(upbeat music) >> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. >> Hi everyone, welcome back to theCUBE's coverage of AWS Public Sector Partner Awards Show. I'm John Furrier, host of theCUBE. We're here in Paolo Alto, California but during COVID, we're doin' all the remote interviews and gettin' the stories and celebrating the awards for the Partner Awards Show. And the award here is most customer-obsessed mission-based win in the federal area. We've got two great guests, Greg Siegel Senior Manager at Accenture and Frank Urbano Program Manager with the FBI Federal Bureau of Investigation. Gentlemen, thank you for joining me and congratulations on the win. >> Thank you. >> Thank you. >> So let's break this down. So you're federal, big category, a lot of intelligence agencies been using the gov cloud and Amazon. What's the mission win? What's the award for? Tell us. >> So I guess the award is the Bureau was shutting down our data centers and we needed to move to an infrastructure that would support our application. That was the first problem that we were trying to actually solve. But also, we know we were always seeing a performance hit on our infrastructure, and we always suspected that by moving to the gov cloud, we'll see an increase in performance because once we went live in our current, in or old environment seven years ago, performance was always an issue, our end users were always complaining and then we moved to our VMs four years after that. We saw an increase in performance a little bit but then once we moved over to the cloud, the FBI secret cloud, we heard crickets. The end users haven't been complaining. Greg and I were actually talking about that the other day how, you know, there's minimal complaints as far as performance. That's going to be one of the themes you hear throughout is performance, performance, performance. >> Got to love the no complaints, that means it's workin', people are doin' their job, gettin' the job done. Greg, I want to get your thoughts on this because Accenture, we've had many conversations with you guys over there about being agile and now you're a partner. You know, the FBI, I saw a presentation in person at Reinvent, I think last year where the FBI was like, "Lookit, our workloads "are increasing and budget isn't increasing "at the same rate." So it's kind of like, you know, "I need more power." It's like that scene in Star Trek, "Scotty, more power," you need to get that power. Take us through that transformation because one, you got a good user experience. That means people are doin' their job. But the cases get bigger, the more workload is there, but the budget's got to be increased or leveraged better. What's your thoughts? How do you tackle that problem because it's do more with less, classic do more with less. >> That's right. Yeah, so as Frank said, I think the system had been live for about seven years and you see over that time in the traditional data centers how the performance requirements increase but as you said, are kind of there on hardware and not easily able to adapt and overcome those. So, you know, when it became clear that the cloud move was a serious consideration we were able to pull on a few other experiences that the firm has had moving similar technologies to the cloud and then kind of combined that with the experience implementing technology at the FBI. And those two components kind of together were able to get us on a path to successfully move to the cloud and be, you know, kind of one of the first big systems at the FBI to make that transition. So that was our approach. >> Frank, I'd like to ask, you mentioned crickets. That means, that's good, actually. No one's complaining. What was it like before when you had the data center? What were some of the complaints? What were some of the challenges that you were dealing with? >> So (chuckling) so some of the challenges we were dealing with was, to give an example, when we went live seven years ago, we actually deployed our application on hardware that was already end of life. And so immediately we saw challenges there. And so by moving to the cloud, it gave us a lot of architectural flexibility. And what I mean by that is that we control, now, our own destiny, meaning that in the past, we would have to put in change requests to have firewall configuration changes. Now that responsibility is with us. Our DBAs had limited access to actually do some type of performance tuning on the backend to our databases. Now we have full control of that. I guess a couple of examples, or one example that I would give is that we're in the COVID era, as you mentioned, right? We have a space where we, prior to COVID, we had about 70 people on staff, both government and at Accenture. And all of our development is done on the secret side. And we have major deliverables due at the end of September. Well, COVID hits, we now have to social distance and come up with a plan, and we have to have reduce our staff of 70, both functional developers down to anywhere between 10 people or less on-site. So that, right there, you know, we were talking major hit in our development effort and in cost, I guess, also. While we're doing our social distancing plan Greg came up to me and said, "Hey, why don't we move "our development environment and our test environment "to the gov cloud and scramble the data. "We'll be able to have our developers remote access in "and continue with our development efforts?" And I told Greg, "Great, put a plan together. "Let's talk to our information security officer." I said, "If he signs off on it, let's get off and running." We met with him, he signed off on them, and within two weeks that dev and test environment was up and running. And now, we're still on-track to meet our deliverable dates in September. >> That's a great example, well, that's awesome insight. Greg, expand on that because this is an example of agility. You talk about readiness, I mean it's unforecasted disruption, there's all kinds of use cases. "Oh, we have a hurricane," or whatever, you know. This is unforeseen and unique. Take us through-- >> Yeah, that's absolutely right. >> The agility piece here, on how you got deployed, time frame, and solution. >> Yeah, definitely. So yeah, it can't be overstated how much of a benefit it was that we had already gone through the process of refactoring a lot of our applications into the cloud and using some of those services available and, you know, able to containerize and take some of those application from where they were, as Frank mentioned, scramble the data, and then able to quickly use the cloud experience that we had to stand up an environment in gov cloud where it was more accessible for development that didn't need to take place on-site, was, essentially, the saving grace. We would have had major slowdowns in delivery, as Frank mentioned and a lot of cost implications there, so it really can't be overstated how much that experience having gone through it and being in a spot where we had that flexibility to quickly replicate our architecture, went a long way towards keeping the mission going as the world deals with the pandemic. >> Yeah, this is just a striking example. You know, first of all, I'm a cloud-biased person. I'm very much a, I lean heavily towards pro-cloud so I'll just say this as total bias. There are companies that have gone cloud and took advantage of that refactoring or reinvention and are in a position not only to hit the deadlines but also be in a position of growth strategy, or in this case, a mission-based expansion for the FBI, as Frank was alluding to. Could you imagine, Frank, if you had the data center challenge and you weren't in the cloud? And the you had to go to Greg, or somebody, and say, "Hey, what do you do?" So imagine you had the data center, and then COVID hits. A lot of people are on that side of the street, right now, goin', "What do we do?" >> Yeah, yeah we would have been dead in the water as Greg mentioned. You know, all of our work streams would have been forced out to the left. I couldn't even imagine, you know, the timelines that we would have had to come up with because we would have had to have come up with some rotation plan to develop, you know, team one can only come in on Mondays and Tuesdays and then team two would come in on Wednesdays and Thursdays which would have pushed out our delivery dates and as Greg mentioned also, cost goes up. Time is money, money's time. >> Yeah, I totally, and people goin' out of business because of it and, or settin' their mission back you know, decades. Greg, talk about what goes on next because obviously, congratulations on being a customer success, it's a great mission win here, but you got to get through this. So how are you guys huddling on this point? What are the conversations? What are you thinking? >> Yeah, so now we're at a point where I think, as I'd mentioned, when we first moved to the cloud, the primary mission was getting there securely, getting there within policy, and getting operational so we were making trade-off decisions on where to lift and shift, and where to refactor. Got through all of that successfully. Got through the initial challenge of COVID which definitely threw some of the plans for a loop as we shifted our operations and focused on getting operational in gov cloud. And now we are at a point where we've stabilized delivery again, and we're re-picking up where we left off on the cloud journey which is really focused now, on continuing to look at the investments that AWS is making in the technologies that are coming next. And it really enables us to get ahead of the trends, easily analyze some of these services, available, and then we enter into conversations with Frank and others and start making those trade-off decisions of when it's time to refactor, retire another part of our application and start to look to go cloud-native. So that's where we are now, is looking for ways to maximize and use those services to, again, save costs, improve performance, all of those things that go along with getting more and more mature in the cloud. >> You know, one of the things, Frank, I want to hear your thoughts on just as while I got you guys here is you think about old school, old guard, as Andy Jassy would say, or Teresa talk about. You got silos and you got all these things: legacy. Okay, got that. But as you guys look at your mission have secure data, catch the bad guys, and protect citizens, right? So (chuckling) I mean, I'm over-simplifying but generally, that's it. Data's critical, right? I mean, speed to the edge of the network which is the field and the people doing the job, is critical. Cloud has an opportunity to make that development cycle faster, and ultimately, the workloads and the impact. Could you share your thoughts on how the cloud and Amazon are bringin' that to the table because havin' the right data at the right time could mean the difference between life or death. >> Yeah, so Greg and I experienced this, and again, it's all about having that architectural flexibility, right? So back in February, we had a requirement where we had to expose a large amount of data to employees about themselves, but not only about themselves, but also to their managers. And so, you know, we went through the basic you know, develop it, and then put it into our test environment, however the problem that we had was that we couldn't assimilate the large amount of data that we're exposing to 40,000 FBI employees. Because when we tested out, everything seemed to go fine, but as luck would have it, once we went operational, the application crashed. Our two main engineers come in my office and within 30 minutes, they identified the problem, they had the solution, and we already implemented the solution. Within 30 minutes. You know, going back in the past, like seven years, like you were mentioning, back in the old days, I would have to go around, beg for funding, buy hardware, then I would have to submit a requisition. It would have to go through the approval process. We then would have to procure the hardware, receive the hardware, install it, test it out, load the application, test it again, and then go into Ops. You know, you're lookin' anywhere from a three month to a nine month delay right then and there that our engineers were able to solve within 30 minutes. >> I mean, again, I'm back to my bias again. I'm old enough to remember when I was in college. I mean, I never programmed on punch cards, so that's kind of dates me, (chuckling) but so I'm post punch card generation. I used to look at the guys runnin' the mainframes sayin', "Look at those old relics over there," and "huggin' the mainframe." But what they did was that the smart people repurposed and got into mini-computers, they got into networking, LANs and PCs. This is kind of the cloud moment where if you're going to hold onto that old way you're going to have that operating model, it's just not effective in any way. I just don't see any benefit, other than have a preserved workload that needs the certain data, or you put containers around it and you can bring that in, but there are those corner cases. But generally speaking, you got to move to the new model. >> Mm-hmm. >> Guys, react to that. What's your thoughts? >> Yeah. >> Evermore. Yeah. >> Yeah, I agree, I mean It can't really be overstated, just the flexibility that exists. I think a lot of times, people get hung up on the you know, most efficient way to move to the cloud or you have to use X amount of cloud services. But it can't be overstated, regardless of the approach that you take to making that migration, that once you are there, the kind of intangibles that you get, the ease to take an idea and test it out, flip the switch on, flip the switch off if you like it or not. It's really just opened the door for the team to take some of the more innovative ideas and we have regular conversations with Frank and others that I think are fun for all of us where we get to look at some of these things and we can actually think about and envision how to get them in without, to Frank's point, "putting in requisitions," doing major activities that are going to derail our other schedules to pilot some of these new ideas. >> Frank, you got to attract some, it's a personnel challenge, too. You want to attract young minds, smart, young people. They want what's contemporary and they want state-of-the-art, they want to be in the right positions, drivin' the right, fastest car they can, and being successful. There's a staff component. What's your thoughts on that? Because, you know, if a young person comes in it's like, "Hey, I want to rock and roll with this new stuff, "not the old stuff I see there." >> Right. >> And so Greg put together an innovation team where we have these great, young minds, right? And you know, they're always bringing different ideas, different services that we can utilize on AWS, and sometimes Greg and I have to pull the reins on 'em, like, "Okay, we'll do that, but we have "major applications that we got to develop and deploy." But it's always refreshing and great to see young people with their innovative ideas that they bring to the table. >> Well, final question for you guys, while I got ya here. You know, I've been reporting, we've been saying on these CUBE interviews, trying to make sense of this COVID environment, what's goin' on and what it exposes. And you can see the obvious things. But it generally exposes this great IoT experiment. We're all IoT devices at this point. You've got work places which are not home and office, workforces which are remote, workloads and workflows that are changing, new things are happening. How do you guys see this? Because it ultimately opens up the fact that the architecture has to support multiple endpoints, edge of the network, new connections, new workflows. How are you guys looking at this? What's your vision on this? >> So Greg, I'll take a first crack at it from a Bureau employee being with the Bureau for 31 years. I would never have thought in my wildest dreams that we'd actually have people workin' from home and being able to remote in, and actually do development. And we did it all within two weeks. It's just incredible the obstacles that the team overcome, but also the flexibility of the FBI leadership, knowing that this had to happen in order to, for continuity of operations. >> Great point, great insight. Greg, your thoughts. >> Yeah, I agree with everything that Frank said. It's been a great partnership and I think that the nice thing that surprised us all was when it got down to it, the security controls and requirements were there and able to be met with the tools at our disposal. So I think the great fear that everybody had to Frank's point, it just wasn't something that was normal to this point. But as we were all forced to reevaluate what we had to do, the fear was, "Well, what accommodations are we "going to have to make from a security standpoint?" And the answer was being able to operate again without exposing any of that data, the risk was really extremely low, to zero. All the folks from security we're able to work closely with in partnership, and make this happen again so we can keep delivering the mission. So I think that partnership and getting through it together and all feeling really comfortable that we're doing it in a secure way was really what enabled us to be successful. >> That's a great point. Frank, he brings up something I didn't bring up which is super important. You mentioned in the old way you got to get all these requisitions in purchase. Security is the same kind of new dynamic which is like, "Okay, you got to get "everything tested," but it goes faster when you have the cloud 'cause that's also another criteria, you got to still got to get the approvals whether you're working with another vendor or integrating with another app. That's still now the new issue. So that's got to be approved faster, so that's also now a bottleneck. How does cloud help make those security reviews go faster? >> Right, so so we were the first ones on the cloud. So or security team was still defining the ATO process for us. However, what we did was we aligned ourselves with that team so that we could meet all the security requirements, but also app out all the security controls. And so from the time that we actually had the design till we went into deployment onto the SC2S or the cloud, and we went through the ATO process, it only took us eight months which really, in the past, that effort could have took anywhere from a year and a half to two years just because of the old ATO process. >> Awesome. Well, Greg and Frank, congratulations on a great award, Amazon Public Sector Partner Awards Show, most customer-obsessed mission-based win in the federal category. Congratulations. >> Thank you. >> Thank you. >> Okay, theCUBE's coverage of AWS Public Sector Partner Awards Show, I'm John Furrier, your host of theCUBE. Thanks for watching. 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(upbeat music) >> Announcer: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. >> Hi everyone, welcome back to theCUBE's coverage of AWS Public Sector Partner Awards Show. I'm John Furrier, host of theCUBE. We're here in Paolo Alto, California but during COVID, we're doin' all the remote interviews and gettin' the stories and celebrating the awards for the Partner Awards Show. And the award here is most customer-obsessed mission-based win in the federal area. We've got two great guests, Greg Siegel Senior Manager at Accenture and Frank Urbano Program Manager with the FBI Federal Bureau of Investigation. Gentlemen, thank you for joining me and congratulations on the win. >> Thank you. >> Thank you. >> So let's break this down. So you're federal, big category, a lot of intelligence agencies been using the gov cloud and Amazon. What's the mission win? What's the award for? Tell us. >> So I guess the award is the Bureau was shutting down our data centers and we needed to move to an infrastructure that would support our application. That was the first problem that we were trying to actually solve. But also, we know we were always seeing a performance hit on our infrastructure, and we always suspected that by moving to the gov cloud, we'll see an increase in performance because once we went live in our current, in or old environment seven years ago, performance was always an issue, our end users were always complaining and then we moved to our VMs four years after that. We saw an increase in performance a little bit but then once we moved over to the cloud, the FBI secret cloud, we heard crickets. The end users haven't been complaining. Greg and I were actually talking about that the other day how, you know, there's minimal complaints as far as performance. That's going to be one of the themes you hear throughout is performance, performance, performance. >> Got to love the no complaints, that means it's workin', people are doin' their job, gettin' the job done. Greg, I want to get your thoughts on this because Accenture, we've had many conversations with you guys over there about being agile and now you're a partner. You know, the FBI, I saw a presentation in person at Reinvent, I think last year where the FBI was like, "Lookit, our workloads "are increasing and budget isn't increasing "at the same rate." So it's kind of like, you know, "I need more power." It's like that scene in Star Trek, "Scotty, more power," you need to get that power. Take us through that transformation because one, you got a good user experience. That means people are doin' their job. But the cases get bigger, the more workload is there, but the budget's got to be increased or leveraged better. What's your thoughts? How do you tackle that problem because it's do more with less, classic do more with less. >> That's right. Yeah, so as Frank said, I think the system had been live for about seven years and you see over that time in the traditional data centers how the performance requirements increase but as you said, are kind of there on hardware and not easily able to adapt and overcome those. So, you know, when it became clear that the cloud move was a serious consideration we were able to pull on a few other experiences that the firm has had moving similar technologies to the cloud and then kind of combined that with the experience implementing technology at the FBI. And those two components kind of together were able to get us on a path to successfully move to the cloud and be, you know, kind of one of the first big systems at the FBI to make that transition. So that was our approach. >> Frank, I'd like to ask, you mentioned crickets. That means, that's good, actually. No one's complaining. What was it like before when you had the data center? What were some of the complaints? What were some of the challenges that you were dealing with? >> So (chuckling) so some of the challenges we were dealing with was, to give an example, when we went live seven years ago, we actually deployed our application on hardware that was already end of life. And so immediately we saw challenges there. And so by moving to the cloud, it gave us a lot of architectural flexibility. And what I mean by that is that we control, now, our own destiny, meaning that in the past, we would have to put in change requests to have firewall configuration changes. Now that responsibility is with us. Our DBAs had limited access to actually do some type of performance tuning on the backend to our databases. Now we have full control of that. I guess a couple of examples, or one example that I would give is that we're in the COVID era, as you mentioned, right? We have a space where we, prior to COVID, we had about 70 people on staff, both government and at Accenture. And all of our development is done on the secret side. And we have major deliverables due at the end of September. Well, COVID hits, we now have to social distance and come up with a plan, and we have to have reduce our staff of 70, both functional developers down to anywhere between 10 people or less on-site. So that, right there, you know, we were talking major hit in our development effort and in cost, I guess, also. While we're doing our social distancing plan Greg came up to me and said, "Hey, why don't we move "our development environment and our test environment "to the gov cloud and scramble the data. "We'll be able to have our developers remote access in "and continue with our development efforts?" And I told Greg, "Great, put a plan together. "Let's talk to our information security officer." I said, "If he signs off on it, let's get off and running." We met with him, he signed off on them, and within two weeks that dev and test environment was up and running. And now, we're still on-track to meet our deliverable dates in September. >> That's a great example, well, that's awesome insight. Greg, expand on that because this is an example of agility. You talk about readiness, I mean it's unforecasted disruption, there's all kinds of use cases. "Oh, we have a hurricane," or whatever, you know. This is unforeseen and unique. Take us through-- >> Yeah, that's absolutely right. >> The agility piece here, on how you got deployed, time frame, and solution. >> Yeah, definitely. So yeah, it can't be overstated how much of a benefit it was that we had already gone through the process of refactoring a lot of our applications into the cloud and using some of those services available and, you know, able to containerize and take some of those application from where they were, as Frank mentioned, scramble the data, and then able to quickly use the cloud experience that we had to stand up an environment in gov cloud where it was more accessible for development that didn't need to take place on-site, was, essentially, the saving grace. We would have had major slowdowns in delivery, as Frank mentioned and a lot of cost implications there, so it really can't be overstated how much that experience having gone through it and being in a spot where we had that flexibility to quickly replicate our architecture, went a long way towards keeping the mission going as the world deals with the pandemic. >> Yeah, this is just a striking example. You know, first of all, I'm a cloud-biased person. I'm very much a, I lean heavily towards pro-cloud so I'll just say this as total bias. There are companies that have gone cloud and took advantage of that refactoring or reinvention and are in a position not only to hit the deadlines but also be in a position of growth strategy, or in this case, a mission-based expansion for the FBI, as Frank was alluding to. Could you imagine, Frank, if you had the data center challenge and you weren't in the cloud? And the you had to go to Greg, or somebody, and say, "Hey, what do you do?" So imagine you had the data center, and then COVID hits. A lot of people are on that side of the street, right now, goin', "What do we do?" >> Yeah, yeah we would have been dead in the water as Greg mentioned. You know, all of our work streams would have been forced out to the left. I couldn't even imagine, you know, the timelines that we would have had to come up with because we would have had to have come up with some rotation plan to develop, you know, team one can only come in on Mondays and Tuesdays and then team two would come in on Wednesdays and Thursdays which would have pushed out our delivery dates and as Greg mentioned also, cost goes up. Time is money, money's time. >> Yeah, I totally, and people goin' out of business because of it and, or settin' their mission back you know, decades. Greg, talk about what goes on next because obviously, congratulations on being a customer success, it's a great mission win here, but you got to get through this. So how are you guys huddling on this point? What are the conversations? What are you thinking? >> Yeah, so now we're at a point where I think, as I'd mentioned, when we first moved to the cloud, the primary mission was getting there securely, getting there within policy, and getting operational so we were making trade-off decisions on where to lift and shift, and where to refactor. Got through all of that successfully. Got through the initial challenge of COVID which definitely threw some of the plans for a loop as we shifted our operations and focused on getting operational in gov cloud. And now we are at a point where we've stabilized delivery again, and we're re-picking up where we left off on the cloud journey which is really focused now, on continuing to look at the investments that AWS is making in the technologies that are coming next. And it really enables us to get ahead of the trends, easily analyze some of these services, available, and then we enter into conversations with Frank and others and start making those trade-off decisions of when it's time to refactor, retire another part of our application and start to look to go cloud-native. So that's where we are now, is looking for ways to maximize and use those services to, again, save costs, improve performance, all of those things that go along with getting more and more mature in the cloud. >> You know, one of the things, Frank, I want to hear your thoughts on just as while I got you guys here is you think about old school, old guard, as Andy Jassy would say, or Teresa talk about. You got silos and you got all these things: legacy. Okay, got that. But as you guys look at your mission have secure data, catch the bad guys, and protect citizens, right? So (chuckling) I mean, I'm over-simplifying but generally, that's it. Data's critical, right? I mean, speed to the edge of the network which is the field and the people doing the job, is critical. Cloud has an opportunity to make that development cycle faster, and ultimately, the workloads and the impact. Could you share your thoughts on how the cloud and Amazon are bringin' that to the table because havin' the right data at the right time could mean the difference between life or death. >> Yeah, so Greg and I experienced this, and again, it's all about having that architectural flexibility, right? So back in February, we had a requirement where we had to expose a large amount of data to employees about themselves, but not only about themselves, but also to their managers. And so, you know, we went through the basic you know, develop it, and then put it into our test environment, however the problem that we had was that we couldn't assimilate the large amount of data that we're exposing to 40,000 FBI employees. Because when we tested out, everything seemed to go fine, but as luck would have it, once we went operational, the application crashed. Our two main engineers come in my office and within 30 minutes, they identified the problem, they had the solution, and we already implemented the solution. Within 30 minutes. You know, going back in the past, like seven years, like you were mentioning, back in the old days, I would have to go around, beg for funding, buy hardware, then I would have to submit a requisition. It would have to go through the approval process. We then would have to procure the hardware, receive the hardware, install it, test it out, load the application, test it again, and then go into Ops. You know, you're lookin' anywhere from a three month to a nine month delay right then and there that our engineers were able to solve within 30 minutes. >> I mean, again, I'm back to my bias again. I'm old enough to remember when I was in college. I mean, I never programmed on punch cards, so that's kind of dates me, (chuckling) but so I'm post punch card generation. I used to look at the guys runnin' the mainframes sayin', "Look at those old relics over there," and "huggin' the mainframe." But what they did was that the smart people repurposed and got into mini-computers, they got into networking, LANs and PCs. This is kind of the cloud moment where if you're going to hold onto that old way you're going to have that operating model, it's just not effective in any way. I just don't see any benefit, other than have a preserved workload that needs the certain data, or you put containers around it and you can bring that in, but there are those corner cases. But generally speaking, you got to move to the new model. >> Mm-hmm. >> Guys, react to that. What's your thoughts? >> Yeah. >> Evermore. Yeah. >> Yeah, I agree, I mean It can't really be overstated, just the flexibility that exists. I think a lot of times, people get hung up on the you know, most efficient way to move to the cloud or you have to use X amount of cloud services. But it can't be overstated, regardless of the approach that you take to making that migration, that once you are there, the kind of intangibles that you get, the ease to take an idea and test it out, flip the switch on, flip the switch off if you like it or not. It's really just opened the door for the team to take some of the more innovative ideas and we have regular conversations with Frank and others that I think are fun for all of us where we get to look at some of these things and we can actually think about and envision how to get them in without, to Frank's point, "putting in requisitions," doing major activities that are going to derail our other schedules to pilot some of these new ideas. >> Frank, you got to attract some, it's a personnel challenge, too. You want to attract young minds, smart, young people. They want what's contemporary and they want state-of-the-art, they want to be in the right positions, drivin' the right, fastest car they can, and being successful. There's a staff component. What's your thoughts on that? Because, you know, if a young person comes in it's like, "Hey, I want to rock and roll with this new stuff, "not the old stuff I see there." >> Right. >> And so Greg put together an innovation team where we have these great, young minds, right? And you know, they're always bringing different ideas, different services that we can utilize on AWS, and sometimes Greg and I have to pull the reins on 'em, like, "Okay, we'll do that, but we have "major applications that we got to develop and deploy." But it's always refreshing and great to see young people with their innovative ideas that they bring to the table. >> Well, final question for you guys, while I got ya here. You know, I've been reporting, we've been saying on these CUBE interviews, trying to make sense of this COVID environment, what's goin' on and what it exposes. And you can see the obvious things. But it generally exposes this great IoT experiment. We're all IoT devices at this point. You've got work places which are not home and office, workforces which are remote, workloads and workflows that are changing, new things are happening. How do you guys see this? Because it ultimately opens up the fact that the architecture has to support multiple endpoints, edge of the network, new connections, new workflows. How are you guys looking at this? What's your vision on this? >> So Greg, I'll take a first crack at it from a Bureau employee being with the Bureau for 31 years. I would never have thought in my wildest dreams that we'd actually have people workin' from home and being able to remote in, and actually do development. And we did it all within two weeks. It's just incredible the obstacles that the team overcome, but also the flexibility of the FBI leadership, knowing that this had to happen in order to, for continuity of operations. >> Great point, great insight. Greg, your thoughts. >> Yeah, I agree with everything that Frank said. It's been a great partnership and I think that the nice thing that surprised us all was when it got down to it, the security controls and requirements were there and able to be met with the tools at our disposal. So I think the great fear that everybody had to Frank's point, it just wasn't something that was normal to this point. But as we were all forced to reevaluate what we had to do, the fear was, "Well, what accommodations are we "going to have to make from a security standpoint?" And the answer was being able to operate again without exposing any of that data, the risk was really extremely low, to zero. All the folks from security we're able to work closely with in partnership, and make this happen again so we can keep delivering the mission. So I think that partnership and getting through it together and all feeling really comfortable that we're doing it in a secure way was really what enabled us to be successful. >> That's a great point. Frank, he brings up something I didn't bring up which is super important. You mentioned in the old way you got to get all these requisitions in purchase. Security is the same kind of new dynamic which is like, "Okay, you got to get "everything tested," but it goes faster when you have the cloud 'cause that's also another criteria, you got to still got to get the approvals whether you're working with another vendor or integrating with another app. That's still now the new issue. So that's got to be approved faster, so that's also now a bottleneck. How does cloud help make those security reviews go faster? >> Right, so so we were the first ones on the cloud. So or security team was still defining the ATO process for us. However, what we did was we aligned ourselves with that team so that we could meet all the security requirements, but also app out all the security controls. And so from the time that we actually had the design till we went into deployment onto the SC2S or the cloud, and we went through the ATO process, it only took us eight months which really, in the past, that effort could have took anywhere from a year and a half to two years just because of the old ATO process. >> Awesome. Well, Greg and Frank, congratulations on a great award, Amazon Public Sector Partner Awards Show, most customer-obsessed mission-based win in the federal category. Congratulations. >> Thank you. >> Thank you. >> Okay, theCUBE's coverage of AWS Public Sector Partner Awards Show, I'm John Furrier, your host of theCUBE. Thanks for watching. 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>> Announcer: From theCUBE Studios in Paolo Alto and Boston, it's theCUBE covering empowering the autonomous enterprise. Brought to you by Oracle Consulting. >> Hi everybody, welcome back. You're watching theCUBE. We go out to the events, we extract the signal from the noise. This is a very special digital event and we're really covering the transformation not only of the industry, but the transformation of Oracle Consulting and its rebirth. Mike Owens is here, Group VP of Cloud Advisory and GM of Oracle Elevate which is a partnership that Oracle announced last Open World with Deloitte. And Don Schmidt is here, who's a Managing Director at Deloitte. Gents, good to see ya, welcome. >> Good to be here, Dave. >> So Don, I want to start with you. Transformation, everybody talks about that. There's a lot of trends goin' on in the industry. What do you guys see as the big gestalt transformation that's going on? >> Yeah, I think there's an inflection point right now. Everybody's been saying they want to get out of their data centers, though leaps haven't really been taking place. They've been kind of moving in small bits. We're now at the point where large transformation at scale of getting out of your data centers is now here. So we are here to try to help our clients move faster. How can we do this more effectively, cost-efficiently, and get them out of these data centers so that they can move on with their day-to-day business? >> So data centers just not an efficient use of capital for your customers is what you're saying. >> No, no there's lots of ways to do this a lot faster, cheaper, and get onto innovation. Spend your money there, not on hardware, floor space, power, cooling. >> Two very well-known brands, you guys get together. So what was the sort of impetus to get together? How's it going? Give us the update on that front. >> Oracle has been really technology focused. It was really created by technologists. And back to the point of what we're trying to do with the Cloud when you're trying to do larger transformation, those aren't some of the skills that we have. We've been bringing in some of those skills in DNA, but if you look at it as why would you try to recreate the situation? Why would you not partner with an organization if it does large business transformation, like a Deloitte? And so the impetus of that is how do we take the technology with a business transformation, pull that together, and back to the one plus one equals three from a customer. That's what they really want. So how to we actually scale that and do really big things and get big outcomes for our customers? Our partnership is not about trying to take a bunch of customers and move a couple application workloads. Our job, what we're really chartered to do is really make huge transformational leaps for our customers using the combined capabilities of the two organizations. So it's a huge paradigm for us to kind of do this. >> And in our collaboration with the two organizations, just the opposite for what Mike just said. So Deloitte wasn't really big in big IT. Business-led transformation is kind of what Deloitte's been known for, along with our cyber practice and so we needed the deep skills of the technical experts. >> So you just described what I would think of as wave one and as you keep peeling, you got the applications, you got the business process, you might have reorganizations. That's really where you guys have expertise, right? >> There's a lot of things you have to sort through and that's where the combined alvic program really synergizes itself around the tools that we have. We both have tools will help make sure we get this right. Deloitte has a product called ATADATA, Oracle has a product called Soar, they marry together properly into this transformational journey to make sure we get the discovery done right and we get the migrations done right, as well. >> Take me through a typical engagement, typical, I know, in quotes, and then how long? Take me to the point at which you start to get business value. What do I got to do to get there? >> So we see two different spectrums on a transformation and it really aligns to what are your objectives. Do you just need to get out of the data center because you're on archaic, dying hardware? Or do you want to take your time and make a little bit more of a transformational journey? Or do you want to play somewhere in the middle of that spectrum? But in either one of those we'll come in and do a discovery conversation. We'll understand what's in your data center, understand what the age or the health of your data center is, help put the customers through a business case, a TCO, how fast or how slow the journey needs to be for them, create what we call wave groups of how fast and we're going to sequence those, over time, to get out of their data center. In parallel, we're going to be doing, as Mike was saying, around all the operational aspects. So while we're doing that discovery, we want to start standing up their Cloud center of excellence. Getting Cloud operations into the organization is a different skillset for IT to have. They're going to need to retrain themselves, retool themselves in the world of Cloud. So we kind of do that in parallel. And then what we want to do is when we start a project, we want to start with a little POC or small, little group of safe applications and we can proof out the model works, move those into the Cloud and then what we want to do is we want to scale that out at its large pace, get the IT savings, get the cost cuts out of the organization. >> Do you guys have specific plays or campaigns that I can do to get started? Maybe do a little test case? Any particular offerings that? >> It's all under the program of Elevate. We've got a couple of campaigns. So the biggest one we've been talking about is around the data center transformation, so that's kind of the first campaign that we're working on together. The next one is around moving JD Edwards specific applications to Oracle's Cloud. And then the third one is around our analytics offering that Deloitte has and how we're going to market to genera, put that in it, as well. Those are our three major campaigns. >> The JDE migration, so you've got what? Situations where people have just broken systems? >> Yeah, I would say it's more of a JDE modernization. So you have an organization, right? They may have a JD, a JDE or JD Edwards instance that's really, it's older. They may be on version nine or something like that. They don't want to go all the way to SaaS 'cause they can't simplify the business processes. They need to do that but they also want to take advantage of the higher level of capabilities of Cloud computing: IoT, mobile, et cetera. So as a modernization, one of the things we're doing is an approach it together. We work with customers, depending on where they're goin' and going, "Hey, great, you can actually modernize "by taking it up to this version of JDE "through an upgrade process," but that allows you then to move it over to Oracle Cloud infrastructure which allows you to tap into all those platform services, the IoT and stuff like that to take to the next level. Then you can actually do the higher level analytics that sits on top of that. So it's really a journey where the customer wants to get. There's a various, kind of four major phases that we can do, or entry points with a customer on the JDE modernization, we kind of work them through. So that's a skill of some of the capabilities that Deloitte has is a deep JDE and as well as Oracle Consulting, and we actually are going to market that together. Matter of fact, we're even at conferences together talking about our approaches, here and in our future. >> In the analytics campaign, so it seems to me a lot of companies don't have their data driven. They want to be data driven, but they're not there yet and so their data's in silos and so I would imagine that that's all about helping them understand where the data is, breaking down, busting down those silos, and then actually putting in sort of an analytics approach that drives them from data to insight. Is that fair? >> Yeah, fair. Yeah, it's not just doin' reporting and dashboards, it's actually having KPI driven insights into their information and their data within their organizations. And so Deloitte has some pre-configured applications for HR, finance, and supply chain. >> Guys, two powerhouses. Thanks so much for explaining in theCUBE and to our audience it. Appreciate it. >> Appreciate it. >> All right, thank you everybody for watching. We'll be right back with our next guest. You're watching theCUBE from Chicago. We'll be right back after this short break. (soft electronic music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019 brought to you by IBM Wear and its ecosystem partners. >> Welcome back to the Cube. It's the Emerald 2019 our 10th year water wall coverage. Three days, two sets, lots of content. Instrument of my co host is Justin Warren. And one of the big stories coming into the show is VM Wear actually went on an acquisition spree. A hold number of acquisitions. Boston based Carbon Black over $2 billion Pivotal brought back into the fold for also, you know, around that ballpark of money on Happy to Welcome to the program. One of those acquisitions, such and Conti, is sitting to my right. He's the co founder of Hana is also a professor at Stanford University. Thank you so much for joining us and joining us. Also for the segment. Shakeri Air, the executive vice president general manager of Telco Edge Cloud at VM Wear, Shaker said, Yes, there's a lot of acquisitions not to play favorites, but maybe this is his favorite. No question about it. All right. Eso such in, you know, boy, you know the Paolo Alto Stanford connection. We were thinking back, You know, the Founders Of'em where, of course, you know came from Stanford. Many acquisitions over the year, including the mega next era acquisition. You know, quite a few years ago, I came out of Stanford. Give us what was the genesis in the Why of Hana. >> It's actually interesting Stanford Connection to So I've been a faculty at Stanford for the last 10 years on dhe. I have seen the SD and moment very close on up front on one of the dirty secrets of S. T M says it makes the netbooks programmable, but someone still has to write the programs on. So that's usually a very complex task on the pieces beyond the company was, Can we use the eye to learn how to program the network rather than humans having to program the network to do management or optimization? So the division really waas can be built? A network that learned how to optimize itself learns how to manage itself on the technology we're building. Is this a pipeline that basically tries to deliver on that for mobile? >> It's great, Sachin, you know, my background is networking and it feels like forever. We've been hooking well. We need to get people from the cli over to the gooey. But we know in today's rightly complex world, whether it's a I or just automation, humans will not be able to keep up with it. And, you know, we know that that's where a lot of the errors would happen is when we entered humans into doing some of this. So what are some of the key drivers that make this solution possible today that, you know, it might not have been able to do done when when one train was first rolling out the first S t n? >> Yeah, talk about it in three dimensions. The one is, Why do we need it today? Right on. Then what is being what is happening that is enabling this today, right? So, apart from what I talked about Stu and I think the other big driver is, the way I like to think about it is that the Internet is going from a means of consumption to a means of control and interaction. So, increasingly, the application to BC driving the next big decade, our very way of controlling things remotely or the network like a self driving car, or be in interacting but very highly rich visual content like E. R. India. So the applications are becoming a lot more demanding on the Net. At the same time, the network is going through a phase off, opening up on becoming disaggregated network complexity is increasing significantly. So the motivation behind the company and why I thought that was the right time to start the company was these two friends are gonna collide with five coming along the applications that are driving five g and then at the complexity increasing our five. So that's why we started the company. What actually is enabling. This is the fact that we have seen a lot of progress with the eye over the last few years. It hasn't really. It hadn't really been applied at scale to networks and specifically mobile that book. So we definitely saw no, actually there, but increasingly, ah, lot of the infrastructure that is being deployed there was more and more telemetry available. There was more and more data becoming available and that also obviously feet this whole engine. So I think the availability of all of these Big Data Technologies Maur data coming in from the network and the need because of these applications and that complexity. I think there's a perfect confluence >> that there's lots of lots of II floating around at the moment, and there's different flavors of it as well. So this machine learning there's Aye aye, sir. When when you say that there's there's a I behind this What? What particular kind of machine learning or a Y you're using to drive these networks? >> This a few different techniques because the problems we solve our anomaly detection off. Then problems are happening in the network predicting how network conditions are going to evolve. For example, predicting what your devices throughput is gonna be the next 30 seconds. We're also learning how to control the knobs in the neck using AI ai techniques. So each of these has different classes of the eye techniques. So, for example, for control we're using reinforcement learning, which is the same technique that Google used to kind of been on alphago. How do you learn how to play a game basically, but area the game you're playing it optimizing the network. But for the others, it's a record of neural networks to do predictions on Time series data. So I think it's a combination of techniques I wouldn't get to wherever the techniques. It's ultimately. But what is the problem you're trying to solve? And then they picked the right technique to solve it, >> and so on that because the aye aye is actually kind of stupid in that it doesn't know what they wouldn't. What an optimized network looks like. We have to show it what that is. So what? How do you actually train these systems to understand? But what is an optimized network? What? How does how does that tell you? Define this is what my network optimal state should be. >> So that's a great question, because in networking like that, any other discipline that wants to use the eye. There's not a lot of label data. What is the state I want to end up at what is a problem state or what is a good state? All of this is labels that someone has to enter, and that's not available axe kid, and we're never gonna be able to get it at the scale we wanted. So one of our secret sauce is if you will, is semi supervised learning but basic ideas that we're taking a lot of domain knowledge on using that domain knowledge to figure out what should be the right features for these models so that we can actually train these models in a scalable fashion. If you just throw it a lot of data any I model, it just does not converge. Hardly constructive features on the other thing is, how do I actually define what are good kind of end state conditions? What's a good network? And that's coming from domain knowledge to That's how we're making I scale for the stomach. >> I mean, overall, I would say, as you look at that, some of the parameters in terms of what you want to achieve are actually quite obvious things like fewer dropped calls for a cellular network. You know, that's good. So figuring out what the metrics need to be and what the tuning needs before the network, that's where Hana comes in in terms of the right people. >> All right, so shake her. Give us a little bit of an understanding as to where this fits into the networking portfolio. You know, we heard no we heard from Patty or two ago. You know what would have strong push? Networking is on the NSX number. Speaks for itself is what's happening with that portfolio? >> No, absolutely. In fact, what we're doing here is actually broader than networking. It's sort off very pertinent to the network off a carrier. But that is a bulk off their business, if you will. I think if you sort of go back and look at the emirs of any any, any vision, this is the notion of having any cloud in any application land on any cloud and then any device connected to those applications on that any cloud side we are looking at particularly to cloud pools, one which we call the Telco cloud and the other is the edge cloud. And both of these fortuitously are now becoming sort of transforming the context of five G. So in one case, in the telco cloudy or looking at their core and access networks, the radio networks, all of this getting more cloud ified, which essentially leads toe greater agility in service deployment, and then the edge is a much more distributed architecture. Many points over which you can have compute storage network management and security deployed. So if you now think about the sort of thousands off nodes on dhe virtualized clouds, it is just impossible to manage this manual. So what you do need is greater. I mean, orders of magnitude, greater automation in the ability to go and manage and infrastructure like this. So, with our technology now enhanced by Johanna in that network portfolio in the Telco Edge Cloud portfolio, were able to go back to the carriers and tell them, Look, we're not just foundational infrastructure providers. We can also then help you automate help you get visibility into your networks and just help you overall manager networks better for better customer expedience and better performance. >> So what are some of the use coasters that you see is being enabled by five G? There's a lot of hype about five short the moment and not just five jail. So things like WiFi six. Yeah, it would appear to me that this kind of technique would work equally well for five g Your wife. I short a WiFi six. So what are some of the use cases? You see these thieves service providers with Toko Edge clouds using this for? Yeah, So I think overall, first of all, I'd >> say enterprise use cases are going to become a pretty prominent part off five, even though a lot off the buzz and hype ends up being about consumers and how much bandwidth and data they could get in or whether five chicken passing preys or not. But in fact, things like on premise radio on whether that is private. Lt it's 40 or five t. These are the kinds of Uschi cases that were actually quite excited about because these could be deployed literally today. I mean, sometimes they're not regulated. You can go in with, like, existing architectures. You don't need to wait for standardization to break open a radio architecture. You could actually do it, Um, and >> so this sort off going in and >> providing connectivity on an enterprise network that is an enhanced state off where it is today. We've already started that journey, for example, with yellow cloud and branch networking. Now, if we can take that toe a radio based architecture for enterprise networking, So we think, ah, use case like that would be very prominent. And then based on edge architectures distributed networks now becoming the next generation Cdn is an example. That's another application that we think would be very prominent. And then I think, for consumers just sort of getting things like gaming applications off on edge network. Those are all the kinds of applications that would consume this sort off high skill, reliability and performance. >> Can you give a little sketch of the company pre acquisition, you know, is the product all g eight? How many customers you? Can you say what you have there? Sure >> it does us roughly three years old. The company itself so relatively young. We were around 33 people total. We had a product that is already deployed with chairman Telcos. So it is in production deployment with Chairman Telco Ondas in production trials with a couple of other tier one telcos. So we built a platform to scale to the largest networks in the world on If I, if I were to summarize it, be basically can observe, makes sense or in real time about every user in the network, what their experiences like actually apply. I modeled on top of that to optimize each user's expedience because one of the vision bee had was the network today is optimized for the average. But as all off our web expedience personalized netbook experiences, not personalized can be build a network Very your experiences personalized for you for the applications, your running on it. And this was kind of a foundation for that. >> I mean, we In fact, as we've been deploying our telco Cloud and carrier networks, we've also been counting roughly how many subscribers are being served up. Today we have over 800 million subscribers, and in fact, I was talking to someone and we were talking about that does. Being over 10% off the population of the world is now running on the lack of memory infrastructure. And then along comes Johanna and they can actually fine tune the data right down to a single subscriber. Okay, so now you can see the sort of two ends of the scale problem and how we can do this using a I. It's pretty powerful. Excellent. >> So So if we have any problems with our our service fighters, b tech support and I love to hear from both of you, you know what this acquisition position means for the future of the places and obviously VM wear global footprint. A lot of customers and resource is. But you know what I mean to your team in your product. >> I mean, definitely accelerating how quickly we can now start deploying. This and the rest of the world be as a small company, have very focused on a few key customers to prove the technology we have done that on. I think now it's the face to scale it on. Repeat it across a lot of other customers, but I think it also gives us a broader canvas to play that right. So we were focused on one aspect of the problem which is around, if you will, intelligence and subscriber experience. But I think with the cloud on but the orchestration products that are coming out of the ember, we can now start to imagine a full stock that you could build a network of full carrier network code off using using remote technology. So I think it's a broad, more exciting, actually, for us to be able to integrate not just the network data but also other parts of the stock itself. And >> it strikes me that this probably isn't just limited to telcos, either. The service providers and carriers are one aspect of this bit particularly five G and things like deployments into factory automation. Yes, I can see a lot of enterprise is starting to become much in some ways a little bit like a tell go. And they would definitely benefit from this >> kind of thing. Yeah, I mean, in fact, that's the basis of our internal even bringing our telco and EJ and I ot together and a common infrastructure pool. And so we're looking at that. That's the capability for deploying this type of technology across that. So you're exactly right, >> Checker want to give you the last word, you know, Telco space, you know? And then, obviously the broader cloud has been, you know, a large growth area. What, you want people taking away from the emerald 2019 when it comes to your team? >> Yeah, I think. To me, Calico's have a tremendous opportunity to not just be the plumbing and networking providers that they can in fact, be both the clowns of tomorrow as well as the application providers of tomorrow. And I think we have the technology and both organically as well as through acquisitions like Ohana. Take them there. So I'm just super excited about the journey. Because I think while most of the people are talking about five D as this wave, that is just beginning for us, it's just a perfect coming together on many of these architectures that is going to take telcos into a new world. So we're super excited about taking them. >> Shaker. Thank you so much for joining against auction. Congratulations and good luck on the next phase of you and your team's journey along the way. Thank you. Thank you for Justin. Warren comes to Minutemen, Stay with us. Still a bit more to go for VM World 2019 and, as always, thank you for watching the Cube.

>> Announcer: From San Francisco, it's theCUBE. Covering VMware Radio 2019. Brought to you by VMware. >> Hi, welcome to theCUBE's exclusive coverage of VMware Radio 2019. Lisa Martin with John Furrier, in San Francisco. This is an internal R&D innovation off site that VMware does, lots of innovation going on here from engineers from all over the globe. We're pleased to welcome Joe Baguley, the CTO from EMEA, from VMware. Joe, welcome to theCUBE. >> Hi. >> So we've been having some great conversations this morning about this tremendous amount of innovation, I mean the potential is massive. Not just from Radio, but from all the other innovation programs that VMware has, really speaks very strongly to the culture of innovation that VMware has had. But of course all this innovation has to be able to be harnessed to deliver what customers need. Talk to us about that, you're in the field, field CTO. What is that connection with the innovation that happens within VMware? How do customers help influence that and vice versa? >> Yeah, I think we're very unique in the structure that we've put around that to drive that innovation over the years. So my job as field CTO is, I call it sort of 50, 50. So 50% is Chief Technology Officer, which is this kind of stuff for Radio and 50% is Chief Talking Officer, which is out with our customers and presenting at conferences, et cetera. But the general remit is connecting R&D in the field. And so for eight years now I've been connecting R&D in the field at VMware, I actually did at my previous company as well. And what we've done is, we've built a series of programs over the years to do that, and one of the biggest ones is the CTO Ambassadors. And so that was, you know, you get to a point, you get to a growth size, I've been here eight years, and suddenly you need someone else to help you because I can't be everywhere. And the original role was, back in the day I was hired to scale Steve Herrod, because Steve Herrod couldn't be in Europe all the time, I was like mini Steve Herrod that could be there when needed. But then eventually I can't be in every European country and our major regions as we get bigger and bigger, and we've grown dramatically. So the CTO Ambassadors is to support that. And that's really, we've got 140 of our top customer facing techies from around the globe in this program called the Ambassadors. And they have to be customer facing, and they have to be individual contributors, so like a pre-sales manager or something doesn't count. They're a massively active community, there's a whole bunch of them here at Radio as well. And their job is really that conduit, that source of information, and also a sounding board, a much shorter range sounding board for R&D. So if R&D want to get a feel of what's going on, they don't have to ask everyone they can bounce off the Ambassadors, which is part of what we do, and that makes it easier. >> So like a filter too, they're also also filtering input from the field, packaging it up for R&D. >> Totally. Yeah, and when you're at an organization of our scale, filtering is really important. Because obviously, you can't have every customer directly talking to every engineer, it's never going to work. (laughs) >> I mean another radio project stay right there, a machine learning based champion CTO to go through all the feedback. >> Yeah, so I started my career, with my previous company doing that, I was the filter. So I'd get a hundred questions a day from various people in the field, and 99 of those I'd bounce right back because I knew the answer. But there was the one that I was like, uh. Then I'd turn around to R&D and ask them. But the great thing was that R&D knew that if I was asking then it was a real question, it wasn't the 99. So the CTO Ambassadors, and what we do in Octo Global field is really a method of scaling that. >> I want to ask you about that because that's a great example of here reputation comes in. Because your reputation is on the line if you go back and pull the fire alarm, if you will, send too many lame requests back, you're going to be lame. So you've got to kind of check, balance there. So that begs the question, how do you do the filtering for the champions that work for you? Is there a high bar? Is there a certain line? Like being a kid, you've got to be this tall to ride the roller coaster. Is there criteria? Is there certification? Take us through the filtering there. >> The Ambassador program is a rotating nomination system. So essentially there's a two year tenure. So what happens is, if you're in the field and you want to be an ambassador, which is a really prestigious thing, then you nominate yourself or get nominated and then people vote on you and you put forward your case, et cetera. Essentially it's a democratic process based on your peers and other people in the company. And then after you're allowed a maximum of two years. Sorry, two tenures so you get four years, if that makes sense, I'm not confusing you. >> John: So term limits? >> Yeah there's term limits, right, we have term limits. And after two terms you have to go out for a year to give someone else a chance because otherwise it will just glub- >> It'll turn into the US government. (laughs) >> But no, it's important to maintain freshness, maintain diversity and all those kind of things. And so it comes back to that filter piece we were talking about before. The reputation is massive, of the CTO Ambassadors. I mean when we started this six years ago as a program, most of R&D were like, who are these Ambassador guys? What value are they going to add? Now, if you're in R&D, one of the best things you can say, if you want to get something done, is what the CTO Ambassador said. I mean, literally it is, you can go and we have- >> John: The routine approach to that. Talk about how you guys add in a new category. So, for instance kubernetes, we saw this years ago when KubeCon was started, theCUBE was there present at the creation of that trend we kind of got it right away. Now Gelsinger and the team sees this as a massive traction layer. So that would be an example, where we need an Ambassador. So do you like just create one or how does that work? >> They create themselves, that's the best thing. So we have an annual conference which is in February, held in Paolo Alto where we all get together along with all the chief technologists, which is the level below me. And the principles, which the most senior field people. So literally the best of the best get together. It's about 200 plus get together for a week. And we are an hour and a half on on one with Pat for example, so Pat's there with all of us in a room. But one of the sessions we do is the shark tank, and there's two of them. One of them is, come up with your really cool, crazy, wacky ideas, and the other one is the acquisition shark tank. So there we get the MNA team, include our E-staff sit in, and the Ambassadors, as teams, will come in and present. We think we should acquire, uh because that's making a big difference. The great thing is, not nine times out of 10 but probably seven times out of 10, the E-staff are going, yeah we know about that, when actually we can't really tell you what's going on but yeah we know about them. But there's the two or three times out of 10 that people are like, oh yeah, so tell me more about them. And it might be a company that's just coming up, it might be 2013 and there's this company called Docker that no one's heard of, but the Ambassadors are shouting about Docker, and saying it's a big, you know. So there's that- >> So white space is too emerging you can see it's a telemetry, literally feedback from the field to direct management on business strategy. >> And our customers are pushing our field in directions faster than maybe R&D get pushed if you know what I mean. >> You guys deserve a lot of credit because Pat Gelsinger was just on this morning with Lisa and me, and we were talking about that. He just came back from the Sales President's club cruise, and one of the comments he said was the sales executive said, hey, who does strategy? Because everything's fitting together beautifully. Which kind of highlights how radiance this all progresses, not like magic, there's a process here, and this kind of points to your job is to fit that pieces in, is that correct? >> Yeah. People always say, as a CTO do you all sit down once a week and talk about strategy? And that's not what you do. There's a hive mind, there's a continual interaction, there's conference calls, there's phone calls, there's meetings, there's get togethers of various different types, groups, and levels. And what happens is there's themes that emerge over that. And so my role specifically, as the EMEA CTO is to represent Europe, Middle East, and Africa's voice in those conversations. And maybe the nuances that we might have around particular product requirements or whatever, to remind people that maybe sit in a bubble in Silicon Valley. >> John: I'm sure you raised your hand on privacy and GDPR? (laughs) >> Just a couple of times, yeah. Yeah, now and again. >> The canary in the coal mine is a really big point that helps companies, if they're not listening to the signals coming in. >> Well you do, and you see a lot. There's a lot of the tech companies that I see, it's often defined as the three bubbles, or your Massimo Re Ferrè, who's now at Amazon. When he was here, did this fantastic blog post talking about the first bubble is Silicon Valley, and the second bubble is North America, and the third bubble is everywhere else. And so you kind of watch these things emerge. And my job is to jump over that pop into the Silicon Valley bubble before something happens and say, no you should be thinking about X, you should think about Y. At an event like Radio I've got a force multiplier because I've got 40 plus Ambassadors with me all popping up at all these little booths you see behind you, and the shows, and the talks. >> And the goal here is not to be a bubble, but to be completely one hive mind. >> And the diversity at VMware just blows my mind, it really does. I think a lot of people comment on it quite often, and in fact I've been asked to be a non-exec director of other companies, to help them advise on their culture. Which is not in tech, in culture, which is quite interesting. And so the diversity that we have here is really infusing people to innovate in a way that they've not done before. It's that diverse set of opinions really helps. >> Well it does. And this, from what we've heard, Radio is a very, there's a lot of internal competition, it's like a badge of honor to be able to respond to the call for papers, let alone get selected. Touch on the synergies, the symbiosis that I feel like I'm hearing between the things that are presented here, the CTO Ambassadors and the customers. Like maybe a favorite example of a product or service that came from, maybe a CTO Ambassador, to Radio, to market. >> Yeah, I'm just trying to think of any one specific one. There are always bits and pieces, and things here and there. I think I should have thought of that before I came on really. I think what you're looking at here is, it's much more about an informed conversation and so it's those ideas around the fact. And also, quite often someone will have a cool idea, and they'll go to the Ambassadors, can you find me five customers that want to try this? Bang, we've got it. So if you're out there on a customer, and someone comes to you as an ambassador and says, I've got a really cool thing I'd like you to try. It might be before, we have a thing called Fling, so it might even be before it's made a fling. You probably heard from Morney how that process goes. Then engage fast, because you're probably getting that conduit direct into the core of R&D. So a lot of the features that people see and functions and products et cetera, that people see. A lot of the work you see, we're doing with the next version if you realized our management platform, a lot of that has been driven by work that's been done by Ambassadors in the field, and what we're doing there. All the stuff you'll see, I've got my jacket over there with NANO EDGE written on it. A lot of the EDGE stuff that you see, a lot of the stuff around ESXi on Arm, a lot of the stuff around that is driven specifically around a particular product range. So a really good example is, a few years ago, probably around four, myself and Ray sat down and had a meeting in VMware Barcelona, with a retail customer, and the retail customer was talking about could we get them an STDC, but small enough to fit in every store. They didn't say that at the time, but that's how we kind of got to it. So that started off a whole process in our minds, and then I went back and we, the easiest actual way for me to do it was to then get a bunch of the Ambassadors to present that as one of their innovation ideas, which became NANO EDGE. I originally called it VX Nook, because we were going to do it on intel Nooks. (laughs) Unfortunately the naming committee wouldn't allow VX Nook, so it became NANO EDGE. And that drove a whole change within the company, I think within R&D. So if you think up until that point, four years ago, most of what we were doing was, how do we run things bigger and faster? It was all like Monster VM, remember that? All those kinds of things, right? How do we get these SAP HANA 12 terabyte VMs running? And really NANO EDGE was not necessarily a product, per se but it was more of a movement driven by a particular individual, Simon Richardson, who had got promoted to Principle as a result, through the Ambassador program. That was driven through our R&D to get them to think small as well as big, you know. So next time you're building that thing, how small can you run your SX, how small can we get an SX? >> John: Small, at scale. Which is EDGE, right? >> And, you know, so get small, at scale, which was EDGE. And so suddenly everyone starts talking about EDGE, and I'm like, hang on I've been talking about this for a while now, but we just didn't really call it that. And then along comes technology like Kubernetes, which is how do you manage thousands of small things. And it's kind of, these things come together. But yes, totally, you can almost say our EDGE strategy, and a lot of the early EDGE work was done and driven out of stuff that was done from CTO Ambassadors. It's just one of the examples. >> What are some of the Kubernetes service mesh? Because one of the things we heard from Pat, and we've heard this before, but most recently at Dell Technologies World, in the last couple of weeks, was don't look down, look up. Which basically means we're automating the infrastructure. I get that, I've covered ad nauseam. But looking up the stack means you're talking about kubernetes app developers, you've got cloud native, you've got services meshes, microservices, new kinds of challenges around instrumentation. How are you guys inside Radio looking at that trend? Because there's some commercial impact, You've got Heptio, you've got Craig and the team, some of the original guys. >> Yeah, yeah. >> As well as you have a future state coming out, with state, pun intended, data, stateless. (laughs) These are new dynamics. >> Yeah, yeah. >> What's the R&D take on this? >> So there's two ways that I really talk to people about this. The first one is, I've got a concept that I talk about called application chromatography. Which sounds mental, but you remember from high school probably, chromatography was where you had that really special paper and you put the dot of liquid on and it spread it to all it's constituent parts. That's actually what's happening with our applications right now. So, we've gone through a history of re-platform. You know, mainframe, blah blah blah blah blah. So then when we got to x86, everything's on x86, along comes cloud, and as you know John, for the last 10 years it's been everything's going to cloud because we think that's the next platform. It's not, but then everything's not going to SAS, it's not all going to paths, it's not all going to Functions, it's not all going to containers. What you're seeing is those applications are coming off that one big server, and they're spreading themselves out to the right places. So I talk to customers now and they say, okay, well actually I need a management plan, and a strategy and an architecture for infrastructure as a service, containers as a service, functions as a service platform as a service and SAS, and I need a structure for that on premises and off premises. So that's truly driving R&D thinking is not how do we help our customers get from one of those to the other? They're going to all of them. >> It sounds like a green screen for media. >> It is, and then the other side of that is I've just had a conversation with some of the best, you know, what these events are like? Some of the best conversations in the water cooler, in the- >> In the hallway, yup exactly. >> I've just had a fascinating conversation with one of our guys has been talking about, oh it's really cool if we got kubernetes cause I could use it right down at the edge. I could use it to manage thousands as a tiny EDGE things. And as I'm talking to him and sort of saying, you know what he's doing, I suddenly went, hang on a second, how does a developer talk to that? He's like, well I've not really thought about that. I said, well that's your problem. We need to stop thinking about things from how can that framework help me? But how can I extend that framework? And so a lot of that- >> Moving beyond just standing up kubernetes, for what purpose? Or is that what you know, the why, what? >> So if the developers there, it shouldn't be all. I'm going to use this new framework to solve my problem or the EDGE if an R&D person would, but people like myself are there to drive them to think of the bigger picture. So ultimately at some point a developer in the future is going to want to sit there and through an API, push out software SQL server, a bit of Mongo over here, some stuff on AWS, go and use the service on our Azure at the same time pushing stuff into their own data center and maybe push a container to every store if they're a retailer and they want to do that through one place. That's what we're building. And you know, driving that, all these bits and pieces you see behind you pulling those all together into this sort of consistent operations model. As I'm sure you've heard many of- >> And it's dynamics not static, so it's not like provisioning the old way. You got to track what's being turned on and off because how do you log off? What goes turns on? What services get turned on? Turned off, turned on. >> If you don't get a theme of really, I suppose not only Radio, but our industry of the last few years, people have always said if that cliche change is constant, right? Oh, change is constant. Yet still architects build systems that are static, right? You guys that just, I'm designing an architect in this new system for the next three years. I'm like, that's stupid. What you need to do is design a system that you know is going to change before you've even finished starting it. More or less started going half way through it. So actually, as I see, I was in a fantastic session yesterday with the Architects around ESXi and VCenter, which might be boring to most, but where we architecting that for scale at a huge way. >> Well, I think that's the key thing I mean this is, first of all, we'd love this conversation because, if you can make it programmable with API and have data available, that's the architecture because it's programmable, it's not static. So you let it morph into however the application, because I think I mentioned green screen, you know chroma keys as we have those concepts here, but that's what you're saying. The apps are going to have this notion of, I need an app right now and then it goes away. Services are going to be provisioning and turning on and off. >> There is a transience, there's a transience to infrastructure, there's a transience to applications, there's a transience to components that traditional mechanisms aren't built to do. So if you look at actually, what are we building here? And what's that sort of hive mind message? It's how do we provide that platform going forward that supports transience? that allows customers to come, I mean people used to use the term agile, but it's been over years and it's not right. It's the fact that literally it's a situation of constant change. And what your deploying onto, it's constantly changing and what you're deploying is constantly changing. So we're trying to work out how do we put that piece in the middle, that is also changing but allows you some kind of constancy in what you're doing, right? So we can plug new things in the bottom, a new cloud here, a new piece of software there, a new piece of hardware there or whatever. And at the same time, there's new ways of doing architecture coming on top. That's the challenge of this, the software defined data centers, almost like an operating system for clouds or the future operating system for all apps on all clouds and all of- >> It's a systems thinking for sure, absolutely. >> Let's put your Chief Talking Officer hat on for a second as we look- >> I thought I've been doing that for the last fifteen minutes. (laughs) >> At VMWorld 2019, which is just around the corner. Any cool ANEA customers that are going to be on stage that we should be excited to hear about it? >> Actually, I was having a meeting yesterday morning about that, so I can't really say, but there's some exciting stuff we're lining up right now. We're obviously now is the time we start thinking about the keynotes, now at the time you start thinking about who's on stage. Myself and a few others are responsible for what those demos are, you know the cool demos you see on stage every year. So we literally had the meeting yesterday morning at Radio to discuss what's going to be the wow at VMWorld this year. So I'm not going to give anything away to you. I'll just say make sure you're there to watch it because it's going to be good. And we're also making sure there's a big difference between what we're doing in Moscone now and what we're going to be doing it in Barcelona when we- >> And when expand theCUBE outside of the United States certainly, we'd love to have you guys plug in and localize some of these unique challenges. Like you said, I agree bubble now the west of the world has different challenges content different. >> Definitely, I think to that end, multicloud is probably more of a thing in Europe than it was necessarily in, in North America for a longer time because those privacy laws you talked about before, people have always been looking at the fact that maybe they had to use a local cloud for some things. You know, a German cloud run by German people in a German data center and they could use another cloud like Amazon for other things. And you know, we have UK cloud who provide a specific government based cloud, et cetera. Whereas in America there was, you could use an American cloud and that was fine. So I think actually in Europe we've already been at the forefront of that multicloud thinking for a while. So it's worth watching. >> It is worth watching, I wish we had more time to, so you're just going to have to come back. >> Definitely, anytime tell me when. >> We look forward to seeing you at VMWorld. We thank you for sharing some insights with John and me on theCUBE today. >> Cool, thank you. >> For John Ferrier, I'm Lisa Martin. You're watching theCUBE's exclusive coverage of VMware Radio 2019, thanks for watching. (upbeat music)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hi, I'm Peter. Boris, And welcome to another cube conversation from our wonderful studios and beautiful Paolo Alto, California. One of the biggest challenge that every enterprises faces how to attend to the volumes of data that are being generated by applications. But more importantly, that the business is now requiring because they want to find new derivative sources of value in their digital business. Transformations is gonna require a significant retooling and rethinking of how we used eight is an asset. And the directions that infrastructure, data management and business are gonna move together over the course of next few years. Now, have that conversation. Got a couple of great guests here. Josie Swoop is a VP of marketing veritas. Welcome to Cuba or back to the Cube. Yeah, thanks. Peter and Rick Clark is a CEO of opt are welcome. Thank you for the first time. >> Great to be here, >> So let me start here. Joey, why don't we start with you? Give us a quick update on Veritas and where your customers are indicating the direction needs to go. >> We've just had, ah, record breaking financial year for us, which ended in end of March. So since divestiture from semantic, as you know better, Toss has been through a transformation and then on a path to growth. So our core businesses are humming with just like I said, the second half of the year specifically was great for us. What we're hearing from customers, Peter, is that they want to elevate their their business problems away from infrastructure to business outcomes. That what they ask veritas to do is, can you abstract away some of those infrastructure plumbing problems, storage, security, data protection and focus on what the applications can give us. That's number one. Number two is Can we standardize? I mean, the example of Southwest comes to mind, right? They have the same plane so they can reroute those planes anytime they have the same pilots flying those planes so they can to standardize. So they collapsed better. And then, lastly, to your point value of data over volume. Everybody talks about the volume. What about the value of data? What is veritas do for for me? Mr. You know God's a customer in our tax extract value of that data, which is growing day by day. >> Well, one of the most interesting things about this challenge of businesses faces they try to attend to these things is that data is often characterizes the new oil. And we we push back against that Because >> data is a new kind of asset, it's an asset that's easily copied. It's an asset that's easily shared. You can easily integrate it. You can apply it to multiple uses with zero loss of fidelity and what it does currently. And so the whole notion of creating new options in the value of data's intrinsic to the questions of digital business. So that suggests that we need to start thinking Maur about data protection, not just from the standpoint of protecting data once it's been created and is sitting there so we can recover it. But new types of utilization, new ways of thinking about data data as it's going to be used, understanding more about dating, protecting that Rick, would you kind of Does that resonate? >> Yeah, absolutely. You know, one of the things that we've sort of seed in the marketplace is certainly over the last 10 years, the Data Sena has become so complex. This is massive fragmentation of data across highly virtualized infrastructures. And then, when public clouds came along, customers didn't really know what workloads they should move up into those clouds. And so what we saw is a huge problem. Is areas of cost and efficiencies, massive problems of risk and then obviously the amount of money that cos of spending on compliance. And so what we were really focusing on is the gaps. What do you not know about? And so we would really >> about your data >> about your data. Exactly. So we really measure the hot beat off the data protection environment, and from that we could actually see where are you? Risk where your exposure, where you're spending too much money, >> Where's your opportunities? Seize your opportunities. So we've got a notion of the the solution that folks are looking for, something that provides greater visibility into their end and data from a risk exposure opportunity. New sources of utilization standpoint talk a bit about how >> at four >> rounds out the veritas portfolio as it pertains of these things that you're seeing customers asked for taking data closer to outcomes and away from the device orientation? >> Absolutely. So Vatos has always been known to be a leader and data protection. We've done that for over 20 years. We also were the first pioneers in software defined storage. And we're number one in market share, according to I. D. C and Gardner as well. Ah, but again to my earlier point, customers have been asking. So what? We've done the plumbing really well and you've scaled. How do you take this to the next level? Extract value from all that data you're sitting on top of that you're protecting. And that's where apt are comes into the picture. We've built some tools natively within veritas of the last three or four years where we try to go and classify the data on in jest, identify things like P I information sensitive data, rock data, redundant, obsolete, trivial data that we can delete. There was a customer who recently deleted 30,000,000 files, just press the delete button and this isn't a highly regulated environment, >> but they were still pretty darn eggs. >> They definitely where but we were able to give them that visualization and information that they required. Now the question those customers are asking us or we're asking us. Before avatar came into the picture was at the infrastructure level. How do I know how much I'm spending on my data protection environments? Do I know where the growth ISS is it all in the traditional workloads of oracle ASAP, Or is it in virtual or is it in the cloud? Right. Am I putting too much data on tape? Is it costing me enough? Can extract the value from that data. So they were asking us infrastructure visualization and i D analytics. Questions which only apt are could answer. And we have some joint customers they were actually using. Apt are already not just with to monitor the vatos ecosystem, but even some of our competitors and the broader i t ecosystem on a single planet class. And that's where I think after really shines is is the agnostic approach they take beyond just veritas are beyond just another storage vendor. >> Well, so way certainly subscribed to this notion that data protection is going to It's gonna be extended, but it's gonna become a strategic digital business capability that does have to be re funk around the concept of data value and sounds like that's the direction you're taking, and you guys have clearly seen that as well. But obviously some of your customers have seen it. So talk to us a little bit about how customers helped you two guys together. >> Yeah, that's a great question. Was interesting. Actually. We had some of the largest companies in the globe actually using ourself with many of the fortune Tien using up self with J. P. Morgan Chase quote calm Western digital. And they came to us with these very precise problems around, you know, howto optimize my risk within the environment, had a streamline, obviously the costs and compliance. And we found that they were very common questions. And so we actually created this agnostic intelligence built into the software a rules engine that would have to correlate data from all of these disparate data sources. Whether Tom primer on the cloud tying that together would provide impactful insights to our customers that could sold real world problems. And we'll do it with kind of what we call the easy button. One of the big problems with a lot of software products out there today. Is there a point solutions to manage pots of the infrastructure companies wanted a single pane of glass where I could see everything across all of my storage. All of my data protection on prim and cloud. And that's really what we bring to the table, that single paying the class. And we do it very simply at scale for the largest customers. And that's in many ways was the synergy, obviously, with a partnership with Veritas. >> So give us some sense of how how customers will see the benefits of this from a rollout standpoint over the next 6 to 18. >> Right? So Step One in this journey for us is to ensure there are customers. Understand that we're going to continue to have that open an agnostic approach Apt are suddenly is not gonna become proprietary batter toss product. It's going to continue on its on its mission to be agnostic across various storage data protection and cloud environments. That's number one. Number two is we're gonna bring the the artificial intelligence and machine learning capabilities that we have in house with Veritas combined that with some of the things that Rick just docked, abide with the capabilities adapt our has combine, it's our customers can gain. I know add value. The one plus one equals three approach there as well. So those air, like the two key pillars for us going forward and eventually will extend apt are to an end to in Data Analytics platform not just I d analytics, where we're looking at infrastructure, but an end to end data. Plus I t analytics platform that spans Veritas is will Is the broader a IittIe ecosystem? >> Well, so it's good to hear that you're gonna let apt are continue to focus on data value as opposed to veritas value. Right talk. Talk to me a little bit. About what Does that analytics piece really mean? Howard Customers going to use it? How are they using it today? How are they gonna >> let me carry that? Said is roughly 30,000 unique metrics that we actually gather across the whole I t infrastructure and we'll look at a classic use cases. One of exposure. What? A lot of companies been enormous amount of money on the data protection infrastructure. The using disparity, tools and technologies they don't always go with. One platform like net backup is an example, right? And so with that, come challenges because there's gonna be gaps they might be backing up a Windows server where they're the backup policy says they're just backing up. The C drive will interrogate VM, where all the hyper visor will look at the network and see that there's a D Dr attached to that volume as well. And there's no backup data protection policy. So enormous amount of exposure if they tried to do a restore, obviously, from the d Dr where there's no protection, right from a cost perspective, there's an enormous amount of white space problem in the storage industry. More and more companies are moving from spinning distal flash arrays. A lot of companies is struggling with How do I protect those old flash A raise the using snapshots that using cloud they're tearing to the cloud the using different backup products. Obviously, we'd prefer that they used their backup, but with our software, we can provide that that inside across the entire data protection framework and storage and show you where is your risk? Where is your inefficiency, where you double protecting things into spending too much, much money? This whole notion of data protection is transaction. A lot of people do what's called distant, distant eight still being voted off site. How do you know that all those transactions are successful? How do you know you can restore based on those s L A's and tying that into you? See, M d B. That's what appetite does. >> So I'ma throw a little bit of a curveball here. So having worked within 90 worked with N i t organizations, it can be I ke historically can has been rolled to the compartmentalizing segment you administrated for servers in Australia for storage of people who are administrating applications and and subsystems. And the cloud is munge ing a fair amount of that together. But one of the places that has always required coordination, collaboration and even more important practice has been in the area of restore firms were shops that did not practice how they would restore, you know, hopefully they never had a problem. But if they did have a problem, if they hadn't practiced that process, they would likely we're not gonna be successful in bringing the business up. Gets even more important digital business. Can you give us a little bit of visibility into how this combination taking the metadata, the metrics of visibility. Taking the high quality service is bringing them together is going to streamline, restore within their prices. >> So first, let me address the first point you made, which is what I call the rise of the versatile is too right. So there are no more specialists in certain jobs. The versatile listen, the cloud or in virtual tend to do three or four jobs when there's back up our story virtualization itself on DDE. What the's Verceles want is to explain an easy barton to restore their VM environment or their big data. And my mother there Hadoop environment. They're not really worried. As a central I t. Team that Hey, what am I going to do with the entire data estate? How did I restore that? So that's the first step. Second step, as the world of I t gets more more complicated on the rise of the worst list continues to happen. Thes folks want to be able to have a resiliency plan. They want to be able to rehearse these restores right, and if they don't have a resiliency plan built in if the data protection is so siloed and does not help them build a resiliency plan. And to end that restore is not gonna be successful. Likely? Right. And that's where Veritas and companies like Veritas come in to help them build those resiliency plans and to end. >> But let me take you back to so the financial industry, for example, there are rules about how fast you you have to be able to restore. I gotta believe that visibility into data that is a value level can help set priorities. Because sometimes you want to bring up this application of this class of applications of this class of users of functions before you bring up those so does does apt are apt are going to provide even greater clarity in the crucial restore >> at 70. One of the biggest challenges for >> a lot of companies with restores is actually finding the data. We had a classic use case with a large Fortune 10 company where they had a bunch of service that were being backed up. There were bolted off the tape, and then it was obviously a different backup product they were using. The actually lost the catalog. The data was still there on tape. They had millions of tapes in the vaults, and they used apt title, identify the barcodes and recover that data literally within a matter of hours. And so not only can we find you your freshest copy the most recent copy, if that's what you want, but we can find where is your data? Because in a lot of cases there's multiple replications, multiple copies of the data across all sorts of assets within your >> infrastructure. Interesting. So last thoughts. When we have you back in the Cube in a year, Where you guys going? Big? >> Hey, listen, the two things that I talked about we're going to continue to expand the support of the ecosystem. The world of I t. Whether it's on Prem virtual or in the cloud with Apt are we? We're going to continue to invest in the artificial Intelligence and ML capabilities are not just apt are but all of that tosses ecosystem and you'll see amore integrated approach on the platform based approach on standardization When we come here >> next, guys, thank you so much. Great conversation. Thanks for being here in the Cube to talk about this important relation between data tooling and sources of business value. Rick Clark is the vice president of the outdoor business unit. Used to be the CEO of actor, but now the vice president. The outdoor business unit Veritas. Josie Stroop is vice president of marketing of Veritas. Once again, guys, thanks very much for being here. Thank you so much for having us. And once again, I'm Peter Burgers. You've been listening to another cube conversation until next time.

(light electronic music) >> Announcer: Live from Stanford University, in Paolo Alto, California, it's theCUBE. Covering Women in Data Science Conference, 2018. Brought to you by Stanford. >> Welcome back to theCUBE, I'm Lisa Martin. At Stanford University, we're here for the third annual Women in Data Science Conference. #WiDS2018, check it out, be part of the conversation, WiDS is in it's third year, but it's aiming to reach about a hundred thousand people this week alone. There's 177 regional WiDS events in 53 countries. This event here, the main event at Stanford, features key notes, technical vision talks, a career panel, and we're excited to be joined next by Dr. Nathalie Henry Riche. I did that in French. >> Yes. (laughs) Who is a researcher at Microsoft, and Natalie, first of all, welcome to theCUBE. >> Thank you, I'm really thrilled to be here. >> Yeah, you gave a technical vision talk on data visualization, and data driven's story telling. Share with our audience, some of the key messages, that the WiDS audience heard from you earlier today. >> Well, I guess, I gave two main messages. The first one is, that a visualization has two superpowers. >> Lisa: Superpowers? >> Superpowers. >> Tell me girl. The first one is enable you to kind of think about your data in a new way. So, just kind of form hypothesis, and answer questions you didn't even know, you had by your data. So, that's the first one. The second super power, is it's really useful to communicate information, and communicate with a large audience. Visualization helps you, kind of convey your point with data, to back it up. So, that's kind of the short one minute. >> I love that, super super hero, super power. So, WiDS is, as I mentioned at the intro, in its third year, and reaching, it's grown dramatically in such a short period of time. This is your first WiDS, and your first WiDS you are a speaker. What was is that attracted you to WiDS, and you went, yes I want to give some of my time to this, and come down from Seattle? >> Well, so I'm French originally, and my studies I did at engineering school, and it was one of three out of 300 men, right? >> Wow. >> So, I was requested a lot for women in computer science, and engineering. So, I actually really like it. Just meeting all of those people, talking about, you know, trying to bring more women in. Part of the job I'm doing is very creative, so, we're trying to come up with new ideas for visualization. I think having, you know, a wide range of people adds to the mix, and we get so many more exciting ideas. So, I really want to try to have more diverse group of people I can work with, and connect to, and so that's why that attracted me to here. >> Excellent, couple of things that you said I've heard a number of times today. The first one is, what Daniela went and shared, who's also a speaker, that often times, some of the few women in tech, and you mentioned being one of three in 300? Are asked to do a lot of other things. Did you find that, that, okay you're one of the few females, you're articulate, you like speaking, we want you to do all these things. >> Yes, and I say no a lot. (laughs) >> 'Cause I have kids, too. >> That's a skill, too. But yeah, it happens a lot. I think as we go further, it's going to be less and less happening. It's better in the end. So, it's kind of a service, I see it as a service to, you know, my field, and my company. But, at the same time, we'll also get a lot of benefits from it. But that said, I try to cut it down to a manageable level, so two hours flight from Seattle works great. >> Right, right, right. Another thing is that, that you mentioned the creativity. I've heard that a number of times, today from our guest Margot Gerritsen, was on as well. Tell me about your thoughts about being in this data science role, the need for creativity. How does, how it, why is that you might consider it, like a softer skill versus the technical skills. But, how important is that creativity in your job, for example? >> So, my job is really like researcher. Trying to have new ideas, and innovate for Microsoft in particular. So, I'm not really a data scientist, but I build the tools for a data scientist. So, knowing that, creativity is important because you need to kind of think out of the box. What is the next generation of tools that they will need? In turn, they need to think out of the box, kind of get more insight out of the data they're collecting. So, creativity is just like, pervasive to this whole data science thing. Problem solving as well, so you need a lot the left brain, and a lot of the right brain. Kind of both of them together. I think that having different cultures, and different genders, even different age ranges just, you know, makes you think out of the box. That's just what's happening. Discussing with people, I was discussing with someone in cosmology, and I was like, whoa. That brought up a lot of different ideas in me, so, to me, that's really critical part of what I'm doing every day. >> I like that, that kind of aligns to what one of our guests said earlier, and that is the thought diversity. Wow, I've never >> Yes. thought of thought diversity. But, you bring up a good point about it's not just about having women in the field, it's also having diversity, in terms of generations. One of the things that's, I think, pretty unique about WiDS, is it's not just about reaching young women in their first semester at University, for example. Maria Clavijo said that's the ideal time to really inspire. But, it's also reinvigorating women who've been in academia, or industry in stem subjects for a long time. So, you have, we have multiple generations, and to your point, that diversity is important, it's not just about gender, ethnicity. It's also about the diverse perspectives that come from being >> Exactly. from different generations. >> So, it's funny, 'cause I was giving this talk earlier, and it was, one part of it was about time line. When I was researching, you know how people draw time? Well there's, depending some culture, it goes from left to right, but some other culture it's front to back, back to front, right to left. So, we need to be aware of all of that, and it's so much easier to just have the people to converse with right in your office, or next door, to be aware of those. So, that's very important, especially to big companies, like Microsoft, 'cause of, you know, a lot of customers world wide. So, it's very important to just be immersed in that. >> Definitely. So, you have been published, you've got published research, and over 60 articles in leading venues, and human-computer interaction, and information visualization. But, something we chatted about off camera, was very intriguing about visualization and children. Tell me a little bit more about that. >> So, I happen to have two kids, you know, seven and four. I'm passionate about what I'm doing, and I just couldn't keep it out of their hands, right? So, I was just starting, you know, seeing what does my daughter learn at school, like, what does she learn in kindergarten? In fact, in kindergarten, I remember one day, she brought back candies, and I'm like did you get candies from school? She's like no, because we were doing a bar chart. I was like, what? (laughs) So, I was very intrigued in, you know, what do we teach, what do your kids learn? It was fascinating to see that, you know, from an early age, they learn how to do those visualizations. But, they don't really learn how you can lie with them, or you know, to kind of think critically about that. That, you know, maybe you can start your bar chart at two, and you know, you would have less candy, I guess. But, you could, kind of convey the wrong messages. So, I became passionate about this, and decided we need to just improve our teaching about how we can represent data, and how we can also misrepresent it. In the hope that for the next generation to come, they'll be able to look at a chart, and think critically about it. Whether or not it tells the right story with the right data. Kind of beyond, just picture's worth a thousand words, then I'm not going to think about it. >> Yeah. >> This is kind of my personal effort that I try to move myself forward. (chuckles) >> Well, it's so important about having that passion, and I think that's one of things that seems to be inherent about WiDS. Even, you know, yesterday seeing on the Twitter stream, WiDS New Zealand starting in five minutes, and it's been really focused on being so, kind of inclusive. Just sort of naturally, and one of the things that I learned in some of my prep for the show, is the bias that is still there, in data interpretation. You kind of talked about that, and I never really thought about it in that way. But, if a particular group of people is looking at a data set, and thinking it says this, and no other opinions, perspectives, thoughts are able to be incorporated to go, well, maybe it says this. >> Yeah. >> Then we're limiting ourselves in terms of one, the potential that the data has to, you know, help a business, create a new business model. But also, we're limiting our perspectives on making a massive social impact with data. >> Yeah, what I find very interesting is visualization often people think about it at the end of the spectrum. Like, I've collected my data, I analyze it, and now I need to pretty picture to kind of explain what I found. But, the most powerful use of visualization, I think, comes early on. Where you actually just collected your data, and you look at it before you run any statistical test. I did that not long ago with French air traffic data in the Hollands, I put them in, and I saw the little airplanes moving around. Then, what we saw, is one air planes doing loops like this. I was like, what is this going on, right? It was just a drone, doing like tests, right? But, somehow it got looped in into that data set. So, by looking at your data early on, you can detect what's wrong with the data. So then, when you actually run your statistical test, and your analysis, you better reflect what was that data in the first place, you know, what could go wrong there? So, I think inserting visualization early on is also critical to understand what we can really know, and do, and ask, about the data in the first place. >> So, it's kind of like, watching the story unfold, rather than going, we've done all this analysis here's the picture, the story is this. The story is, your sort of, turning it sort of page by page, it sounds like, and watching it, and interpreting it, as it's unfolding. >> Rethinking what you collected in the first place. Is that the right data you collected to answer the question you wanted to ask? Is it a good match or not? Then, rethink that, you know, collect new data, or the missing one, and then go on with your analysis. So, I think to me, it's really a thinking tool. >> It also sounds like another, we talked about the technical skills that had, obviously that a computer scientist, data scientist needs to have. But, there's other skills. Empathy, communication, collaboration. Sounds like also, there needs to be an ideal kind of skill set, it has to include open mindedness. >> Yes. >> Tell me a little bit about some of your experiences there, and not being married to, the data must say this. So, if it doesn't, I'm not going to look anywhere else. Where is open mindedness, in terms of being a critical skill set that needs to come to the field? >> Yeah, I mean we, that's that is totally a re-critical point. Think already, when you're collecting the data, especially as a scientist, when I run experiment, I kind of know what I want to find. Sometimes, you don't find it. You need to kind of embrace it. But, it's hard to have because sometimes, it's like those unconscious bias you have. Like, you're not really necessarily controlling them, and just the way you collected the data in the first place, maybe just, you know, skewed your result. So, it's very important to kind of think ahead of time of all of those bias you could have, and think about all of what could go wrong. Often, the scientific process is actually that trying to think about all of the stuff that could go wrong, and then check whether or not they're wrong. We're trying to infuse that, a little bit over Microsoft as well, kind of, you know, the data that we collect, can we analyze them, can we have teams of people who really think is that the right data? Are we collecting like, world-wide for example? Are we just collecting from the US? So, there's a lot of those, kind of, ethical, and bias, kind of training, and effort to try and remove that. The maximum from our work, and I think that it's across the entire world. I think, with all of this data collection everywhere, we kind of have to do that, very consciously. >> I think two things kind of speak to me that out of what you just said, that we've heard a number of times today. One, that failure, and I don't mean to say that failure is not a bad thing. That's how you, >> That's how you learn, Exactly, >> and grow. Exactly, in many ways it's not a bad F-word, it's this is how everybody that's successful got to wherever they are. But, it's also about embracing, as you said, the word embracing, embracing the fact that you might be bring bias into this, and you have to be okay with maybe this is the wrong data set. If you consider that a failure, consider it, to your point, a growth opportunity. That is one of the themes that we've heard today, and you've, kind of, elaborated on that. The second one is, be okay getting uncomfortable, get out of that comfort zone. Consciously uncomfortable, because when you're able to do that, the possibilities are limitless. >> Yes, and that's what I try to do everyday, 'cause I try to push all of the software that we're doing, and Microsoft is so big, you know, and all of those software are like so there. (laughs) So trying to come up with new ideas, like so many are failures, you know. Oh they won't make money, or they don't actually work when you, you know, for this population. So, most of my work is failure. (laughs) But hey, one success when you know why, and I'm happy about it. >> Exactly, but it's just charting that course to getting to the ah, this is the pot of gold at the end of the rainbow. Well Nathalie, thank you so much for taking some time to talk with us on theCUBE, and sharing your stories. Congratulations on being a speaker, your first WiDS, and we look forward to seeing you back next year. >> Thank you very much. >> We want to thank you for watching theCUBE. I'm Lisa Martin, live from WiDS 2018 at Stanford University. Stick around, I'll be back with my next guest after a short break. (light electronic music)

>> Announcer: Live from Las Vegas it's theCUBE, covering NetApp Insight 2017. Brought to you by NetApp. (upbeat techno music) >> Hello, everyone. Welcome to this special CUBE presentation. We are here at the Mandalay Bay in Las Vegas, Nevada for NetApp Insight 2017. I'm John Furrier, your co-host and co-founder of SiliconANGLE Media. Here at theCUBE, here with Keith Townsend for all day today. Keith Townsend at CTO Advisor covering NetApp 2017 here at the Mandalay Bay in Las Vegas. And before we kickoff a long day of great conversations with thought leaders, experts, executives, and also customers of NetApp who are transitioning to a whole digital world, a digital transformation. We can't not address the massacre that happened only a few days ago here in Las Vegas, here at the Mandalay Bay, our second home of theCUBE. If you know theCUBE, you know that we're here all the time. Hits home for us, but that pales in comparison to the families and victims of the 58 dead, 59 total but 58 that have died plus the shooter. Over 500 injured in the heinous cowardly act from the shooter who killed those people. Really I'm trying to kind of hold it together because it really hits home for me because, like 9/11, it's one of those moments that this is planned. This was a coordinated attack, kind of like the Oklahoma bombing, and it reflects on our society. I want to make a comment. And Keith, I'd like to get your thoughts in a minute. But first I would like to say our hearts and prayers are with the victims and families. And want to put a shout out to the first responders because if you look at the Mandalay Bay and what happened here, there could have been a lot more that have died. And that is really a testament to the people who responded, to this unpredictable act. And our prayers go out to the families and victims. And again, a shout out to the law enforcement people. Keith, this is a tragedy that people are trying to make sense out of it. And you know, we have to move on. Obviously, we're here at the NetApp event. A lot of great things to talk about with data and the future and how society will change with technology. But this is a time in history where we're seeing a societal shift. But we got to make sense of it. >> Yeah, you know, John, I'm going to try and keep it together as well. I think this is my seventh time in Vegas this year. And I'm sure every time I've spent at least some time in Mandalay Bay. This event, you know, I had a personal tragedy in my own life of losing my nephew to gun violence. We're all scratching for answers and trying to find a solution to this. And I'm a little bit ... It's a tough moment I think, personally, for us and our friends in the community. But the folks here at NetApp have done a really great job. Not just NetApp but the community in general, here in Las Vegas there's been folks in the community that have organized blood drives. The Red Cross has actually asked us to stop donating blood because of the outpouring of support. And I think that focus of hope in changing the world is what I would like to focus on. >> Well, I mean, take a company like NetApp having their annual customer event, partner event here at Mandalay Bay. It's their big event. And on their doorstep this happens. How they've handled themselves, I think, shows the culture of NetApp. They respect, they took pause. They canceled the first day. They handled it with extreme class. George Kurian put out there a personal story. But this is what it's about. We've got to move on. But I think to me, it's not about politics. It's not about any of that. It's about how do we move forward? And I hate to use a cliché, it's a wake up call. The world has changed in an instant through a prism of a known life. We heard that at 9/11. It's been 16 years. Enough's enough. And here's the deal, we have to be awake. We are realizing that, not the digital transformation for the enterprise, it is a transformation around the world. If you look at geopolitics, or you look at what's happened even today in the news. Even though the President of the United States is here to visit with the families, the Senate Intelligence Committee points out more fake news influenced via social media on Facebook with the Russians hacking the election. They didn't really hack the election, they just used advertising and albatross Facebook among other platforms to manipulate the election. Equifax hack, turns out as I reported originally on theCUBE, it was a state-sponsored activity, it was not a hack. These are new realities. And this is the theme that we see at theCUBE across our events that we go to, the new reality that we are living in a completely different society and it's on us to lean in and be part of the solution. And it's not about being a political solution or saying, "Hey, I'm praying." I mean, we're praying. But you can pray. Praying is what you do, action is another. But it's not about just the gun laws or this or that, it's about the society and the communities. The GoFundMe's are going crazy for the victims, but you can't replace the mother. We had a loss in our community, former Cisco employee lost her life, three kids. The communities have to lean in, individuals have to lean in if they have expertise. I think this is going to be a call to arms that's going to have a revolutionary effect on people. And I think it's an opportunity for the technology industry to lean in, use what we know. We have AI. We got blockchain. We got machine-learning. And this data, the slogan of NetApp couldn't be more perfect. Changing the world with data this is the mandate. >> So, George Kurian gave an ardent, and just compassionate... I had a tough time keeping myself together at the end of yesterday's keynote. George shared how data helped save his son's life. His 13-year-old son comes home every day thankful for technology. And we need to find ways to use AI, use machine learning to impact our communities. While we're talking about the larger, global community, even in my hometown of Chicago that's ravished by violence. You know, there's ways to use social media, data, AI-driven changes to help create policies and to help enable community organizers to understand the source of this nonsense basically. We say this is the new normal, but we should never grow numb to it. >> And I'm grateful -- >> John: No, it's not normal. It's not normal. And this is why I tell my daughter who's the class president of junior high school, Paolo Alto High School, this is not normal. This is not normal. This is not what we want. >> Keith: No! >> You know, you're personal tragedy, hit home with you personally. You had to rationalize it. And you're also a very active participant in the community. This is a new opportunity. The new normal is to behave differently, not the outcome. How do you look at that? Given what you've been through personally and now this, it brings together emotions but then the logic has to kick in. >> Keith: Right. >> You have to execute, actually take action. >> So, it started again Monday when a bunch of us had to make the decision on whether or not we're going to make the trip to Vegas to participate in a enterprise IT show. Your initial gut reaction is, "You know what, so many dead. What does it really matter to go to a conference at this point in time?" And then, you start to rationalize. "You know what? My way of life, our way of life cannot change. We can't allow this tragic event to change how we approach it." And again, NetApp and George did a great job of kicking off the conversation saying that we need to use this as a pivot point to drive the conversation to how us technologists can leverage this. >> Let's take this to where NetApp's living right now. NetApp Insight 2017 is the even we're kicking off here, all day coverage, here on theCUBE with Keith Townsend, expert in the field. Cloud, data, storage, it's all converging. But the reality is is that NetApp has SolidFire. They've bought great company. You're seeing a DNA transfer off of the original DNA of NetApp which has been very innovative culture. They have a very big success story as a start up, went public, and now are continuing to transform. Their customers are transforming but you bring up this new normal that the behavior we want to change and the outcomes that will become of it, speaks to the culture of what we're seeing in the enterprise transformation. A new class of developers are coming in. And the class of developers are about DevOps, their about infrastructure as code. And these new developers, have a new mindset. >> Yeah, so NetApp, a storage company, right? They store bits, retrieve bits. Not so much. They spent a hour on stage yesterday, even before they talked about any products, any architectures, talking about the value of data. Data is the ... And John, you've talked about data for as long as I've known you. Data is the number one asset of any company and NetApp focused not on storage, not on arrays, not on how fast the speeds and feeds go, but the value of data and extracting that value from your subsystems and then going into the conversation around how NetApp can assist in that journey in leveraging data. >> Okay, we're going to kickoff Day One coverage with NetApp Insight 2017 here on theCUBE. Changing the world with data. That is the focus, that is the conversation. And that is an aperture, that's the entire world from how you store the data, how to use the data. How do you to put it to work? How do you create value and transformation? This is theCUBE bringing the action here from the Mandalay Bay in Las Vegas for NetApp Insight 2017. Stay with us. We'll be right back with our next guest after this short break. (upbeat techno music)

>> [John} Hello everyone and welcome to Special Cube Presentation here in Paolo Alto, I'm John Furrier at Silicon Angle, a Special Presentation with Druva. The data protection space is being disrupted big time with a lot of venture capital investment, almost 250 million dollars invested this quarter, in data protection, it's certainly disrupting the Cloud game, we had a great line-up of experts, and thought leaders here, to talk about the news from Druva, and the impact to the industry around digital transformation and my first guest is Jaspreet Singh, who's the CEO and Founder of Druva, great to see you again. >> Good morning John, good to see you again. >> Digital transformation is accelerating, data protection is being disrupted, millions of dollars are coming in, you guys are playing a role, what is the role that Druva's playing, in the digital transformation acceleration? >> Absolutely, to think about the world, right, you think of companies like Domino's or Tesla, the thing that software companies, right, they deliver, the server they should deliver via software of, a software approach of the traditional business model, in the heart of this transformation of enterprises becoming softed and digitalized, is data at the core. And data today, will outlive most systems, and the more and more fragmented their approach to data becomes, you store data on prem, in the Cloud, everywhere in between, the data management has to become more and more centralized, so Druva is in the core of this transformation, making it a data transformation, and making sure the data architects of the future, have a better approach of manageability and protection, with the Druva platform. >> You guys had a busy month this month, you got a couple of big news we're going to be talking about today, funding and next generation platform, walk us through that. >> Absolutely, so we have two big news to announce today, the first one being 80 million dollars of capital raised, led by Riverwood Capital followed by most other investors, including Sequoia, excellent Tenaya Capital, and then the number two, being we're announcing a whole new Druva Cloud platform, which wholistically takes our entire product portfolio and puts it together in a nice, simplistic approach to manage an entire information workload in a single platform in the Cloud. >> 80 million is a lot of funding, that brings you up to 200? >> 200 our total capital raised, it's a great validation for the market, it's a great validation for the Druva product portfolio, and great validation for customers who have trusted Druva so far, to put us towards one of the top, I think, no more than 10 Start-ups have raised capital more than 200 million dollars, in our space, so it's a great place to be, to be here today. >> Talk about the data, as a service, the data management as a service that you guys are doing, on the Druva Cloud platform, how does that solve the customer problems, how does that relate to the growth and Cloud and specifically, private Cloud, or true private Cloud, wherever that you want to slice that out, this is a new segment, talk about that. >> Absolutely, so there's a lot of Cloud washing in the market, about the Cloud data management prediction, the whole nine yards, but eventually, for us, the Cloud is not a technology, it's a business model. When you service the customer, as a predictable assailer across the globe, at a predictable price point, it is consistent throughout the world, right, it's how you build your products, how you build security around it, how you think of the customer experience as the central focal point, of everything you do, and how you drive innovation with customers, you know, and then adopting the product going forward. And then also how you build your ecosystem of partners, and your resellers to sort of adopt this whole motion of servicing a customer, managing data, all in the Cloud, and the core of the innovation is the fact that the more and more data gets decentralized, the more and more centralized the data management has to be, and today Cloud solves great a pain point there by offering simplicity of data management, and offering an assailer, a predictable assailer which the world really needs for data management service, and the hardware, software part of the world, is very, very hard to deliver. >> And what do you guys do specifically that solves that problem and helps in that area? >> So today, Druva delivers a end-to-end platform, this platform you know, think of a traditional enterprise which had to buy a, you know data management was a complicated beast, you had to had a backup play, a archival play, a DR play, eDiscovery play, and for each of these technologies, the solution you had to buy a hardware, a software, a tiering solution like a tape or a cloud, or you had to buy services, and then piecemeal them together. You know, as you have more and more regulations, and you have more and more demands on the data, as data is becoming your new oil of economy, you want to put them together in a way that they talk to each other, not disturb the workflows with the department and the people involved, and managing it as the same data, so Druva does is builds a, it offers a very wholistic platform, a scalable, simple platform on the Cloud, which puts together these multiple workloads of back up DR, archival eDiscovery governance, into a single platform, purely deliver a service without any dedicated hardware or software needed to manage an entire data landscape, with end point servers or cloud data. >> 80 million is a lot of financing, congratulations, great validation to you, by the way and you guys had good funding all along the way, because of this new, fresh financing, how does that change or does it change your competitive position and how do you guys compare from the other Cloud data management companies, we hear about, I mean, there's a lot of people out there, trying to attack this area, how do you guys compare and what's the differentiation? >> I think our differentiation still goes back to the same thesis, our core thought process being that, secondary data or your data management has to live purely in the Cloud, not on appliance, not a software, and Cloud is not a graveyard, you know, where you can just dump your data, and call it Cloud, it's a way for you to store data, use it wholistically, not just for protection, but governance and even for the intelligence. This funding helps us establish ourselves even better in the marketplace, proves validates to your point, our position in the market and you know, as I think of my years being an entrepreneur, of capital is critical for growth, it doesn't replace creativity, so we still have to focus on our core innovation of global market, but funding truly helps in building a firm foot forward in the market. >> Take a minute to describe what the Druva Cloud platform is, and how that address some of these next generation challenges, that are out there. >> So think of Druva Cloud as an Amazon marketplace, an Amazon service console for data management, right, when you think of offer tips to five on Amazon, you think of an experienced to manage your productivity, or in general, enterprise IT, or on the Cloud, the build up management was a piecemeal approach of putting together a software and a hardware together and experience was broken because of so many moving parts. We deliver pure social experience on the Cloud, which not only integrates the front end of, you know, being a simple interface to look at back-up or DR for all your workload, we're also a simplistic way of searching for workloads and you'll see a demo today, in the session of how you can interact with data by simple search, to show you not just the workflow, but the documentation behind it and the whole nine yards. But wholistically, behind the you know, there's a great saying, saying that the complexes compete in, but simple is genius, right, so to make it really simple, behind the whole, the Druva console, is a consolidated or a completely integrated data platform, which lets you take a wholistic approach of storing and managing information all in the Cloud, which is wrapped around security or rather paradigms to really make sure that it's a end-to-end delivered servers and experience, versus just a software wrapped around a legacy hardware approach. >> With the Druva Cloud platform, can organizations embrace more data protection? >> Absolutely, so simplicity is still key to it, right, data management is still something which helps you take care of your data risks and which is pretty pertinent to any organization, with a simple and scalable approach, with a predictable assailer, more organizations can trust Cloud with the corporate data, and they will be more pertinent to pay as you go for a data management play than building a hardware and software story, spending all the money upfront, which we believe will increase adoption, increase trust, in their own data and the Cloud. >> When will the Druva Cloud platform be available? >> So, today we're going a technical preview, for our most important customers, they get to play with it, and give us their feedback of how they feel about it, you know, we're integrating multiple parts, and instilling the feedback around how we can involve giving them more and more control and visibility, we expect a general availability for most of our customers by end of the year. >> Congratulations on the financing, it's a great validation, we'll give you the final word on this segment, to just share with the folks that are watching, what they should squint through all the news, and what does it mean to them, what's the impact of this announcement, these announcements? >> I think a couple of years ago, there's a massive transformation on the primary storage, where you know the EMCs of the world, were vulnerable and so came re-tan excel pure, right, now the whole backlash is going to be on the secondary storage, where the bigger, much bigger market on secondary data and storage, is a lot more vulnerable by the big players, still showing a lot of weakness, and Cloud is a great story here where a very complex solution can be delivered, with the wholistic and simplistic approach, so there's a great time in the market for us to innovate, it's a great time when the customers to trust the Cloud and get a great story all from Druva or other players, purely in the Cloud, and great time for entrepreneurs like us to execute and bring a cutting edge solution to the market. >> We have a lot more to drill down on, thanks so much, and congratulations on your success. >> Thank you. >> Thanks for sharing.

>> Commentator: Live from San Jose, California. It's theCUBE covering Big Data Silicon Valley 2017. >> Okay, welcome back everyone. We are here live in Silicon Valley for Big Data SV (mumbles) event in conjunction with Strata + Hadoop. Our companion event, the Big Data NYC and we're here breaking down the Big Data world as it evolves and goes to the next level up on the step function, AI machine learning, IOT really forcing people to really focus on a clear line of the side of the data. I'm John Furrier with our announcer from Wikibon, George Gilbert and our next guest, our two executives from Trifacta. The founder and Chief Strategy Officer, Joe Hellerstein and Adam Wilson, the CEO. Guys, welcome to theCUBE. Welcome back. >> Great to be here. >> Good to be here. >> Founder, co-founder? >> Co-founder. >> Co-founder. He's a multiple co-founders. I remember it 'cause you guys were one of the first sites that have the (mumbles) in the about section on all the management team. Just to show you how technical you guys are. Welcome back. >> And if you're Trifacta, you have to have three founders, right? So that's part of the tri, right? >> The triple threat, so to speak. Okay, so a big year for you guys. Give us the update. I mean, also we had Alation announce this partnering going on and some product movement. >> Yup. >> But there's a turbulent time right now. You have a lot of things happening in multiple theaters to technical theater to business theater. And also within the customer base. It's a land grand, it seems to be on the metadata and who's going to control what. What's happening? What's going on in the market place and what's the update from you guys? >> Yeah, yeah. Last year was an absolutely spectacular year for Trifacta. It was four times growth in bookings, three times growth in customers. You know, it's been really exciting for us to see the technology get in the hands of some of the largest companies on the planet and to see what they're able to do with it. From the very beginning, we really believed in this idea of self service and democratization. We recognize that the wrangling of the data is often where a lot of the time and the effort goes. In fact, up to 80% of the time and effort goes in a lot of these analytic projects and to the extent that we can help take the data from (mumbles) in a more productive way and to allow more people in an organization to do that. That's going to create information agility that that we feel really good about and there are customers and they are telling us is having an impact on their use of Big Data and Hadoop. And I think you're seeing that transition where, you know, in the very beginning there was a lot of offloading, a lot of like, hey we're going to grab some cost savings but then in some point, people scratch their heads and said, well, wait a minute. What about the strategic asset that we were building? That was going to change the way people work with the data. Where is that piece of it? And I think as people started figuring out in order to get our (mumbles), we got to have users and use cases on these clusters and the data like itself is not a used case. Tools like Trifacta have been absolutely instrumental and really fueling that maturity in the market and we feel great about what's happening there. >> I want to get some more drilled out before we get to some of these questions for Joe too because I think you mentioned, you got some quotes. I just want to double up a click on that. It always comes up in the business model question for people. What's your business model? >> Sure. >> And doing democratization is really hard. Sometimes democratization doesn't appear until years later so it's one of those elusive things. You see it and you believe it but then making it happen are two different things. >> Yeah, sure. >> So. And appreciate that the vision they-- (mumbles) But ultimately, at the end of the day, that business model comes down to how you organized. Prove points. >> Yup. >> Customers, partnerships. >> Yeah. >> We had Alation on Stephanie (mumbles). Can you share just and connect the dots on the business model? >> Sure. >> With respect to the product, customers, partners. How was that specifically evolving? >> Adam: Sure. >> Give some examples. >> Sure, yeah. And I would say kind of-- we felt from the beginning that, you know, we wanted to turn what was traditionally a very complex messy problem dealing with data, you know, in the user experience problem that was powered by machine learning and so, a lot of it was down to, you know, how we were going to build and architect the technology needed (mumbles) for really getting the power in the hands of the people who know the data best. But it's important, and I think this is often lost in Silicon Valley where the focus on innovation is all around technology to recognize that the business model also has to support democritization so one of the first things we did coming in was to release a free version of the product. So Trifacta Wrangler that is now being used by over 4500 companies, ten of thousands of users and the power of that in terms of getting people something of value that they could start using right away on spreadsheets and files and small data and allowing them to get value but then also for us, the exchange is that we're actually getting a chance to curate at scale usage data across all of these-- >> Is this a (mumbles) product? >> It's a hybrid product. >> Okay. >> So the data stays local. It never leaves their local laptop. The metadata is hashed and put into the cloud and now we're-- >> (mumbles) to that. >> Absolutely. And so now we can use that as training data that actually has more people wrangle, the product itself gets smarter based on that. >> That's good. >> So that's creating real tangible value for customers and for us is a source of very strategic advantage and so we think that combination of the technology innovation but also making sure that we can get this in the hands of users and they can get going and as their problem grows up to be bigger and more complicated, not just spreadsheets and files on the desktop but something more complicated, then we're right there along with them for products that would have been modified. >> How about partnerships with Alation? How they (mumbles)? What are all the deals you got going on there? >> So Alation has been a great partner for us for a while and we've really deepened the integration with the announcements today. We think that cataloging and data wrangling are very complimentary and they're a natural fit. We've got customers like Munich Re, like eBay as well as MarketShare that are using both solutions in concert with one another and so, we really felt that it was natural to tighten that coupling and to help people go from inventorying what's going on in their data legs and their clusters to then cleansing, standardizing. Essentially making it fit for purpose and then ensuring that metadata can roundtrip back into the catalog. And so that's really been an extension of what we're doing also at the technical level with technologies like Cloudera Navigator with Atlas and with the project that Joe's involved with at Berkeley called Ground. So I don't know if you want to talk-- >> Yeah, tell him about Ground. >> Sure. So part of our outlook on this and this speaks to the kind of way that the landscape in the industry's shaping out is that we're not going to see customers buying until it's sort of lock in on the key components of the area for (mumbles). So for example, storage, HD (mumbles). This is open and that's key, I think, for all the players in this base at HTFS. It's not a product from a storage vendor. It's an open platform and you can change vendors along the way and you could role your own and so on. So metadata, to my mind, is going to move in the same direction. That the storage of metadata, the basic component tree that keeps the metadata, that's got to be open to give people the confidence that they're going to pour the basic descriptions of what's in their business and what their people are doing into a place that they know they can count on and it will be vendor neutral. So the catalog vendors are, in my mind, providing a functionality above that basic storage that relates to how do you search the catalog, what does the catalog do for you to suggest things, to suggest data sets that you should be looking at. So that's a value we have on top but below that what we're seeing is, we're seeing Horton and Cloudera coming out with either products re opensource and it's sort of the metadata space and what would be a shame is if the two vendors ended up kind of pointing guns inward and kind of killing the metadata storage. So one of the things that I got interested in as my dual role as a professor at Berkeley and also as a founder of a company in this space was we want to ensure that there's a free open vendor neutral metadata solution. So we began building out a project called Ground which is both a platform for metadata storage that can be sitting underneath catalog vendors and other metadata value adds. And it's also a platform for research much as we did with Spark previously at Berkeley. So Ground is a project in our new lab at Berkeley. The RISELab which is the successor to the AMPLab that gave us Spark. And Ground has now got, you know, collaboratives from Cloudera, from LinkedIn. Capital One has significantly invested in Ground and is putting engineers behind it and contributors are coming also from some startups to build out an open-sourced platform for metadata. >> How old has Ground been around? >> Joe: Ground's been around for about 12 months. It's very-- >> So it's brand new. How do people get involved? >> Brand new. >> Just standard similar to the way the AMPLab was? Just jump in and-- >> Yeah, you know-- >> Go away and-- >> It comes up on GitHub. There's (mumbles) to go download and play with. It's in alpha. And you know, we hope we (mumbles) and the usual opensource still. >> This is interesting. I like this idea because one thing you've been riffing on the cue ball of time is how do you make data addressable? Because ultimately, you know, real time you need to have access to data really really low (mumbles) to see the inside to make it work. Hence the data swamp problem right? So, how do you guys see that? 'Cause now I can just pop in. I can hear the objections. Oh, security! You know. How do you guys see the protections? I'd love to help get my data in there and get something back in return in a community model. Security? Is it the hashing? What's the-- How do you get any security (mumbles)? Or what are the issues? >> Yeah, so I mean the straightforward issues are the traditional issues of authorization and encryption and those are issues that are reasonably well-plumed out in the industry and you can go out and you can take the solutions from people like Clutter or from Horton and those solutions have plugin quite nicely actually to a variety of platforms. And I feel like that level of enterprise security is understood. It's work for vendors to work with that technology so when we went out, we make sure we were carburized in all the right ways at Trifacta to work with these vendors and that we integrated well with Navigator, we integrated with Atlas. That was, you know, there was some labor there but it's understood. There's also-- >> It's solvable basically. >> It's solvable basically and pluggable. There are research questions there which, you know, on another day we could talk about but for instance if you don't trust your cloud hosting service what do you do? And that's like an open area that we're working on at Berkeley. Intel SGX is a really interesting technology and that's based probably a topic for another day. >> But you know, I think it's important-- >> The sooner we get you out of the studio, Paolo Alto would love to drill on that. >> I think it's important though that, you know, when we talk about self service, the first question that comes up is I'm only going to let you self service as far as I can govern what's going on, right? And so I think those things-- >> Restrictions, guard rails-- >> Really going hand in here. >> About handcuffs. >> Yeah so, right. Because that's always a first thing that kind of comes out where people say, okay wait minute now is this-- if I've now got, you know-- you've got an increasing number of knowledge workers who think that is their-- and believe that it is their unalienable right to have access to data. >> Well that's the (mumbles) democratization. That's the top down, you know, governance control point. >> So how do you balance that? And I think you can't solve for one side of that equation without the other, right? And that's really really critical. >> Democratization is anarchization, right? >> Right, exactly. >> Yes, exactly. But it's hard though. I mean, and you look at all the big trends where there was, you know, web one data, web (mumbles), all had those democratization trends but they took six years to play out and I think there might be a more auxiliary with cloud when you point about this new stop. Okay George, go ahead. You might get in there. >> I wanted to ask you about, you know, what we were talking about earlier and what customers are faced with which is, you know, a lot of choice and specialization because building something end to end and having it fully functional is really difficult. So... What are the functional points where you start driving the guard rails in that Ikee cares about and then what are the user experience points where you have critical mass so that the end users then draw other compliant tools in. You with me? On sort of the IT side and the user side and then which tools start pulling those standards? >> Well, I would say at the highest level, to me what's been very interesting especially would be with that's happened in opensource is that people have now gotten accustomed to the idea that like I don't have to go buy a big monolithic stacks where the innovation moves only as fast as the slowest product in the stack or the portfolio. I can grab onto things and I can download them today and be using them tomorrow. And that has, I think, changed the entire approach that companies like Trifacta are taking to how we how we build and release product to market, how we inter operate with partners like Alation and Waterline and how we integrate with the platform vendors like Cloudera, MapR, and Horton because we recognize that we are going to have to be meniacal focused on one piece of this puzzle and to go very very deep but then play incredibly well both, you know, with all the rest of the ecosystem and so I think that is really colored our entire product strategy and how we go to market and I think customers, you know, they want the flexibility to change their minds and the subscription model is all about that, right? You got to earn it every single year. >> So what's the future of (mumbles)? 'Cause that brings up a good point we were kind of critical of Google and you mentioned you guys had-- I saw in some news that you guys were involved with Google. >> Yup. >> Being enterprise ready is not just, hey we have the great tech and you buy from us, damn it we're Google. >> Right. >> I mean, you have to have sales people. You have to have automation mechanism to create great product. Will the future of wrangling and data prep go into-- where does it end up? Because enterprises want, they want certain things. They're finicky of things. >> Right, right. >> As you guys know. So how does the future of data prep deal with the, I won't say the slowness of the enterprise, but they're more conservative, more SLA driven than they are price performance. >> But they're also more fragmented than ever before and you know, while that may not be a great thing for the customers for a company that's all about harmonizing data that's actually a phenomenal opportunity, right? Because we want to be the decision that customers make that guarantee that all their other decisions are changeable, right? And I go and-- >> Well they have legacy systems of record. This is the challenge, right? So I got the old oracle monolithic-- >> That's fine. And that's good-- >> So how do you-- >> The more the merrier, right? >> Does that impact you guys at all? How did you guys handle that situation? >> To me, to us that is more fragmentation which creates more need for wrangling because that introduces more complexity, right? >> You guys do well in that environment. >> Absolutely. And that, you know, is only getting bigger, worse, and more complicated. And especially as people go from (mumbles) to cloud as people start thinking about moving from just looking at transactions to interactions to now looking at behavior data and the IOT-- >> You're welcome in that environment. >> So we welcome that. In fact, that's where-- we went to solve this problem for Hadoop and Big Data first because we wanted to solve the problems at scale that were the most complicated and over time we can always move downstream to sort of more structured and smaller data and that's kind of what's happened with our business. >> I guess I want to circle back to this issue of which part of this value chain of refining data is-- if I'm understanding you right, the data wrangling is the anchor and once a company has made that choice then all the other tool choices have to revolve around it? Is that a-- >> Well think about this way, I mean, the bulk of the time when you talk to the analysts and also the bulk of the labor cost and these things isn't getting the data from its raw form into usage. That whole process of wrangling which is not really just data prep. It's all the things you do all day long to kind of massage these data sets and get 'em from here to there and make 'em work. That space is where the labor cost is. That also means that's spaces were the value add is because that's where your people power or your business context is really getting poured in to understand what do I have, what am I doing with it and what do I want to get out of it. As we move from bottom line IT to top line value generation with data, it becomes all the more so, right? Because now it's not just the matter of getting the reports out every month. It's also what did that brilliant in sales do to that dataset to get that much left? I need to learn from her and do a similar thing. Alright? So, that whole space is where the value is. What that means is that, you know, you don't want that space to be tied to a particular BI tool or a particular execution edge. So when we say that we want to make a decision in the middle of that enables all the other decisions, what you really want to make sure is that that work process in there is not tightly bound to the rest of the stack. Okay? And so you want to particularly pick technologies in that space that will play nicely with different storage, that play nicely with different execution environments. Today it's a dupe, tomorrow it's Amazon, the next day it's Google and they have different engines back there potentially. And you want it certainly makes your place with all the analytic and visualizations-- >> So decouple from all that? >> You want to decouple that and you want to not lock yourself in 'cause that's where the creativity's happening on the consumption side and that's where the mess that you talked about is just growing on the production side so data production is just getting more complicated. Data consumption's getting more interesting. >> That's actually a really really cool good point. >> Elaborating on that, does that mean that you have to open up interfaces with either the UI layer or at the sort of data definition layer? Or does that just mean other companies have to do the work to tie in to the styles? The styles and structures that you have already written? >> In fact it's sort of the opposite. We do the work to tie in to a lot of this, these other decisions in this infrastructure, you know. We don't pretend for a minute that people are going to sort of pick a solution like Trifacta and then build their organization around it. As your point, there's tons of legacy, technology out there. There is all kinds of things moving. Absolutely. So we, a big part of being the decoder ring for data for Trifacta and saying it's like listen, we are going to inter operate with your existing investments and we're going to make sure that you can always get at your data, you can always take it from whatever state its in to whatever state you need to be in, you can change your mind along the way. And that puts a lot of owners on us and that's the reason why we have to be so focused on this space and not jump into visualization and analytics and not jump in to its storage and processing and not try to do the other things to the right or left. Right? >> So final question. I'd like you guys both to take a stab at it. You know, just going to pivot off at what Joe was saying. Some of the most interesting things are happening in the data exploration kind of discovery area from creativity to insights to game changing stuff. >> Yup. >> Ventures potentially. >> Joe: Yup. >> The problem of the complexity, that's conflict. >> Yeah. >> So how does we resolve this? I mean, besides the Trifacta solution which you guys are taming, creating a platform for that, how do people in industry work together to solve that problem? What's the approach? >> So I think actually there's a couple sort of heartening trends on this front that make me pretty optimistic. One of these is that the inside of structures are in the enterprises we work with becoming quite aligned between IT and the line of business. It's no longer the case that the line of business that are these annoying people that they're distracting IT from their bottom line function. IT's bottom line function is being translated into a what's your value for the business question? And the answer for a savvy IT management person is, I will try to empower the people around me to be rabid fans and I will also try to make sure that they do their own works so I don't have to learn how to do it for them. Right? And so, that I think is happening-- >> Guys to this (mumbles) business guys, a bunch of annoying guys who don't get what I need, right? So it works both ways, right? >> It does, it does. And I see that that's improving sort of in the industry as the corporate missions around data change, right? So it's no longer that the IT guys really only need to take care of executives and everyone else doesn't matter. Their function really is to serve the business and I see that alignment. The other thing that I think is a huge opportunity and the part of who I-- we're excited to be so tightly coupled with Google and also have our stuff running in Amazon and at Microsoft. It's as people read platform to the cloud, a lot of legacy becomes a shed or at least become deprecated. And so there is a real-- >> Or containerized or some sort of microservice. >> Yeah. >> Right, right. >> And so, people are peeling off business function and as part of that cost savings to migrate it to the cloud, they're also simplified. And you know, things will get complicated again. >> What's (mumbles) solution architects out there that kind of re-boot their careers because the old way was, hey I got networks, I got apps and stacks and so that gives the guys who could be the new heroes coming in. >> Right. >> And thinking differently about enabling that creativity. >> In the midst of all that, everything you said is true. IT is a massive place and it always will be. And tools that can come in and help are absolutely going to be (mumbles). >> This is obvious now. The tension's obviously eased a bit in the sense that there's clear line of sight that top line and bottom line are working together now on. You mentioned that earlier. Okay. Adam, take a stab at it. (mumbling) >> I was just going to-- hey, I know it's great. I was just going to give an example, I think, that illustrates that point so you know, one of our customers is Pepsi. And Pepsi came to us and they said, listen we work with retailers all over the world and their reality is that, when they place orders with us, they often get it wrong. And sometimes they order too much and then they return it, it spoils and that's bad for us. Or they order too little and they stock out and we miss revenue opportunities. So they said, we actually have to be better at demand planning and forecasting than the orders that are literally coming in the door. So how do we do that? Well, we're getting all of the customers to give us their point of sale data. We're combining that with geospatial data, with weather data. We're like looking at historical data and industry averages but as you can see, they were like-- we're stitching together data across a whole variety of sources and they said the best people to do this are actually the category managers and the people responsible for the brands 'cause they literally live inside those businesses and they understand it. And so what happened was they-- the IT organization was saying, look listen, we don't want to be the people doing the janitorial work on the data. We're going to give that work over to people who understand it and they're going to be more productive and get to better outcomes with that information and that brings us up to go find new and interesting sources and I think that collaborative model that you're starting to see emerge where they can now be the data heroes in a different way by not being the ones beating the bottleneck on provisioning but rather can go out and figure out how do we share the best stuff across the organization? How do we find new sources of information to bring in that people can leverage to make better decisions? That's in incredibly powerful place to be and you know, I think that that model is really what's going to be driving a lot of the thinking at Trifacta and in the industry over the next couple of years. >> Great. Adam Wilson, CEO of Trifacta. Joe Hellestein, CTO-- Chief Strategy Officer of Trifacta and also a professor at Berkeley. Great story. Getting the (mumbles) right is hard but under the hood stuff's complicated and again, congratulations about sharing the Ground project. Ground open source. Open source lab kind of thing at-- in Berkeley. Exciting new stuff. Thanks so much for coming on theCUBE. I appreciate great conversation. I'm John Furrier, George Gilbert. You're watching theCUBE here at Big Data SV in conjunction with Strata and Hadoop. Thanks for watching. >> Great. >> Thanks guys.