching. Keep it right there. We've got great content. Tons of content coming at the Snowflake Data Cloud Summit. This is Dave Volonte for the Cube. Keep it right there.

>> Hello everyone, and welcome back to our wall-to-wall coverage of the Datacloud summit, this is Dave Vellante, and we're seeing the emergence of a next generation workload in the cloud, more facile access, and governed sharing of data is accelerating time to insights and action. Alright, allow me to introduce our next guest. Aimee Irwin is here, she's the vice president of strategy for Experian, and Matt Glickman is VP of customer product strategy at Snowflake, with an emphasis on financial services, folks, welcome to theCUBE, thanks so much for coming on. >> Thanks Dave, nice to be here. >> Hey so Aimee, obviously 2020's been pretty unique and crazy and challenging time for a lot of people, I don't know why, I've been checking my credit score a lot more for some reason on the app, I love the app, I had to lock it the other day, I locked my credit, somebody tried to do, and it worked, I was so happy, so thank you for that. So, we know Experian, but there's a ton of data behind what you do, I wonder if you could share kind of where you sit in the data space, and how you've seen organizations leverage data up to this point, and really if you could address some of the changes you're seeing as a result of the pandemic, that would be great. >> Sure, sure. Well, as you mentioned, Experian is best known as a credit bureau. I work in our marketing services business unit, and what we do is we really help brands leverage the power of data and technology to make the right marketing decisions, and better understand and connect with consumers. So we offer marketers products around data, identity, activation, measurement, we have a consumer-view data file that's based on offline PII and contains demographic interest, transaction data, and other attributes on about 300 million people in the US. And on the identity side we've always been known for our safe haven, or privacy-friendly matching, that allows marketers to connect their first party data to Experian or other third parties, but in today's world, with the growth in importance of digital advertising, and consumer behavior shifting to digital, Experian also is working to connect that offline data to the digital world, for a complete view of the customer. You mentioned COVID, we actually, we serve many different verticals, and what we're seeing from our clients during COVID is that there's a varying impact of the pandemic. The common theme is that those who have successfully pivoted their businesses to digital are doing much better, as we all know, COVID accelerated very strong trends to digital, both in e-commerce and in media-viewing habits. We work with a lot of retailers, retail is a tale of two cities, with big box and grocery growing, and apparel retail really struggling. We've helped our clients, leveraging our data to better understand the shifts in these consumer behaviors, and better psych-map their customers during this really challenging time. So think about, there's a group of customers that is still staying home, that is sheltered in place, there's a group of customers starting to significantly vary their consumer behavior, but is starting to venture out a little, and then there's a group of customers that's doing largely what they did before, in a somewhat modified fashion, so we're helping our clients segment those customers into groups to try and understand the right messaging and right offers for each of those groups, and we're also helping them with at-risk audiences. So that's more on the financial side, which of your customers are really struggling due to the pandemic, and how do you respond. >> That's awesome, thank you. You know, it's funny, I saw a twitter poll today asking if we measure our screen time, and I said, "oh my, no." So, Matt, let me ask you, you spent a ton of time in financial services, you really kind of cut your teeth there, and it's always been very data-oriented, you're seeing a lot of changes, tell us about how your customers are bringing it together, data, the skills, the people, obviously a big part of the equation, and applications to really put data at the center of the universe, what's new and different that these companies are getting out of the investments in data and skills? >> That's a great question, the acceleration that Aimee mentioned is real. We're seeing, particularly this year, but I think even in the past few years, the reluctance of customers to embrace the cloud is behind us, and now there's this massive acceleration to be able to go faster, and in some ways, the new entrants into this category have an advantage versus the companies that have been in this space, whether it's financial services or beyond, and in a lot of ways, they all are seeing the cloud and services like Snowflake as a way to not only catch up, but leapfrog your competitors, and really deliver a differentiated experience to your customers, to your business, internally or externally. And this past, however long this crisis has been going on, has really only accelerated that, because now there's a new demand to understand your customer better, your business better, with your traditional data sources, and also new, alternative data sources, and also being able to take a pulse. One of the things that we learned, which was an eye-opening experience, was as the crisis unfolded, one of our data partners decided to take the datasets about where the cases were happening from the Johns Hopkins, and World Health Organization, and put that on our platform, and it became a runaway hit. Thousands of our customers overnight were using this data to understand how their business was doing, versus how the crisis was unfolding in real time. And this has been a game-changer, and it's only scratching the surface of what now the world will be able to do when data is really at their fingertips, and you're not hindered by your legacy platforms. >> I wrote about that back in the early days of the pandemic when you guys did that, and talked about some of the changes that you guys enabled, and you know, you're right about cloud, in financial services cloud used to be an evil word, and now it's almost, it's become a mandate. Aimee, I wonder if you could tell us a little bit more about what your customers are having to work through in order to achieve some of these outcomes. I mean, you know, I'm interested in the starting point, I've been talking a lot, and writing a lot, and talking to practitioners about what I call the data life cycle, sometimes people call it the data pipeline, it's a complicated matter, but those customers and companies that can put data at the center and really treat that pipeline as the heart of their organization, if you will, are really succeeding. What are you seeing, and what really is the starting point, there? >> Yes, yeah, that's a good question, and as you mentioned, first party, I mean we start with first party data, right? First party data is critical to understanding consumers. And different verticals, different companies, different brands have varying levels of first party data. So a retailers going to have a lot more first party data, a financial services company, than say, an auto manufacturer. And while many marketers have that first party data, to really have a 360 view of the customer, they need third party data as well, and that's where Experian comes in, we help brands connect those disparate datasets, both first and third party data to better understand consumers, and create a single customer view, which has a number of applications. I think the last stat I heard was that there's about eight devices, on average, per person. I always joke that we're going to have these enormous, and that number's growing, we're going to have these enormous charging stations in our house, and I think we already do, because of all the different devices. And we seamlessly move from device to device, along our customer journey, and, if the brand doesn't understand who we are, it's much harder for the brand to connect with consumers and create a positive customer experience. And we cite that about 95 percent of companies, they are looking to achieve that single customer view, they recognize that they need that, and they've aligned various teams from e-commerce, to marketing, to sales, to at a minimum adjust their first party data, and then connect that data to better understand consumers. So, consumers can interact with a brand through a website, a mobile app, in-store visits, you know, by the phone, TV ads, et cetera, and a brand needs to use all of those touchpoints, often collected by different parts of the organization, and then add in that third party data to really understand the consumers. In terms of specific use cases, there's about three that come to mind. So first there's relevant advertising, and reaching the right customer, there's measurement, so being able to evaluate your advertising efforts, if you see an ad on, if I see an ad on my mobile, and then I buy by visiting a desktop website, understanding, or I get a direct mail piece, understanding that those interactions are all connected to the same person is critical for measurement. And then there's personalization, which includes improved customer experience amongst your own touchpoints with that consumer, personalized marketing communication, and then of course analytics, so those are the use cases we're seeing. >> Great, thank you Aimee. Now Matt, you can't really talk about data without talking about governance and compliance, and I remember back in 2006, when the federal rules of civil procedure went in, it was easy, the lawyers just said, "no, nobody can have access," but that's changed, and one of the things I like about what Snowflake's doing with the data cloud is it's really about democratizing access, but doing so in a way that gives people confidence that they only have access to the right data. So maybe you could talk a little bit about how you're thinking about this topic, what you're doing to help customers navigate, which has traditionally been such a really challenging problem. >> Another great question, this is where I think the major disruption is happening. And what Aimee described, being able to join together first and third party datasets, being able to do this was always a challenge, because data had to be moved around, I had to ship my first party data to the other side, and the third party data had to be shipped to me, and being able to join those datasets together was problematic at best, and now with the focus on privacy and protecting PII, this is something that has to change, and the good news is, with the data cloud, data does not have to move. Data can stay where it belongs, Experian can keep its data, Experian's customers can hold onto their data, yet the data can be joined together on this universal, global platform that we call the data cloud. On top of that, and particularly with the regulations that are coming out that are going to prevent data from being collected on either a mobile device or as cookies on web browsers, new approaches, and we're seeing this a lot in our space, both in financials and media, is to set up these data clean rooms, where both sides can give access to one another, but not have to reveal any PII to do that join. This is going to be huge, now you actually can protect your customers' and your consumers' private identities, but still accomplish that join that Aimee mentioned, to be able to relate the cause and effect of these campaigns, and really understand the signals that these datasets are trying to say about one another, again without having to move data, without having to reveal PII, we're seeing this happening now, this is the next big thing, that we're going to see explode over the months and years to come. >> I totally agree, massive changes coming in public policy in this area, and we only have a few minutes left, and I wonder if for our audience members that are looking for some advice, what's the, Aimee, what's the one thing you'd recommend they start doing differently, or consider putting in place that's going to set them up for success over the next decade? >> Yeah, that's a good question. You know, I think, I always say, first, harness all of your first party data across all touchpoints, get that first party data in one place and working together, second, connect that data with trusted third parties, and Matt suggested some ways to do that, and then third, always put the customer first, speak their language, where and when they want to be reached out to, and use the information you have to really create a better customer experience for your customers. >> Matt, what would you add to that? Bring us home, if you would. >> Applications. The idea that data, your data can now be pulled into your own business applications the same way that Netflix and Spotify are pulled into your consumer and lifestyle applications, again, without data moving, these personalized application experiences is what I encourage everyone to be thinking about from first principles. What would you do in your next app that you're going to build, if you had all your consumers, if the consumers had access to their data in the app, and not having to think about things from scratch, leverage the data cloud, leverage these service providers like Experian, and build the applications of tomorrow. >> I'm super excited when I talk to practitioners like yourselves, about the future of data, guys, thanks so much for coming on theCUBE, it was a really a pleasure having you, and I hope we can continue this conversation in the future. >> Thank you. >> Thanks. >> Alright, thank you for watching, keep it right there, we got great content, and tons of content coming at the Snowflake data cloud summit, this is Dave Vellante for theCUBE, keep it right there.

>>live from Orlando, Florida It's the cue covering Microsoft Ignite Brought to you by Cohee City. >>Welcome back, everyone to the Cubes Live coverage of Microsoft IC night here at the Orange County Convention Center in Orlando, Florida I'm your host, Rebecca Knight, coasting along side of stew. Minutemen >>were joined by Patrick Moorehead. He is the founder and principal principal analyst. Atmore Insights and strategy Thank you so much for returning to the Cube. You're a good friend of the queue. >>Thanks for having me on. I mean, it's a great show, and I literally look for the Cube everywhere. >>Very nice. You >>do about 40 events year, and I'm pretty sure you're in >>about exactly, exactly. >>We've got a few more for you to cut. Come Thio. Yeah, in the other place. Year is >>not over. So so many announcements. Today, an 87 page book from From the Microsoft comes team. One of the things that is getting a lot of attention is azure arc. Satya Nadella himself said, I am so excited about this. This marks the beginning of hybrid computing. What are your first impressions of it, and are you able to see the immediate of differences between Stack and an arc >>S o. I think I would say completely expected. Uh, we're out of this drunken sailor mode where everything's going to the public cloud. Oh, my gosh. And everybody is toast. Who's not doing this? Okay, And now we're in this somewhat sober right where 80% of the workloads are still on Prem. And 20 of those have gone on to either SAS or I as or pass, but it's expected now. Microsoft already had a full stack i e azure stack, but this takes it up a notch because you been deployed arc anywhere on anybody's cloud. They even showed a demo of doing backups to eight of us. So whether it's on Prem, and I'm sure they're gonna show it running on GC, Pia's well >>so Patrick, For for a number years we've been saying, When you line up the big hyper scale er's and say who's doing well, a hybrid. Microsoft's been at the top of the list there because they have a strong footprint in my data center. Microsoft gave everyone the green light to go. Do sass is much you can because they're pushing everybody toe. 03 65. And, of course, Azure is growing in, You know, one of the leaders in Public Cloud. The announcements this week were compelling, but it may be kind of rethink is that I think you laid it out well and said, But we've been talking about hybrid cloud your number years, but we're not really there. So you are. It's a first piece. It's only in tech preview. I think you're saying for a singular application, which is databases. That's right. When you look out there and you see you know the VM wear on AWS Azure, Google, Oracle, IBM, you look a AWS with outposts and those things. How is Microsoft doing today at delivering for what customers need, you know today and moving forward on their cloud journey? >>So Microsoft was first out of the gate with azure stack, right? They were doing hybrid before it was cool. It was interesting for about two years when they were rolling in outer building it they weren't talking about it. So I was thinking, Wait a second, is it not catching on, or do they want to put more on the big cloud azure? But in fact they have been diligently working behind the scenes. And while they had to show Wall Street this Hayward, the public cloud, they were actively building out their hybrid opportunities. And I do believe that when it comes to the slice of hybrid they are leading right now. Now it depends on where you start. I guess where I do is their leading if you have a major public cloud. Okay, eight of us, obviously there were the outposts, and everybody in the audience were all in the audience. We gasped when Andy Jassy brought that out. We kind of knew something was being worked on and focus a CZ well. And I think to be a credible player you have tohave both implementations, going one way and going the other, being able to work with other people's clouds but also noticed everybody has their single pane of glass strategy. If you want to go all in on Microsoft, you have arc on dhe. That's really the classic Microsoft embrace and extend. >>Yeah, Patrick, you said, all in on Microsoft. And if I if I look at the enterprise, you've obviously got some Microsoft. There's probably some things you're doing. An azure right, You're you're running. 03 65. You know, there's lots of pieces in the more Microsoft portfolio, but most people aren't all in on anything today. That's right, The same thing. I looked at Antos and said in Google Cloud or in my data center shore. But anthros on AWS And >>no Veum no, no virtualized applications on Antos either. >>So the same question for Microsoft is if I'm in a W s, you know, have a big footprint of AWS. Is this gonna fly or you know what? What? What's your what's your take >>s? So it's funny where I've wound up after 30 years of doing this stuff is there's always gonna be a lock in. You just have to pick the lock and that you want. Some people are comfortable with an A p. I lock in. Some are comfortable with a hardware lock. In some people are comfortable with a development environment, and you're gonna pick one. Just what is it gonna be? The reality is in a Fortune 500. You're gonna have multiple panes of glass using to determine which two or which three are you comfortable with? Maybe all the panic last for deployment. Maybe we'll have a panic glass for ops. The interesting thing that I'm really looking for, though, is where this heads with multi cloud. Because I believe at least to my definition, multi cloud is kind of fiction if you talk about actually managing it because Dev ops are cool. But you know, when you got a multi cloud, you break Dev and you break ups. So this is a way Arc is a way to keep. If you buy into their Dev and the Rapps and their security, you would go all in on our. >>So I'm actually interested in what you were talking about with Microsoft going sort of working behind the scenes to Wall Street, presenting this one thing but really working behind the scenes and then talking about being at the conference in everyone, gasping at Andy Jassy how much our company's really paying attention to every birth of these companies in terms of their competition with each other to to be number one. >>Oh, they'll all say that they don't track the competition, but they all say they all have these massive competitive teams that are operating in a real time and I guarantee you all of Microsoft's competitors Aire watching all these are are here on doing that. Now I think the best companies are looking forward trying to change the game if they have to change the game. Trench vendors are really have been playing catch up mode, right? If you were 100% on Prem and you were talking about the public cloud, you're gonna be in trouble. I think, actually, oracles a great example of they're in trouble, particularly with I s I c databases of service. But it's like too little, too late. And I think they're paying the price right >>now. Patrick A Thanks for teeing up the Oracle piece because one of one of the topics that saga repeatedly talked about in the keynote was trust. It's actually the exponential t to the environment. If you talk about the ecosystem. Microsoft. If you look at the hyper scale, er's is probably more trust in others. We talk about people wanting to break up cos well, you know, we tried to break up Microsoft back years ago way know what happened there, and Oracle was up on stage it Oracle openworld saying you want to run or go on the cloud. Here's Azure. There are partner. We actually think that was a keep east of the jet ideal eyes enabling that environment. So the question I have for you is first, Do you agree that the ecosystem believes that Microsoft is more trusted? But what about customers? I think you actually made a tweet about it, right? Because I wonder, you know, historically speaking, Microsoft was not the most trusted. It was the one that, you know, I was right behind Oracle esta who I spent the most. Licensing money to Microsoft has changed. Are they trusted partner for companies building their strategy? >>I have to say, based on the last, we'll call it five years level of Microsoft Trust has raised. And there are other players who make Microsoft look like the super trust zone. Okay, I mean, in what they're maybe what they're doing in a breaking consumer privacy, Let's say, 95% of your businesses advertising right. >>Let's just say what you imagine this right? >>Having commercial offerings that are SAS offerings out there. I think you do have to ask the question, but But listen, I think, um, nobody's mother Theresa here. Okay, Everybody's trying to get business, but I do believe particularly Cincinnati has been here. Level has trust has has gone up, and I hear it from clients that I that I meet with all the time other people are on the naughty list for sure. Even those 95% advertising companies who haven't, let's say, done something. That's horrible. But it's just the notion that something could go wrong. I mean, enterprises, they're slow to adopt their very conservative and makes great fun. >>Exactly So. Well, one of the other big announcement is power platform, not water. What are you What are your impressions of this? I mean, is it is it just semantics? I mean, is this just really the umbrella of a lot of things we've seen before? Or is it something new and different? >>So we wait, did see some brand changes of name changes, but we did did see Cem Cem riel movement here. I like to put even though they're different. I like to put a B I dynamics 3 65 and power kind of in the same region because it's Hey, I'm teeing up. Um, hr at for you or C R Ram, But then you're gonna build APS on top of that. And that's what where power comes into play, I think the r p a portion was relatively new and what they brought out. But I wouldn't say this was the big news rollout for, uh, for power. I do think, interestingly enough, is it is it is their largest growth area. If you think about what? Let's a sales force tracking up. What s a P is doing out there? Even a work day? That is, if I look at the cubic dollars that are available, that is their first or second business driver. So I was expecting a little bit more news here. How about you? >>Well, I mean, I I'm I'm just the host here. You're the analyst. You know what you're talking about? I think that how I mean, what do you think? Do? >>Yeah. No, Patrick, you know, from people I've been talking to, there's a mixture of some of it was pulling everything together, but there is a rapid movement. You know, when I talked to the r p. A vendor's out there, it's not right. It's not like they're all quaking in their boots. They're still partner with Microsoft shirt. We see IBM in S A p. Everybody's going after that environment. Come on. Our P a is the gateway drug to a I ITT. It's Rebecca was at exactly show recently talking about that so back to that trust. Their Microsoft is not usually making announcements that you walk across the booth and there's a few people you know saying, Can we roll out the beer early? Because we think our business is ruined. That's where some of that trust isn't Microsoft. But that being said, you know, it was curious to me that they didn't have any big partnerships announcement last year. McDermott was up on stage on Dhe. You know he's changed companies since then, but there was a couple of small open source announcements, but not any large partnership announcement. So ecosystem majorly important. Any commentary from you how Microsoft is doing in that grand battle for you? >>So if I look the past couple of years when some of the biggest players CEOs were on stage right, it was about OD I Hey, let's share our data s a P, probably one of the bigger one even though they're doing with Salesforce's. Well, and I think that was a giant giant leap for folks and second of all way, working to see Larry on stage. Because by the way, that I agree with you on Jen. I That was a huge deal to me. Was Oracle outsourcing? I asked Asher, right, That would have been newsworthy. Okay, if I look at what could have been up here, not that there aren't more strategic deals that could be done. I think they're I think people are busy executing at this point. But if you look at who's gonna share the data without the eye that was the biggest. Working with different clouds. Well, we're not gonna get eight of us to get up on stage here, right? We're not gonna get G c. P here on stage, although, although we could have gotten WebEx up stage because apparently WebEx at a Cisco and teams are becoming friends. And maybe we'll see that on a slightly smaller stage >>enterprise connect kind of launch than it is a Microsoft show. >>Exactly. But I was surprised, you know, and I think it's a testament to how powerful teams actually is on. It's funny when, um um teams, which everybody thought was dead after Slack was announced and hang out with Google has actually ended up being the darling off the enterprise. And not just because it comes free with your M one subscription, right? It's really it's a good product. It's a shockingly good product. You don't have to do any of the any security. If you have any security challenges of anything in Microsoft, you'll avenues you here. But that's not the case. It all uses the back and of Microsoft for security and and regulatory. So anyways, I know I'm veering off here. But there was one partner announcement that I saw. It was Cisco WebEx being friends with teams. >>Can't we all just get along? I mean, there we go. When there's money, everybody exactly every continually we can't. It's too >>expensive to go out on your own. >>Patrick always so much fun to have you and I should having you. I'm Rebecca Knight. For Sue Mittleman, >>stay tuned For more of the cubes, live coverage of Microsoft ignite

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to this cube conversation Michael Gray is here is the chief technology officer of Boston based thrive Michael good to see you coming on glad to be here so tell us about thrive what do you guys all about you know thrive started almost 20 years ago as a traditional managed service provider but really in the past four to five years transformed into a next generation managed service provider primarily now we're focusing on cybersecurity cloud hosting and public cloud hosting as well as disaster recovery so dig into that next generation yeah people use that term but what does it mean well the needs of our customers really changed over time before you could maybe simply roll out some antivirus and do some desktop management some server management but with the way some of the innovation is exploded in the cloud and the way application development has changed all of our businesses we've noticed that our customers have all kinds of new needs that includes much higher focus on cybersecurity these things can't be an after afterthought the other things with all the data that we see coming from our customers they may need a much higher level of performance than they ever did before from their their local hosting or or in the cloud so what Amazon Web Services came out you know 2006 timeframe every set up ms P's like drive they're in big trouble the exact opposite is happening for your business yeah yeah yeah you know why is that number one and number two how do you compete with the big cloud providers you know somebody like Amazon or even Azure those services are not easy to roll out you still need someone to understand what the businesses are and then translate those into technology solutions for us when someone starts asking how do I transform my business whether it be in the public cloud or the private cloud that's a tremendous opportunity to bring our knowledge and all of our engineering support to those customers to help them transform so I mean I I liken it to you know I could hire a plumber I could hire an electrician I could hire but I don't want to be the general contractor I'm happily happy to pay an expert at that who's got contacts deep expertise and and push the responsibility on them is that a fair analogy yeah I do think it is fair you know obviously it's a it's a much more technical environment than something like that so it's much more complicated you know the other thing is when we start to understand some of these business problems and pull the pieces apart we have a tremendous amount of expertise and experience where we can help those customers understand how to solve those business problems how to implement the technology and then how to be successful in whatever way they're trying to transform their business so you sort of touched on some of the trends in your business did talk more about your customers it's my understanding is it's mostly small and mid-sized customers is that correct you know there's far more mid-market than there ever were before I think people in the mid market are realizing that they do need to take some of these services outside their walls I notice a lot of mid-market customers that are focusing on their core business if you're a manufacturing company a biotech financial services company you can realize very quickly that you're not in the cloud hosting business and no matter how many people they hire grow your staff can be very difficult to actually be successful in these technologies despite all the different pieces that Amazon or Azure offers in the public cloud you still have to figure out how these systems work and how they apply to your business well to midsize companies and especially small companies they obviously aren't the resources that a large company has so you bring a lot of that infrastructure expertise along yeah and I think part of it is you know we have such a big exposure to a very large customer base so a problem that a customer may see that they think is maybe perhaps special to them we've solved that problem maybe hundreds of times and we can give them a lot of insight into how other companies of similar verticals have solved those problems you start out as sort of a local MSP and that have expanded over time yeah that's correct so we've expanded pretty rapidly over the past three to four years now we're we have five offices primarily in the East Coast and really started to help the mid-market who's now started to understand that they need to frankly outsource some of these solutions or get in business with a partner like us who can help them take those outside their walls and provide them a much higher level of service often at the end of the day the investments much lower for the customer so paint a picture of your your infrastructure what that look like yep so we have a data centers you know I have three primary data centers in New England the New Jersey New York area and then in the south all those data centers actually have infinite at storage which is you know something that I'm a huge fan of and one of the things that I like to offer in all of our data centers is I don't necessarily it doesn't matter to me geographically where the customer would like their workloads that's one of the things that the public cloud offers you can move resources around geographically depending maybe where your headquarters is or some of your branch offices we provide the same solutions at often a much higher performance level and we've extracted all the complications of where to put these so if a customer is in San Francisco and they'd like to dr2 New England not an issue but all of a sudden if they change their headquarters or maybe they do an acquisition and they need to change that footprint I can change that on the fly for them so and I've walked through many data centers of MSPs over the years yeah and ten years ago yeah you had one of everything yeah yeah compact server yeah yeah yes so I would imagine you had similar challenges you mentioned Infini debt yeah trying to essentially run your entire storage yeah yeah so we've um we've acquired several other MSPs over the past several years we had a lot of disparate storage platforms a lot of investments made some of them hung on to maybe for too long some of them you know were purchased for a specific business reason that might not be there anymore at this point we've standardized on Infini debt it's enabled our business to do a lot of new and innovative services so high performance storage replication similar to what you'd see in the public cloud but also we can support very complicated very data hungry clothes so you're sexually replacing so older storage systems with infinite at maybe you can describe the before and after you know frankly with with acquiring a lot of msps you name a storage platform we had it at some point through this standardization the the beauty of it is a consolidation so I can leverage the folks that manage our infinite at across the country all right so my TCO on something like this is is is really kind of amazing I can leverage a lot of experience with the defender that when I go in and need to do a data center consolidation I have some things that are knowns there's a lot of unknowns and acquisitions and all the due diligence in the world there's still going to be things that maybe not every detail has been figured out but when I roll out an infinite at I know I've solved one very foundational problem right out of the gate so and I want to come back on the TCO but before I do when I talk to people like you and I'm not a CTO but a lot of times I infer that people are comparing the the latest and greatest in this case infinite at yeah with what they had that's five six seven years old sure of course the TCO is the share that okay so I'm a push a little bit is is I presume you looked at infinite ad and other storage suppliers and I'm interested in what you found in those comparisons is it is it is it just great TCO relative to what you had that was five years old or is it real after the other yeah yeah so you know when it comes right down to it I've seen every marketing pitch for a storage platform you can possibly imagine I've seen every bullet list of features I've seen every we have proprietary technology that does X&Y you know eventually when you put it on the floor it's not everything that was in the sales process maybe there's something that was uncovered on a licensing side maybe the performance wasn't quite what someone said it would be the thing about infinite at is they've delivered on everything they've said in the sales process and you don't find that very often the other thing I need to mention too is that even post sale the discussion about the technology continues it's always a discussion about how the technology is built and how it enables you it's not we have a new feature coming on the roadmap that is gonna solve X&Y problem they've worked out the very foundational problems you know the other thing I do want to mention about Infini debt is being such a strong engineering company I know the best an engineer I can rely on them to make good engineering decisions so I want to ask you about performance because when I first saw infinite out you know we were on the on the flash bandwagon we got early on that yeah and these guys came in and said actually we can beat flash performance using our architecture and software and so forth yeah be like really so I'll ask you yeah have you found that from a performance standpoint so I have and you know I run into a lot of situations where there's technology leaders that are maybe buying into a specific brand name you know if we put X technology in I know for a fact that it's gonna beat the performance of an infinite at my approach with that is I have seen all the platforms and I agree there's a lot of great products out there high performance sit down and take a look at the way the technology has been built and have an open mind and you'll most likely be convinced that that technology is the right answer a lot of times I like to sit back and and say look I'm not gonna push any vendor any software partner any manufacturer on you take a step back and have an open mind of technology it'll make a big difference when you actually listen well I'm sure you've heard the sales pitches are you using those slow spinning business mic spinning discs or mechanical yeah yeah yeah yeah your experience has been and we've had Brian Carmody on yep yes of others yeah so then we have Moshe come in here yes Blaine that's sure and so but I always like to talk to the customer and get the affirmation yes yeah well again to me the the conversation with infinitive is always about engineering you know it's not a great deal of marketing first of course everybody does marketing that happens on a regular you have to do that to run a business but if you want to talk purely about how things have been designed that conversation often eclipses a lot of other marketing from other storage vendors so talk about your your how you spend your time yeah it's acting you know infrastructure roadmaps and so forth to get more sort of I got to get this stuff up and running today describe yeah you know we've set a path to build a very high performance nationwide cloud we are going up against the public cloud by the way I'm a public cloud partner right I do both we do hybrid hosting I want to give the customer the best of both worlds which may be a cliche but we really are aiming to get there that's one of my primary tasks is establishing a technology vision you know I can describe to a customer where our cloud is going and I can stand behind that with the public cloud we do have to Lou a little bit of reading the tea leaves so I I help people with trying to understand what you know maybe the public cloud vision might be but also how I fit together with that that public cloud with private cloud hosting and the other thing primary goal of mine is bringing in some of these different functions of IT so for instance high-performance cloud private cloud Plus cyber security I can bring those two together for you in a cohesive solution that that's what I spend a lot of my time so as you look out you know put on your your your binoculars maybe even your telescope big trend in one of the big trends is hyper-converged in bringing in storage compute and networking all together yep if I'm inferring correctly you're going for more of a Best of Breed approach yet and yet in you guys have the engineering expertise you have to do that can you can you talk about the philosophy there sure sure well one of the things that I like to do is just abstract some of these confusing and complicated conversations from our customers you know if we're gonna talk about SD win and make sure I have SD weigh in in my data center I can tell the customer I can give you that functionality and you don't have to worry about how these different pieces go together I'm happy to be transparent you know there's a lot of things in the public cloud that simply information you can't get I'm actually willing to share how those solutions that I built go together because I want people to see that transparent I want them to trust us so you know when when we go and start putting these together these are things where when the customer does have a question they want to drill in because they have concerns I can eliminate those very quickly you talking about private cloud earlier I want to come back to share and just so we always say on the cube bring the cloud experience to your data wherever it lives yeah it's all about that operating mom yep yeah so as you see tool chains like kubernetes yep yeah a cloud native stuff yeah come in you want to have that cloud experience you want to have yourselves a fantasy pass that on yep do you have customers yeah how do you look at that yeah what role does storage infrastructure playing to me and this is something that's primary to thrive focuses application enablement we're an application enablement company so if your application is best run in Azure and then we want to put it there a lot of times we'll find that just due to business problems or legacy technologies we have to build private clouds or even for security reasons we want to build private cloud or purely just because we're running into a lot of public cloud refugees you know they didn't realize a lot of the maybe incidental fees along the way actually climbed up to be a fairly big budget number so you know we want to really look at people's applications and enable them to be highly high-performance but also highly secure I want to come back to the TCO I said oh yeah sure when you do the total cost of ownership analysis yeah what you find is it really boils down to the to the labor yeah piece of yep and see I'm curious as to when you brought in Infini debt yeah what the business impact was you know economically yeah no there's other non TCO thing yeah more so was it the labor cost that got reduced did you redeploy those resources well actually Hardware first and foremost and you know this is going back many years but and and I think I would say this is true for any datacenter cloud provider the minute the phone rings and someone says my storage is slow we're losing money okay because we've had to pick up the if someone needs to address that we have eliminated all storage performance helpdesk issues it's now one thing I don't need to think about anymore we have we know that we can rely on our performance and we know we don't need to worry about that on a day to day basis and that is not in question now the other thing is really as we started to expand our infinite at footprint geographically we suddenly started to realize not only do we have this great foundation built but we can the leverage and invest when we made to do things that we couldn't do before maybe we could do them but they required another piece of technology maybe we could do them or they required some more licensing something like that but really when we started the standardization we did it for operational efficiency reasons and then suddenly realize that we had other opportunities here and I have to hand it to infinity they're actually the ones that helped us craft this story not only is this just a solid foundation but it's something you can build on top of so talk about the performance I want to ask you yeah I've had certainly Brian Carmody Craig Hobart and I have sat down and Craig actually made the statement you know the only bottleneck really is when the the system gets filled yeah you just dive in the architecture has that been your experience if this so reduced or eliminated traditional storage bottlenecks oh absolutely and you know I mentioned before that this is sort of formance is now becoming afterthought to me you know and a little bit the way we look at our storage platform is weet from a performance standpoint not a capacity standpoint we can throw whatever we want at the infinite at and sort of the running joke internally is it will just smile and say is that all you got you mean like mixed workload so you don't have to sort of tune each array for a particular workload yeah yeah and you know I can imagine as someone that might be listening to what I'm saying well hey come on you know they can't really be that good and I'm I'm telling you from seeing a day-to-day again you can just throw the workloads at it and it will do what it says it does you don't see that every day now as far as capacity goes you know they there's capacity on demand model which you know we're a huge fan of they also have some other models the flex model which is very useful for budgeting purposes what I will tell you is you have to sacrifice at least one floor tile for an affinity it's very off-putting at first on day one and I remember my reaction but again as I saying earlier when you start peeling back two pieces of the technology and why these things are and the different flexibility on the financial side you realize that this actually isn't a downside it's an upside so the asset leverage of that floor tile as well exactly also make a big deal about a petabyte yes Gail is it important to you or what kind of scale are we talking about in terms of if you can share yeah absolutely so you know we obviously have multiple petabytes of storage for thrive for our customers again you know when someone has a large data set if we were to say we cannot handle that we're gonna be out of business pretty quickly this is one of the things the infinite flexibility of the public cloud again if you consider the public cloud both our competition and our partner you know we need to be able to offer that same kind of electricity in that same kind of endless capacity and at this point although I don't have completely unless capacity I have a tremendous amount of options I have workloads I can move different places and again a lot of times now it's more about performance than it is capacity oh you gotta give me something okay something that you wanna that should be doing to make your life better yeah I mean I gotta tell you it solves so many problems that is actually hard to come up with and again I'm smiling here because I've been down this road with those storage providers I've been let down by other storage writers I guess the son degree I maybe I'm waiting for them to let me down but I don't think they're going to that's a really interesting part I think that I'm you know the new trees cloud which is something that's been added over time you know a public cloud interaction is something that is desperately needed in the storage space so I'm interested to see how that product grows if I'm gonna give you something you know but again these are enablement platforms these aren't you know we need to do a feature comparison between a cloud and a public cloud and a private cloud last question some gifts are stuff you're working on yes II always like the SCT oh is that question yeah you know one of the the really interesting things to me is that we're finally getting there with anomaly detection not only you know just pure we found one event that that went out somewhere that doesn't make sense but we're profiling user behavior now AI and machine learning has been one of the big items that we've been promised for years but a lot of times it was just a tag line I think a lot of things that are happening in the public cloud computing space around profiling users and being able to reduce the amount of noise in the security space I think we're finally here and I think you know in the next 12 to 18 months AI isn't gonna become a cool feature said it's going to become a standard of a lot of security products so applying machine intelligence to a lot of the data that you have a lot of metadata yeah infrastructure metadata yeah yeah and you know even if you take for instance you know I'll pull it back to our storage conversation earlier if there's a storage activity is some sort of activity that's outside the norm that actually could be a security incident itself so you know pulling in data feeds is something that we've conquered its what are you gonna do with it now and we needed some humans to be able to pull that off before I think AI and machine learning is finally at the point where it's not out of reach for your average customer it doesn't take someone with a data analytics degree or something like that we can now buy these kind of products off the shelf and and leverage them for a lot of value oh Michael you've been a great guest thanks so much if you're welcome back anytime all right happy to be here all right and thank you for watching everybody this is Dave Volante in the cube we'll see you next time

>> From Tavern on the Green in Central Park, New York, it's theCUBE covering Veritas Solution Day. Brought to you by Veritas. >> Welcome to New York City, everybody. We're here in the heart of Central Park at the beautiful location, Tavern on the Green. You're watching theCUBE, the leader in live tech coverage. And this is our special coverage of the Veritas Solutions Day. The hashtag is VtasVision. Veritas Vision last year was a big tent customer event, several thousand customers at that event and Veritas decided this year to go out to the field. 20 of these solution days, very intimate events, couple hundred customers, keynote presentations from Veritas, breakout sessions, getting deep into the product but also talking strategy, and intimate conversations with executives, CxOs, CIOs, backup admins, and of course, New York City is one of those places where you get very advanced customers pushing the envelope, very demanding. I often joke they're as demanding as New York sports fans, and so they have high expectations. But they also have a lot of money, and so the vendor community loves to come to New York, they love to get intimate with these customers in New York, as do we at theCUBE. So we're going to be talking to customers today, we're going to be talking to executives of Veritas, some partners. So I want to talk a little bit about what's going on in the marketplace, in this backup and recovery space. It's transforming quite dramatically. For those of you who follow theCUBE, you know last year at VMworld, last two years, actually, data protection was one of the hottest topics at the event. Of course, multi-cloud, of course there was a lot of AI talk and containers and Kubernetes. But staid old backup, old, reliable data protection was one of the hottest topics. We're seeing VC money pour into this space. We're seeing upstarts like Cohesity and Rubrik trying to take aim at the incumbents like Veritas and Commvault, and IBM, and Dell EMC, so those traditional companies, those enterprise companies that have large install bases are trying to hold onto that install base and migrate their platforms to a modern software-defined platform, API-based, using containers, using microservices, building on top of the code that they've developed, simplifying the UI, and at the same time, allowing for an abstraction layer across clouds and multi-clouds. So what are the big drivers that are really pushing the trends, the megatrends of this space? Well, certainly digital transformation is one of them. The last 10 years of big data, people have gathered all this data, and now that data is in this place and people are now applying machine intelligence to that data. They're doing a lot of this work in the cloud. So digital transformation, data, big data, cloud, multi-cloud, simplification. People want a much simpler experience, so bringing the cloud experience to their data, wherever the data might live. Because of course, you get the three laws of cloud. You've got the law of physics, right? Physics says you can't just shove everything into the cloud. It just takes too long. If I have big bog of data, if I have a petabyte of data, you know how long that's going to take to put into the cloud? So I may not just move it in there unless I stick it on a Chevy truck and it cart it over on a bunch of tapes and nobody really wants to do that. So there's the law of physics. There's also the law of economics. It's very expensive to move that data. You need a lot of network bandwidth, so, you know, you might not necessarily put everything into the cloud, you might keep stuff on-prem. And of course, there's a law of the land. And the law of the land says, well, if I'm in country X, let's say Germany, that data can't leave that country. It's got to be physically proximate inside the boundaries, the borders of the country, by local law. So these three laws are something that was put forth to us by Pat Gelsinger in theCUBE at VMworld this year. We've evolved that thinking, but it's very true when we talk to customers about this. These are trends that are driving their decisions about cloud and multi-cloud and where to put it. We talked in theCUBE about the stat that the average enterprise has eight clouds. Well, we're a small enterprise and we have eight clouds, so I think that number's actually much, much higher, especially when you include SAS. So lots of data, lots of copies of data, so you need a way to abstract all that complexity and have a single place to protect your data. Now, a big part of this, digital transformation is driving more intense requirements on recovery point objectives and recovery time objectives, RPO and RTO, what do those words mean? Recovery point objective, think about... Ask a businessperson, how much data are you willing to lose? And they go, oh, what are you talking about? I don't want to lose any data. But if you think about it and you ask the next question, how much are you willing to spend so that you lose no data, and if they have to spend millions and millions of dollars to do that, they might relax that requirement a little bit. They might say, well, you know, if I lose 15 minutes of data in any given time and have to recreate it, not the end of the world. So that's what RPO is, is essentially the point in time that you go in to recover and how much data loss you're exposed to. And the way this works is you take, let's say, snapshots to simplify the equation, you push those offsite away from any potential disaster, and it's that gap between when you actually capture the data and when that disaster might happen that you're exposed. So to make that as close as zero as possible, that gap as close to zero as possible, is very, very expensive, so a lot of companies don't want to do that. At the same time, digital transformation's pushing them to get as close to zero as possible without breaking the bank. The other part of that equation is recovery time objective, how long it takes to get the application and the data back and running. And because of digital transformation, people want to make that virtually instantaneously. So because of digital transformation, people are re-architecting their data protection strategies to have near-instantaneous recovery. This all fits into the megatrend of cloud. People want it to be simpler, they want it to mimic the cloud-like experience, almost as if I'm on Amazon or I'm on Netflix, so simplifying the recovery process and the backup process is something that we're going to hear a lot more of. Automation is another big theme. People tend to automate through scripts. Well, scripts are fragile, scripts tend to break. When changes are made in software, scripts tend to have to be rewritten and maintained. And so it's a very high maintenance type of activity to do scripts, and over time, they just fade away, or don't, they stop working. So automation through API is very, very important, something that you're hearing much more, is much more thematic in this world of data protection. The other is getting more out of the corpus of data in my data protection infrastructure, because, let's face it, backup and recovery, it's like insurance. I hope I never need it, but if I do need it, it's very valuable at that point in time that I do need it. But it's an expense. It's not driving bottom-line revenue. It's not necessarily cutting cost. It is indirectly in the form of reducing the cost of downtime, but that's harder. That's kind of viewed oftentimes as a soft dollar benefit. So what you're hearing is a lot of the vendor community and the user community are talking about getting more out of the data that they have and out of the backup and recovery infrastructure by bringing analytics, and machine intelligence, or AI and machine learning to the equation. Studying analytics to identify anomalous behavior, maybe identifying security breaches, creating air gaps such that I can potentially thwart ransomware or other malware infections, analyzing the corpus of backup data because it holds all the company's corporate data, it's accessible. If you can analyze that data and look for anomalies, you might be able to thwart an attack. So getting more out of that data through analytics. Predictive maintenance is another example of data analytics that's driving some of these trends beyond just backup and recovery. And also governance. Governance and privacy are kind of, security and privacy are two sides of the same coin, so with GDPR, the General Data Protection Regulation that came out, that went into effect in terms of fines going into effect this past May, very, very onerous and expensive fines, people are using their data protection corpus and the analytics around that to reduce their risk and to better govern their data. So these are some of the big trends that we're seeing. So Veritas is a leader here, we're going to be covering this all day. Veritas and some of its other brethren that have been around for decades are getting attacked by a lot of the upstarts, but they got the advantage that the install vendors have the advantage of a large install base. The incumbent vendors have the advantage of a large install base. The upstarts have the advantage of they're starting with a clean sheet of paper. We're going to talk to customers and find out what are they thinking in terms of their backup approach. Industry data suggest that over half of the customers that you talk to are rethinking their backup strategies because of digital transformation. Well, we're going to talk to some customers. Are they thinking about sticking with Veritas or they thinking about migrating? Why or why not? What are some of the advantages and considerations there? So Veritas, a long, rich story going back to the '80s when the company was founded, was a hot IPO, really super hot company, got sold to Symantec for about 13.5 billion, and then Symantec spun it out to private equity several years ago in an eight billion dollar go-private sale, and subsequently, Veritas got off the 90-day shot clock. We heard this from companies like Dell where they didn't have to report and get abused by the street for either missing a number or having one little metric that was off. So they could write their own narrative. They could invest in R&D, they could have more patient capital. And so you saw this from the Carlisle group that took Veritas private and has been sort of this march toward a new platform, spending money on R&D, and now, really going to market very aggressively. Another thing you're going to hear about is partnerships, partnerships with AWS and some of the other cloud-providers. There's a partnership that's being announced with the flash storage company, Pure, today. So we're going to dig into some of that. So we'll be here all day, Tavern on the Green. You're watching theCUBE and we're here in New York City. Keep it right there, we'll be right back. I'm Dave Vellante, back shortly. (digitalized music)

>> Live from Orlando, Florida, it's theCUBE. Covering Microsoft Ignite brought to you by Cohesity and theCUBE's ecosystem partners. >> Welcome back everyone to day two of theCUBE's live coverage of Microsoft Ignite. We are coming at you from the Orange County Civic Center in Orlando, Florida. I'm your host Rebecca Knight along with my cohost Stu Miniman. We're joined by Patrick Moorhead, he is the founder and president and principal analyst at Moor Insights and Strategy. Thank you so much for coming back on theCUBE. You're an esteemed CUBE-alum. >> Gosh, this is great, can you introduce me on every show please? >> I would be happy to, delighted. So, Patrick, before the cameras were rolling, we were talking about how many, frankly, tech shows you go to a year, you said 40, 45. >> That's about right, I live in Austin but I actually live on a bunch of planes, kind of like you do, right. >> Right, sure, sure, yeah. So this is your 10th time at Ignite, or an Ignite like show, it used to be called Tech Ed, so what are your first quick takes on what this conference, what you're seeing, what you're hearing? >> So, Microsoft has a three layers, like a three-layered cake to their events, you have developers, you have customers, and you have channel. And this is their customer event, so what might seem like rehash or maybe build or inspire is if customers who haven't heard this content before. So it's really about getting them engaged and things like that and, what we've heard, first and foremost is we had 45 Azure announcements but I think the biggest news, was about the open data initiative that, I mean, how often do you have the three CEOs up on stage, where most corporate data sits, with Microsoft, SAP and Adobe, so it was impressive. And that's probably the number one thing so far. >> Okay, let's dissect that a little bit. What are your thoughts, I mean, we're sort of questioning, it's a big idea, >> Right. >> When will customers actually see the benefit and is there a benefit to customers? >> When I look at these big corporate announcements I'm thinking, is this thing paper or is this thing real? How far does it go? I think this is real, when I dug under the covers, in some, bendy NDA things, that I can't give details on, there's meat there for sure, but, where this all starts, is, is two things are going on here, first of all, to do machine learning correctly, you have to have a lot of data, right? Yesterday's big data, is today's machine learning. You have to have it all together, now you can pull in disparate data sources into your enterprise and work on that data, but it takes a lot of cleansing, you know most of the time in machine learning, is getting the data ready to be worked on. What having data interoperability standards means is you can bring it in, you don't have to cleanse it as much and you can do real time analytics and machine learning on it so it's agreement that says, we're all going to come in, if it's customer data, it's going to look like this, with different fields. Now you would think that something like XML could do this, but this is bigger and from a competitive standpoint, I have to ask the big question, where's Salesforce and where's Oracle, they're the two odd-companies out. >> Really interesting, you mention that there were a lot of Azure announcements here, something like 45. I was reading, Corey Sanders had a blog of list and lists and lists and it's typical of what we've seen in the cloud. You and I, we go to AWS re:invents, and it's like let's talk about all the compute instances, all the cool new storage, all the things, there's cheering and, you know, everything for every micro and macro thing that happens there but are there any things that jumped out at you? We had Jeffrey Silver on the program yesterday, he talked about the databoxes, like the Edge and the various versions of those, those seem kind of interesting when we talk about data and movement but anything in the Azure space that got your attention? >> So aside from the databoxes, I was really excited about AutoML. So, three ways you can do ML, you can do everything from scratch, you can take an off-the-shelf API and then you can use something in the middle, which says, kind of like the three bears, right in the middle, Google at GCP announced something like this and so did Azure. And essentially what this is, is it auto-tags your data. It's smart enough to know that this is an image as opposed to you having to start at the very beginning and hand code some data and that's not automatic because the key, so a good example might be an audio machine learning algorithm where, you might need it for an airplane versus a car, versus the factory floor, versus a smart-phone application. Those are all different environments and your algorithm's going to be different but, as an enterprise, you might not have the PhD on staff to be able to do that, but you can't live with the off-the-shelf API. >> There's another thing that kind of struck me, a little bit of dissonance I saw there, you've got a Microsoft surface sitting in front of you, Microsoft, it's gotten into hardware in a lot of places when they talked about their IoT Ps, they're like, we're going to put things out on the edge and then on the other stream it's like, well, but they're open and it's APIs and developers and software, not only Adobe and SAP but the announcement with Red Hat, talking about all they're doing with Linux, how do you reconcile the, I've heard people in Microsoft, we want to completely vertically integrate the stack and that's not something that I hear from the Googles and Amazons of the world, I thought we were kind of past that, no one company can do it all. On the other hand, they're very open and give you choice. How do you look at those pieces? >> This all stems with the slowdown of Moore's Law for general CPU compute. So, as Moore's Law is slowing down, we need to throw different kinds of accelerators at the same problem, to keep innovation going up and to the right at an increasingly faster pace. So people have gone to GPUs and CPUs and almost every one of the big infrastructure players has done that, whether it's Google, Apple, AWS, they all have their own hardware. Part of it is to accelerate time to market, the other is to get a lock-in, I'm still trying to figure out which one this is. Microsoft is saying very clearly in Azure IoT Edge that you can send your data, even if you have their hardware to AWS and GCP and I think enterprises are going to take a quick look. I've been doing this almost 30 years, I've gray hairs to show for it, but you just have to pick your lock-in, right? Enterprise AT always gets locked in and the question is, what you lock in on? If you go with Oracle and then build applications around it you're locked into Oracle. If you go with a certain hardware OEM, you could be locked into a certain OEM with converse infrastructures, so, I think it's just picking the poison, you're going to have some people who are very comfortable with going all Microsoft and you'll have some people who'll want to piece part it together and look to the future We still have people who were brought up on mainframes and they don't want to be there, they want to have flexibility and fluidity. >> One of the things you were talking about with the slow down of Moore's Law, Microsoft and frankly every other technology giant is really trying to stay ahead of the innovation curve. Microsoft, 42 years old, a middle-aged company, and really, in the tech world, a really old company. Is Microsoft effective at this? I mean, do you see, that this is a creative, an ingenuitive, an innovative company? >> Microsoft is one of the only companies that has been able to turn the corner from being aged and experienced, I guess like us, and moving into the new zone and everybody, in everybody's work has had to do that. Analysts used to, I remember getting Gartner and IDC reports on paper, but now it's very different. We're up here on theCUBE, we're on Twitter, we're doing research reports, so everything is changing and Microsoft has had to change too. Five years ago, when Azure hadn't really taken off, they had a billion dollar write-down on surface hardware, bought Nokia, shut Nokia down, you're wondering, wait a second, what really is happening but then Satya came in and, to the company's credit, has completely turned around. I will state though there is a difference between perception and reality, I think a lot of the things that Ballmer had in place were absolutely the right things, I think Satya takes a lot of credit for it, but these things just didn't magically appear when Satya came in. So, a lot of the things they did were right, and it was perceived to be new leadership and therefore they're looking good. >> I love it, 'cause, we had quite a few Microsoft people on the program and a lot of them, 10, 20 years with the company, and they said, it's still the vision that we had but, one articulated it really well, he said, we're even more focused on the customer than ever and that gets me really excited. I want to ask you, when people look at this show, 'cause it's such a broad ecosystem, so many different views, what will they be talking about later in the year? My initial take coming out of it is, I'm a little surprised that we're talking so much about things like Windows 2019 and the Office 365, Microsoft 365, Dynamics 365, obviously it's Microsoft's strength, it's where they've got the most customers but are they operating still relevant in the future? >> I met with the program manager of Windows 29 servers last night, Erin, and she had said that they had 1,300 people they had to turn away from the Windows 2019 server and there was 4,000 people and I flippantly said, oh my gosh, I didn't think Microsoft still did that, it's all as a service, but I was just kidding of course. But I think that that shows the, how long it takes for people to move but I think what we'll be talking about in a year is has Microsoft delivered on its IoT commitments in IoT Azure Central, how much of their business has moved to, I'll call it, on-prem software in a box, to as a service, so, Dynamics 365, Office 365, and then finally I think we're going to see the workflow, and here's something that my head finally went ding on, is, Microsoft's strategy to surround the data and then do workflow on it to supplant Oracle SAP applications around the data. That's what I think we'll be talking about in a year. >> One other specific I wanted to see if you've got some data on because it's something we wanted to understand, Azure Stack, the press, all agog on it for the last couple of years, I really haven't talked to, I've talked to the partners that are working in, you know, people like Intel, Lenovo, and the like that are doing it but I haven't talked to too many customers they've employed service providers, yes, but what are you hearing, what are you seeing, is Azure Stack a big deal or is it just one of the pieces in a multi-cloud data applications strategy that Microsoft has? >> So, Azure Stack is a big deal and I think that it's getting to it's a slow boil, to be honest with you, the company changed hardware strategies, it was first an ODM model and then it went to an OEM model and a very narrow OEM model. The compute requirements to Azure Stack were too big to some people so it's a slow boil, but I look at what has the competition done? Now to be even a public cloud player, you have to have an on-prem capability. With Google it's PKE On-Prem, you have Greengrasss, and Amazon DB that's on-prem sitting on top of Vmware, so hyper-cloud, multi-cloud is a real thing, I just think it's getting a little bit slower start than everybody had thought. >> Great, well Patrick, thank you so much for your insights. These were terrific, it's great having you on the show. >> Thanks for having me. >> I'm Rebecca Knight for Stu Miniman, we will have more from theCUBE's live coverage of Microsoft Ignite in just a little bit. (upbeat music)

>> Announcer: Live, from Washington D.C. It's Cube Conversations, with John Furrier. >> Hello there, welcome to the special Cube Conversation, I'm John Furrier with the Cube here in Washington D.C. at the headquarters of Amazon Web Services Public Sector, here in Arlington, Virginia, right around the corner from D.C. Our next guest is Robert Groat, with the Executive Vice President of Technology at Smartronix, a service provider in Cloud and an IT. Thanks for joining us. >> Thank you John. >> So we're in D.C. and the Cube's getting the lay of the land, so much innovation happening around Cloud and disruption, you got one group going, scratching their heads, wondering what's happening, some groups saying what happened, and you got people making it happen, right? >> Exactly. >> What's the big "ah-ha" moment people might not know looking into D.C. now? What is the real trend? What are the people that are making it, what are they doing? Is it the Cloud, is it mobile, is it data-driven? >> Yeah, I think it's all of those components, but I think one of the things that you're really seeing is that the Cloud is enabling these organizations, these traditional organizations, to really transform in the way that they deliver and consume IT services. IT services have been a mess in this town for a long time, the contracting process has been a mess, some of the things that happened, some of the smaller organizations have had a chance to be really innovative and take a leadership role in delivering services to the community and not just the large beltway bandits that we've seen in the past. So I think some of the "ah-ha" moments are probably around, you know, we've been working, Smartronix has been working with the public sector and Cloud since 2009, so really one of the early pioneers, and we used to run across all of these issues where security was the blocker, and it would take a long time to convince people that the security in the Cloud really was what it needed to be. Now we're seeing, in terms of an "ah-ha" moment, we're seeing that security is the enabler, we're seeing that these organizations are really embracing the fact that you can do things in the Cloud from the security perspective that you could never do before. And I think that you've got this kind of next generation of managed service provider that embraces those tenants of how to manage services and manage security services and it's really disrupting the way that the Federal Government's done business in the past. >> You know, we were at the Public Sector Summit last June, and we were commeters, the first time the Cube was at an event, which we had been to other ones before that, but it was very clear to me that we're in a no-excuses government at this point, cause there's a lot of forcing functions. You have one, connected social media, and everyone's like hey, why can't I do that over there? It's like the old iPhone moment on the enterprise. Why can't I bring me iPhone to work? You know, years ago, right? >> Exactly. >> Now you have security looking down the barrel, and IOT happening, and you don't have a thing, so you have Swiss cheese called malware, attacking every hole, every corner of the network potentially is compromised. >> Exactly. >> So security is forcing, and we're at cyberwar. >> We are! >> You can't deny that, so why isn't the Congress emergency funding for more security, or is it happening? >> Well, they need to be, but if you look at, if you look at the way traditional data centers are built and on-premise infrastructure is built, you had a variety of contractors coming in, each kind of doing their own thing, you had this heterogeneous infrastructure that was all built and kind of tangled together, and there wasn't this great way of being able to look at Cloud services or be able to look at a Greenfield environment, and have everything that's happening in that environment aware to you. And that's really what the Cloud is enabling. You're actually. >> You mean program the whole infrastructure? >> Programmable infrastructure, exactly. You're actually, every single thing that happens in a Cloud environment ends up being an API call. Each one of those API calls ends up being logged, and when you have every event that's happening in your environment, you don't have that in a traditional data center. When you have every event that's happening in that environment, and you can apply some of these new primatives that AWS is providing around machine learning and AI, now you're using those to attack those vectors that you're talking about, to protect critical infrastructure, really in ways that you couldn't do before, and you can actually, with this programmable infrastructure, you can actually really look at being able to respond to events, and have autonomic response and remediation of these events. So when something happens, you've programmatically defined how you're going to respond to those events, and it's repeatable. >> Yeah, one of the things I'll share with you, I did an interview with, I think it was the CTO or the CSO of Fortinet, which is a security vendor, >> Mhmm. >> And we were talking, and we were totally geeking out, he was like the complexity of the Cloud actually is an advantage in the security, and I said what do you mean by that? He goes, most of the hackers will focus the main payload of their vector on one particular item, and that's where all their energy, if they have to hunt too far, they kind of give up.6 >> It's just like on the battlefield. The surface area of attack matters, and when you have such a wide, vast surface area of attack, there's no way for them to. >> So you agree with that? >> 100% agree with that. >> How is that, how do I turn that complexity, obviously there's a main range of tools to make the Cloud easier, but complexity of scale, how do I turn that as an IT person or a manager, or an executive, into a security advantage? What do I do? >> So the security advantage is that every time you build a rule, every time you think about compliance and maintaining compliance for your organization, you're actually starting to build knowledge and a new capability. That can be applied programmatically now, across your entire set of enclaves that you use for managing infrastructure, so when we develop one thing as a manage service provider, to make sure we're meeting some kind of compliance mandate, that now can be shared across all of our clients in the space, and this can start to really help create that protective ops infrastructure. >> So you scale more observation space to get more data, that gives you also an advantage. >> It does, it does. And then when you can actually take that data and use it to train to understand where these advance persistent threats are, you can then really start to do things, that this was the province of really large organizations, only in the past. And now AWS has democratized that ability to use these tools around artificial intelligence and machine learning to improve security. >> Robert, you can't go back five years without hearing, are you kidding me, that Cloud is insecure. Turns out, Cloud is becoming a better security paradigm than building on site because of human error or other force majors or any kind of other acts. >> That's exactly right. Anybody who's looking at it from a security perspective and thinks that they can have the same kind of security that, you know, a multi-billion dollar company like AWS can provide, they're mistaken. And the main thing around that is, they don't have transparency to every event happening in that environment, and that's what you get when you start to utilize Cloud services. >> Yeah, I think Verizon was the first company that notified me that this might be the trend. I think this was like a 2011 time-frame. Don't discount a multi-tenant Cloud. >> Exactly. >> Like okay, and they realized and have been tracking that like okay, so big trends in technology, tailwinds and headwinds. What trends are tailwinds for the growth, and what are the headwinds, what's the blockers? >> Well the tailwinds is the fact that I think everybody's kind of not resigned to the fact, but they're seeing the Cloud first as probably a strategy that they should take. And, you know, we've seen the government be laggards in the past with adopting new technology, I think what they're seeing now, especially in the Department of Defense, and then some of the Federal organizations that we're working with, they're actually seeing that perhaps their adversaries are having a competitive advantage by moving into the Cloud, maybe they should look at the competitive advantages that they should have moving into the Cloud infrastructure. Not just security, but the ability to be innovative and agile and deliver services much faster than they've ever been able to deliver them before. >> Well we had a different approach and automated actual code bases so that you can actually deploy services and automatically code them up with glue instantly, so it's interesting. >> That is one of the fundamental things, that when you start looking at infrastructure's code, and you look at things that you can make repeatable in these environments, then look at how many times the government's probably built out a particular enterprise software staff, whether it's Share-A-Plan or >> Authentication. >> It all gets repeated, once that gets cauterized and done right with the right subject-matter experts, then you can start to create service catalogs that these organizations can use and rapidly deploy things in a repeatable and manageable fashion. >> This is an open-source ethos. >> It is. >> We're on the shoulders of others, why replicate something that's already a service, throw it in a service catalog, make it a micro-service, make it an API. >> And that culture's finally transformed in the Federal Government, that didn't used to be the culture, right? >> People must be like, finally! >> It used to be, I have to have my arms wrapped around this, I have to be able to understand everything that's happening, and you would always hear some of these larger organizations say, you know, I don't want to have vendor lock-in. Even now sometimes, you'll see it a little bit. I don't want go with, maybe AWS, because I'll have vendor lock-in, yet for dozens of years, they've been locked into proprietary databases to commercial enterprise platforms, these behemoth software things that AWS again has helped to democratize by providing these primitives and allowing people to build things backed on open-source. >> You're speaking our language, we talk about this all the time, the lock-in, there's always a lock-in spec somewhere, if it's good, the issue is proprietary software and switching costs. >> Yes. >> And choice, right? So that the dimensions to evaluate for customers that we've seen that's successful is, okay, I don't mind lock-in if it's a damn good solution, I'm going to lock that in. >> Right. >> But I have choice. This is going to be interesting, right? So the multi-cloud conversation that is going on around the DOD is interesting, we've been reporting and out in the field, we've been getting the data coming in, saying hey, this DOD kind of overture is interesting, because now if they take the same route as the CIA, we're talking about massive infiltration of Amazon Web Services across the government, because that CIA's kicking ass and taking names with Amazon. >> Mhmm. >> Now you've got the DOD looking down potentially a single-cloud option, other vendors are crying foul calling, we need spec in policy, which is a hijack model of putting in multi-cloud requirement. What's your thoughts on that? Should it be requirement or should we jump off? >> Well, for one, when you have innovators in a space and they take a lead in the space, you're going to get, that's a forcing function for other companies to compete, and that's not a bad thing, it really isn't. And a lot of these organizations, there might be reasons that are very valid reasons for them to consider multi-cloud, or even consider what they have within their own on-premise infrastructure. You've got, you know, tens and tens of years of legacy technical debt in your data center, there's not a reason to pull everything into the Cloud environment, there might be reasons to just let that die a slow death and sunset that. >> Got the mainframe. >> And, like the mainframe stuff, for them to look at even migrating mainframe capabilities into the Cloud, it's a lot of rewrite, it's a lot of things that need to happen. And maybe there's ways that you can extend that on-premise environment, breathe a little bit of life into the on-premise environment, while you're building out your new infrastructure. And that's probably the right path to take. >> And some people choose to have Cobalt code running banks right now, and just because they have that process. >> And it's working, and you know, they'll inevitably come to the time that they have to do that migration. >> Great commentary, great to have you on, great to chat about the technology trends. Smartronix, what are you guys doing, how do you guys fit into this trend, take a minute to talk about what you guys do, and your opportunity. >> Sure, Smartronix is about a 20-year-old company, we talk about some of our competitors will talk about being born in the Cloud, we were actually pretty much born in the enterprise, we helped the Marine Core establish their network operation security command, 20 some years ago, we were first to kind of lead virtualization technologies to help the forward-deployed forces move in and create kind of these tactical data centers, mobile data centers that can move into theater, so it's always kind of been on the forefront of network operations and cybersecurity, and innovative solutions, innovative use of technology, in government. >> The battle field's an instant case of how to deploy. >> Absolutely. >> You need wireless. >> Austere environments, you know, low-power, they used to bring trucks in to be able to set up their mobile data center, and we actually using virtualization technology back in 2004, you know. >> You got to push the envelope. >> You have to. >> Your job is to push the envelope. >> And that's really where I think Smartronix has done a really good job, is that we've helped these large organizations that are in very secure and highly-regulated compliance-driven environments, and utilize technology in innovative ways. More securely, and more optimally in these environments. So when we had a chance in 2009, to do a solution for President Obama at the time, they introduced the Recovery Act, they needed a website to track 750 billion dollars worth of funding. We came in with a pretty innovative solution. They said they had 10 weeks to build this, you're not going to do that in a data center environment. We came in with a solution that said on day one, we're going to utilize Amazon Web Services capabilities, we're going to build out the test endeavor while we build out the data center environment, and we're going to make your deadline by October 1st. And that was really the jumpstart of what we did. >> Do you meet your deadline? >> We absolutely did. >> What was that other website that you didn't actually get the deadline done, they had to bring in? >> Yeah, the healthcare. >> Oh, the Obama. >> So this one was recovery.gov, a very well-documented success, it ended up being the very first cloud-first initiative for the Federal Government. The very first government property running on public Cloud infrastructure, and then from there we migrated to >> Well, he doesn't get the credit he deserves on open government. >> He doesn't. >> He opened up data sets, he changed the game. >> He did, and again, that was, I think when you look at historically, when you look back at the CTOs and CIOs of the Federal Government at that time, they were really trying to look to see how commercial technologies could be applied in the government, how you could get that agility and innovation, and speed of business of commercial and do that in the Federal Government. And I think we embraced that at Smartronix pretty early on, and we were kind of on the leading edge sometimes of delivering this kind of abilities and services. >> Literally. So, you guys are the right group to call for IT to get modernized, because this is is problem. No one can hide anymore, there's no more excuses. And again, this is the lack of innovation. If you've been sitting around not innovating, now there's cyberwars attacking, you got cybersecurity, IT needs to transform, they got to do it like really fast. >> You got all of these competing pressures, security, you've got time, you've got cost, you've got capabilities, all of those things competing. You need to have a trusted advisor, a partner, to get you through that. What Smartronix has created, we call it our four pillars, and these are very simple pillars, but it's really really required for really looking at Cloud services strategy. You have to help the organization define what the business outcomes are that they want in these environments, help them think through what the roadmap and strategy is to get there, and then when you go to the second pillar, which is design, there's unique ways to design things to make it cloud-native, to utilize cloud-native services that also, when you get to the implementation and migration point, you're building these in a programmatic way that makes it easier to operate and manage, and that's the fourth pillar. So if you can get these organizations to think from strategy all the way through to run, all the way through to operations management, you're going to have the more effective organization and better services in your environment. >> Robert Groat, Executive Vice President of Technology at Smartronix, thanks for spending that time with me. >> Thanks, John. >> I'm John Furrier with the Cube, in Washington D.C., actually in Arlington, Virginia at Amazon Web Services Public Sector headquarters, thanks for watching. (bright music)

>> Live from Boston, Massachusetts, it's the CUBE, covering IBM Chief Data Officer Summit, brought to you by IBM. (soft electronic music) >> Welcome to theCUBE's coverage of IBM Chief Data Strategy Officer Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, co-hosting here today with Dave Vellante. >> Hey, Rebecca. >> Great to be working with you again. >> Good to see you again. It's been a while. >> It has. >> Last summer, in the heat of New York. >> That's right, and now here we are in the dreariness of Boston. Dave, we just finished up the keynote. As you said, it's a meaty keynote. It's a seminal time for Chief Data Officers at companies. What did you hear? What most interested you about what Joe Kavanaugh said? >> Well, a couple things. I think it's worthwhile going back a few years. The ascendancy of the Chief Data Officer as a role and a title kind of emerged from the back-office records management side of the house. It really started in regulated industries. Financial services, healthcare, and government. For obvious reasons. These are data-oriented companies. They're highly regulated. There's a lot of risk. So, there's really sort of a risk-first approach. Then, that sort of coincided with the big data meme exploding. Then, this whole discussion of is data an asset or a liability? Increasingly, organizations are looking at it, as we know, as an asset. So, the Chief Data Officer has emerged as the individual who is responsible for the data architecture of the company, trying to figure out how to monetize data. Not necessarily monetize explicitly the data, but how data contributes to the monetization of the organization. That has a lot of ripple effects, Rebecca, in terms of technology implications, skillsets, obviously security, relationships with line of business, and fundamentally the organization and the mission of the company. So, IBM has been pretty leading and aggressive about going after the Chief Data Officer role, and has events like this, the Chief Data Officer Summit. They do them, kind of signature moments, and these little its and bit events. I don't know how many people you think are here. >> 150, I think. >> 150? Okay. And they're the data-rowdy of the Boston community. They're chartered with figuring out what the data strategy is. How to value data and how to put data front and center. Everybody talks about being a data-driven organization, but most organizations-- Everybody talks about becoming a digital business, but a digital business means that you are data driven. The data is first. You understand how to monetize data. You know how to value data. Your decisions are data-driven. I would say that less than 10% of the organizations that we work with are of that ilk. So, it's early days still. What was interesting about what Jim Kavanaugh says, they put forth this cognitive blueprint that Inderpal Bhandari, who'll be on theCUBE later, envisioned and has brought to life in his two years as the Chief Data Officer here at IBM. Now, what I like about what IBM is doing is they're sharing their dog food experience with their clients. He talked about that enterprise blueprint architecture but he also talked about what IBM is doing to transform. So, James Kavanaugh is the Senior Vice President of Transformation at IBM, and works directly for Jenny Remetti. He fundamentally talked about IBM as an organization that is data-first, cloud, and consumerization was the other big trend. Now, I don't know if IBM's hit on all three of those yet but they're certainly working to get there. The other thing that was interesting is they talked about the data warehouse as the former king, and now process is king. What I think is interesting about that, I want to explore this with those guys, is that technology largely is well known today. People have access to technology. You can get security from-- You can log in with Twitter linked in our Facebook. You can-- Look at Uber and Waze. They're really software companies but they're built on other platforms, like the cloud, for example. These horizontal platforms. It's the processes that are new and unknown. You know, when you look at these emerging companies like Air BnB and Uber and Waze, and so forth, the processes by which consumers interact with businesses are totally changed. >> Exactly. That is what Jim and James and Inderpal were saying is that this explosion in data is really forcing companies to rethink their business models. And it's-- Their reporting structures, how they innovate, the kinds of things that they're working on, the kinds of risks that are keeping them up at night. >> Yeah, Kavanaugh cited a study for 4,000 CXOs and they said the number one factor impacting business sustainability in the next five years are technology-related. Which again, I want to poke at that a little bit, because to me technology is not the problem. It's process and skill sets and people are the really big challenges. But, I think really what I interpret from that data, what the CXOs are saying, the challenge is applying technology to create a business capability that involves all the process changes, the organizational changes, the people and skills set issues. Of course, they threw in a little fear, uncertainty, and doubt with GDPR, the recent breaches. The other big thing that you hear from IBM at these events is that IBM is a steward of your data. That it's your data, we're not going to-- They have this notion of data responsibility. He didn't mention-- He said the unnamed west coast companies. Of course, he's talking about Google and Amazon, who are sucking in our data and then advertising to us and telling us, hey there's a special and what to buy and what movie to watch, and so forth. That's not IBM's business. But, there's a nuance there that again, I want to explore with these guys if we have time is, while IBM is not taking your data and then turning it into business through advertising, IBM is training models. I'm interested in hearing IBM's response about where's the dividing line between the model-- sorry, the data, and the model. If the data is informing the model, the model then becomes IP. What happens to that IP? Does it get shared across the client base within an industry? So, I really want to understand that better. >> Right, and that is one thing that Jim Kavanaugh will talk about, definitely, is the responsibility that IBM has in terms of our data and protecting it and keeping it private. >> Yeah, so what I like about these events is they're intimate. We get into it with the CDOs. We got CDOs at banks, we have the influencer panel coming on, a lot are data practitioners. And, so much has changed over the last three or four years that we're happy to be here with the CUBE. >> It is. It's going to be a great day. So, we will have much more here at the IBM Chief Data Officer Strategy Summit. I'm Rebecca Knight for Dave Vallante. Stay tuned. (soft electronic music)

>> Live from Boston, Massachusetts, it's theCUBE, covering IBM Chief Data Officer Summit, brought to you by IBM. (techno music) >> We are wrapping up theCUBE's coverage of the IBM CDO Strategy Summit here in Boston, Massachusetts. I'm your host Rebecca Knight, along with Dave Vellante. It's been a great day here in Boston at the CDO Strategy Summit. >> Yeah, I like these events, they're packed with content, very intimate. You know, not a lot of vendor push -- well, one vendor I guess is pushing. >> (laughs) >> But I like the way, we were talking to Chris Penn about earned media and owned media and paid media - this is all media. It's really the quality of the content that differentiates those media, and IBM always has really solid content here. A lot of practitioners, a lot of, not so much how to but hands on stories, use cases. >> Right. >> Maturity models, things of that nature. And I think we are seeing the maturity of the CDO role from a back office function to one that's sort of morphed into or evolved into data quality and part of the whole data-warehouse-as-king push, and that meant a lot of reporting, a lot of compliance, a lot of governance, to one that is really supporting a monetization mission of the business. And when you think about monetization at the simplest level, there's two ways to get there. You cut costs and you grow revenue. Now you should be careful, not all of these companies are for-profit firms, but in a commercial sense those are really the two levers that you can push, in a lot of forms. Productivity, time to market, time to value, quality, things of that nature, but at the end of the day it comes down to spending less, making more. >> Right, exactly, and I think that you made a great point in that data was the back office, it was sort of something we had to worry about, manage a bit, but now it's really front and center in the organization, and then thinking about using it to make money and to save money. And I think that's what we're learning about too, and what I've appreciated is how candid IBM is being, frankly, about mistakes that it has made, and it's saying this is a blueprint because we've learned. We've learned where we went wrong, and here's what we have to offer other companies to learn from us. >> Well, it's interesting too, if you take my little simple model of how to get value out of data, from IBM's standpoint, it's really a lot of opportunities to cut costs. A huge organization, 300,000 employees so we heard, from Jim Cavanaugh and Indabal Bendari today, how they're applying a lot of their data driven expertise to not only capture that data but understand how they can become more efficient. We haven't seen the growth from IBM. >> That's true. >> Everybody talks about the string of quarterly declines in terms of revenue. The good news is the pace of that decline is slow, that's the best you could say about IBM's top line, but the bottom line seems to be working. And IBM's such a huge machine that you can actually squeeze a lot of cash flow by saving some money. And there are a lot of stories about IBM and the supply chain and making that more efficient, which as we heard was a main focus of a lot of the CFOs, or CXOs out there. So, I mean IBM, we always talk about the steamship, you know, turning, and this has been a five- to seven-year turn, it's going to be interesting to see if IBM really will be perceived as a data driven company. They're pushing cognitive, there's a lot of blow back about Watson and how it's very services-led. Having said that, IBM's trying to do things that Google and Facebook and Amazon aren't trying to do. IBM's trying to solve cancer, for example. >> Right, right. >> Those other companies are trying to push ads in your face. So, got to give props to IBM for that effort. >> The social innovation piece I think is really a part of this company's DNA. >> Yeah, I mean, you know, again, frankly the Silicon Valley crowd sort of poo poos Watson from a technological perspective, honestly I'm not really qualified to address that question, but IBM tends to take capital and pour it into long-term businesses and eventually gets there. So, it's not there yet, and so, but if IBM can use the data to become a more efficient company, be more responsive to its customers, understand the needs of its clients better, that's going to yield results. >> And I think the other part that we've heard a lot about today is the cultural transformation that's needed to make these dramatic changes in your business. As you said, IBM is a huge company, hundreds of thousands of employees dispersed across the globe, so teams working across time zones, across cultures, across languages. That is difficult to really say, no, this is where we're going, this is our blueprint for success. Everyone come on board. >> Well, and you've seen some real cultural shakeups inside of IBM. I mean I was mentioning just a very small example, when you go to the third floor at Armonk now, the big concrete building, it's now all open, this is a corporate executive office. It's an open area with open cubicles, they're nice cubes, believe me, the cubes are nicer than your office, I guarantee it. But they're open, you can see executives, you can talk to executives in an open way. That's not how IBM used to be, it was very closed off and compartmentalized. >> Or everyone was working from home. That frankly... >> Well, that's the other piece of it, right? >> Yeah. >> They said, hey, guys, time to create the beehive effect. And that's created a lot of dislocation, a lot of concerns and blow back, but personally I like that approach. If you're trying to foster collaboration, nothing beats face to face contact. That's why we still have events and that's why theCUBE... >> That's why we're here. >> ...comes to these events, right? >> No, you're absolutely right, a growing body of research has really pointed to the value and the benefit of an open office to spur collaboration, spur creativity, to get colleagues really working and understanding the rhythms of each other's interpersonal lives and work lives, and really that's where the good ideas come from. >> Yeah, so I mean those decisions are tough ones for organizations to make, but I'm presuming that IBM had some data... >> Yeah. >> ...related to this, I hope they did, and made that decision. You know, and it's way too early to tell if that was the right or the wrong move. Again, I tend to lean toward the beehive approach as a positive potential outcome. >> Right, exactly. So, the other piece that we've heard a little bit about today is this talent shortage, the skills shortage because you made this great point when we were talking to Chris Penn of Shift Communications. So much of all of this stuff is now math and science, and that's not what you typically think of as someone who's in marketing, for example. We have a real shortage of people who know data science and analytics, and that's a big problem that a lot of these companies are facing and trying to deal with, some more successfully than others. >> Yeah, I mean I think that the industry is going to address that problem because all this deep learning stuff and this machine learning and AI, it is largely math and it's math that's known. When you really peel the onion and get into the sort of the type of math, you hear things like, oh, support vector machines and probabilistic latent cement tech indexing. >> (laughs) >> Okay, but these are concepts in math and algorithms that have been proven over time, and so I guess my point is, I think organizations are going to bring people in with strong math and computer skills and people who like data and can hack data, and say, okay, you're a data scientist, now figure it out. And over time I think they will figure it out, they'll train people. The hard part about that is, not necessarily the math, if you're good at math you're good at math, it's applying that math to help your organization understand A. How to monetize data, B. How to have data that's trusted. We heard that a lot. >> Yeah. >> So the quality of the data. C. Who gets access to that data, how do you secure and protect that data, what are some of the policies around that data. And then in parallel, how do you form relationships with the line of business? You got geeks talking to wallets. >> Right, yeah. >> How do you deal with that? >> You need the intermediary who can speak both languages. >> And then ultimately the answer to that I think is in skill sets and evolving those skill sets. So those are sort of the five things that the chief data officer has to think about, three are in parallel, or, three are in sequential and two are in parallel. >> Yeah, you also mentioned the trust in the data, and you were talking about it from an internal standpoint of colleagues agreeing, alright, this is what the data is telling us, this is clearly the direction we go in, but then there's the trust on the other side too, which is the trust that the company has with customers and clients to feel okay about using our data, using my data to make decisions. >> Well, I think it's a great point. It was interesting to hear Chris Penn's response to that. He was basically saying, well, we could switch suits, but it's not going to have the same impact. I'm not buying it. I'm really going to keep pushing on this issue because, while I agree that IBM doesn't have the same proclivity to take data and push ads in front of your face, it's unclear to me how you train models and somehow those models don't seep out. Now, IBM has said, we heard some IBM executives say, no, they're the customers' models. But you know, ideas get in people's heads and things happen. And that's just one example. There are many, many other examples. So think about internet of things and the factory floor, and you've got some widget on the floor that's capturing data, and that widget manufacturer wants to use data for predictive analytics, for predictive failures, sending data back home, and then who knows what other insights they're going to gather from that data? Whose data is that? Is that data owned by the widget manufacturer, is that data owned by the factory? >> Right. >> It's their process, it's their work flow. Now of course if I'm the factory owner I'm going to say it's my data, if I'm the widget manufacturer I'm going to say that's my data, so... >> And you're both right. >> And you're both right. >> That's the problem here, is that there's no real arbiter to say, to make that determination. >> Yeah, and I don't think these things have been challenged in court and certainly not adequately, and so there's a lot of learnings that are going to occur over the next decade, and we'll watch that evolution. >> But Jim Cavanaugh is right, we are at a real seminal moment here for this explosion in data, which is really changing the role of the CDO and how it fits in with the rest of the organization. >> Yeah, and I think the other thing to watch is how (mumbles) talks about data driven organizations, digital businesses, cognitive businesses, what are those? Those are kind of buzzwords, but what do they mean? What they mean, in our view, is how well you leverage data to create a competitive advantage, and that's what a digital business does. It uses data differentially (chuckles) to retain customers, attract and retain customers. And so that's what a digital business is, that's what a cognitive business is. Most businesses really aren't digital businesses today, or cognitive businesses today, they're really few and far between. So a lot of work has to be done before we reach that vision. Yeah, everybody throws out the Ubers and the Airbnb's, those are sort of easy examples, but when you have giant logistic systems and supply chains and ERP systems and HR systems with all this stovepipe data, becoming a "digital business" ain't so easy. >> No, and we are really in early days, exactly. So that's something to discuss at the next CDO Strategy Summit. >> And I think there was a lot of discussion early on when the CDO role emerged that they're essentially going to replace the CIO, I don't see it that way. There's a lot of discussion about what's the growth path for the CIO, is it technology or is it business? But I think the CIO's okay. >> Yeah? >> I think the CDO, I think actually there's more overlap between the chief digital officer and the chief data officer, because if you buy the argument that digital equals data, then the chief data officer and the chief digital officer are kind of one in the same. >> Right, right. >> So that to me is a more interesting dynamic than the CIO versus the CDO. I don't see those two roles as highly overlapping and full of friction. I really see that the chief digital officer and the chief data officer are more, should be more aligned and maybe even be the same role. >> And it gets back to the organizational politics that are involved, with all of these massive changes taking place. >> Well, again, first, the starting point for a CDO in a for-profit company is, how can we use data to create value and monetize that value? Not necessarily sell the data, but how does data contribute to our value creation as a company? So, with that as the starting point, that leads to, okay, well, if you're going to be data driven, then you better have measurements, you better have a system. I mean do you use enterprise value, do you use simple ROI, do you use an IOR calculation, do you use a more sophisticated options-based calculation? I mean, how do you measure value and how do you determine capital allocation as a function of those value measurements? The vast majority of the companies out there certainly can't answer that across the board, the CFO's office might be able to answer some of that, but deep down the line of business in the field where decisions are being made, are they really data driven? They're just starting, I mean this is first, second inning. >> Right, right, right. So there's much more to come. Great. Well, you have watched theCUBE's coverage of the IBM CDO Summit. Thanks for tuning in. For Rebecca Knight and Dave Vellante, we'll see you next time. (techno music)

>> Live from Boston, Massachusetts, it's the CUBE covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back to the CUBE's live coverage of the IBM CDO Strategy Summit here in Boston, Massachusetts. I'm your host, Rebecca Knight, along with my co-host Dave Vellante. We're joined by Mark Lack. He is the Strategy Analytics and Business Intelligence Manager at Mueller Inc. Thanks so much for joining us, Mark. >> Thank you for the invite. >> So why don't you tell our viewers a little bit about Mueller and about what you do there. >> Sure, Mueller Inc. is based in the southwest. Ballinger, Texas, to be specific. And, I don't expect anybody, unless they Google it right now, would be able to find that city. But that's where our corporate headquarters and our main manufacturing plant has been. And, we are a company that manufactures and retails steel building products. So, if you think of a warehouse, or a backyard building or even a metal roof, or even I was looking downtown, or downstairs, earlier today, this building is made out of big steel girders. We take those and form them into a product that a customer can use for storage or for living or for any of whatever their use happens to be. Typically, it might be agricultural, but you also find it in very, very large buildings. Mueller is a retailer that happens to manufacture its products. Now, that's a very important distinction, because the company, up until about 15, 20 years ago, viewed itself as a manufacturer that just happened to retail its products. And so when you take the change in the emphasis, your business changes. The way you approach your customers, the way you approach your products, the way you market yourself, is completely different from one side to the other. We've been in business since 1930s, been around for a very long time. It's a family owned business that has it's culture and it's success rooted in West Texas. We have 40 locations all over the southwest. We're headquartered in Ballinger, Texas. We're as far east as Oak Grove, Louisiana and as far west with locations as Albuquerque, New Mexico. >> So you do cognitive analytics for Mueller, so tell our viewers a little bit about what you do there. >> Sure. Mueller has always been on the forefront of technology. Not for technology's sake, but really for effectiveness and efficiency's sake. So Mueller did business process reengineering when it was common for much larger organizations to do. But Mueller took it under as the reality for us to manage our business in the future. We need to have the professional tools to be able to do this. So we set on in our industry using technology in novel ways that our competition just doesn't do. So with the implementation of technology, what you have is a lot of data that comes along. And so we've been very effective using it for our balance scorecard to report metrics and keep the organization on track with that. Giving information back to various parts of the organization and then also creating an analytics platform and program that allows us to really dive deep into the organization and the data and everything that's being thrown off from modern technology. So cognitive analytics. This is something, as you hear about in technology today is, from the robots to artificial intelligence. Cognitive analytics, I think is for us a better way of looking at it of augmented intelligence. We have all of this data, we have these wonderful systems that help give us information to give us the answers we need on our business processes. We have some predictive analytics that help us to identify the challenges going ahead. What we don't have is the deep dive into using these technologies of cognitive to take all of this big data and find answers to situations that it would take a hundred people a hundred years to find out to be able to mine through. So the cognitive analytics is our new direction of analytics, and to be honest with you it's really the natural progression from our traditional analytic system. So as I said before, we have the regular analytics, we have the predictive analytics. As we get into cognitive, this is the next generation of how do we take this data that we have, that's coming at a volume and a velocity and a variety that is so difficult to look at as it is in a spreadsheet, and offload this onto system that can help us to interpret, give us some answers that we can then judge and then make decisions from. >> So, as you said, you have a lot of data. You got customer data, you got supply chain data, you got product data, you got sales data, retail location data. What's the data architecture look like? I mean, some data is more important than other data. How did you approach this opportunity? >> So, a few years ago I went to the first World of Watson, which was in New York. There was about a thousand attendees and Ginni Rometty had had this great presentation and it was very inspiring and she asked, "What will you do with Watson?" And at the time I had no idea what we were going to do with Watson, and so I sat on the plane on the way back and I thought through what are the business case scenarios that we can use to use artificial intelligence in a steel building company in Ballinger, Texas. Don't forget the irony of that part. As we're going to to go back to start using cognitive. So I thought through this and I went to our owner and we had many, many conversations on cognitive. You had the jeopardy, the Watson championship and you started thinking about all of these systems. But the real question was how could we take a new technology and apply it to our existing business to make a difference? And I'm getting to the answer to your question on how it got structured. So we went down the path of investigating Watson, and we've realized that the cognitive is part of our future. And so we plan on leveraging cognitive in many ways. We'd like to see it sales effectiveness, operations effectiveness, transportation effectiveness. There are all sorts of great ideas that we have. One of the challenges we have, and the reason I'm here at the CDO Summit, is when we start to look at our data, the question is are we cognitive ready? And I'll be honest to you, we are for today for a sliver of what cognitive capability is. As you've always heard the numbers 80% of your data is in unstructured format. So we have lots and lots of unstructured data. We have a lot of structured data. When it comes to the analytics around our structured data, we're pretty good, but when you start talking about unstructured data, how do we now take this to add to our structured data and then have a more complete picture of the problem that we're searching? So what I'm hoping to gain here at the CDO Summit is talking to some of these world-class leaders in data operations and data management to help understand what their pain points were. Learn from them so I can take that back and help to architect what our needs are so that we can take advantage of this entire cognitive future that's... >> So you're precognitive. So cognitive ready, let's unpack that a little bit. That means, that what you've got a level of confidence in the data quality? You've got an understanding of how to secure it, govern it, who gets access to it? What does that mean, being cognitive ready? >> So it's going to to be all of those. All of the above. First is, do you have the data? And we all have data, whether it's in spreedsheet on our systems, whether it's in our mobile phone, whether it's on our websites, whether it's in our EIP systems, and I can keep going on >> You got data. >> We have data, but the question is, do we have access to the data? And if you talk to some people, well sure, we have access to the data. Just tell me what data you want and I'll get you access. Okay, well, that is one answer to a much larger problem, because that's only going to give you what your asking for. What the cognitive future is promising for us is we may not know the questions to ask. I think that's the difference between traditional analytics and then the cognitive analytics. One of the benefits of cognitive will be the fact that cognitive will give answers to questions that we're never asked. And so now that this happens, what do we do with it? You know, when we start thinking about having attacking a problem, you know, being data ready, having the data there, that's part of the problem. And I think most companies say we're pretty good with our data. But with the 80% that we don't have access to, the real question is, are we missing that crucial piece of information that prevents us from making the right decision at the right time? And so our approach, and what I'm going to go back with, is understanding the data architecture that those who have gone before me that I can pick up and bring back to my organization and help us to implement that in a way that will make it cognitive ready for the future. You know, it's not just the access to the data; it's having the data. And I had lunch a few years ago with Steve Mills who was a senior executive for IBM, and one of the people at lunch was bold enough to ask him, "How do we know what data to capture?" And he said, very bluntly, "All of it." Now this was about five years ago. So, back then, you're shaking your heads saying, "We don't have storage capabilities. "We don't have the ability to store all these data." But he had already seen the future, and what he was telling us right then was all of it is going to be valuable. So where we are today, we think we know what data's valuable. But cognitive's going to help us to understand what other data might me valuable as well. >> So I'm interested in your job from the perspective of the organizational change. And you work for, as you said, a small family-owned company. Smallish of family-owned company. And we've heard a lot of today about the business transformation, the technology involved, and how that has really changed dramatically over the last decade. But then, there's also this other piece which is the social and cultural change within these organizations. Can you describe your experience in terms of how your colleagues interpret your world? >> You're asking me those questions 'cause you can see the bruises from whatever I have to accomplish. (laughter) You know, within an organization, one of the benefits of working that I found at Muller, and it's a family organization, is that those who work there, and I've been there for 18 years, and I'm still considered a newcomer to the organization right after 18 years. But we're not there unless we have a strong commitment to the organization and to the culture of the company. So, while we may not always agree as to what the future needs to hold, okay? We all understand we need to do what's best for this company for its long term survival. At the end of the day, that's what we're there to do. So culturally, when you first come up with saying you're going to do artificial intelligence, you know, you got a lot of head-scratching, especially in West Texas. I have a hard time explaining even to those around me what it is that I do. But, once you start telling the story that we have data, we have lots of data, and that there might be information in that data that we don't know now but in the future we may have, and so, it's important for us to capture that data and store it. Whether or not we know that there's immediate value, we know there's some value, okay? And if we can take that leap that there's going to be some value, and we're here with the help of the organization faces, we know that there are challenges to every organization. We're a still building company in Ballinger, Texas. Now I know I keep saying that, but what if a company like Uber comes up with metal building and all of a sudden, we have new challenges that we never thought we'd face? Many organizations that have been up, industries that have been in upheaval from these changes in either technology access or a new idea that splits the difference. We want to make sure we can stay ahead, and so when we start talking about that from a culture, we're here for the long term value of the company. We're committed to this organization, so what it do we need to do? And so, you know, the term "out of the box thinking" is something that sometimes we have to do. That doesn't mean it's easy. It doesn't mean that we all immediately say, "Aha! This is what we're going to do." It takes convincing. It takes a lot of conversation, and it takes a lot of political capital to show that what it is that we're going to do is going to make sense and use a lot of good examples. >> Well, and you come to tongue-in-cheek about people rolling their eyes about AI and so forth, but any manufacturer who sees 3D printing and the way it's evolved goes "Wow!" And then the data that you can capture from that, so, I wanted to ask you, when you talk to your colleagues and people are afraid that robots are going to take over the world and so forth, but what are the things that when you think about augmented intelligence that, you know, where do the machines leave off and the humans pick up? What kinds of things do humans do in your world that machines don't do that well? >> So, you know, if I go back and think about analytics, for example, there's a lot of time collecting data, storing data, translating data, creating contract to retrieve that data, putting that data into a beautiful report and then handing it out. Think of all that time that it takes to get there, right? A lot of people who are in analytics think that they're adding value by doing it. But to be honest with you, they're not. There's no value in the construct. And so, what the value is in the interpretation of that data. So what do computers do well and what do we do well? We do well at interpreting what those findings tell us. If we can offload those transactions back to a machine that can set the data for us, automatically construct the data, put it into a situation for us that can then allow us to then interpret the results? Then we're spending the majority of our time adding value by interpreting and making changes with the company versus spending that same time going back and constructing something that may or may not be something that may add value. So we spend 80% of our time creating data for a report. The report, now we have to test the report to determine, can I communicate this the right way? You have machine learning now and you have tools that will then take this data and say, "Oh, this is numerical data. "This looks like general ledger data. This is the type of way this data should be displayed." So I don't have to think of a graph. It suggests one for me. So what it does is then allow me to interpret the results, not worry about the construct. >> So you can focus on the things that humans do well. But the other thing I want to talk to you about is the talent issue. I mean you guys, you've mentioned before that you're based in West Texas and you are working on a real vanguard in your industry. As I said, you were someone who is thinking about whether or not Uber is going to say, "Let's make steel buildings." I mean, is that a problem that you're facing, that your company is facing? >> Well, there is no joke, right, that the fact of the future's going to have a man and a dog. And the man's job is to feed the dog, and the dog's job is to bite the man if he tries to touch any of the machinery, right? So, I don't think that we're there. The jobs aren't going to be eliminated to where people are not able to add value. But finding a talent, back to your question, is the expectation that we have of talent, it is scarce. Finding people that have the skills to now interpret the data, so you can find people that have a lot of time that can do any of those steps in between. But now, what's happened is, you want people to add value, not create constructs that don't add the value. So the type of talent that you look for are people who can interpret this information to give us the better answers that we need for the organization to thrive. And that's really where I see the talent shifting is on more forward-looking, outcome-based, value-based decision making, not as much on the development of items that could be offloaded to a machine. >> Yeah, I mean, interpretation, creativity, ideation. I mean, machines have always replaced humans. We've talked about this on The Cube before, but the first time in human history, machines are replacing humans in cognitive functions. I mean, you gave an example of the workflow of developing a report, which... >> Kenney Company can relate to, yeah. >> But yeah, 10 years ago, that was like super valuable. Today it's like, "Let's automate that." >> Well, but the challenge I think where people have is where do they add value? What is the problem that we're trying to solve? It's where do we add value. If we add value creating the construct, you aren't going to be employed, because something else is going to do that. >> But if you add value on focusing on the output and being able to interpret that output in a way that adds value to your company, you'll be employed forever. So, you know, people that can solve problems, take the information, make decisions, make suggestions that are going to make the company better, will always be employed. But it's the people who think they add value flipping a switch or programming a lever, now, they think their value's very important there, but I think what we have to do and it behooves us, is to translate those jobs into where do you add value? Where is the most important thing you need to be doing for the success of this company? And that I think is really the future. >> Are you... We haven't asked any IoT questions today. I want to ask you, are you sort of digitizing, instrumenting for your customers the end products of what you guys produce, and how was that creating data? >> You know, we haven't, we talked about it. We don't have products that, we're not selling things that are machinery that might break down and give us information, and so, we're building final products that are there, that people will then do different things with. So, IoT hasn't worked for us from a product standpoint, but we are looking at our various machinery and making sure that we have understanding as to those events that are causing a break down. One of the challenges we have in our industry is if we have a line that manufactures apart, if it goes down, okay, now it shuts everything down. So we have a duplicate, which can get very expensive. We have duplicates of everything, and how many duplicates do you need to have to make sure you have duplicates of the duplicates? So if we can start to look at the state of this coming from our machinery, and use that as a predictor, then we can use that, and so you have sort of an IoT thing there by looking at the data that's there. But is it feeding back into our normal reporting systems? It's not necessarily like it is from a smartphone are enabled like that. >> No, but it's anticipating a potential outage. >> Sure. >> And avoiding that. Yeah, great. >> Well Mark, thanks so much for coming on The Cube. It was wonderful conversation. >> Thank you. >> I'm Rebecca Knight with Dave Vellante. We will have more from the CDO Summit just after this. (upbeat music)

>> Live from Boston, Massachusetts, it's the Cube, covering IBM Chief Data Officer Summit. Brought to you by IBM. >> Welcome back to the Cube's live coverage of the IBM CDO Summit here in Boston Massachusetts. I'm your host, Rebecca Knight, along with my co-host Dave Vellante. We are joined by Caitlin Halferty. She is the Chief of Staff IBM Data Office, and also John Backhouse, the chief information officer and senior VP at CareEnroll. Thank you both so much for coming on the Cube. >> Great to be here. >> Thank you, good to see you. >> So before the cameras were rolling, John, we were talking about how you have this very unique vantage point and perspective on the role of the CIO and CDO. Can you tell our viewers a bit about your background? >> Sure. I started off in the military. I was in the army for 12 years as a military intelligence officer. I then moved to the NHS, which is a national health service in England and where I wrote the Clinical Care Pathways for myocardial infraction and diabetes pre-hospital. I then moved to the USA and became Chief Data Officer for Envision Healthcare, one of the largest hybrid providers of insurance and clinical care. And then I became a CIO for a multi-state Medicare program. >> So you've been around, so to speak (laughter) But the last two roles, CIO and CDO, so how would you describe them? I mean obviously two different places, but is it adversarial? Is it cooperative? What is the relationship like? >> I think its, the last couple of years, CDO role has matured, and it's become a direct competition between a CIO and a CDO. As my experiences I've been fighting for the same budget. I've been fighting for the same bind, I've been fighting for the same executives to sponsor my programs and projects. I think now as the maturity of the CDO has stepped out, especially in health, the CDO has a lot more power between the conduit between the business and IT. If the CDO sits in IT he's doomed for failure because it's a direct competition of a CIO role. But I also think the CIO role has changed in the way that the innovation has stepped up. The CIO role used to be "Your career is over, CIO." (laughter) Now it's the innovational aspect of infrastructure, cloud cognitive analysts, cognitive solutions and analytics so that the way the data is monetized and sold and reused, in the way that the business makes decisions. So I see a big difference. >> How much of that, sort-of authority, if I can use that term, of the chief data officer inside of a regulated company versus you're in the office of the chief data officer in an unregulated company, compare and contrast. >> Well, the chief data officer's got all the new regulatory compliancies coming down the GDC, the security, safe harbor, and as the technology moves in to cloud it becomes even harder. As you get PCI, HIPPA and etc. So, everything you do is scrutinized to a point where you have to justify, why, what, and when. And then you have to have the custodian of who is responsible. So then no longer can you say, "I got the data for this reason." You have to justify why you have that information about anything. And I think that regulatory component is getting stronger and stronger. >> And you know, we've often talked about the rise of the CDO role and how it's changed over the last few years. Primarily it started in response to regulatory and compliance concerns within financial services industries as we know banking and insurance, healthcare. And we're seeing more and more retail consumer products. Other industries saying look, "We don't really have enterprise-wide management of data across the organization" Investing in that leadership role to drive that transformation. So I'm seeing that spread beyond the regulated industries. >> Well Caitlin, in the keynote you really kicked off this conference by reminding us of why we're all here and that is to bring chief data officers together, to share those practices, to share what they've learned in their own organizations. Hearing John talk about the fight for resources, the fight to justify its existence. What do you think, how would you tease out the best practices around that? >> The way we've approached it, you know, I've mentioned this cognitive enterprise blueprint that we highlighted and released this morning. And this has been an 18-month project for us. And we've done it in close partnership with folks like John, giving a lot of great insight and feedback. And essentially the way we see it is there's these four pillars. So it's the technology piece and getting the technology right. It's the business process, both CDO-owned processes as well as enterprise-wide. And then the new piece we've added is around data, understanding the data part of it is so important. And so we've delivered the blueprint and then taking it to the next level to figure out what are the top used cases. How do we prioritize to your question, where prioritized-used cases. >> So, come back to the overlap between the CIO and CDO. I remember when I first met Ender Paul, we had him on the Cube and he's seared into my brain he's five points that the CDO has to do, the imperative. And three were sequential two were in parallel. One was figure out how to monetize, how you're data can contribute to the monetization of your company. Second was data trust and sources, third was access to that data and those were sequential >> Right. Processes and then he said "Line of business and skill sets were the other two that you kind of do in parallel, >> Absolutely. forge relationships with a lot of businesses and re-skill. Okay, so with that as the Ender Paul framework for what a CDO's job was... I loved it, I wrote a blog about it, (laughter) I clipped it. >> That's very good >> But the CIO hits a lot of those areas, certainly data access, of trust and security, the skill sets. Thinking about that framework, first of all do you buy it? I presume it's pretty valid, but where do you see the overlap and the collaboration? >> So I think that the framework works out and what IBM has produced is very tangible, it means you can take the pieces and you can action them. So, before you have to reflect on one: building the team, getting the right numbers in the team, getting the right skill sets in the team. That was always a challenge because you're building a team but you're not quite sure what the skill set is until you've started the plan and the math and you've started down that pathway, so with that blueprint it helps you to understand what you're trying to recruit for, is one aspect, and then two is the monetization or getting the data or making it fit for purpose, that's a real challenge and there's no magic wand for this, you know it depends on what the business problem is, the business process and understanding it. I'm very unique cause not only have I understand the data and the technology I actually give it the clinical care as well, so I've got the translations in the clinical speak into data, into business value. So, I can take information and translate it into value very quickly, and create a solution but it comes back to that you must have a designer and the designer must be an innovator, and an innovator must stay within the curve and the object is the business problems. That enables, that blueprint to be taken and run with, and hit the ground very quickly in an actionable manner. for me information in health is about insights, everybody's already doing the medical record, the electronic record, the debtor exchange. It's a little immature in health and a proper interoperability but it there and it's coming it's the actually use of and the visualization of population analysis. It used to be population health, as in we knew what we were doing after the fact, now we need to know what we are doing before the fact so we can target the outreach and to move the right people in the right place at the right time for the right care, is a bigger insight and that's what cognitive and the blueprint enables. >> So Caitlin, it feels like these two worlds are really coming together, you know, in the early days it was just really regulated businesses. >> Correct. >> Now with GDPR now everybody is a regulated business, >> Right. >> And given that EMR, and Meaningful Use and things like that are kind of rote now. >> Yeah. >> Regulated industries are really driving for that value holy grail. >> Yeah. >> So, I wonder if you could share your perspectives on those two worlds coming together. >> Yeah I do see them coming together, as well as the leadership. >> Right, yeah. >> Across the C-sweep, it's interesting we host these two in-person summits, one in the spring in San Francisco one here in Boston in the fall and we get about 120 or so CDOs that join us. We pull for, what are top topics and we always get ones around data monetization, talent, the one again that came up this year was changing nature of to the point on building those deep analytics partnerships within the organization, changing the relationships between CDOs and C-sweep peers. We do a virtual call with about 25 CDO's and we had John as our guest speaker, recently >> Yeah. And it was our best attended call, (laughter) it was solely focused on how CDOs and CIOs can partner together to drive business critical cross-enterprise initiatives, like GDPR in ways that they haven't in the past. >> Yeah. >> It was a reinforcement to me that building those relationships, that analytic partnership piece, is still top of mind to our CDO community. >> Yeah, and I think that the call itself was like sun because I invited the chief of their office and now he's the innovator and the chief information officer used to be the guy who kept the lights on, that's no longer the fact. The chief information officer is the innovator of the infrastructure, the design, the monetization, the value, the business and the chief in their office now has become the chief designer of information to make it fit for purpose, for presentation, for analytics, for the cognitive use of the business. Those roles now, when you bring them together, is extremely powerful and as the maturity comes of these chief there officer roles with the modern approach to chief information then you have a powerful, powerful dynamic. >> Well let's talk about the chief innovator, it reminds me of 1999. (laughter) >> If you want to be a CEO you've got to go the CEO's office and then Y2K on the whole thing blew up. (laughter) >> What's different now though, is the data >> Yeah. - [Caitlin] Absolutely. >> There certainly was a lot of data back then but not nearly like it is today and the technology underneath it, the whole cloud piece, but I wonder if you could talk about the innovation piece of that a little bit more >> Sure. and it's relationship to the data. >> So, I mean we've always been let's all go to the data warehouse, let's have a data lake, let's get the data scientist to fix the data lake. (laughter) >> Yeah. >> And then he's like " Whoa, well what did he do?" "Does it do anything? Show me." And you know now that physical massive environment of big service and big cages and big rooms with big overhead expenses is no longer necessary. I've just put 91 servers for an entire state's data and population in a cloud environment, multiple security levels with multiple methods of new innovational cloud management. And I've been able to standup 91 server in six and a half minutes. I couldn't even procure that... (laughter) - Right. >> Before >> I'd be months, and months >> Yeah, to put physical architecture together like that but now I can do it in six and a half minutes, I can create DR rapidly, I can do flip over active-active and I can really make the sure of it. Not only can I use the infrastructure I can enable people to get information at the point where it's needed now, far easier than I ever did before. >> So talking about how the technology has moved and evolved and changed so rapidly for the better but yet there is still a massive talent shortage of the people who, as you said - [John] Yeah >> Who can speak the language and take the data and immediately translate it into business value. What are you doing now about this talent shortage? What's your take on it and what are we doing to fix it? >> Yeah >> I would say, in one of the morning keynotes, Jim Cavanaugh our SVP for transportation operations got that question around how do you educate internally what it means to be a cognitive enterprise when there are so many questions about what does that really mean? And then how do you access skill against those new capabilities? He spoke about some of the internal hackathons that we did and ran sort of an internal shark tank-like to see how those top projects rise, align resources against it and build those skills and we've invested quite a lot internally as I know many of our clients have around what we call cognitive academy to ensure that we've one: figured out and defined what it means in this new...what type of new skills and then make sure that we're able to retrain and then keep and retain some of our new talents. So I think we're trying that multi-prong approach to retrain and retain as well. >> You guys use the term cognitive business we use the term digital business cause we can't use IBM's terms (laughter) But to us there the same thing >> Why not? >> Cause it's all about... (laughter) >> Cause were independent - [Caitlin] Dave's upset here >> But to us it's all about how you leverage data >> Yeah. >> And how you use data to >> Yeah. >> Maintain and to get and maintain costumers. So since we're playing CX bingo >> Yeah right. >> Chief digital officer, Bob Lord >> Right >> Bob Lord and Ender Paul Endario are two totally different people and there roles are quite different, but if it's all about the data and you buy that premise what is the chief digital officer do? they are largely driving revenue >> Absolutely >> That's understandable but it's part of your job too >> Right >> Or former job as a CDO and now as an innovation officer. Where do those roles fit? >> I think there's a clear demarcation line and especially when you get into EIM solutions as in Enterprise Information Management. And you start breaking those down and you've got to break them down into master data management and you start putting the domains together, the multi-master domains, and one of them is media, and media needs someone to own it, be the custodian, manage it, and present it to the business for consumption, the other's are pure data driven. >> Yeah. >> Master patient, master member, master costumer, master product, they all need data driven analytics to present information to the business. You can't just show them a sequel schemer and say "There you go." >> Yeah. (laughter) >> It doesn't work so there is different demarcations of specialist skills and the presentation and it got to be that hybrid between the business and IT. The business and the data, the business and the consumer and that is, I think the maturity of way this X-sweet is going these days >> Yeah. >> One thing we've seen internally to that point, I agree there's a clear demarcation there, is when we do partner with the digital office it can be to aid say digital sellers so we have a joint project going where we are responsible for the data piece of it >> Yeah. >> And then we are enabling our digital sellers, we're calling it cognitive sales advisor to pull dispersed pieces of costumer data that are currently housed in cylos across the organization, pull that into a digital, user friendly app, that can really enable those sellers, so I think there's some nice opportunities just as there are CDOs and CIOs to partner, for a data officer and a digital officer as well. >> One of our earlier guests was talking about some of the things that he's hearing in the break out sessions and he said "You know they could have been talking about the same stuff ten years ago, these intractable organizations that aren't quite there yet." What do you think we will be talking about next CDO summit? Do you think there will come a point where were not talking about is data important? Or does data have a role in the organization? When do you think that will happen? (laughter) >> Every time I say we're done with governance right? >> Yeah >> We're done and then governance >> Comes right back - Top topic (laughter) >> If you get the answer to that can I have the locker notes? (laughter) >> Sure >> Exactly, Exactly >> I think in the next ten years we're not going to ask anymore about what did we do, we're going to be told what we did. As in we're going to be looking forward, thing are going to be coming out and saying this is the projected for the next minute, second, hour, month, year and that's the big change. We are all looking back, what did we do? How did we do? What was the goals we tried to achieve? I don't think that's going to be what we ask next month, next year, next week. It's going to be you're going to tell me what I did and you're going to tell me what I'm doing. And that's going to change, and also the healthcare market, the way that health is prescriptive, they're not prescribed anymore. They way that we diagnose things against the prognosis, I think that the way we manage that information is going to change dramatically. I would say too, I've been working quite a bit with a client in Vegas, a casino, and their current issue or problem is they have all this data on what their guest do from the moment they check in, they get their hotel key, they know where spend, where they go to dinner, what type of trip they're on, is it business is is pleasure. Are the kids in town, different behaviors, spending patterns accordingly. >> Yeah. >> And the main concern they relate to us is I can't do anything about it until my guest has exited the property and then I'm sending them outreach emails trying to get them back, or trying to offer a coupon. >> Yeah. >> You know post - [John] Yeah, yeah. >> And they're gone. >> And what if I could do some real time analysis and deliver something of value to my guest while they are on site and we are starting to see some of that with Disney and some other companies. - [John] Yeah. >> But I think we will see the ability to take all this data that we already have and deliver it. >> In real time. -[John] Yeah. >> Influence behavior >> Right >> And spending patterns in real time that's what I'm excited about. >> Yeah and these machines will actually start making decisions, certain decisions for the brand. >> Yeah >> Right >> At the point where it can affect an outcome. >> Right, right, Which I think is hard >> It's starting >> Yeah >> No question, you certainly see it in fraud detection today, you mentioned Disney. >> The magic bands >> Right >> And the ability to track >> Yeah >> Where you are and that type of thing, yeah >> Great >> We're starting cyber security cause cyber security, an aspect of user log, server log, network, are looking for behavioral patterns and those behavioral patterns are telling us where the risks and the vulnerabilities are coming from. >> Thing that humans >> Yep >> Would not see that >> People don't see the patterns, yep. >> You're absolutely right, >> right >> They just wouldn't see the patterns of the risk. >> Excellent, well John, Caitlin, thanks so much for coming on the Cube it's always a pleasure to talk to you. >> Thank you - Great, thank you. >> I'm Rebecca Knight for Dave Vellante we'll have more just after this.

>> Live from Boston, Massachusetts. It's The Cube! Covering IBM Chief Data Officer's Summit. Brought to you by IBM. (techno music) >> Welcome back to The Cube's live coverage of the IBM CDO Strategy Summit here in Boston, Massachusetts. I'm your host Rebecca Knight along with my Co-host Dave Vellante. We're joined by Jennifer Gibbs, the VP Enterprise Data Management of TD Bank, and Seth Dobrin who is VP and Chief Data Officer of IBM Analytics. Thanks for joining us Seth and Jennifer. >> Thanks for having us. >> Thank you. >> So Jennifer, I want to start with you can you tell our viewers a little about TD Bank, America's Most Convenient Bank. Based, of course, in Toronto. (laughs). >> Go figure. (laughs) >> So tell us a little bit about your business. >> So TD is a, um, very old bank, headquartered in Toronto. We do have, ah, a lot of business as well in the U.S. Through acquisition we've built quite a big business on the Eastern seaboard of the United States. We've got about 85 thousand employees and we're servicing 42 lines of business when it comes to our Data Management and our Analytics programs, bank wide. >> So talk about your Data Management and Analytics programs a little bit. Tell our viewers a little bit about those. >> So, we split up our office of the Chief Data Officer, about 3 to 4 years ago and so we've been maturing. >> That's relatively new. >> Relatively new, probably, not unlike peers of ours as well. We started off with a strong focus on Data Governance. Setting up roles and responsibilities, data storage organization and councils from which we can drive consensus and discussion. And then we started rolling out some of our Data Management programs with a focus on Data Quality Management and Meta Data Management, across the business. So setting standards and policies and supporting business processes and tooling for those programs. >> Seth when we first met, now you're a long timer at IBM. (laughs) When we first met you were a newbie. But we heard today, about,it used to be the Data Warehouse was king but now Process is king. Can you unpack that a little bit? What does that mean? >> So, you know, to make value of data, it's more than just having it in one place, right? It's what you do with the data, how you ingest the data, how you make it available for other uses. And so it's really, you know, data is not for the sake of data. Data is not a digital dropping of applications, right? The whole purpose of having and collecting data is to use it to generate new value for the company. And that new value could be cost savings, it could be a cost avoidance, or it could be net new revenue. Um, and so, to do that right, you need processes. And the processes are everything from business processes, to technical processes, to implementation processes. And so it's the whole, you need all of it. >> And so Jennifer, I don't know if you've seen kind of a similar evolution from data warehouse to data everywhere, I'm sure you have. >> Yeah. >> But the data quality problem was hard enough when you had this sort of central master data management approach. How are you dealing with it? Is there less of a single version of the truth now than there ever was, and how do you deal with the data quality challenge? >> I think it's important to scope out the work effort in a way that you can get the business moving in the right direction without overwhelming and focusing on the areas that are most important to the bank. So, we've identified and scoped out what we call critical data. So each line of business has to identify what's critical to them. Does relate very strongly to what Seth said around what are your core business processes and what data are you leveraging to provide value to that, to the bank. So, um, data quality for us is about a consistent approach, to ensure the most critical elements of data that used for business processes are where they need to be from a quality perspective. >> You can go down a huge rabbit whole with data quality too, right? >> Yeah. >> Data quality is about what's good enough, and defining, you know. >> Right. >> Mm-hmm (affirmative) >> It's not, I liked your, someone, I think you said, it's not about data quality, it's about, you know it's, you got to understand what good enough is, and it's really about, you know, what is the state of the data and under, it's really about understanding the data, right? Than it is perfection. There are some cases, especially in banking, where you need perfection, but there's tons of cases where you don't. And you shouldn't spend a lot of resources on something that's not value added. And I think it's important to do, even things like, data quality, around a specific use case so that you do it right. >> And what you were saying too, it that it's good enough but then that, that standard is changing too, all the time. >> Yeah and that changes over time and it's, you know, if you drive it by use case and not just, we have get this boil the ocean kind of approach where all data needs to be perfect. And all data will never be perfect. And back to your question about processes, usually, a data quality issue, is not a data issue, it's a process issue. You get bad data quality because a process is broken or it's not working for a business or it's changed and no one's documented it so there's a work around, right? And so that's really where your data quality issues come from. Um, and I think that's important to remember. >> Yeah, and I think also coming out of the data quality efforts that we're making, to your point, is it central wise or is it cross business? It's really driving important conversations around who's the producer of this data, who's the consumer of this data? What does data quality mean to you? So it's really generating a lot of conversation across lines of business so that we can start talking about data in more of a shared way versus more of a business by business point of view. So those conversations are important by-products I would say of the individual data quality efforts that we're doing across the bank. >> Well, and of course, you're in a regulated business so you can have the big hammer of hey, we've got regulations, so if somebody spins up a Hadoop Cluster in some line of business you can reel 'em in, presumably, more easily, maybe not always. Seth you operate in an unregulated business. You consult with clients that are in unregulated businesses, is that a bigger challenge for you to reel in? >> So, I think, um, I think that's changing. >> Mm-hmm (affirmative) >> You know, there's new regulations coming out in Europe that basically have global impact, right? This whole GDPR thing. It's not just if you're based in Europe. It's if you have a subject in Europe and that's an employee, a contractor, a customer. And so everyone is subject to regulations now, whether they like it or not. And, in fact, there was some level of regulation even in the U.S., which is kind of the wild, wild, west when it comes to regulations. But I think, um, you should, even doing it because of regulation is not the right answer. I mean it's a great stick to hold up. It's great to be able to go to your board and say, "Hey if we don't do this, we need to spend this money 'cause it's going to cost us, in the case of GDPR, four percent of our revenue per instance.". Yikes, right? But really it's about what's the value and how do you use that information to drive value. A lot of these regulation are about lineage, right? Understanding where your data came from, how it's being processed, who's doing what with it. A lot of it is around quality, right? >> Yep. >> And so these are all good things, even if you're not in a regulated industry. And they help you build a better connection with your customer, right? I think lots of people are scared of GDPR. I think it's a really good thing because it forces companies to build a personal relationship with each of their clients. Because you need to get consent to do things with their data, very explicitly. No more of these 30 pages, two point font, you know ... >> Click a box. >> Click a box. >> Yeah. >> It's, I am going to use your data for X. Are you okay with that? Yes or no. >> So I'm interested from, to hear from both of you, what are you hearing from customers on this? Because this is such a sensitive topic and, in particularly, financial data, which is so private. What are you, what are you hearing from customers on this? >> Um, I think customers are, um, are, especially us in our industry, and us as a bank. Our relationship with our customer is top priority and so maintaining that trust and confidence is always a top priority. So whenever we leverage data or look for use cases to leverage data, making sure that that trust will not be compromised is critically important. So finding that balance between innovating with data while also maintaining that trust and frankly being very transparent with customers around what we're using it for, why we're using it, and what value it brings to them, is something that we're focused on with, with all of our data initiatives. >> So, big part of your job is understanding how data can affect and contribute to the monetization, you know, of your businesses. Um, at the simplest level, two ways, cut costs, increase revenue. Where do you each see the emphasis? I'm sure both, but is there a greater emphasis on cutting costs 'cause you're both established, you know, businesses, with hundreds of thousands, well in your case, 85 thousand employees. Where do you see the emphasis? Is it greater on cutting costs or not necessarily? >> I think for us, I don't necessarily separate the two. Anything we can do to drive more efficiency within our business processes is going to help us focus our efforts on innovative use of data, innovative ways to interact with our customers, innovative ways to understand more about out customers. So, I see them both as, um, I don't see them mutually exclusive, I see them as contributing to each. >> Mm-hmm (affirmative) >> So our business cases tend to have an efficiency slant to them or a productivity slant to them and that helps us redirect effort to other, other things that provide extra value to our clients. So I'd say it's a mix. >> I mean I think, I think you have to do the cost savings and cost avoidance ones first. Um, you learn a lot about your data when you do that. You learn a lot about the gaps. You learn about how would I even think about bringing external data in to generate that new revenue if I don't understand my own data? How am I going to tie 'em all together? Um, and there's a whole lot of cultural change that needs to happen before you can even start generating revenue from data. And you kind of cut your teeth on that by doing the really, simple cost savings, cost avoidance ones first, right? Inevitably, maybe not in the bank, but inevitably most company's supply chain. Let's go find money we can take out of your supply chain. Most companies, if you take out one percent of the supply chain budget, you're talking a lot of money for the company, right? And so you can generate a lot of money to free up to spend on some of these other things. >> So it's a proof of concept to bring everyone along. >> Well it's a proof of concept but it's also, it's more of a cultural change, right? >> Mm-hmm (affirmative) It's not even, you don't even frame it up as a proof of concept for data or analytics, you just frame it up, we're going to save the company, you know, one percent of our supply chain, right? We're going to save the company a billion dollars. >> Yes. >> And then there's gain share there 'cause we're going to put that thing there. >> And then there's a gain share and then other people are like, "Well, how do I do that?". And how do I do that, and how do I do that? And it kind of picks up. >> Mm-hmm (affirmative) But I don't think you can jump just to making new revenue. You got to kind of get there iteratively. >> And it becomes a virtuous circle. >> It becomes a virtuous circle and you kind of change the culture as you do it. But you got to start with, I don't, I don't think they're mutually exclusive, but I think you got to start with the cost avoidance and cost savings. >> Mm-hmm (affirmative) >> Great. Well, Seth, Jennifer thanks so much for coming on The Cube. We've had a great conversation. >> Thanks for having us. >> Thanks. >> Thanks you guys. >> We will have more from the IBM CDO Summit in Boston, Massachusetts, just after this. (techno music)