>> From the Bellagio Hotel in Las Vegas, it's theCUBE, covering UiPath FORWARD IV, brought to you by UiPath. >> Welcome back to theCUBE, live at the Bellagio in Las Vegas, Lisa Martin, with Dave Vellante, we are with UiPath at FORWARD IV. The next topic of conversation is going to be a good one. And that's because it's automation for good. I've got two guests here joining Dave and me. James Droskoski, strategic account exec at UiPath joins us, and Brian Klochkoff, head of automation at Dentsu. Guys, welcome to the program. >> Yeah, thank you. >> Thanks for having us. >> Yeah. Happy to be here. >> We're going to, we're going to dig into automation for good, which is going to be a really feel good conversation. We're going to get into what you're doing. But Brian, I wanted you to give the audience an overview of Dentsu as an organization. Who are you? What do you guys do? >> Sure. So Dentsu is a large network of advertising agencies. We're about 45,000 people large, $10 billion plus in revenue, going across about 125 markets. So we're a large enterprise advertising media, creative CXM type business. We're really focused on helping to elevate our clients' value when it comes to the value proposition around marketing, advertising, and media. >> So you think about that as a, as a, as a, a business that maybe, you know, it's hard to understand where automation might fit in. On the other hand, it's like a lot of moving parts, a lot of arms and legs. >> Brian: Mm-hmm. So how are you applying automation to the business? >> Sure. So when we first started doing proof of concepts level approaches, we approached things in a traditional, Hey, let's go look at the shared services groups. Why are we having invoice processing delays? Things like that. And we started being a bit more prescriptive and proactive about how we were applying the limited POC budget we had to go after these problems. And we started doing some root cause analysis to understand the interaction between the back office functions and the mid-office functions. And what we uncovered was that we could actually be really good custodians of budget and enable people at the same time by solving for problems at a root cause analysis level. So what I mean by that is maybe an invoice is coming down the pipe, and it's not getting processed because it's missing critical information that could be easily added six processes upstream. So what really helped elevate the conversation that we're having around automation for good and be a catalyst for we're going to talk about a bit later is we just started connecting people from the mid-office to the back office, helping them understand, Hey, if we actually follow a process properly, put the right controls in place with RPA to generate critical data elements on those invoices, Shaler in the back office doesn't have to work the weekends because there's not a pipeline back load of invoices for him to process. So we actually connected those mid-office people with the back office people, and it really drove that human connection to drive the change management within our automation journey. And that's kind of been the crux of what we've wanted to do over the past four years, finding ways to elevate our people's potential by integrating automation and AI into their actual day-to-day work. >> Hmm. So tech for good is a theme that you hear a lot and as a, as a media company, that, that, that kind of, we're not gotcha media, you know, we more want to tell the story of tech athletes, and I think we've done a pretty good job of that over the past decade, but so it goes to tech's under fire constantly, especially big tech. We hear the Facebook hearings today and so forth, but so automation kind of early days, oh, you're going to take away my job. I think generally speaking with the fatigue of Zoom and the perpetual workday, people begin to understand that, Hey, maybe automation is a good thing. But automation for good, what, what is that, James? >> Yeah, well, it's, it's not doing technology for the sake of technology. You know? At the end of the day, when we implement solutions with our customers like Dentsu, it's about, what's the impact, what's the change, what's the benefit? And what's unique about Dentsu is because they've grown through acquisition and there are lots of different companies come together, you have to focus on the people first because there is no one process or one system that we can look and just automate that system or process. So automation for good is about focusing on the people, and how do we take the solutions and the programs and the technologies we have and make an impact so that somebody's day is better. Their, their, their job is better. The process they're doing is easier and they can focus on more of the things that make them different. You know? Specifically as we'll uncover in the conversation, you know, we looked at a program that Dentsu is doing around working with different types of people, as far as people with autism, and what was the impact we could do there? And that's uncovered a journey that we've been together for the last two years around seeing how we can make an impact with those types of folks who might not get the same types of opportunities as everybody else. >> Brian, talk about the, the catalyst for that program at Dentsu a couple years ago. >> Sure. So it goes back to that foundational layer of elevating people's potential. So the testimonial that we had from our own employees around applying automation in meaningful ways to progress their day-to-day came from an employee in the mid-office who said, I didn't go $160,000 in student debt to copy paste stuff from Excel into this proprietary platform that we use for media. And that really resonated with us, as leaders in this space, and with our executive leadership, because there was a gap between what our peoples' skills were and what they were actually doing. They wanted to do Mad Men type stuff. They want it to be the Don Drapers and the Peggy Olsons of our industry. And they were losing that opportunity because we weren't tapping into the skills that they had to drive human centric solutions for our clients. So taking that concept, we looked at the partnerships that we have with our outsourcing providers and Autonomy Works, which we're going to doing a session later tomorrow with the CEO, Dave Friedman, we're going to spend a lot of time talking about how the unique skill sets of that company and those people can actually elevate them to do more tech enabled work, but also enabling our own team to focus on building solutions with the skills that we have by allowing them to use the skills that they have to do the machine learning training of models and things like that, which they really excel at from a detail oriented perspective. And that's not only a feel good story, but it's, it's great for our business because the resources on my immediate team are building product, they're building solutions, and we can rely on an excellent partner in them to help us with the maintenance overhead that we're creating through those solutions. And eventually through automation cloud, driving better outcomes through positive, negative reinforcement within machine learning. >> And there are specific examples with individuals with autism. Correct? >> Correct. That's right. >> Yeah. >> Add some color to that. What is that all about? >> Yeah. Let me tell you a little story. So when, when they first brought the conversation to me, I was terrified because I, the type of work that they were outsourcing was very repetitive rule-based. And I'm like, this is perfect for automate. This is exactly what we automate. I was terrified that the program we were going to work on together was going to eliminate the program. And so I was, you know, cautiously, you know, approached it. >> How ironic. >> Yeah. I was like, Hey, that sounds like a great idea. And I hung up. I was like, oh, how are we going to, how am I going to figure out this one? But through the conversation, and we just started, you know, brainstorming and putting our heads together. What was interesting is because of the way that automations work, as far as being very structured and repetitive, it lends itself well to workers with autism. It's exactly the way they think. And what we actually found after kind of coming up with the collaborative ideas, hey, wait a second. We were already doing these kind of botathon hackathon type programs with the Dentsu employees, teaching them the skills, how to build automations for themselves. What if we kind of modified it and adjusted it to cater to these types of individuals who learn differently, and we have to approach it differently. And we went through the program, we adjusted everything. And what was incredible to see was they thrived with the ability to learn how to work this way. They built things that made them more productive, that created more capacity. They could do more with less now, work with more customers, do more work for, for their, for their customers because they had this almost assistant that was kind of like them. And it was, it was just so rewarding. You know, we talk about, again, what's automation for good all about? It's about that personal reward. >> Brian: Yeah. >> I mean, for me, you know, we didn't sell any more licenses or it wasn't about the commercial transaction. It was about, you know, catering to the segment of the workforce that, first of all, it was very educate, enlightening to me to see how many folks are out there that are unemployed. And I got to meet these first 15 individuals that couldn't have been more amazing and more smart and more diligent and hardworking. And the numbers are something in the lines of between 50% and 90% unemployed because they just don't get the same opportunities as people without autism. It's kind of the world's set up for us. So to know that we could do this kind of program together to go have an impact in this community, was the reward in and of itself. And, you know, we've since been working together on how we continue to expand that, how do we, you know, take that forward and, and bring that everywhere. Cause that's, the end of the day, I think beyond, you know, revenue, this is the stuff that really matters, especially in an organization at Dentsu that this is important. >> Yeah. And I think building on the missed opportunity piece around 50% to 90% being unemployed, that's a missed opportunity for business as well. So those skills are so niche and they're so necessary for us to thrive within an environment that's moving as rapidly as we are. Because we just can't keep pace with the change of feature sets that are being released coupled with maintaining existing solutions that we've built. So it's in cross enabling people to really complement each other's unique skills and strengths based off of strong, true partnership. So it really became a beautiful three-way partnership between Dentsu, Autonomy Works and UiPath that we continue to evolve as UiPath makes additional releases with emerging tech that we're officially hearing about right now. So we have a ton of different ideas of how we can bring that into the fold. And what resonates with us the most is hearing different perspectives on how to apply that coming from that working group. So just a different way of thinking about things and the diversity of thought really resonates with, Hey, are we actually applying this thing the right way? Should we be thinking about this differently? Because you get a lot of yes people, you know, when we come and talk to people about how to apply this technology. And when you have somebody with a different perspective, it's able to help us figure out what our long-term strategy is actually going to look like, by taking advantage of the resources and partnerships that we already have in place. >> In terms of that strategic vision, how do you think this three-way partnership that you mentioned is going to influence that percentage of those, these individuals who are unemployed? What are you, any predictions on how much you can bring that down with automation? >> I think that depends on Dave's staffing plan. But, but the goal is to grow, right? So I mean this, this is a, a startup out of Chicago that has, you know, a healthy amount of staff. But finding ways to apply those skills in new ways with technology that's emerging, the horizon is your, is your end point. Right? And I think with the advent of low-code no-code machine learning coming into this type of a platform, it's, it's only opportunistic. There's only, there's only things ahead of us to do that. We just have to make sure that we train people properly and give them that opportunity because they're going to run with it with the right leadership and those skills. >> Yeah. What's exciting also is, is, you know, what started as an idea and a conversation that's now turned into a pilot program and a little bit of expansion of the stuff we're working on together, we've taken some of the excitement and spread it beyond that now. So we've got partners like ENY and PWC and Revature that are saying, and Special Eastern and Automatic, who helped in the initial program saying, how can we help? What can we do? How can we broaden this? And how can we go out to the larger community and make a bigger impact? So, you know, I think it's exciting. We know, we can see how fast RPA and these types of technologies are causing change. And we've got to make sure that people don't get left behind. Especially, you know, someone as this important part of a segment of a workforce. If we can equip them with these skills to be relevant to their current employers or future employers, I think it's, it's critical. You know, another like moment for me during this process was I took for granted, you know, what working actually means, right? It creates independence for us, right? So you get a job, you get paid and generate income. You have the independence now to go live on your own, provide for yourself. A lot of these individuals, I learned, are still living with their parents because they can't get employment. They don't have that independence that we take for granted. So I think, again, that's the essence of what automation for good is all about, is, is being able to go make an impact like that, to that community. And it's, you know, we talk about cultures and brands and you know, it's also great to work with an organization like Dentsu cause they get it, right? Their product is ideas. It's human capital is their, their main ingredient of what they generate value for their customers. And so be able to take that and help people is just, I think what it's all about. >> You're lucky both to be in a business that the incentives are aligned. >> Yeah. >> You're not in businesses that are designed to appropriate data and push ads in front of our face. >> Yeah. >> In a lot of big companies, it's almost like, okay, we got to do this. I don't mean to overstate this, but we have to do this because we're big and we're rich. >> Yeah. >> And so, and if we don't, we're going to get attacked. >> Yeah. Okay. And it's sort of more like a check, check box and to put somebody in charge of it. >> Yep. >> You know, oftentimes a woman or a person of color. And I shouldn't be negative on that. >> Yeah. >> That's fine. That's good to do. But it just seems like there's a nice alignment with automation. AI could be similar because I mean, AI could be used for really bad. Automation. Okay, it maybe takes, the perception is it takes jobs away, but it's a really nice alignment that you can point at a lot of different initiatives. >> Yeah. >> So I think that's really a fortunate dynamic. >> And that's, you know, that's what defines a partnership, right? It's that alignment of long-term interests that, you know, you make the investments now and the sacrifices now to drive that. It's not just commercial. It's not just transactional. >> Dave: Yeah. >> I mean, we were talking about the opportunities for these types of people and for us as a customer and for UiPath. It's it exists within that AI conversation that you were just talking about >> Dave: Yeah. >> Because from a technical perspective, you want to mitigate as much algorithmic bias within your training models. That's what these people are doing. It's helping to train models much more rapidly and effectively and objectively than we could have done otherwise. And that's, having that as part of our extended partnership within our network is going to accelerate the type of work that we want to do within the releases that we're seeing coming out of this conference. Because we don't have to worry about, oh, well, we've got to focus on tax forms and training the models to notice a signature. Because Autonomy Works has us covered there. They're enabling us to do more. We're enabling them to do a little more. And that's, that's the beauty of this intersection between the partners. >> Brian, I presume you talk with prospective customers of UiPath. And I presume also that you probably looked at some of their competitors. If you think about what differentiates this fast moving company, they talked this morning about the cadence of releases. Woo. Very fast. >> Brian: Yeah, it's a lot. >> Why UiPath for Dentsu? >> UiPath has been a tremendous partner for us since about 2017. And we've been able to move on that journey with UiPath. We've been able to help understand the products roadmaps and move at a similar pace as each other. So we're really lucky in that we have the flexibility as an advertising and media company that we're not beholden to internal audits, external audits, and really defined regulatory bodies. So we made a decision, I don't know what, six, seven months ago to collapse six UiPath on-prem instances and migrate to cloud with the sponsorship of our global CTO and our America CTO, just because it was the right thing to do. And because it would enable this type of partnership with external providers. So being able to move at that similar pace from a release cycle, but also from a feature adoption perspective, it's, it just makes the most sense for us. And we have that liberty to go to go do those things as we need to. >> Yeah. So the move to the cloud, you get, you're able to take advantage much faster. >> Yeah. >> Because what did we hear this morning? You release every six months. >> James: Yep. >> Yes. Which is typical for an on-prem. >> James: Yeah. >> And then, but you got to prepare for that. >> James: Yeah. >> I don't know how many N minus ones you support, but it's not infinite. >> James: Yeah. >> You got to move people along, so people have to prep. Whereas now in the cloud, there's the feature. Boom. >> Yeah. >> So being invested in automation for good topic, it's not, it's about automation for good across people in general, within internally to us and externally to us. For our clients, for our employees, and for our partners. The automation cloud enables that to happen much more seamlessly because we don't have the technical debt in place that requires people to VPN into our network and go through the bureaucracy of security, legal, and privacy. Which we've already done by the way, but those conversations bureaucratically still need to happen. With automation cloud, we're able to spin up Autonomy Works employees in real-time and give them the right set of access to go pursue the use cases that they want to, and that we need them to. So that, that technical debt release that we've experienced through the automation cloud is what's enabling us to do this type of good work. >> That makes sense. A bit more, less friction, obviously greater scale. >> Yeah. >> Easier to experiment. >> Yeah. >> Fail fast. >> We went from 12 separate programs to one program in a matter of a couple of months. >> It was wild. >> Yeah. >> And I imagine you're only really scratching the surface here with what you're doing with automation, that really, the horizon is the limit, as you said. Guys, thank you for joining us, talking about automation for good, what you're doing at Dentsu RPA with autistic adults. There's probably so many other great use cases that will come from this. Guys, we appreciate your time. >> Yeah. >> Yeah, thanks for having us. >> Yeah, thank you. >> Thanks, you guys. >> Awesome. >> For Dave Vellante, I'm Lisa Martin coming to you from Vegas UiPath FORWARD IV. (upbeat music plays)

>> Narrator: From the Bellagio hotel in Las Vegas, it's the Cube, covering UiPath Forward IV, brought to you by UiPath. >> Welcome back to the Cube, live at the Bellagio in Las Vegas. Lisa Martin, with Dave Vellante. We are with UiPath at Forward IV. The next topic of conversation is going to be a good one, and that's because it's automation for good. I've got two guests here joining Dave and me, James Droskoski, Strategic Account Exec at UiPath joins us and Brian Khlochkoff, head of automation at Dentsu. Guys, welcome to the program. >> Yeah. Thank you. >> Thanks for having us. >> Yeah. Happy to be here. >> So we're going to, we're going to to dig into automation for good, which is going to be a really feel-good conversation. We're going to get into what you're doing, but Brian, I wanted you to give the audience an overview of Dentsu as an organization. Who are you, what do you guys do? >> Sure. So Dentsu is a large network of advertising agencies. We're about 45,000 people large, 10 billion plus in revenue, going across for 125 markets. So we're a large enterprise advertising media, creative CXM type business. We're really focused on helping to elevate our clients' value when it comes to the value proposition around marketing, advertising, and media. >> So you think about that as a, as a, as a, a business that maybe, you know, it's hard to understand where automation might fit in. On the other hand, it's like a lot of moving parts, a lot of arms and legs. >> Brian: Hmmm. So how are you applying automation to the business? >> Sure. So when we first started doing proof of concepts level approaches, we approach things in a traditional, hey, let's go look at the shared services groups. Why are we having invoice processing delays? Things like that. And we started being a bit more prescriptive and proactive about how we were applying the limited POC budget we had to go after these problems. And we started doing some root cause analysis to understand the interaction between the back office functions and the mid office functions. And what we uncovered was that we could actually be really good custodians of budget and enable people at the same time by solving for problems at a root cause analysis level. So what I mean by that is even the invoices coming down the pipe, and it's not getting processed because it's missing critical information that could be easily added six processes upstream. So what really helped elevate the conversation that we're having around automation for good and be a catalyst for what we're going to talk about a bit later is, we just started connecting people from the mid office to the back office, helping them understand, hey, if we actually follow process properly, put the right controls in place with RPA to generate critical data elements on those invoices, Shaler in the back office doesn't have to work the weekends because there's not a pipeline backload of invoices for them to process. So we actually connected those mid office people with the back office people, and it really drove that human connection to drive the change management and then our automation journey. And that's kind of been the crux of what we've wanted to do over the past four years, finding ways to elevate our people's potential by integrating automation and AI into their actual day-to-day work. >> Hmm. So tech for good is a theme that you hear a lot and as a, as a media company, that, that, that kind of, we're not gotcha media, you know, we've more want to tell the story of tech athletes, and I think we've done a pretty good job of that over the past decade, but so it goes, tech's under fire constantly. It was basically big tech. We hear the Facebook hearings today and so forth, but so automation kind of early days, oh, you're going to take away my job. I think generally speaking with the fatigue of Zoom and the perpetual workday, people begin to understand that, hey, maybe automation is a good thing, but automation for good, what, what is that, James? >> Yeah, well, it's, it's not doing technology for the sake of technology. You know, at the end of the day, when we implement solutions with our customers like Dentsu, it's about, what's the impact? What's the change? What's the benefit? And what's unique about Dentsu is, because they've grown through acquisition and there are lots of different companies come together, you have to focus on the people first cause there is no one process or one system that we can look and just automate that system or process. So automation for good is about focusing on the people and how do we take the solutions and the programs and the technologies we have, make an impact so that somebody's day is better. Their, their, their job is better. That process are doing is easier and they can focus on more of the things that make them different. You know, specifically as we, we'll uncover in the conversation, you know, we looked at a program that Dentsu is doing around working with different types of people, as far as people with autism and what was the impact we could do there. And that's uncovered a journey that we've been together for the last two years around seeing we can have, we can make an impact with those types of folks who might not get the same types of opportunities that everybody else. >> Brian, talk about the, the catalyst for that program at Dentsu, couple years ago. >> Sure, so it goes back to that foundational layer of elevating people's potential. So the testimonial that we had from our own employees around applying automation, meaningful ways to progress their day to day came from an employee in the mid office who said, I didn't go $160,000 in student debt to copy paste stuff from Excel into this proprietary platform that we use for media. And that really resonated with us as leaders in this space and with our executive leadership, because there was a gap between what our people's skills were and what they were actually doing. They wanted to do Mad Men type stuff. They wanted to be the Don Draper's and the Peggy Olsen's of our industry. And they were losing that opportunity because we weren't tapping into the skills that they had to drive human-centric solutions for our clients. So taking that concept, we looked at the partnerships that we have with our outsourcing providers and Autonomy Works, which we're going to be doing a session later tomorrow with the CEO, Dave Friedman, we're going to spend a lot of time talking about how the unique skill sets of that company and those people can actually elevate them to do more tech-enabled work, but also enabling our own team to focus on building solutions with the skills that we have by allowing them to use the skills that they have to do the machine-learning training of models and things like that, which they really Excel at from a detail-oriented perspective. And that's not only a feel good story, but it's, it's great for our business because the resources on my immediate team are building product, they're building solutions, and we can rely on an excellent partner in them to help us with the maintenance overhead that we're creating through those solutions. And eventually through automation cloud, driving better outcomes through positive, negative reinforcement within machine learning. >> And there's specific examples with individuals with autism, correct? >> Correct. That's right. >> Add some color to that. What is that all about? >> Yeah. Let me tell you a little story. So when, when they first brought the conversation to me, I was terrified because I, the type of work that they were outsourcing was very repetitive rule-based and I'm like, this is perfect for automate. This is exactly what we automate. I was terrified that the program we were going to work on together was going to eliminate the program. And so I was, you know, cautiously, you know, approached it- (Dave laughs) >> How ironic. (laughing) >> I was like, hey, that sounds like a great idea. And I hung up. I was like, oh, how are we going to, how am I going to figure out this one? But through the conversation, and we just started, you know, brainstorming and putting our heads together. What was interesting is, because of the way that automations work, as far as being very structured and repetitive, it lends itself well to workers with autism. It's exactly the way they think and what we actually found after kind of coming up with the collaborative ideas, hey, wait a second. We were already doing these kind of bodathon, hackathon type programs with the Dentsu employees, teaching them the skills, how to build automations for themselves. What if we kind of modified it and adjusted it to cater to these types of individuals who learn differently, we have to approach it differently. And we went through the program, we adjusted everything. And what was incredible to see was they thrived with the ability to learn how to work this way. They built things that made them more productive, that created more capacity. They could do more with less now, work with more customers, do more work for, for their, for their customers because they had this almost assistant that was kind of like them. And it was, it was just so rewarding. You know, we talk about, again, what's automation for good all about? It's about that personal reward. >> Brian: Yeah. I mean, for me, you know, we didn't sell any more licenses or it wasn't about the commercial transaction. It was about, you know, catering to the segment of the workforce that, first of all, it was very educate, enlightening to me to see how many folks are out there that are unemployed. And I got to meet these first 15 individuals that couldn't have been more amazing and more smart and more diligent and hardworking, and that the numbers are something in the lines of between 50% and 90% unemployed because they just don't get the same opportunities as people without autism. It's kind of the world's set up for us. So to know that we could do this kind of program together to go have an impact in this community, was the reward in and of itself. And, you know, we've since been working together on how we continue to expand that, how do we, you know, take that forward and bring that everywhere? Cause that's the end of the day, I think beyond, you know, revenue, this is the stuff that really matters, especially in an organization at Dentsu that, this is important. >> Yeah. And I think building on the missed opportunity piece around 50% to 90% being unemployed, that's a missed opportunity for business as well. So those skills are so niche and they're so necessary for us to thrive within an environment that's moving as rapidly as we are, because we just can't keep pace with the change of feature sets that are being released, coupled with maintaining existing solutions that we've built. So it's in cross enabling people to really compliment each other's unique skills and strengths based off of strong, true partnership. So it really became a beautiful three-way partnership between Dentsu, Autonomy Works and UiPath that we continue to evolve as UiPath makes additional releases with emerging tech that we're officially hearing about right now. So we have a ton of different ideas that we can bring that into the fold. And what resonates with us the most is hearing different perspectives on how to apply that coming from that working group. So just a different way of thinking about things and the diversity of thought really resonates with, hey, are we actually applying this thing the right way? Should we be thinking about this differently? Cause you get a lot of, yes, people, you know, when we come and talk to people about how to apply this technology and when you have somebody with a different perspective, it's able to help us figure out what our long-term strategies are actually going to look like, but taking advantage of the resources and partnerships that we already have in place. >> In terms of that strategic vision, how do you think this three-way partnership that you mentioned is going to influence that percentage of those, these individuals who are unemployed? What are you, any predictions on how much you can bring that down with automation? >> I think that depends on Dave's staffing plan. (James laughs) But, but the goal is to grow, right? So I mean this, this is a, a startup out of Chicago that has, you know, a healthy amount of staff, but finding ways to apply those skills in new ways with technology that's emerging, the horizon is your, is your end point. Right? And I think with the advent of low-code no-code machine-learning, coming into this type of a platform, it's, it's only opportunistic, there's only, there's only things ahead of us to do that. We just have to make sure that we train people properly and give them that opportunity cause they're going to run with it with the right leadership and those skills. >> Yeah. What, what's exciting also is, is, you know, what started as an idea and a conversation that's now turned into a pilot program and a little bit of expansion of the stuff we're working on together, we've taken some of the excitement and spread it beyond that now. So we've got partners like ENY and PWC and Revature that are saying, and Specialisterne and Automattic who helped in the initial program saying, how can we help? What can we do? How can we broaden this and how can we go out to the larger community and make a bigger impact? So, you know, I think it's exciting. We know we can see how fast RPA and these types of technologies are causing change. And we got to make sure that people don't get left behind. Especially, you know, someone as this important part of a segment of a workforce. If we can equip them with these skills to be relevant to their current employers or future employers, I think it's, it's critical. You know, another like, moment for me during this process was, I took for granted, you know, what working actually means, right? It creates independence for us, right? So you get a job, you get paid and generate income. You have the independence now to go live on your own, for, provide for yourself. A lot of these individuals, I learned are still living with their parents because they can't get employment. They don't have that independence that we take for granted. So I think, again, that's the essence of what automation for good is all about is, is being able to go and make an impact like that, to that community. And it's, you know, we talk about cultures and brands and, you know, it's also great to work with an organization like Dentsu cause they get it, right? Their product is ideas. It's human capital is their, their main ingredient of what they generate value for their customers. And so be able to take that and help people is just, I think what it's all about. >> You're lucky both to be in a business that the incentives are aligned. >> Yeah. >> You're not in businesses that are designed to appropriate data and push ads in front of our face or- >> James: Yeah. >> And a lot of big companies, It's almost like, okay, we got to do this. I mean, I don't mean to overstate this, but we have to do this because we're big and we're rich. >> James: Yeah. >> And so, and if we don't, we're going to get attacked. >> James: Yeah. >> Okay, and some of it, I can check, check box and to put somebody in charge of it. >> James: Yep. >> You know, often times a woman or a person of color. And I shouldn't be negative on that. >> James: Yeah. That's fine. That's good to do. But it just seems like there's a nice alignment with automation. >> James: Oh. >> AI could be similar because I mean, yeah. It can be used for really bad. Automation, okay, maybe takes, the perception is that it takes jobs away, but it's a really nice alignment that you can point at a lot of different initiatives. >> Yeah. >> So I think that's really a fortune- >> I know that's, that's what defines a partnership, right? It's that alignment of long-term interests that, you know, you make the investments now and the sacrifices now to drive that. It's not just commercial. It's not just transactional. >> Dave: Yeah. >> We were talking about the opportunities for these types of people and for us as a customer and for UiPath, it's, it exists within that AI conversation that you were just talking about. >> Dave: Yeah. >> Because from a technical perspective, you want to mitigate as much algorithmic bias within your training models. That's what these people are doing. It, it's helping to train models much more rapidly and effectively and objectively than we could have done otherwise. And that's, having that as part of our extended partnership within our network is going to accelerate the type of work that we want to do within the releases that we're seeing coming out of this conference because we don't have to worry about oh, well, we got to focus on tax forms and training the models to notice a signature because Autonomy Works has us covered there. They're enabling us to do more. We're enabling them to do a little more. >> Hmmm. And that's, that's the beauty of this intersection between the partners. >> Brian, I presume you talk with prospective customers of UiPaths. And I presume also that you probably looked at some of their competitors. If you think about what differentiates this fast-moving company, they talked this morning about the cadence that releases. Whew, very fast. (laughing) >> Brian: Yeah, that's a lot. >> Why UiPath for Dentsu? >> UiPath has been a tremendous partner for us since about 2017. And we've been able to move on that journey with UiPath. We've been able to help understand the product roadmaps and move at a similar pace as each other. So we're really lucky in that we have the flexibility as an advertising and media company that we're not beholden to internal audits, external audits, and really defined regulatory bodies. So we made a decision, you know, what, six, seven months ago to collapse six UiPath on-prem instances and migrate to cloud with the sponsorship of our global CTO and our Amaris CTO, just because it was the right thing to do. And because it would enable this type of partnership with external providers. So being able to move at that similar pace from a release cycle, but also from a feature adoption perspective, it's, it just makes the most sense for us. And we have that liberty to go to go do those things as we need to. >> Yeah, so the move to the cloud, you get, you're able to take advantage much faster- >> James: Yeah. >> Because what did, what did we hear this morning? You release every six months? >> James: Yep. >> Yes. Which is typical for an on-prem. >> James: Yeah. >> And then, but you got to prepare for that. >> James: Yeah. I don't know how many N minus ones you support, but it's not infinite. >> James: Yeah. >> You got to move people along. So people have to prep, whereas now in the cloud, there's the feature, boom. >> Oh yeah. So being investing automation for good topic, it's not, it's about automation for good across people in general, within internally to us and externally to us, for our clients, for our employees and for our partners. The automation cloud enables that to happen much more seamlessly because we don't have the technical debt in place that requires people to VPN into our network and go through the bureaucracy of security, legal, and privacy, which we've already done by the way, for those conversations, bureaucratically still needs to happen. With automation cloud, we're able to spin up autonomy Works employees in real time and give them the right set of access to go pursue the use cases that they want to, and that we need them to. So that, that technical debt release that we've experienced through the automation cloud is what's enabling us to do this type of good work. >> It makes sense. A bit more, less friction, obviously, greater scale. >> Yeah. >> Easier to experiment. >> Yeah. >> Fail fast. >> We went from 12 separate programs to one program in a matter of a couple of months. >> It was wild. (Brian laughs) >> And I imagine you're only really scratching the surface here with what you're doing with automation. That really the horizon is the limit as you said. Guys, thank you for joining us, talking about automation for good. What you're doing at Dentsu RPA with autistic adults, there's probably so many other great use cases that will come from this. Guys, we appreciate your time. >> Yeah. >> Thanks for having us. Thank you. >> Thanks you guys, awesome. >> For Dave Vellante, I'm Lisa Martin coming to you from Vegas, UiPath forward IV. [light-hearted music plays]

>>Hello, everyone. This is not appropriate to lapse of America. I'm going to talk about the motivation. For zero knowledge goes back to the heart off, winding down identity, ownership, community and control. Much of photography exists today to support control communications among individuals in the one world. We also consider devices as extensions of individuals and corporations as communities. Here's hoping you're not fit in this picture. What defines the boundary off an individual is the ability to hold a secret with maybe, it says, attached to the ownership. Off some ethic, we want the ability to use the secret to prove ownership of this asset. However, giving up the secret itself essentially announced ownership since then, anybody else can do the same. Dear Knowledge gives us tools to prove ownership without revealing the secret. The notion of proving ownership off a digital object without revealing it sounds very paradoxical outside the model off. So it gives us a surprise when this motion was formalized and constructed by Goldwasser Miccoli and back off in the late eighties, we'll focus on the non interactive >>version of Siri, a knowledge our music in the >>stock, which was first developed by blow Tillman and Peggy, where the general it can span multiple rounds of communications music only allows a single message to be trusted. No, let's get into some technical details for musics. The objective of for music is to show that an object X, which you can think off as the public footprint, often asset, belonging clan and the language without revealing its witness. W, which you can think off as the Future Analytics team consists off three algorithms, video proof and very. The key generation process is executed by a trusted third party and the very opposite, resulting in a common >>random string, or steers, which is made public. The >>true vendor produces a proof by based on the CIA's X and the very fine with the checks. The proof against X and accepts or rejects music off course has to satisfy some properties. We needed to be correct, which basically says that when everyone follows the protocol correctly on, so we can expect, we need to be thought, which says that a false statement cannot be proven. The channel is a trickier properly to form this. How do we capture the intuition behind saying that the proof there is no knowledge of the witness. One way to capture that is to imagine their tools is the real world where the proof is calculated. Using the witness on there's a simulation worth where the proof is calculated without a witness. To make this possible, the simulator may have some extra information about the CIA's, which is independent off the objectives. The property then requires that it is not possible to effectively distinguish these words Now. It is especially challenging to construct music's compared to encryption signature schemes, in particular in signature schemes. The analog off the Hoover can use a secret, and in any case, the analog off the very fire can use a secret. But in is it's none of the crew layer and the verifier can hold a secret. Yeah, in this talk, I'm going to focus on linear subspace languages. This class is the basis of hardness. >>Assumptions like GH and deliver >>on has proved extremely useful in crypto constructions. This is how we express DD it and dealing as linear software. We will use additive notation on express the spirit logs as the near group actions on coop elements. You think the syntax we can write down Deitch on dealing Jupiter's very naturally a zoo witness sector times a constant electric so we can view the language as being penetrated by a constant language. Metrics really was hard by many groups in our instructions. What does it mean? S while uh, Standard group allows traditions and explain it off by in your group also allows one modification In such groups, we can state various in yourself facing elections. The DDN is the simplest one. It assumes that sampling a one dimensional space is indistinguishable from something full professional. The decisional linear assumption assumes the theme from tours is three dimensional spaces generalizing the sequence of Presumptions. The scaling the resumption asks to distinguish between gay damaged examples and full it and >>examples from a K plus one national space. >>Right, So I came up with a breakthrough. Is the construction in Europe 2008 in particular? There? Music for many years Off Spaces was the first efficient >>construction based on idiots and gear. Structurally, >>it consisted of two parts Our commitment to the witness Andre question proof part and going how the witness actually corresponds to the object. The number of elements in the proof is linear in the number >>of witnesses on the number of elements in the object. >>The question remains to build even shorter visits. The Sierras itself seemed to provide some scoop Rosa Russo fix. See how that works for an entire class of languages? Maybe there's a way to increase proof efficiency on the cost of having had Taylor Sierra's for each year. This is what motivates quality and after six, where we let the solace depend on the language itself. In particular, we didn't require the discrete logs of the language constants to generate this, Yes, but we did require this constant student generated from witness sample distributions. This still turns out to be sufficient for many applications. The construction achieved a perfect knowledge, which was universally in the sense that the simulator was independent. However, soundness is competition. So here's how the construction differed from roots high at a very high level, the language constants are embedded into the CIA s in such a way that the object functions as it's only so we end up not needing any separate commitment in the perfect sense. Our particular construction also needed fewer elements in the question proof, as there On the flip side, the CIA's blows up quadratic instead of constant. Let's get into the detail construction, which is actually present with this script. Let the language apparently trace by Giovanni tricks with the witness changing over time, we sat down and matrices >>D and B with appropriate damages. >>Then we construct the public series into what C. S. D is meant to be used. By the way. On it is constructed by >>multiplying the language matrix with D and being worse, Sierra's V is the part that is meant to be used by the very fair, and it is constructed using details be on be embedded in teaching. >>Now let's say you're asked to computer proof for a candidate X with fitness number we computed simply as a product of the witness with CSP. The verification of the truth is simply taking with the pairing off the candidate and the proof with the Sierras. Seeming threats is equal to zero. If you look carefully. Sierra's V essentially embedded in G to the kernel of the Matrix, owned by the language metrics here and so to speak. This is what is responsible for the correctness. The zero knowledge property is also straightforward, >>given the trapdoor matrices, D and B. Now, >>when corrected journalism relatively simple to prove proving illnesses strictly The central observation is that, given CSP, there is still enough entropy. >>India and me to >>random I seriously in particular Sierra's we Can we expand it to have an additional component with a random sample from the kernel allows it. This transformation is purely statistical. No, we essentially invented idiots are killing their talent in the era of kernel part in this transform sitting within show that an alleged proof on a bad candidate and we used to distinguish whether a subspace sample was used for a full space >>sample was used at the challenge. The need >>to have the kernel of the language in this city. That's the technical >>reason why we need the language to come from a witness. Sample. >>Uh, let's give a simple illustration >>of the system on a standard Diffie Hellman, which g one with the hardness assumption being idiot. >>So the language is defined by G one elements small D, E and F, with pupils off the phone due to the W. After that ugly, the CIA is is generated as follows example D and >>B from random on Compute Sierra speak as due to the day after the being verse and Sierra's V as G to do to do the big on day two of the video. The >>proof of the pupil >>detail that I do after the bill is computed using W. As Sierra Speed race to the party. I know that this is just a single element in the group. The verification is done by bearing the Cooper and the proof with the Sierras VMS and then checking in quality. The >>similar can easily compute the proof using trapdoors demand without knowing that what we are expecting. People leave a Peter's die and reduce the roof size, the constant under a given independent of the number of witnesses and object dimensions. Finally, at Cryptocurrency 14 we optimize the proof toe, one group >>element under the idiots. In both the works, the theorists was reduced to linear sites. The >>number of bearings needed for ratification was also industry in years. This is the crypto Ford in construction in action, the construction skeleton remains more or less the famous VR turkey. But the core observation was that many of the Sierras elements could were anomaly. Comite. While still >>maintaining some of this, these extra random items are depicted in red in this side. >>This round of combination of the Sierras elements resulted in a reduction of boat, Bruce says, as also the number of clearings required for education in Europe in 2015 kills, and we came up with a beautiful >>interpretation of skill sets based on the concept of small predictive hash functions. >>This slide is oversimplified but illustrated, wanting, uh, this system has four collecting >>puzzle pieces. The goodness of the language metrics okay again and a key Haider when >>the hidden version of the key is given publicly in the Sears. Now, when we have a good object, the pieces fit together nicely into detectable. However, when we have a bad object, the pieces no longer fit and it becomes >>infeasible to come up with convincing. Zero knowledge is demonstrable by giving the key to the simulator on observing that the key is independent of the language metrics. >>Through the years, we have extended >>enhanced not mind to be six system, especially with our collaborators, Masayuki Abby Koko Jr. Born on U. >>N. Based on your visits, we were able to construct very efficient, identity based encryption structure, resulting signatures >>public verifiable CCS, secure encryption, nine signatures, group signatures, authorities, key extremes and so on. >>It has also been gratifying to see the community make leaps and bounces ideas and also use queuing visits in practical limits. Before finishing off, I wanted to talk to you a little bit about >>some exciting activities going on Hyper ledger, which is relevant for photographers. Hyper >>Leisure is an open source community for enterprise. Great. It's hosted by the minute formation on enjoys participation from numerous industry groups. Uh, so difficult funded to efforts in Africa, we have versa, which is poised to be the crypto home for all. Blocking it and practice a platform for prospecting transactions are part of the legs on the slide here, >>we would love participation from entity inference. So >>that was a brief history of your analytics. Thanks for giving me the opportunity. And thanks for listening

live from San Francisco it's the queue covering micron insight 2019 back to you by micron welcome back to micron insight 2019 in San Francisco you watching the cube the leader and live tech coverage we're wrapping up our day Dave Volante with David Floria we're Kia Jones is here she's the senior principal for 5g connectivity in the GPM group at Microsoft great to see you great to see you guys it's been a wonderful day yeah nice job up on stage today you know we're gonna talk a little bit about a 5g and get your perspectives on it but tell us more about your group and sort of what you focused yeah well you know I'm in Azure and azure is even though it's our cloud infrastructure there has to be a lot of backbone support so inside of networking we have all those components that would support the physical structure of cloud technology so we focus on virtualizing a lot of the different managed services that we have and we provide those to customers for scalability and sustainable models that allow them to pretty much transport data safely what's it like inside of Microsoft these days I mean what a transformation of the company I did a little segment on LinkedIn the other day a little video segment there's a lot of ways if you want to spend some money there's a lot of ways to spend money with Microsoft you know you got cloud you got an application management you got security you got all the abs I mean really is you're hitting on all cylinders it's what a dynamic what's it like inside of there these days you know I think I think the world now is very different I see Microsoft making a huge transformation over the last have only been there three years but what I can say to you is that I see that the opportunity is there for partnership now which is something that I don't think we focused on we did too well in the past with our new CEO Satya Nadella and Peggy Johnson who leads our business development I mean we are really taking the the game and just changing and and making making it more something that we can do with everyone instead of in silo and so the culture is definitely changing is their opportunity yeah but I think our company is dedicated and focused on you know creating more diverse technology that can meet two customer's needs all over the yeah I mean windows are still a huge part of Microsoft's business but it's not the future of Microsoft it's very very impressive to see that transformation all right what what should we know about 5g what's Microsoft's put point of view on 5g what's the opportunity for you well that's a great question a lot of people were like Microsoft and 5g how does that work well in the past I think with the telcos and all the communication service providers we've always been either their customer or they've been our customer the new world that we're going into now is how do we help the telcos now be better enablers so that we can accelerate business and so I took over this charter along with my boss Yusuf Khalidi and about a year ago and our vision for what we thought we could do came to really great reality when we understood the the ecosystem that already existed this this business of 5g is not as simple as it sounds so what we decided to do and we released a press release back in July was we're going pretty much all in in a sense with AT&T in helping them with their global strategy for really Wireless you know to help stabilize their wireless network and combine some software-defined principles and capabilities so what they're they're already planning for in the future so I think with that transformation honestly a lot of it is unknown but we're taking a day by day we're talking earlier about a lot of is unknown in terms of like what apps are going to emerge who's gonna pay for what but but there's a lot of hype around 5g certainly a lot of folks in the technology community you're excited about it yeah help us understand what's real and what's not what's hype and what sort of things that users can actually expect and then I want to know exact months and you know what I think if you can imagine it it's a possibility I think it all boils down to the type of partnerships I always say that it's the power of three in the sense in the past has always been the power of two where two companies come together we can make it work well now you need you need an extra component not only do you need a company like Microsoft but you need to tell Co but you're going to need a system integrator right and I'm not talking about the hardware side but more of the software application side I think if a lot of people talking about like these things we know that smart city we think that's a possibility real soon mmm I still think we got it way to go with a lot of the townships and the city infrastructures moving so slow with governmental policies changing I think that we can likely see improvement in connected vehicles connected you know Internet of Things in and if everything is coming we first must be able to connect the dots with those things first before we actually bring in a government entity I think they have a lot of questions that we're not yet ready to answer and so I think there's a lot of great need for POCs and that's what my team focuses on inside of Azure networking he's looking at what can be the next PLC where we can help truly define the next generation requirements you're kind of acting as the accelerant I like the power three analogy a bump set spike yeah right now fashion sports analogies in the cube and then you know you point about I think governments is right on I was saying the earlier to David that I participated in a mayor of Boston as this you know the Smart City future initiative and you're talking 2050 oh yeah you know that's their time horizon I'm trying to figure that that's right around the corner yeah I mean I can't believe we're about to be in the 2020 feels like I just graduated high school when you're looking at these opportunities there seems to be a big divergence of opinion in terms of networking between are you going to push the processing out to the edge and do as much of it possible there and only take the the subset of data from that processing or are you going to bring it in to some sort of center to do do the processing there yeah what are you what are you seeing in your five-year as the models of computer putting together compute storage and networking yeah for me I have a this is rukia's opinion but I think that in the future when we talk about compute we need to be able to chop it up and we need to sell it to individuals individuals could be enterprises or consumer in my world and the way I think about this I think that we have an enormous amount of opportunity to give customers freedom and flexibility if we're not able to give them freedom and flexibility I think that we really limit the possibilities of what truly podgy can bring and so in my world I believe that you should be able to prepay for your computing power I believe that you can literally distribute it among all your devices within your families like you know you have the family rate plans that the telcos are selling well think about this and that family rate plan now there's an additional component that you will sell which will be compute I may not want to go as fast as you like for gaming for instance absolutely right okay gaming for everyone and at the speed of what you need so atomic of components of compute that you can actually assign to individual users applications workloads yeah it's not - you told me tomorrow rookie what do you want to do that's not saying ok so what what are you doing here what's the connection between sort of Microsoft your role and you know this micron insight event micron is a a great partner with with Microsoft I think we do a lot of business as it relates to chips I specifically am here because Peggy Johnson supports the company and she's over our business development operations for the companies and she believes micron is on to something and so I'm proud to be here and getting to know more about the business visit micron and the partnerships that we can create in the future well we more partnerships obviously you need membrane storage to run all this totally do we can do it part of the build-out well Rukia thank you so much for for coming on the cube we'll give you the last word your takeaway is what should we be watching for from you and your group yeah I mean I think that as we go forth with our partnership with AT&T which happens to be one of the global carriers around the world we are planning for some amazing things and we will make announcements at our Microsoft ignite event in early November and so I hope that everyone will attend that event and perhaps support us by sharing the information and coming to talk to us about new partnerships with our clouds networking department great well we'll be there at ignite hope to have you back on that'll be great thank you and thank you everybody thank you David Fleur a great job with the crew which is a wrap from Pier 27 at Microsoft blending Microsoft mega you both say the same names right the insight conference micron inside 2019 check out Silicon angle comm check out the cube net for all the videos and we'll see you next time is Dave Volante for David floor thank you

>> Announcer: Live from San Francisco, it's theCUBE! Covering Informatica World 2017. Brought to you by Informatica. >> Welcome back, everyone. We're live in San Francisco for CUBE's exclusive coverage of Informatica World 2017. I'm John Furrier, SiliconANGLE. Our next guest, Anil Chakravarthy who's the CEO of Informatica, CUBE alumni multiple times, but the chief executive officer leading the charge of a great private company doing very well. Welcome back to theCUBE. >> It's great to be here, John. Thanks very much. >> We've got a couple of things to talk about, but I want to just jump in. Behind us you see the new logo, Informatica. Really kind of the last leg of the stool, if you will, you guys have gone private, >> Yep. >> Great product work over the years. You know I've been pretty complimentary of you guys, although we've had a critical analysis session yesterday. But all the big bets were very well done playing off. You've got a great product team, great leadership team, new CIO hire. But the last leg of the stool is the brand. >> Anil: That's right. >> You guys haven't been showboating much. Now you got to kind of brag and be humble about it and get the word out. New marketing program, what's that all about? >> Yeah that's exactly right. So you just said, the transformation that we are going through, three big steps is the transformation. The product portfolio transformation, we've been talking about that. This is all driven by cloud, by big data, and machine learning, and all of that. Then the transformation of the business model, from license to subscription and cloud services. And now the brand transformation. And we see the brand transformation as actually catching up to where the company actually was. We were just talking about that right before we got started. We actually have done a lot of things. Like for instance, did you know that we are doing 1 trillion transactions a month in the cloud? I mean, very few people knew about that. >> Yeah, what's more impressive on that, I found that out earlier it was 1 billion in January. >> Anil: It's unbelievable. It's-- >> I mean how do you do that? It's a growth hockey stick, straight up. >> It's a hockey stick, it's huge, it's huge growth, and that's driven by the fact that we are the leader in cloud data management for the biggest ecosystems, for Salesforce, for Amazon, for Azure, and that drives a lot of the data volume across the cloud. >> Before we get in the keynotes, on that note, one of the big bets you know I've been very impressed on is the cloud play, right? The data architecture of things, the winning formula. But you got cloud presses, you had Amazon Web Services. Google just announced span or horizontally scalable database, generally available. You were on the of the three data partners on the front end of that. >> Anil: That's correct. >> And part of the launch of Google. >> That's correct, yeah. >> I didn't know that. >> So you know, the way we think of the world is from our customer's perspective. It really is the best way to think about it is as the enterprise cloud. Put it together. All the data you have in the enterprise that you have generated over the years, that's still very valuable data. And then the data you have in the cloud. And you can't think of those two things as separate. For instance, you could have customer data, the same customer. John, you're the customer of a retailer. Some of that data about you is in their on-premises systems, and some of the data may be in a cloud system, but it is all interconnected data and you can't have two separate silos. We believe that we are the only ones that can really manage that. And that's why we are supporting every major cloud platform or cloud system, just like we are supporting every major on-premises system. >> Yeah, you guys call it Switzerland. It was a great way to describe it. But really to me it puts bigger than that, is that you guys make data ready. And that's really the value of what I call the tier two data layer that's building, where you've got stuff in memory, I get that, it's some odyssey streaming stuff, and things going on there. But now, then you have third tier, archive, but data tier two is just like all the data: IoT, structured data. That's growing, but the cost of storage is getting lower and lower. Now companies are incented to store. How is that impacting your business? We heard that at DellEMC World over and over and obviously they're in the storage business, but the tier two storage is significantly growing. >> Well data is still growing at over 25% a year. That's a huge number given all the way the size that you have, so it's going to be within by 2020, it'll be over 15 zetabytes, and a zetabyte, for those of you who are interested, is 10 to the 21. That's a huge amount of data. And what we're seeing is, the value comes from being able to first of all see your way through the data, being able to understand what data is valuable and what's not, and then connect the data. If you have customer data, product data, location data, et cetera, being able to put all of that together. That's really where the value comes from. >> So I've got to ask you about your keynote. You talk about the digital transformation's unfolding and data is the critical foundation for digital transformation. Okay, we've heard digital transformation. I mean, I'm not to say it's played, I know you guys have your theme, but this business transformation going on. So digital transformation is a known trend, but it kind of is played in my mind. I want to know what's different about Informatica now. Why is it unfolding now versus two years ago when we started talking about digital transformation? What's the most relevant thing now? >> Well I think the biggest relevance is, two years ago, as you exactly said, people were talking about digital transformation. Now they're doing digital transformation. Now you're seeing, you know, we talk about our own customers like Tesla or GE or Amazon doing it, but lots of other customers are actually doing the digital transformation. Now when you first take the first step toward the digital transformation, that's when you realize, my data, I got to fix the data foundation. If I can't have a data foundation, then I just, you know, everybody cares about a good customer experience. If I can't tell all the interactions a customer has with my company, and that data is in different places, there is no way I can provide a good customer experience because the customer knows what they're doing with me and I don't know what they're doing with me. And that's really the foundation for the data foundation. >> I want you to take a minute to just re-explain that because this is something comes up all the time and I get different answers and people have different definitions. What does it mean to have a digital data foundation and what are some of the impacts to the customers when they do have that? >> Think of it the simplest way. Let's say you have a customer and a lot of the new customers are like that. You are a bank, and you have a customer who doesn't want to talk to anybody. They only want to do everything through a mobile application. They want to file a loan application through the mobile, they want to check their balance through mobile, they want to deposit a check through mobile, et cetera, et cetera. If they have a problem, they might talk to somebody through a chat on a mobile, but they don't really want to talk to a live person. And this is, by the way, a common scenario now. Now they are doing probably 20 different things through the mobile. But when you get into your back end, that's the front end. You can put 20 things on the mobile, but the back end you've got 20 different things. But you have to have a single picture across those 20 things. When did the customer interact with us? What did they do? What is the pattern of that customer? How do you profile what the customer is doing? If you don't have that picture, everything that you do with the customer is going to just appear disconnected to them. It's going to frustrate them even more. And that's really the reason we have to have the data foundation. >> Okay, so, that's kind of a data layer, I get that, and believe me, horizontally-scalable data, making it accessible only helps the apps. The question to you is, your reaction to people saying, "Hey, Anil, I got to be innovative. "I got to free the data up and I got to let it grow "and you know a thousand flowers bloom, all this goodness. "But hey, I got to control it." So that's a huge issue. I've got governance, I've got compliance, there's laws now. So am I stuck in the mud? I want to be innovative and go fast, but now I've got to govern it and control it. How do you answer that question? >> You can do both now and that's the reason why we're announcing CLAIRE and all these innovations that we announced this. The advent of machine learning and metadata let's you do both. You basically say, look, I can use all these new technologies to find out what data I have. It's not going to slow you down. In fact, if you set up something like an intelligent data lake, because it has the metadata layer, you are actually opening up the data you have to the end user without having to come through IT for every piece of data, which means they can go faster. That's where the innovation happens. So you can do both. >> John: So it's a control catalog, basically. >> It's exactly right. It's a controlled catalog and you basically get to define different levels of trust. You can say, this data is curated data, it's trusted data and we can vouch for it. And maybe other data that's just shared collaboratively, and you can just flag it and then that way the user knows, okay here's data that I'm getting from a central system and this is what I need to use when I'm talking about something like revenue. And I'm tying something like a trend of what's going on. I might be able to use other data and that's the key there. >> Talk about the trend around CLAIRE. A lot of buzz here at the show. CLAIRE stands for clairvoyant. It's got the word AI in it. It's a name. SAP's got Leonardo, Salesforce has Einstein, all these different terms, but it's a clever way to point to AI, augmented intelligence, and machine learning. >> Anil: Correct. >> What does that mean for Informatica as a company? Certainly it kind of humanizes it. >> Anil: Correct. >> Shows the access of data should be democratized. What does it mean for you guys and the customers? How does that play out in your mind as the CEO? What do you see CLAIRE doing? >> Well the three big points I'll make about CLAIRE. First of all, when we built CLAIRE, we did not invent the artificial intelligence or the machine learning. A lot of that is already available. So we took a lot of the best algorithms in machine learning and applied them to metadata and applied them to data management. That's the secret sauce. It's not the building the AI itself, it's the use of the AI for data management. That's number one. Second, we defined CLAIRE very clearly and we said it's not a product. It's an engine, it's an AI-powered engine. In fact, I call for CLAIRE, I say it's cloud-scale, AI-powered real time engine, that's CLAIRE. Right, so it's an acronym, but it's the engine that powers other products. The third big thing is we're telling customers, you're going to get the benefit of CLAIRE, but you don't need to deploy CLAIRE. When you buy any of our products that are powered by CLAIRE or any of our solutions that are powered by CLAIRE, that will automatically come in there. So it means once you have any product like our enterprise information catalog or our secured source or data governance, you're starting to use CLAIRE and then you can use CLAIRE for other use cases as well. >> What's been the reaction? You know, and obviously you get nervous, CEO, probably got these things out there, probably wonder what the reaction is. What's your take on the reaction? >> People are very intrigued. I know that's what they, they look at CLAIRE and go, what is CLAIRE? How are you guys using it? I think people are asking us, tell us a little bit more about how AI is being used in the world of data and data management. So it's absolutely the reaction we wanted. >> So I got to ask you this question. I asked Mark Hurd the same question at the Oracle media day a few weeks ago. I want to ask you the same question. Everyone's number one at everything now. You guys are number one in six quadrants. Oracle's number one, the Dell E's. Everyone's number one at something. So the question really is, not so much about being number one, congratulations, you've got some magic quadrant wins that was highlighted in the keynote. But you guys are going through a transformation. You're telling your customers that they're going through a transformation. Wouldn't it make sense that the transformation scoreboard looks different than the old way? And I want to get your thoughts on this because, not that we have the answer, but there's one answer in customer wins, but as this new world transforms and unfolds, what's the scoreboard look like? How, because it's not as clean to say, this is the category, you're starting to see a little blending, as you mentioned how data is evolving. What's the new scoreboard look like? >> Is it the scoreboard for us or for the customer? >> John: You guys, the industry. How do I know if you're doing well? Obviously customer wins is obviously number one. >> Yeah, I think the best way to. I'll give you a couple of metrics, financial and nonfinancial, okay. From a nonfinancial perspective, as you said, a couple of key metrics. One is customers. How many new customers, how many new customers, reference customers do we have? Second one that you want to look at is just mind share or when people think about digital transformation, do they think of, hey, Informatica, they have a key role in my digital transformation. Just looking at mind share and so on, because that's a good leading indicator. In terms of the nonfinancial, or the financial metrics for us, obviously as more customers do what we call enterprise cloud data management, you're going to see our subscription revenue grow dramatically and you know, that's something that when you look at our subscription revenue, you'll see that impact of the enterprise cloud data management. >> And you guys made the move to subscription, obviously went private. Bruce Chizen and Jerry Held, your board members talked about this. You can do a lot of things 'cause it doesn't, it impacts the P&L but that it's still baking out, it's evolving, you're private, not public, but you want to get it right before you go public. >> That's correct. >> How do you feel about the progress on that front now? >> Oh we're making fabulous progress. We're very pleased with where we are. From my perspective, we are ahead of where we thought we would be by this time. I think customer buying behavior has converged really nicely with where we are in terms of where we want to go. So I think that's definitely been a big plus. >> Sally Jenkins, your new CMO, you got to feel good about her coming on the board-- >> Anil: Oh she's done a great job. >> High impact. She said on theCUBE that you guys are the hottest privately held pre-IPO startup. >> Anil: That's right. >> Twenty years in the making, whatever. I mean, but you guys are private. >> Billion dollar startup. >> But you act like a startup, which is why we like you guys a lot. You guys are like a very hustling like a startup. But now you're growing and you're getting beyond the 200 million, over a billion dollars now. When's the IPO coming? >> Yeah, I mean, you know look, I can tell you the factors that will be the lead to the perfect timing for the IPO. When those factors come together, I don't have a crystal ball right now, but I can tell you it weighs both on us and the market. From our perspective, we are making this big shift in the business model. We want to make sure that we can say, hey look, now the shift is very clear and stable and we can see where they where you know we'll be able to project out our own forecast for the next three, four quarters. So that's one key indicator for us. The second key indicator that we look at is the total revenue growth of the company and what percent of the growth of the revenue is recurring revenue for us. So we're going to be looking at those two factors. And of course from the market perspective, we want to make sure that the market wants to, continues to be. >> If you wait four years til we have a new president, and then heard all the politics from the Kara Swisher thing was, got a lot of people stirred up, in the conversation. But in all seriousness now, you also have private equity so you have to make the company worth money after they go public so you've got to have some growth left in you, right, I mean you guys are, you feel good about the? >> Oh we really do because you know, we look, that's where these six categories that we talked about make a lot of sense. You look at data integration, data quality, master data management, these are all categories that are well established. We know the patterns and we are seeing very good growth in those categories. Then you look at the new categories: cloud, big data management, data security. Those are all coming into their own right now. So that's why when you look at our portfolio, you go, wow, there are some that you already have great, well established and going well. These other ones, they're well established but they also have a lot of promise and future growth. >> Great chatting with you. You're a great, insightful, and inspiration. You guys have done a great job. But I've got to ask you the question because I think you have an interesting role. I mean, you have, you're acting like a startup, but you're not a startup. You went private from a public company. You've got a great board of directors. You've got Jerry Held and Bruce Chizen on there, but you've also got private equity sharks on the board. So, that's my definition, I won't say you said that. >> No, no, but I was actually in the private equity world, to my pleasant surprise, I've seen the whole spectrum of investors and our guys on the board are very much growth-oriented. They know that the value gets created for them through growth so it's well aligned. >> Yeah, but you're not sitting back having pizza and drinking wine. These PE guys, they're financially driven. >> Anil: That's right. >> So the question is, advice to other startups, whether they're venture backed or other companies going through innovation strategy. How do you manage the success of having such good product excellence? I know you've got good people, so that's an easy one answer. How as a CEO do you maintain the disciple to have the cadence of the financial performance? Because those guys look, they're probably not going to give you, hey how we doing? Numbers matter, but you're transforming technology and products. >> That's right, so what we do is-- >> How do you do it? >> We have a scorecard which has both the short term and the longterm metrics and we look at both of those. You know, we do monthly business reviews. So the pulse of the company has definitely quickened. We're operating at a new level of intensity. But when we look at the scorecard, it's not just the immediate financial metrics. It's things like, for example, are we building the back end infrastructure to be a subscription company? That doesn't get done in a month. >> John: That's an IT challenge, right? >> That's an IT challenge, a process challenge, it takes 12 months, 18 months, the kind of things that you talk with Graeme about. But that is an example of, you can have a scorecard. You don't necessarily have to look at a scorecard just for the short term metrics. You look at it for both short term and what makes you successful over the longterm. And that's, you know, that's what we're doing is just keep our eye on the ball, focus on a few things, both short term and longterm, and make sure we're doing them well. >> How about customer wins? To me, that's the scoreboard ultimately as we look at it at our team. How are you doing on customer wins? Can you share some, I see you have a lot of great customers. I met a few last night, obviously big wigs, big names. >> Anil: Yeah, exactly. >> What are some of the big wins look like and why are you winning? >> Well you know, we have 7,000 plus customers. We have a great customer base. Just at this show we've had 85% of our sessions here at the show have had customer or partner speakers. That gives you a sense of customers want to talk about us. A couple of ones that I would highlight for example, which are fairly recent for example, Amazon is one. They just spoke at the show and in fact the CMO of Amazon was here, Ariel Kelman. And he spoke about he is a customer of Informatica and how he's using Informatica for his own marketing systems and the marketing data analytics that he is doing. Another example is Tesla. You know, we talked about them at the show. >> I got a test drive on Friday with one. >> There you go, exactly, and then they are using us for the Tesla and the Solar City acquisition and driving synergies there. So lots of great examples. >> John: Tough customers, by the way, very, very finicky. >> Oh they are very demanding, very demanding customers and we are really proud to be serving them. >> Okay, final question, Anil. What's next? How do you look forward. Obviously this event, congratulations on getting the branding out. Peggy and the team did a great job. Sally and the team did a great job. What about next? What's next? >> Yeah, you know, what's next for us is simply work with customers to first of all get our story out, understand their priorities, and make sure that they understand that we can be a great partner for them. So we believe that this is the beginning of that journey. We talked about digital transformation and how we help them. Now we take the show on the road to our customers, make sure that we help them at their pace to transform. >> So bring the message out, build the brand. >> Absolutely. >> That's the key priority. >> And then continue. >> Product side, what's going on the products? >> Well on the product side, for instance, you saw a teaser of all the big trends. Machine learning, cloud, big data, security, all of these have full-fledged roadmaps that we're going to be working on over the course of the next six months. >> Anil, great to see you. Congratulations, you can tell, you're still intense. You've got the intensity, it's not going to stop by the way. >> Anil: No it's not. >> It's not like you're not going to get more intense as you guys grow. And congratulations. >> Thank you for having me on your show. >> We are here live in San Francisco for Informatica World 2017 with the CEO here, Anil Chakravarthy, inside theCUBE. I'm John Furrier. Thanks for watching. Stay with us for more coverage from Informatica World after this short break. (techno music)

>> Live from Las Vegas it's The Cube covering NAB 2017. Brought to you by HGST. >> Welcome back to The Cube. We are live at NAB 2017. I'm Lisa Martin. Very, very excited, kind of geeking out right now to be joined by our next two guests. Sam Blackman, the co-founder and CEO of AWS Elemental, welcome to The Cube. >> Sam: Thank you so much. >> And we have NASA astronaut, Tracy Caldwell Dyson. Both of you, welcome to The Cube. >> Thank you. >> Today has been a very historic day for technology and space. This was the first ever live 4k video stream that happened between you on Earth, Sam, and Doctor Peggy Whitson, aboard the International Space Station. >> Sam: Yes. >> Wow. Tell us about that. >> It was truly amazing to be part of history and the amount of technology that came into play to make this possible. You know, sitting in the conference room in NAB in the middle of Las Vegas, seeing astronauts 250 miles ahead, going around the Earth, 17,000 miles an hour and a seamless, beautiful 4k picture. It was mind blowing. Hard to believe it's happened still. >> I can't even imagine. I'm getting goosebumps for you. Tell us some of the things that Dr. Whitson shared about her experiences. What was the interaction like? >> Well, Commander Whitson and Colonel Fisher was also in the interview and that guy is hilarious, by the way. >> Yeah, he is. >> He is hilarious. They talked about how advanced imaging technology really helps NASA perform experiments and bring experiments that are happening on the space station down to Earth for researchers to use that data and discover how the world works inside the universe. Some of the really interesting examples revolved around some experiments they showed. With thin film technology they had a very small, metallic structure that they could pull water out of and then corral that water, convert it into a spherical shape and in the 4k resolution, you could just see every element of that thin film in a way that looked like it was right next to us. I mean, it was transformative. >> Tracy: Yeah. >> I bet it was. Well, speaking of transformative, this was, I mentioned, a really historic event for a number of reasons. Obviously, for those of us on the ground, for AWS Elemental. But, Tracy, from your perspective, you've been in space for 188... I had it here somewhere, hours. >> Yeah, days. >> You've been on STS118, you've been on the Soyuz to the station on expeditions 23 and 24. What does this capability now mean in the life of an astronaut? >> I think what it does is it helps us bring the experience to everybody here on Earth. It is so hard to capture what we are not just seeing, but experiencing. The richness, the detail, the vividness of the colors and how they're changing are all a part of looking at our beautiful planet. And just from that alone, being able to bring that to the American people, the world, really, is, I think to me a great relief. Because it grieves me to think about how in the world I would describe this beautiful, magnificent view to everybody back home. >> I can imagine. You've done extra-vehicular space walks. >> Tracy: Yes. >> And I can imagine it's indescribable. >> It is. And from the fact you're looking at our planet from 250 miles above, you see the curvature of the Earth, you see it moving at a super high speed, you don't feel the wind in your face, but there's no doubt you're traveling very fast. Just the fact that you are out in the vacuum of space. If you could bring parts of that experience to people back home ... I'm excited to think about how that would transform just the way people think, not to mention the way that they act towards our planet. >> I also think inspiration ... We were talking before we went on that you were about 14 when the Challenger incident happened, we all kind of remember exactly where we were, and that really, a teacher being in space was so inspirational to you. Can you imagine shifting the conversation and what this technology is able to do inspiring the next generation of people that want to be the next Tracy Caldwell Dyson? >> Well, I think what the technology does today, especially in imaging capabilities, is it provides so much more detail than I could even describe. That a young person today watching that, and our generation today is so visual, that they're going to pick up on things that I wouldn't even think to describe to them. And it's going to capture their imagination in ways that are astounding. Compared to I, who, just the sheer knowledge of knowing there was a teacher that was going into space, propelled me to work really hard. I can only imagine what this generation's going to be capable of because of the images that we're bringing to them. >> It's so exciting. Sam, this is really kind of the tip of the iceberg. From AWS Elemental's perspective, first of all, you just had a rebrand. But what does this mean for the future of the video ecosystem? >> Well, I think it really shows you how the technology components came come together to create unbelievable pictures no matter where you are on the planet or in space. We had a live 4k encoder on the space station itself sending down signals to Johnson Space Center, then Johnson Space Center sending redundant links to Las Vegas, here, and the convention center. And then processing the video, the interview with Tracy, here in the space center-- or, here in NAB and then using the cloud to distribute that all over the world. So these 4k images, which take a significant amount of bandwidth, can be created in space, delivered here, produced and delivered anywhere in the world using the power of the cloud and advanced networking technology. And that's pretty amazing, when you think about it. >> Lisa: It really is. I don't think the three of us are smiling big enough. >> I know. It hurts! >> There's so much relief in this face. >> Lisa: I can imagine >> I bet. >> I absolutely can imagine, I think. One of the cool things about-- This is our first time at NAB with The Cube, but we're here: Media, entertainment, Hollywood. What this shows is this transcendence of technology to space. And there's so much interest in space. In fact, Tracy, you were an advisor to Jessica Chastain on "The Martian," which is probably pretty exciting. >> Oh, absolutely. It is. >> But just the transcendence of that and how this technology can be used to power things that everybody can understand, movies and things. But also the future of space exploration, which I can imagine, right now in the era of the space shuttle being retired now, depending on Soyuz rockets to get to the space station as the next vehicle is delivered, this must be quite inspirational for you as an astronaut, as not only is the next vehicle in development, but also, the exploration of Mars. In fact, you were just last month with President Trump. >> Tracy: Yes. >> As they signed a bill. What are your thoughts about that and how do you see imaging technology being an instrumental part of Mars exploration? >> In so many ways, but at the top is the momentum. Like you said, with Hollywood has captured space in some real endearing ways. And the images from NASA, from the human space flight program to Hubble to deep space, it is propelling ... it's momentum. And I think we need that momentum, especially with our young folks because they're going to be the ones, let's face it, who are going to be in the best condition to be on the planet of Mars. So, if we can continue to feed them the images as lifelike as we can, so that they feel they're there, I think we are heading in the right direction to actually being there. >> Wow, fantastic! Congratulations to both of you. Thank you both so much for joining us on The Cube. We can't wait to see what's next. >> Sam: Thank you so much. >> Tracy: Thank you. Thank you. >> Well, for Tracy and Sam, I'm Lisa Martin. You've been watching The Cube live from NAB 2017. Stick around, we'll be right back. (funky music)

Yeah, I'm Aala, They're the co-founder back to back. This is the cube silicon angle.com, Silicon angle dot TV's production of the cube, our flagship telecasts. We go out to the event. That was a great conversation. I was really just, just cool. I could have, we could have probably hit on a few more things, obviously well read. Awesome. Co-founder of Cloudera a. You were, you did a good job teaming up with that co-founder, huh? Not bad on the cube, huh? He's not bad on the cube, isn't he? He, >>He reads the internet. >>That's what I'm saying. >>Anything is going on. >>He's a cube star, you know, And >>Technology. Jeff knows it. Yeah. >>We, we tell you, I'm smarter just by being in Cloudera all those years. And I actually was following what he was saying, Sad and didn't dust my brain. So, Okay, so you're back. So we were talking earlier with Michaels and about the relational database thing. So I kind of pick that up where we left off with you around, you know, he was really excited. It's like, you know, hey, we saw that relational database movement happen. He was part of that. Yeah, yeah. That generation. And then, but things were happening or kind of happening the same way in a similar way, still early. So I was trying to really peg with him, how early are we, like, so, you know, as the curve, you know, this is 1400, it's not the Javit Center yet. Maybe the Duke world, you know, next year might be at the Javit Center, 35,000 just don't go to Vegas. So I'm trying to figure out where we are on that curve. Yeah. And we on the upwards slope, you know, down here, not even hitting that, >>I think, I think, I think we're moving up quicker than previous waves. And actually if you, if you look for example, Oracle, I think it took them 15, 20 years until they, they really became a mature company, VM VMware, which started about, what, 12, 13 years ago. It took them about maybe eight years to, to be a big company, met your company, and I'm hoping we're gonna do it in five. So a couple more years. >>Highly accelerated. >>Yes. But yeah, we see, I mean, I'm, I'm, I've been surprised by the growth. I have been, Right? I've been told, warned about enterprise software and, and that it takes long for production to take place. >>But the consumerization trend is really changing that. I mean, it seems to be that, yeah, the enterprises always last. Why the shorter >>Cycle? I think the shorter cycle is coming from having the, the, the, the right solution for the right problem at the right time. I think that's a big part of it. So luck definitely is a big part of this. Now, in terms of why this is changing compared to a couple of dec decades ago, why the adoption is changing compared to a couple of decades ago. I, I think that's coming just because of how quickly the technology itself, the underlying hardware is evolving. So right now, the fact that you can buy a single server and it has eight cores to 16 cores has 12 hards to terabytes. Each is, is something that's just pushing the, the, the, the limits what you can do with the existing systems and hence making it more likely for new systems to disrupt them. >>Yeah. We can talk about a lot. It's very easy for people to actually start a, a big data >>Project. >>Yes. For >>Example. Yes. And the hardest part is, okay, what, what do I really, what problem do I need to solve? How am I gonna, how am I gonna monetize it? Right? Those are the hard parts. It's not the, not the underlying >>Technology. Yes, Yes, that's true. That's true. I mean, >>You're saying, eh, you're saying >>Because, because I'm seeing both so much. I'm, I'm seeing both. I'm seeing both. And like, I'm seeing cases where you're right. There's some companies that was like, Oh, this Hadoop thing is so cool. What problem can I solve with it? And I see other companies, like, I have this huge problem and, and, and they don't know that HA exists. It's so, And once they know, they just jump on it right away. It's like, we know when you have a headache and you're searching for the medicine in Espin. Wow. It >>Works. I was talking to Jeff Hiba before he came on stage and, and I didn't even get to it cuz we were so on a nice riff there. Right. Bunch of like a musicians playing the guitar together. But like he, we talked about the it and and dynamics and he said something that I thoughts right. On money and SAP is talking the same thing and said they're going to the lines of business. Yes. Because it is the gatekeeper that's, it's like selling mini computers to a mainframe selling client servers from a mini computer team. Yeah. >>There's not, we're seeing, we're seeing both as well. So more likely the, the former one meaning, meaning that yes, line of business and departments, they adopt the technology and then it comes in and they see there's already these five different departments having it and they think, okay, now we need to formalize this across the organization. >>So what happens then? What are you seeing out there? Like when that happens, that mean people get their hands on, Hey, we got a problem to solve. Yeah. Is that what it comes down to? Well, Hadoop exist. Go get Hadoop. Oh yeah. They plop it in there and I what does it do? They, >>So they pop it into their, in their own installation or on the, on the cloud and they show that this actually is working and solving the problem for them. Yeah. And when that happens, it's a very, it's a very easy adoption from there on because they just go tell it, We need this right now because it's solving this problem and it's gonna make, make us much >>More money moving it right in. Yes. No problems. >>Is is that another reason why the cycle's compressed? I mean, you know, you think client server, there was a lot of resistance from it and now it's more much, Same thing with mobile. I mean mobile is flipped, right? I mean, so okay, bring it in. We gotta deal with it. Yep. I would think the same thing. We, we have a data problem. Let's turn it into an >>Opportunity. Yeah. In my, and it goes back to what I said earlier, the right solution for the right problem at the right time. Like when they, when you have larger amounts of unstructured data, there isn't anything else out there that can even touch what had, can >>Do. So Amar, I need to just change gears here a minute. The gaming stuff. So we have, we we're featured on justin.tv right now on the front page. Oh wow. But the numbers aren't coming in because there's a competing stream of a recently released Modern Warfare three feature. Yes. Yes. So >>I was looking for, we >>Have to compete with Modern Warfare three. So can you, can we talk about Modern Warfare three for a minute and share the folks what you think of the current version, if any, if you played it. Yeah. So >>Unfortunately I'm waiting to get back home. I don't have my Xbox with me here. >>A little like a, I'm talking about >>My lines and business. >>Boom. Water warfares like a Christmas >>Tree here. Sorry. You know, I love, I'm a big gamer. I'm a big video gamer at Cloudera. We have every Thursday at five 30 end office, we, we play Call of of Beauty version four, which is modern world form one actually. And I challenge, I challenge people out there to come challenge our team. Just ping me on Twitter and we'll, we'll do a Cloudera versus >>Let's, let's, let's reframe that. Let team out. There am Abalas company. This is the geeks that invent the future. Jeff Haer Baer at Facebook now at Cloudera. Hammerer leading the charge. These guys are at gamers. So all the young gamers out there am are saying they're gonna challenge you. At which version? >>Modern Warfare one. >>Modern Warfare one. Yes. How do they fire in? Can you set up an >>External We'll >>We'll figure it out. We'll figure it out. Okay. >>Yeah. Just p me on Twitter and We'll, >>We can carry it live actually we can stream that. Yeah, >>That'd be great. >>Great. >>Yeah. So I'll tell you some of our best Hadooop committers and Hadoop developers pitch >>A picture. Modern Warfare >>Three going now Model Warfare three. Very excited about the game. I saw the, the trailers for it looks, graphics look just amazing. Graphics are amazing. I love the Sirius since the first one that came out. And I'm looking forward to getting back home to playing the game. >>I can't play, my son won't let me play. I'm such a fumbler with the Hub. I'm a keyboard controller. I can't work the Xbox controller. Oh, I have a coordination problem my age and I'm just a gluts and like, like Dad, sorry, Charity's over. I can I play with my friends? You the box. But I'm around big gamer. >>But, but in terms of, I mean, something I wanted to bring up is how to link up gaming with big data and analysis and so on. So like, I, I'm a big gamer. I love playing games, but at the same time, whenever I play games, I feel a little bit guilty because it's kind of like wasted time. So it's like, I mean, yeah, it's fun and I'm getting lots of enjoyment on it makes my life much more cheerful. But still, how can we harness all of this, all of these hours that gamers spend playing a game like Modern Warfare three, How can we, how can we collect instrument, all of the data that's coming from that and coming up, for example, with something useful with predicted. >>This is exactly, this is exactly the kind of application that's mainstream is gaming. Yeah. Yeah. Danny at Riot G is telling me, we saw him at Oracle Open World. He's up there for the Java one. He said that they, they don't really have a big data platform and their business is about understanding user behavior rep tons of data about user playing time, who they're playing with. Yeah, Yeah. How they want us to get into currency trading, You know, >>Buy, I can't, I can't mention the names, but some of the biggest giving companies out there are using Hadoop right now. And, and depending on CDH for doing exactly that kind of thing, creating >>A good user experience >>Today, they're doing it for the purpose of enhancing the user experience and improving retention. So they do track everything. Like every single bullet, you fire everything in best Ball Head, you get everything home run, you do. And, and, and in, in a three >>Type of game consecutive headshot, you get >>Everything, everything is being Yeah. Headshot you get and so on. But, but as you said, they are using that information today to sell more products and, and, and retain their users. Now what I'm suggesting is that how can you harness that energy for the good as well? I mean for making money, money is good and everything, but how can you harness that for doing something useful so that all of this entertainment time is also actually productive time as well. I think that'd be a holy grail in this, in this environment if we >>Can achieve that. Yeah. It used to be that corn used to be the telegraph of the future of about, of applications, but gaming really is, if you look at gaming, you know, you get the headset on. It's a collaborative environment. Oh yeah. You got unified communications. >>Yeah. And you see our teenager kids, how, how many hours they spend on these things. >>You got play as a play environments, very social collaborative. Yeah. You know, some say, you know, we we're saying, what I'm saying is that that's the, that's the future work environment with Skype evolving. We're our multiplayer game's called our job. Right? Yeah. You know, so I'm big on gaming. So all the gamers out there, a has challenged you. Yeah. Got a big data example. What else are we seeing? So let's talk about the, the software. So we, one of the things you were talking about that I really liked, you were going down the list. So on Mike's slide he had all the new features. So around the core, can you just go down the core and rattle off your version of what, what it means and what it is. So you start off with say H Base, we talked about that already. What are the other ones that are out there? >>So the projects that we have right there, >>The projects that are around those tools that are being built. Cause >>Yeah, so the foundational, the foundational one as we mentioned before, is sdfs for storage map use for processing. Yeah. And then the, the immediate layer above that is how to make MAP reduce easier for the masses. So how can, not everybody knows how to learn map, use Java, everybody knows sql, right? So, so one of the most successful projects right now that has the highest attach rate, meaning people usually when they install had do installed as well is Hive. So Hive takes sequel and so Jeff Harm Becker, my co-founder, when he was at Facebook, his team built the Hive system. Essentially Hive takes sql so you don't have to learn a new language, you already know sql. And then converts that into MAP use for you. That not only expands the developer base for how many people can use adu, but also makes it easier to integrate Hadoop through all DBC and JDBC integrated with BI tools like MicroStrategy and Tableau and Informatica, et cetera, et cetera. >>You mentioned R too. You mentioned R Program R >>As well. Yeah, R is one of our best partnerships. We're very, very happy with them. So that's, that's one of the very key projects is Hive assisted project to Hive ISS called Pig. A pig Latin is a language that ya invented that you have to learn the language. It's very easy, it's very easy to learn compared to map produce. But once you learn it, you can, you can specify very deep data pipelines, right? SQL is good for queries. It's not good for data pipelines because it becomes very convoluted. It becomes very hard for the, the human brain to understand it. So Pig is much more natural to the human. It's more like Pearl very similar to scripting kind of languages. So with Peggy can write very, very long data pipelines, again, very successful projects doing very, very well. Another key project is Edge Base, like you said. So Edge Base allows you to do low latencies. So you can do very, very quick lookups and also allows you to do transactions. So you can do updates in inserts and deletes. So one of the talks here that had World we try to recommend people watch when the videos come out is the Talk by Jonathan Gray from Facebook. And he talked about how they use Edge Base, >>Jonathan, something on here in the Cube later. Yeah. So >>Drill him on that. So they use Edge Base now for many, many things within Facebook. They have a big team now committed to building an improving edge base with us and with the community at large. And they're using it for doing their online messaging system. The live mail system in Facebook is powered by Edge Base right now. Again, Pro and eBay, The Casini project, they gave a keynote earlier today at the conference as well is using Edge Base as well. So Edge Base is definitely one of the projects that's growing very, very quickly right now within the Hudu system. Another key project that Jeff alluded to earlier when he was on here is Flum. So Flume is very instrumental because you have this nice system had, but Hadoop is useless unless you have data inside it. So how do you get the data inside do? >>So Flum essentially is this very nice framework for having these agents all over your infrastructure, inside your web servers, inside your application servers, inside your mobile devices, your network equipment that collects all of that data and then reliably and, and materializes it inside Hado. So Flum does that. Another good project is Uzi, so many of them, I dunno how, how long you want me to keep going here, But, but Uzi is great. Uzi is a workflow processing system. So Uzi allows you to define a series of jobs. Some of them in Pig, some of them in Hive, some of them in map use. You can define a series of them and then link them to each other and say, only start this job when these other jobs, two jobs finish because I'm waiting for the input from them before I can kick off and so on. >>So Uzi is a very nice framework that will will do that. We'll manage the whole graph of jobs for you and retry things when they fail, et cetera, et cetera. Another good project is where W H I R R and where allows you to very easily start ADU cluster on top of Amazon. Easy two on top of Rackspace, virtualized environ. It's more for kicking off, it's for kicking off Hadoop instances or edge based instances on any virtual infrastructure. Okay. VMware, vCloud. So that it supports all of the major vCloud, sorry, all of the me, all of the major virtualized infrastructure systems out there, Eucalyptus as well, and so on. So that's where W H I R R ARU is another key project. It's one, it's duck cutting's main kind of project right now. Don of that gut cutting came on stage with you guys has, So Aru ARO is a project about how do we encode with our files, the schema of these files, right? >>Because when you open up a text file and you don't know how to what the columns mean and how to pars it, it becomes very hard to work for it. So ARU allows you to do that much more easily. It's also useful for doing rrp. We call rtc remove procedure calls for having different services talk to each other. ARO is very useful for that as well. And the list keeps going on and on Maha. Yeah. Which we just, thanks for me for reminding me of my house. We just added Maha very recently actually. What is that >>Adam? I'm not >>Familiar with it. So Maha is a data mining library. So MAHA takes some of the most popular data mining algorithms for doing clustering and regression and statistical modeling and implements them using the map map with use model. >>They have, they have machine learning in it too or Yes, yes. So that's the machine learning. >>So, So yes. Stay vector to machines and so on. >>What Scoop? >>So Scoop, you know, all of them. Thanks for feeding me all the names. >>The ones I don't understand, >>But there's so many of them, right? I can't even remember all of them. So Scoop actually is a very interesting project, is short for SQL to Hadoop, hence the name Scoop, right? So SQ from SQL and Oops from Hadoop and also means Scoop as in scooping up stuff when you scoop up ice cream. Yeah. And the idea for Scoop is to make it easy to move data between relational systems like Oracle metadata and it is a vertical and so on and Hadoop. So you can very simply say, Scoop the name of the table inside the relation system, the name of the file inside Hadoop. And the, the table will be copied over to the file and Vice and Versa can say Scoop the name of the file in Hadoop, the name of the table over there, it'll move the table over there. So it's a connectivity tool between the relational world and the Hadoop world. >>Great, great tutorial. >>And all of these are Apache projects. They're all projects built. >>It's not part of your, your unique proprietary. >>Yes. But >>These are things that you've been contributing >>To, We're contributing to the whole ecosystem. Yes. >>And you understand very well. Yes. And >>And contribute to your knowledge of the marketplace >>And Absolutely. We collaborate with the, with the community on creating these projects. We employ committers and founders for many of these projects. Like Duck Cutting, the founder of He works in Cloudera, the founder for that UIE project. He works at Calera for zookeeper works at Calera. So we have a number of them on stuff >>Work. So we had Aroon from Horton Works. Yes. And and it was really good because I tell you, I walk away from that conversation and I gotta say for the folks out there, there really isn't a war going on in Apache. There isn't. And >>Apache, there isn't. I mean isn't but would be honest. Like, and in the developer community, we are friends, we're working together. We want to achieve the, there's >>No war. It's all Kumbaya. Everyone understands the rising tide floats, all boats are all playing nice in the same box. Yes. It's just a competitive landscape in Horton. Works >>In the business, >>Business business, competitive business, PR and >>Pr. We're trying to be friendly, as friendly as we can. >>Yeah, no, I mean they're, they're, they're hying it up. But he was like, he was cool. Like, Hey, you know, we know each other. Yes. We all know each other and we're just gonna offer free Yes. And charge with support. And so are they. And that's okay. And they got other things going on. Yes. But he brought up the question. He said they're, they're launching a management console. So I said, Tyler's got a significant lead. He kind of didn't really answer the question. So the question is, that's your core bread and butter, That's your yes >>And no. Yes and no. I mean if you look at, if you look at Cloudera Enterprise, and I mentioned this earlier and when we talked in the morning, it has two main things in it. Cloudera Enterprise has the management suite, but it also has the, the the the support and maintenance that we provide to our customers and all the experience that we have in our team part That subscription. Yes. For a description. And I, I wanna stress the point that the fact that I built a sports car doesn't mean that I'm good at running that sports car. The driver of the car usually is much better at driving the car than the guy who built the car, right? So yes, we have many people on staff that are helping build had, but we have many more people on stuff that helped run Hado at large scale, at at financial indu, financial industry, retail industry, telecom industry, media industry, health industry, et cetera, et cetera. So that's very, very important for our customer. All that experience that we bring in on how to run the system technically Yeah. Within these verticals. >>But their strategies clear. We're gonna create an open source project within Apache for a management consult. Yes. And we sell support too. Yes. So there'll be a free alternative to management. >>So we have to see, But I mean we look at the product, I mean our products, >>It's gotta come down to product differentiation. >>Our product has been in the market for two years, so they just started building their products. It's >>Alpha, It's just Alpha. The >>Product is Alpha in Alpha right now. Yeah. Okay. >>Well the Apache products, it is >>Apache, right? Yeah. The Apache project is out. So we'll see how it does it compare to ours. But I think ours is way, way ahead of anything else out there. Yeah. Essentially people to try that for themselves and >>See essentially, John, when I asked Arro why does the world need Hortonwork? You know, eventually the answer we got was, well it's free. It needs to be more open. Had needs to be more open. >>No, there's, >>It's going to be, That's not really the reason why Warton >>Works. >>No, they want, they want to go make money. >>Exactly. We wasn't >>Gonna say them you >>When I kept pushing and pushing and that's ultimately the closest we can get cuz you >>Just listens. Not gonna >>12 open source projects. Yes. >>I >>Mean, yeah, yeah. You can't get much more open. Yeah. Look >>At management >>Consult, but Airs not shooting on all those. I mean, I mean not only we are No, no, not >>No, no, we absolutely >>Are. No, you are contributing. You're not. But that's not all your projects. There's other people >>Involved. Yeah, we didn't start, we didn't start all of these projects. Yeah, that's >>True. You contributing heavily to all of them. >>Yes, we >>Are. And that's clear. Todd Lipkin said that, you know, he contributed his first patch to HPAC in 2008. Yes. So I mean, you go back through the ranks >>Of your people and Todd now is a committer on Edge base is a committer on had itself. So on a number >>Of you clearly the lead and, and you know, and, but >>There is a concern. But we, we've heard it and I wanna just ask you No, no. So there's a concern that if I build processes around a proprietary management console, Yes. I'm gonna end up being locked into that proprietary management CNA all over again. Now this is so far from ca Yes. >>Right. >>But that's a concern that some people have expressed. And, and, and I think one of the reasons why Port Works is getting so much attention. So Yes. >>Talk about that. It's, it's a very good, it's a very good observation to make. Actually, >>There there is two separate things here. There's the platform where all the data sets and then there's this management parcel beside the platform. Now why did we make the management console why the cloud didn't make the management console? Because it makes our job for supporting the customers much more achievable. When a customer calls in and says, We have a problem, help us fix this problem. When they go to our management console, there is a button they click that gives us a dump of the state, of the cluster. And that's what allows us to very quickly debug what's going on. And within minutes tell them you need to do this and you to do that. Yeah. Without that we just can't offer the support services. There's >>Real value there. >>Yes. So, so now a year from, But, but, but you have to keep in mind that the, the underlying platform is completely open source and free CBH is completely a hundred percent open source, a hundred percent free, a hundred percent Apache. So a year from now, when it comes time to renew with us, if the customer is not happy with our management suite is not happy with our support data, they can, they can go to work >>And works. People are afraid >>Of all they can go to ibm. >>The data, you can take the data that >>You don't even need to take the data. You're not gonna move the data. It's the same system, the same software. Every, everything in CDH is Apache. Right? We're not putting anything in cdh, which is not Apache. So a year from now, if you're not happy with our service to you and the value that we're providing, you can switch. There is no lock in. There is no lock. And >>Your, your argument would be the switching costs to >>The only lock in is happiness. The only lock in is which >>Happiness inspection customer delay. Which by, by the way, we just wrote a piece about those wars and we said the risk of lockin is low. We made that statement. We've got some heat for it. Yes. And >>This is sort of at scale though. What the, what the people are saying, they're throwing the tomatoes is saying if this is, again, in theory at scale, the customers are so comfortable with that, the console that they don't switch. Now my argument was >>Yes, but that means they're happy with it. That means they're satisfied and happy >>With it. >>And it's more economical for them than going and hiding people full-time on stuff. Yeah. >>So you're, you're always on check as, as long as the customer doesn't feel like Oracle. >>Yeah. See that's different. Oracle is very, Oracle >>Is like different, right? Yeah. Here it's like Cisco routers, they get nested into the environment, provide value. That's just good competitive product strategy. Yes. If it they're happy. Yeah. It's >>Called open washing with >>Oracle, >>I mean our number one core attribute on the company, the number one value for us is customer satisfaction. Keeping our people Yeah. Our customers happy with the service that we provide. >>So differentiate in the product. Yes. Keep the commanding lead. That's the strategist. That's the, that's what's happening. That's your goal. Yes. >>That's what's happening. >>Absolutely. Okay. Co-founder of Cloudera, Always a pleasure to have you on the cube. We really appreciate all the hospitality over the beer and a half. And wanna personally thank you for letting us sit in your office and we'll miss you >>And we'll miss you too. We'll >>See you at the, the Cube events off Swing by, thanks for coming on the cube and great to see you and congratulations on all your success. >>Thank >>You. And thanks for the review on Modern Warfare three. Yeah, yeah. >>Love me again. If there any gaming stuff, you know, I.