(bright music) >> Hello, everyone. Welcome to theCUBE special presentation of International Women's Day. I'm John Furrier, host of theCUBE. This is a global special open program we're doing every year. We're going to continue it every quarter. We're going to do more and more content, getting the voices out there and celebrating the diversity. And I'm excited to have an amazing guest here, LaDavia Drane, who's the head of Global Inclusion Diversity & Equity at AWS. LaDavia, we tried to get you in on AWS re:Invent, and you were super busy. So much going on. The industry has seen the light. They're seeing everything going on, and the numbers are up, but still not there, and getting better. This is your passion, our passion, a shared passion. Tell us about your situation, your career, how you got into it. What's your story? >> Yeah. Well, John, first of all, thank you so much for having me. I'm glad that we finally got this opportunity to speak. How did I get into this work? Wow, you know, I'm doing the work that I love to do, number one. It's always been my passion to be a voice for the voiceless, to create a seat at the table for folks that may not be welcome to certain tables. And so, it's been something that's been kind of the theme of my entire professional career. I started off as a lawyer, went to Capitol Hill, was able to do some work with members of Congress, both women members of Congress, but also, minority members of Congress in the US Congress. And then, that just morphed into what I think has become a career for me in inclusion, diversity, and equity. I decided to join Amazon because I could tell that it's a company that was ready to take it to the next level in this space. And sure enough, that's been my experience here. So now, I'm in it, I'm in it with two feet, doing great work. And yeah, yeah, it's almost a full circle moment for me. >> It's really an interesting background. You have a background in public policy. You mentioned Capitol Hill. That's awesome. DC kind of moves slow, but it's a complicated machinery there. Obviously, as you know, navigating that, Amazon grew significantly. We've been at every re:Invent with theCUBE since 2013, like just one year. I watched Amazon grow, and they've become very fast and also complicated, like, I won't say like Capitol, 'cause that's very slow, but Amazon's complicated. AWS is in the realm of powering a generation of public policy. We had the JEDI contract controversy, all kinds of new emerging challenges. This pivot to tech was great timing because one, (laughs) Amazon needed it because they were growing so fast in a male dominated world, but also, their business is having real impact on the public. >> That's right, that's right. And when you say the public, I'll just call it out. I think that there's a full spectrum of diversity and we work backwards from our customers, and our customers are diverse. And so, I really do believe, I agree that I came to the right place at the right time. And yeah, we move fast and we're also moving fast in this space of making sure that both internally and externally, we're doing the things that we need to do in order to reach a diverse population. >> You know, I've noticed how Amazon's changed from the culture, male dominated culture. Let's face it, it was. And now, I've seen over the past five years, specifically go back five, is kind of in my mental model, just the growth of female leaders, it's been impressive. And there was some controversy. They were criticized publicly for this. And we said a few things as well in those, like around 2014. How is Amazon ensuring and continuing to get the female employees feel represented and empowered? What's going on there? What programs do you have? Because it's not just doing it, it's continuing it, right? And 'cause there is a lot more to do. I mean, the half (laughs) the products are digital now for everybody. It's not just one population. (laughs) Everyone uses digital products. What is Amazon doing now to keep it going? >> Well, I'll tell you, John, it's important for me to note that while we've made great progress, there's still more that can be done. I am very happy to be able to report that we have big women leaders. We have leaders running huge parts of our business, which includes storage, customer experience, industries and business development. And yes, we have all types of programs. And I should say that, instead of calling it programs, I'm going to call it strategic initiatives, right? We are very thoughtful about how we engage our women. And not only how we hire, attract women, but how we retain our women. We do that through engagement, groups like our affinity groups. So Women at Amazon is an affinity group. Women in finance, women in engineering. Just recently, I helped our Black employee network women's group launch, BEN Women. And so you have these communities of women who come together, support and mentor one another. We have what we call Amazon Circles. And so these are safe spaces where women can come together and can have conversations, where we are able to connect mentors and sponsors. And we're seeing that it's making all the difference in the world for our women. And we see that through what we call Connections. We have an inclusion sentiment tracker. So we're able to ask questions every single day and we get a response from our employees and we can see how are our women feeling, how are they feeling included at work? Are they feeling as though they can be who they are authentically at Amazon? And so, again, there's more work that needs to be done. But I will say that as I look at the data, as I'm talking to engaging women, I really do believe that we're on the right path. >> LaDavia, talk about the urgent needs of the women that you're hearing from the Circles. That's a great program. The affinity circles, the groups are great. Now, you have the groups, what are you hearing? What are the needs of the women? >> So, John, I'll just go a little bit into what's becoming a conversation around equity. So, initially I think we talked a lot about equality, right? We wanted everyone to have fair access to the same things. But now, women are looking for equity. We're talking about not just leveling the playing field, which is equality, but don't give me the same as you give everyone else. Instead, recognize that I may have different circumstances, I may have different needs. And give me what I need, right? Give me what I need, not just the same as everyone else. And so, I love seeing women evolve in this way, and being very specific about what they need more than, or what's different than what a man may have in the same situation because their circumstances are not always the same and we should treat them as such. >> Yeah, I think that's a great equity point. I interviewed a woman here, ex-Amazonian, she's now a GSI, Global System Integrator. She's a single mom. And she said remote work brought her equity because people on her team realized that she was a single mom. And it wasn't the, how do you balance life, it was her reality. And what happened was, she had more empathy with the team because of the new work environment. So, I think this is an important point to call out, that equity, because that really makes things smoother in terms of the interactions, not the assumptions, you have to be, you know, always the same as a man. So, how does that go? What's the current... How would you characterize the progress in that area right now? >> I believe that employers are just getting better at this. It's just like you said, with the hybrid being the norm now, you have an employer who is looking at people differently based on what they need. And it's not a problem, it's not an issue that a single mother says, "Well, I need to be able to leave by 5:00 PM." I think that employers now, and Amazon is right there along with other employers, are starting just to evolve that muscle of meeting the needs. People don't have to feel different. You don't have to feel as though there's some kind of of special circumstance for me. Instead, it's something that we, as employers, we're asking for. And we want to meet those needs that are different in some situations. >> I know you guys do a lot of support of women outside of AWS, and I had a story I recorded for the program. This woman, she talked about how she was a nerd from day one. She's a tomboy. They called her a tomboy, but she always loved robotics. And she ended up getting dual engineering degrees. And she talked about how she didn't run away and there was many signals to her not to go. And she powered through, at that time, and during her generation, that was tough. And she was successful. How are you guys taking the education to STEM, to women, at young ages? Because we don't want to turn people away from tech if they have the natural affinity towards it. And not everyone is going to be, as, you know, (laughs) strong, if you will. And she was a bulldog, she was great. She's just like, "I'm going for it. I love it so much." But not everyone's like that. So, this is an educational thing. How do you expose technology, STEM for instance, and making it more accessible, no stigma, all that stuff? I mean, I think we've come a long way, but still. >> What I love about women is we don't just focus on ourselves. We do a very good job of thinking about the generation that's coming after us. And so, I think you will see that very clearly with our women Amazonians. I'll talk about three different examples of ways that Amazonian women in particular, and there are men that are helping out, but I'll talk about the women in particular that are leading in this area. On my team, in the Inclusion, Diversity & Equity team, we have a program that we run in Ghana where we meet basic STEM needs for a afterschool program. So we've taken this small program, and we've turned their summer camp into this immersion, where girls and boys, we do focus on the girls, can come and be completely immersed in STEM. And when we provide the technology that they need, so that they'll be able to have access to this whole new world of STEM. Another program which is run out of our AWS In Communities team, called AWS Girls' Tech Day. All across the world where we have data centers, we're running these Girls' Tech Day. They're basically designed to educate, empower and inspire girls to pursue a career in tech. Really, really exciting. I was at the Girls' Tech Day here recently in Columbus, Ohio, and I got to tell you, it was the highlight of my year. And then I'll talk a little bit about one more, it's called AWS GetIT, and it's been around for a while. So this is a program, again, it's a global program, it's actually across 13 countries. And it allows girls to explore cloud technology, in particular, and to use it to solve real world problems. Those are just three examples. There are many more. There are actually women Amazonians that create these opportunities off the side of their desk in they're local communities. We, in Inclusion, Diversity & Equity, we fund programs so that women can do this work, this STEM work in their own local communities. But those are just three examples of some of the things that our Amazonians are doing to bring girls along, to make sure that the next generation is set up and that the next generation knows that STEM is accessible for girls. >> I'm a huge believer. I think that's amazing. That's great inspiration. We need more of that. It's awesome. And why wouldn't we spread it around? I want to get to the equity piece, that's the theme for this year's IWD. But before that, getting that segment, I want to ask you about your title, and the choice of words and the sequence. Okay, Global Inclusion, Diversity, Equity. Not diversity only. Inclusion is first. We've had this debate on theCUBE many years now, a few years back, it started with, "Inclusion is before diversity," "No, diversity before inclusion, equity." And so there's always been a debate (laughs) around the choice of words and their order. What's your opinion? What's your reaction to that? Is it by design? And does inclusion come before diversity, or am I just reading it to it? >> Inclusion doesn't necessarily come before diversity. (John laughs) It doesn't necessarily come before equity. Equity isn't last, but we do lead with inclusion in AWS. And that is very important to us, right? And thank you for giving me the opportunity to talk a little bit about it. We lead with inclusion because we want to make sure that every single one of our builders know that they have a place in this work. And so it's important that we don't only focus on hiring, right? Diversity, even though there are many, many different levels and spectrums to diversity. Inclusion, if you start there, I believe that it's what it takes to make sure that you have a workplace where everyone knows you're included here, you belong here, we want you to stay here. And so, it helps as we go after diversity. And we want all types of people to be a part of our workforce, but we want you to stay. And inclusion is the thing. It's the thing that I believe makes sure that people stay because they feel included. So we lead with inclusion. Doesn't mean that we put diversity or equity second or third, but we are proud to lead with inclusion. >> Great description. That was fabulous. Totally agree. Double click, thumbs up. Now let's get into the theme. Embracing equity, 'cause this is a term, it's in quotes. What does that mean to you? You mentioned it earlier, I love it. What does embrace equity mean? >> Yeah. You know, I do believe that when people think about equity, especially non-women think about equity, it's kind of scary. It's, "Am I going to give away what I have right now to make space for someone else?" But that's not what equity means. And so I think that it's first important that we just educate ourselves about what equity really is. It doesn't mean that someone's going to take your spot, right? It doesn't mean that the pie, let's use that analogy, gets smaller. The pie gets bigger, right? >> John: Mm-hmm. >> And everyone is able to have their piece of the pie. And so, I do believe that I love that IWD, International Women's Day is leading with embracing equity because we're going to the heart of the matter when we go to equity, we're going to the place where most people feel most challenged, and challenging people to think about equity and what it means and how they can contribute to equity and thus, embrace equity. >> Yeah, I love it. And the advice that you have for tech professionals out there on this, how do you advise other groups? 'Cause you guys are doing a lot of great work. Other organizations are catching up. What would be your advice to folks who are working on this equity challenge to reach gender equity and other equitable strategic initiatives? And everyone's working on this. Sustainability and equity are two big projects we're seeing in every single company right now. >> Yeah, yeah. I will say that I believe that AWS has proven that equity and going after equity does work. Embracing equity does work. One example I would point to is our AWS Impact Accelerator program. I mean, we provide 30 million for early stage startups led by women, Black founders, Latino founders, LGBTQ+ founders, to help them scale their business. That's equity. That's giving them what they need. >> John: Yeah. >> What they need is they need access to capital. And so, what I'd say to companies who are looking at going into the space of equity, I would say embrace it. Embrace it. Look at examples of what companies like AWS is doing around it and embrace it because I do believe that the tech industry will be better when we're comfortable with embracing equity and creating strategic initiatives so that we could expand equity and make it something that's just, it's just normal. It's the normal course of business. It's what we do. It's what we expect of ourselves and our employees. >> LaDavia, you're amazing. Thank you for spending the time. My final couple questions really more around you. Capitol Hill, DC, Amazon Global Head of Inclusion, Diversity & Equity, as you look at making change, being a change agent, being a leader, is really kind of similar, right? You've got DC, it's hard to make change there, but if you do it, it works, right? (laughs) If you don't, you're on the side of the road. So, as you're in your job now, what are you most excited about? What's on your agenda? What's your focus? >> Yeah, so I'm most excited about the potential of what we can get done, not just for builders that are currently in our seats, but for builders in the future. I tend to focus on that little girl. I don't know her, I don't know where she lives. I don't know how old she is now, but she's somewhere in the world, and I want her to grow up and for there to be no question that she has access to AWS, that she can be an employee at AWS. And so, that's where I tend to center, I center on the future. I try to build now, for what's to come, to make sure that this place is accessible for that little girl. >> You know, I've always been saying for a long time, the software is eating the world, now you got digital transformation, business transformation. And that's not a male only, or certain category, it's everybody. And so, software that's being built, and the systems that are being built, have to have first principles. Andy Jassy is very strong on this. He's been publicly saying, when trying to get pinned down about certain books in the bookstore that might offend another group. And he's like, "Look, we have first principles. First principles is a big part of leading." What's your reaction to that? How would you talk to another professional and say, "Hey," you know this, "How do I make the right call? Am I doing the wrong thing here? And I might say the wrong thing here." And is it first principles based? What's the guardrails? How do you keep that in check? How would you advise someone as they go forward and lean in to drive some of the change that we're talking about today? >> Yeah, I think as leaders, we have to trust ourselves. And Andy actually, is a great example. When I came in as head of ID&E for AWS, he was our CEO here at AWS. And I saw how he authentically spoke from his heart about these issues. And it just aligned with who he is personally, his own personal principles. And I do believe that leaders should be free to do just that. Not to be scripted, but to lead with their principles. And so, I think Andy's actually a great example. I believe that I am the professional in this space at this company that I am today because of the example that Andy set. >> Yeah, you guys do a great job, LaDavia. What's next for you? >> What's next. >> World tour, you traveling around? What's on your plate these days? Share a little bit about what you're currently working on. >> Yeah, so you know, at Amazon, we're always diving deep. We're always diving deep, we're looking for root cause, working very hard to look around corners, and trying to build now for what's to come in the future. And so I'll continue to do that. Of course, we're always planning and working towards re:Invent, so hopefully, John, I'll see you at re:Invent this December. But we have some great things happening throughout the year, and we'll continue to... I think it's really important, as opposed to looking to do new things, to just continue to flex the same muscles and to show that we can be very, very focused and intentional about doing the same things over and over each year to just become better and better at this work in this space, and to show our employees that we're committed for the long haul. So of course, there'll be new things on the horizon, but what I can say, especially to Amazonians, is we're going to continue to stay focused, and continue to get at this issue, and doing this issue of inclusion, diversity and equity, and continue to do the things that work and make sure that our culture evolves at the same time. >> LaDavia, thank you so much. I'll give you the final word. Just share some of the big projects you guys are working on so people can know about them, your strategic initiatives. Take a minute to plug some of the major projects and things that are going on that people either know about or should know about, or need to know about. Take a minute to share some of the big things you guys got going on, or most of the things. >> So, one big thing that I would like to focus on, focus my time on, is what we call our Innovation Fund. This is actually how we scale our work and we meet the community's needs by providing micro grants to our employees so our employees can go out into the world and sponsor all types of different activities, create activities in their local communities, or throughout the regions. And so, that's probably one thing that I would like to focus on just because number one, it's our employees, it's how we scale this work, and it's how we meet our community's needs in a very global way. And so, thank you John, for the opportunity to talk a bit about what we're up to here at Amazon Web Services. But it's just important to me, that I end with our employees because for me, that's what's most important. And they're doing some awesome work through our Innovation Fund. >> Inclusion makes the workplace great. Empowerment, with that kind of program, is amazing. LaDavia Drane, thank you so much. Head of Global Inclusion and Diversity & Equity at AWS. This is International Women's Day. I'm John Furrier with theCUBE. Thanks for watching and stay with us for more great interviews and people and what they're working on. Thanks for watching. (bright music)

>>Okay, welcome back. Everyone's Cube's coverage here in Las Vegas for Amazon re Mars machine learning, automation, robotics, and space out. John fir host of the queue. Got a great set of guests here talking about AI, Jason Montgomery CTO and co-founder man and Ryans CEO, founder guys. Thanks for coming on. We're just chatting, lost my train of thought. Cuz we were chatting about something else, your history with DataRobot and, and your backgrounds entrepreneurs. Welcome to the queue. Thanks >>Tur. Thanks for having >>Us. So first, before we get into the conversation, tell me about the company. You guys have a history together, multiple startups, multiple exits. What are you guys working on? Obviously AI is hot here as part of the show. M is Mars machine learning, which we all know is the basis for AI. What's the story. >>Yeah, really. We're we're here for two of the letters and Mars. We're here for the machine learning and the automation part. So at the high level, man is a no code AI application development platform. And basically anybody could log in and start making AI applications. It could be anything from just texting it with the Twilio integration to tell you that you're doing great or that you need to exercise more to integrating with zenes to get support tickets classified. >>So Jason, we were talking too about before he came on camera about the cloud and how you can spin up resources. The data world is coming together and I, and I like to see two flash points. The, I call it the 2010 big data era that began and then failed Hadoop crashed and burned. Yeah. Then out of the, out of the woodwork came data robots and the data stacks and the snowflakes >>Data break snowflake. >>And now you have that world coming back at scale. So we're now seeing a huge era of, I need to stand up infrastructure and platform to do all this heavy lifting. I don't have time to do. Right. That sounds like what you guys are doing. Is that kind of the case? >>That's absolutely correct. Yeah. Typically you would have to hire a whole team. It would take you months to sort of get the infrastructure automation in place, the dev ops DevOps pipelines together. And to do the automation to spin up, spin down, scale up scale down requires a lot of special expertise with, you know, Kubernetes. Yeah. And a lot of the other data pipelines and a lot of the AWS technologies. So we automate a lot of that. So >>If, if DevOps did what they did, infrastructure has code. Yeah. Data has code. This is kind of like that. It's not data ops per se. Is there a category? How do you see this? Cuz it's you could say data ops, but that's also it's DevOps dev. It's a lot going on. Oh yeah. It's not just seeing AI ops, right? There's a lot more, what, what would you call this? >>It's a good question. I don't know if we've quite come up with the name. I know >>It's not data ops. It's not >>Like we call it AI process automation >>SSPA instead of RPA, >>What RPA promised to be. Yes, >>Exactly. But what's the challenge. The number one problem is it's I would say not, not so much all on ever on undifferent heavy lifting. It's a lot of heavy lifting that for sure. Yes. What's involved. What's the consequences of not going this way. If I want to do it myself, can you take me through the, the pros and cons of what the scale scope, the scale of without you guys? >>Yeah. Historically you needed to curate all your data, bring it together and have some sort of data lake or something like that. And then you had to do really a lot of feature engineering and a lot of other sort of data science on the back end and automate the whole thing and deploy it and get it out there. It's a, it's a pretty rigorous and, and challenging problem that, you know, we there's a lot of automation platforms for, but they typically focus on data scientists with these large language models we're using they're pre-trained. So you've sort of taken out that whole first step of all that data collection to start out and you can basically start prototyping almost instantly because they've already got like 6 billion parameters, 10 billion parameters in them. They understand the human language really well. And a lot of other problems. I dunno if you have anything you wanna add to that, Ryan, but >>Yeah, I think the other part is we deal with a lot of organizations that don't have big it teams. Yeah. And it would be impossible quite frankly, for them to ever do something like deploy text, track as an example. Yeah. They're just not gonna do it, but now they can come to us. They know the problem they want solved. They know that they have all these invoices as an example and they wanna run it through a text track. And now with us they can just drag and drop and say, yeah, we want tech extract. Then we wanted to go through this. This is what we >>Want. Expertise is a huge problem. And the fact that it's changing too, right? Yeah. Put that out there. You guys say, you know, cybersecurity challenges. We guys do have a background on that. So you know, all the cutting edge. So this just seems to be this it, I hate to say transformation. Cause I not the word I'm looking for, I'd say stuck in the mud kind of scenario where they can't, they have to get bigger, faster. Yeah. And the scale is bigger and they don't have the people to do it. So you're seeing the rise of managed service. You mentioned Kubernetes, right? I know this young 21 year old kid, he's got a great business. He runs a managed service. Yep. Just for Kubernetes. Why? Because no, one's there to stand up the clusters. >>Yeah. >>It's a big gap. >>So this, you have these sets of services coming in now, where, where do you guys fit into that conversation? If I'm the customer? My problem is what, what is my, what is my problem that I need you guys for? What does it look like to describe my problem? >>Typically you actually, you, you kind of know that your employees are spending a lot of time, a lot of hours. So I'll just give you a real example. We have a customer that they were spending 60 hours a week just reviewing these accounts, payable, invoices, 60 hours a week on that. And they knew there had to be a better way. So manual review manual, like when we got their data, they were showing us these invoices and they had to have their people circle the total on the invoice, highlight the customer name, the >>Person who quit the next day. Right? >>No like they, they, Hey, you know, they had four people doing this, I think. And the point is, is they come to us and we say, well, you know, AI can, can just basically using something like text track can just do this. And then we can enrich those outputs from text track with the AI. So that's where the transformers come in. And when we showed them that and got them up and running in about 30 minutes, they were mind blown. Yeah. And now this is a company that doesn't have a big it department. So the >>Kind, and they had the ability to quantify the problem >>They knew. And, and in this case it was actually a business user. It was not a technical >>In is our she consequence technical it's hours. She consequences that's wasted. Manual, labor wasted. >>Exactly. Yeah. And, and to their point, it was look, we have way more high, valuable tasks that our people could be doing yeah. Than doing this AP thing. It takes 60 hours. And I think that's really important to remember about AI. What're I don't think it's gonna automate away people's jobs. Yeah. What it's going to do is it's going to free us up to focus on what really matters and focus on the high value stuff. And that's what people should >>Be doing. I know it's a cliche. I'm gonna say it again. Cause I keep saying, cause I keep saying for people to listen, the bank teller argument always was the big thing. Oh yeah. They're gonna get killed by the ATM machine. No, they're opening up more branches. That's right. That's right. So it's like, come on. People let's get, get over that. So I, I definitely agree with that. Then the question, next question is what's your secret sauce? I'm the customer I'm gonna like that value proposition. You make something go away. It's a pain relief. Then there's the growth side. Okay. You can solve from problems. Now I want this, the, the vitamin you got aspirin. And I want the vitamin. What's the growth angle for you guys with your customers. What's the big learnings. Once they get the beach head with problem solving. >>I think it, it, it it's the big one is let's say that we start with the account payable thing because it's so our platform's so approachable. They go in and then they start tinkering with the initial, we'll call it a template. So they might say, Hey, you know what, actually, in this edge case, I'm gonna play with this. And not only do I want it to go to our accounting system, but if it's this edge case, I want it to email me. So they'll just drag and drop an email block into our canvas. And now they're making it >>Their own. There is the no code, low code's situation. They're essentially building a notification engine under the covers. They have no idea what they're doing. That's >>Right. They get the, they just know that, Hey, you know what? When, when like the amount's over $10,000, I want an email. They know that's what they want. They don't, they don't know that's the notification engine. Of >>Course that's value email. Exactly. I get what I wanted. All right. So tell me about the secret sauce. What's under the covers. What's the big, big, big scale, valuable, valuable, secret sauce. >>I would say part of it. And, and honestly, the reason that we're able to do this now is transformer architecture. When the transformer papers came out and then of course the attention is all you need paper, those kind of unlocked it and made this all possible. Beyond that. I think the other secret sauce we've been doing this a long time. >>So we kind of, we know we're in the paid points. We went to those band points. Cause we weren't data scientists or ML people. >>Yeah. >>Yeah. You, you walked the snow and no shoes on in the winter. That's right. These kids now got boots on. They're all happy. You've installed machines. You've loaded OSS on, on top of rack switches. Yeah. I mean, it's unbelievable how awesome it's right now to be a developer and now a business user's doing the low code. Yep. If you have the system architecture set up, so back to the data engineering side, you guys had the experience got you here. This is a big discussion right now. We're having in, in, on the cube and many conversations like the server market, you had that go away through Amazon and Google was one of the first, obviously the board, but the idea that servers could be everywhere. So the SRE role came out the site reliability engineer, right. Which was one guy or gal and zillions of servers. Now you're seeing the same kind of role with data engineering. And then there's not a lot of people that fit the requirement of being a data engineer. It's like, yeah, it's very unique. Cause you're dealing with a system architecture, not data science. So start to see the role of this, this, this new persona, because they're taking on all the manual challenges of doing that. You guys are kind of replaced that I think. Well, do you agree with it about the data engineer? First of all? >>I think, yeah. Well and it's different cuz there's the older data engineer and then there's sort of the newer cloud aware one who knows how to use all the cloud technologies. And so when you're trying, we've tried to hire some of those and it's like, okay, you're really familiar with old database technology, but can you orchestrate that in a serverless environment with a lot of AWS technology for instance. And it's, and that's hard though. They don't, they don't, there's not a lot of people who know that space, >>So there's no real curriculum out there. That's gonna teach you how to handle, you know, ETL. And also like I got I'm on stream data from this source. Right. I'm using sequel I'm I got put all together. >>Yeah. So it's yeah, it's a lot of just not >>Data science. It's >>Figure that out. So its a large language models too. We don't have to worry about some of the data there too. It's it's already, you know, codified in the model. And then as we collect data, as people use our platform, they can then curate data. They want to annotate or enrich the model with so that it works better as it goes. So we're kind of curating, collecting the data as it's used. So as it evolves, it just gets better. >>Well, you guys obviously have a lot of experience together and congratulations on the venture. Thank you. What's going on here at re Mars. Why are you here? What's the pitch. What's the story. Where's your, you got two letters. You got the, you got the M for the machine learning and AI and you got the, a for automation. What's the ecosystem here for you? What are you doing? >>Well, I mean, I think you, you kind of said it right. We're here because the machine learning and the automation part, >>But >>More, more widely than that. I mean we work very, very closely with Amazon on a number of front things like text track, transcribe Alexa, basically all these AWS services are just integrations within our system. So you might want to hook up your AI to an Alexa so that you could say, Hey Alexa, tell me updates about my LinkedIn feed. I don't know, whatever, whatever your hearts content >>Is. Well what about this cube transcription? >>Yeah, exactly. A hundred percent. >>Yeah. We could do that. You know, feed all this in there and then we could do summarization of everything >>Here, >>Q and a extraction >>And say, Hey, these guys are >>Technicals. Yeah, >>There you go. No, they mentioned Kubernetes. We didn't say serverless chef puppet. Those are words straight, you know, and no linguistics matters right into that's a service that no one's ever gonna build. >>Well, and actually on that point, really interesting. We work with some healthcare companies and when you're basically, when people call in and they call into the insurance, they have a question about their, what like is this gonna be covered? And what they want to key in on are things like I just went to my doctor and got a cancer diagnosis. So the, the, the relevant thing here is they just got this diagnosis. And why is that important? Well, because if you just got a diagnosis, they want to start a certain triage to make you successful with your treatments. Because obviously there's an >>Incentive to do time. That time series matters and, and data exactly. And machine learning reacts to it. But also it could be fed back old data. It used to be time series to store it. Yeah. But now you could reuse it to see how to make the machine learning better. Are you guys doing anything, anything around that, how to make that machine learning smarter, look doing look backs or maybe not the right word, but because you have data, I might as well look back at it's happened. >>So part of, part of our platform and part of what we do is as people use these applications, to your point, there's lots of data that's getting generated, but we capture all that. And that becomes now a labeled data set within our platform. And you can take that label data set and do something called fine tuning, which just makes the underlying model more and more yours. It's proprietary. The more you do it. And it's more accurate. Usually the more you do it. >>So yeah, we keep all that. I wanna ask your reaction on this is a good point. The competitive advantage in the intellectual property is gonna be the workflows. And so the data is the IP. If this refinement happens, that becomes intellectual property. Yeah. That's kind of not software. It's the data modeling. It's the data itself is worth something. Are you guys seeing that? >>Yeah. And actually how we position the company is man team is a control plane and you retain ownership of the data plane. So it is your intellectual property. Yeah. It's in your system, it's in your AWS environment. >>That's not what everyone else is doing. Everyone wants to be the control plane and the data plan. We >>Don't wanna own your data. We don't, it's a compliance and security nightmare. Yeah. >>Let's be, Real's the question. What do you optimize for? Great. And I think that's a fair, a fair bet. Given the fact that clients want to be more agile with their data anyway, and the more restrictions you put on them, why would that this only gets you in trouble? Yeah. I could see that being a and plus lock. In's gonna be a huge factor. Yeah. I think this is coming fast and no one's talking about it in the press, but everyone's like run to silos, be a silo and that's not how data works. No. So the question is how do you create siloing of data for say domain specific applications while maintaining a horizontally scalable data plan or control plan that seems to be kind of disconnected everyone to lock in their data. What do you guys think about that? This industry transition we're in now because it seems people are reverting back to fourth grade, right. And to, you know, back to silos. >>Yeah. I think, well, I think the companies probably want their silo of data, their IP. And so as they refine their models and, and we give them the ability to deploy it in their own stage maker and their own VPC, they, they retain and own it. They can actually get rid of us and they still have that model. Now they may have to build, you know, a lot of pipelines and other technology to support it. But well, >>Your lock in is usability. Exactly. And value. Yeah. Value proposition is the lock in bingo. That's not counterintuitive. Exactly. Yeah. You say, Hey, more value. How do I wanna get rid of it? Valuable. I'll pay for it. Right. As long as you have multiple value, step up. And that's what cloud does. I mean, think that's the thing about cloud. That's gonna make all this work. In my opinion, the value enablement is much higher. Yeah. So good business model. Anything else here at the show that you observed that you like, that you think people would be interested in? What's the most important story coming out of the, the holistic, if you zoom up and look at re Mars, what's, what's coming out of the vibe. >>You know, one thing that I think about a lot is we're, you know, we have Artis here, humanity hopefully soon gonna be going to Mars. And I think that's really, really exciting. And I also think when we go to Mars, we're probably not gonna send a bunch of software engineers up there. >>Right. So like robots will do break fix now. So, you know, we're good. It's gone. So services are gonna be easy. >>Yeah. But I, oh, >>I left that device back at earth. I just think that's not gonna be good. Just >>Replicated it in one. I think there's like an eight >>Minute, the first monopoly on next day delivery in space. >>They'll just have a spaceship that sends out drones to Barss. Yeah. But I think that when we start going back to the moon and we go to Mars, people are gonna think, Hey, I need this application now to solve this problem that I didn't anticipate having. And in science fiction, we kind of saw this with like how, right? Like you had this AI on this computer or this, on this spaceship that could do all this stuff. We need that. And I haven't seen that here yet. >>No, it's not >>Here yet. And >>It's right now I think getting the hardware right first. Yep. But we did a lot of reporting on this with the D O D and the tactile edge, you know, military applications. It's a fundamental, I won't say it's a tech, religious argument. Like, do you believe in agile realtime data or do you believe in democratizing multi-vendor, you know, capability? I think, I think the interesting needs to sort itself out because sometimes multi vendor multi-cloud might not work for an application that needs this database or this application at the edge. >>Right. >>You know, so if you're in space, the back haul, it matters. >>It really does. Yeah. >>Yeah. Not a good time to go back and get that highly available data. You mean highly, is it highly available or there's two terms highly available, which means real time and available. Yeah. Available means it's on a dis, right? >>Yeah. >>So that's a big challenge. Well guys, thanks for coming on. Plug for the company. What are you guys up to? How much funding do you have? How old are you staff hiring? What's some of the details. >>We're about 45 people right now. We are a globally distributed team. So we hire every like from every country, pretty much we are fully remote. So if you're looking for that, hit us up, definitely always look for engineers, looking for more data scientists. We're very, very well funded as well. And yeah. So >>You guys headquarters out, you guys headquartered. >>So a lot of us live in Columbus, Ohio that's technically HQ, but like I said, we we're in pretty much every continent except in Antarctica. So >>You're for all virtual. >>Yeah. A hundred percent virtual, a hundred percent. >>Got it. Well, congratulations and love to hear that Datadog story at another time >>Or DataBot >>Yeah. I mean data, DataBot sorry. Let's get, get all confused >>Data dog data company. >>Well, thanks for coming on and congratulations for your success and thanks for sharing. Yeah. >>Thanks for having us for having >>Pleasure to be here. It's a cube here at rebars. I'm John furier host. Thanks for watching more coming back after this short break.

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Welcome to the cubes coverage of UI path forward for live from Las Vegas. We're here at the Bellagio. Lisa Martin, with Dave a long time, very excited to have in-person events back ish. I'll say we're going to be talking about automation as a boardroom imperative. We have two guests joining us here, James Matras here consulting principal. America's intelligent automation leader at UI and Irv. Dennis retired EA partner, and former CFO of HUD gentlemen. Welcome to the program. Exciting topic automation as a boardroom imperative, James says COO and start with you. How do you discuss the value of automation as being a key component and driver of transformation? >>That's a great question. I think what we've seen in the last couple of years is the evolution of what automation used to be. Two is going nine. And we've seen the shift from what we call generation one, which is very RPA centric type automation to more generation two, which is the combined integration of multiple technologies. It can target an intern process and it's quite important that you understand the pivotal shift because it's not enabling us to move from a task micro top agenda to a macro agenda actually impacts an organization at a strategic level. The ability to be able to look at processes more deeply to automate them in an end to end process collectively and use these different technologies in a synergistic manner truly becomes powerful because it shifts the narrative from a micro process agenda into more systemic area. >>So gen zero is an Emmanuel gen one is RPA point tools that individual maybe getting their personal productivity out. And then now you're saying gen three is across the enterprise. Where are we in terms of, you know, take your experience from your practical experience? Where do you think the world is? It's like probably between zero and one still. Right. But the advanced folks of thinking about gen three, w what's your, >>Yeah, it's a great question. And, um, when you and I, I can do the comparison being private and public sector on this because I was 37 years with E Y then went into retirement and CFL at HUD CFO. Ed was, was a HUD was nowhere. They had to just do all the intelligence digitalization, um, throughout, uh, from scratch. The private sector is probably five or six years ahead of them. But when you think about James talks about the gen one, two and three, the private sector is probably somewhere between two and three. And I know we're talking about the board in this conversation. Um, boards probably have one and two on their radar. Some boards may have three, some may not, but that's where the real strategic focus for boards needs to be is looking forward and, and getting ahead. But I think from a public sector standpoint, lot to go private sector, more to go as well. But, uh, there's a, there's a bit of a gap, but the public sector is probably only about three or four years behind the private sector >>To be okay. Let's look at the numbers, look at, look at the progress for the quarter. And now it's like discussion on cyber discussion on digital discussion on automated issue. It really changed the narrative over the last decade. >>Yeah, I think when you think of boards today, the lots of conversation on cyber that that conversation has been around for a while. A lot of conversation on ESG today, that conversation is getting, getting very popular. But I think when you think of next three, a Jen talks that bear James talks about, um, that's got to start elevating itself if it's not within the boardroom right now, because that will be the future of the company. And the way I think of it from a board's conversation is if a company doesn't think of themselves as a technology company in all aspects, no matter what you do, you are a technology company or you need to be. And if you're not thinking along that way, you're gonna, you're gonna lose market share and you're going to start falling behind your competitors. >>Well, and how much acceleration did the pandemic bring to just that organizations that weren't digital forward last year are probably gone? >>I think it certainly has shifted quite a lot. There's been a drive, the relevance of technology and hard plays for us in the modern workforce in the modern workplace has fundamentally changed the pandemic. We reimagine how we do things. Technology has progressed in itself significantly, and that made a big difference for, for all the environments as a result of that. So certainly is one of the byproducts of the pandemic has been certainly a good thing for everybody. >>Where does automation fit in the board? Virginia? You've got compensation committee. You've probably, I mean, there's somebody in charge of cyber. You got ESG now there's automation part of a broader digital agenda. Where's what's the right word. >>You know, I, I would personally put it in a enterprise risk management from a standpoint that if you're not focused on it, it's going to be a risk to the enterprise. And, um, when you think of automation and intelligent automation and RPA, uh, I think boards have a pretty good sense of how you interface with your customers and your vendors. I think a big push ought to be looking internally at your own infrastructure. You know, what are you, what are you doing in the HR space? What are you doing in a financial statement, close process? What are you doing your procurement process? I suspect there's still a lot of very routine transactions and processing within those, that infrastructure that if you just apply some RPA artificial intelligence, that data extraction techniques, you can probably eliminate a lot of man hours from the routine stuff. And, and the many man hours is probably not the right way to think of it. You could elevate people's work from being pushing numbers around to being data analyzers. And that's where the excitement is for people to see. >>It's not how it's viewed at organizations. We're not eliminating hours. Well focusing folks on much more strategic down at a test. >>Yes. I would say that that's exactly right now in the private sector, you're always going to have the efficiency play and profitability. So there will be an element of that. I know when at HUD we're, we're focused, we were not focused on eliminating hours because we needed people and we focused on creating efficiencies within the space and having people convert from, again, being Trent routine transactions, to being data analyzers and made the jobs, I'm sure. Fund for them as well. I mean, this is a lot of fun stuff. And, and if, uh, uh, companies need to be pushing this down through their entire infrastructure, not just dealing with our customers and the third parties that they deal with >>Catalyst or have been public sector. So you mentioned they may be five or six years behind, but I've seen certain public sector organizations really lean in, they learn from, from the private sector. And then even when you think about some of the military, how advanced they are absolutely. You know, the private could learn from them and if they could open it up. But >>So, yeah, I think that's, that's well said I was in this, you know, the that's the civilian part with, with the housing and urban development. I think the catalyst is, uh, bringing the expertise in, uh, I know when I, when I came, I went to HUD to elevate their financial infrastructure. It was, it was probably the worst of the cabinet agency. The financials were a mess. There was no, there was a, uh, there was not a clean audit opinion for eight years. And I was there to fix that and we fixed it through digitalization and digital transformation, as well as a financial transformation. The catalyst is just creating the education, letting people know what is, what, what technology can do. You don't have to be a programmer, but it's like driving a car. Anybody can drive a car, but we can't mechanic, you know, work as a mechanic on it. >>So I think it's creating education, letting people know what it can do. And at HUD, for example, we did a very simple, I was telling James earlier, we did a very simple RPA project on an, an, a financial statement, close process. It was 2,600 hours, six months. Once we implemented the RPA, brought that down to 70 hours, two weeks, people's eyes exploded with it. And then all of a sudden, I said, I want everyone to go back and come back with, with any manual process, any routine process that can convert to an RPA. And I got a list of a hundred, then it came then became trying to slow everything down. We're not going to do it overnight. Yeah, exactly. >>So, but it was self-funding. It was >>Self-funded. Yes. >>And, and how do you take that message to customers that it could be self-funding how how's that resonating >>Very well. And I think it was important. I always like to say, it's a point of differentiation because you look at, uh, mentioned earlier that organizations are basically technology companies. That's what they are. But now if you look across that we no longer compete at the ERP level without got SAP, Oracle, it's not a point of differentiation. We don't compete the application layer where they've got service. Now, black line, how we use them is helpful. We competed the digital layer and with automation is a major component of that. That's where your differentiation takes place. Now, if you have a point of differentiation, that is self-funding, it fundamentally changes the game. And that's why it's so important for boards to understand this, because that risk management, if you've not doing it, somebody is getting ahead of the game much faster than you are. >>Yeah. Yeah. You mentioned ERP and it, and it triggered something in my mind. Cause I, I said this 10 years ago about data. If in the nineties, you, you couldn't have picked SAP necessarily as the winner of ERP. But if you could have picked the companies that were using ERP could have made a lot of money in the stock market because they outperform their peers. And the same thing was true with data. And I think the same thing is going to be true with automation in the coming decade. >>Couldn't agree more. And I think that's exactly the point that differential acceleration happening this. And it's harder because of the Europeans. Once you knew what it was, you can put the boundaries on it. Digital, the options are infinite. It's just continuous progress as are from there. >>I've got a question for you. You talked about some great stats about how dramatically faster things were took far less time. How does that help from an adoption perspective? I know how much cultural change is very difficult for folks in any organization, but that sort of self-serving how does that help fuel adoption? >>Well, it's interesting. Um, it's, it is a, we're actually going to talk about this tomorrow. It is a framework and it's got to start at the leadership has got to start with governance. It's got to start with a detailed plan. That's executable. And it's got to start with getting buy-in from not only your, the, the organization, but the people you're dealing with outside the organization. Um, it's, it's, uh, I think that's absolutely critical. And when you bring this back to the boardroom, they are the leaders of the companies. And, and I, James, I talked about this as we're getting ready for tomorrow's session. I think the number one thing a board can do today is an own personal self assessment. Do they understand automation? Do they understand what next generation three is? Do they understand what the different components can do? And do they understand how the companies are implementing it? And if I was a board member, uh, on our boards, I say, we need to understand that or else this is nothing's going to happen. We're going to be here at the reliance of the CEO and the CFO strategy, which may or may not include or be thinking about this next three. So leadership at the top is going to drive this. And it's so critical. >>We were talking about catalyst before. And you mentioned education and expertise. I'm always curious as to what drew you to public sector because it's, yeah, I mean, very successful, you know, you're, you're with one of the global SIS directly, you can make a lot more money and that side. So what was it did, was it a desire to it's a great country? Was it >>Take one for the team and I'm going to do a selfish plug here. I just actually wrote a book in this whole thing called transforming a federal agency. What's the name of the book transforming and federal agency. And it's, uh, I spent my time at E Y for 37 years, fully retired. I wanted to give back and do meaningful work. And we lived in Columbus, Ohio, as I was talking about earlier, I was going to go teach and I got a call from the president's personnel office to see if I wanted to come. And these, the CFO at HUD with secretary Carson and change turn the agency around, uh, that took me a little while to say yes, because I wasn't sure I wanted something full time. It was a, it was in DC. So I'd be in a commuting role back and forth. My family's in Columbus. >>Um, but it was, uh, I did it and I loved it. It was, uh, I would pray, I would ask anyone that's has the ability to go into public service at any point in their career to do it. It's it was very rewarding. It was one of my favorite three years of life. And to your point, I didn't have to do it, but, uh, if I wanted to do something and give back and that met the criteria and we were very successful in turning it around with the digital transformation and a lot of stuff that we're talking about today gave me the ability to talk about it because I helped lead it >>For sharing that and did it. So did it start with the CFO's office? Because the first time I ever even heard about our RPO RPA was at a CFO conference and I started talking to him like, oh, this is going to be game changing. Is that where it started? Is that where it lands today? >>From an infrastructure standpoint, the CFO has the wonderful ability to see most processes within a company and its entire lifestyle from beginning to end. So CFO has that visibility to understand where efficiencies can happen in the process. And so the CFO plays a dramatically important role in this. And you think about a CFO's role today versus 20 years ago, it's no longer this, the bean counter rolling up numbers that become a business advisors to the board, to the CEO and to the executive suite. Um, so the CFO, I think has probably the best visibility of all the processes on a global basis. And they can see where the, the efficiencies and the implementation of automation can happen. >>So they can be catalysts and really fueling the actual >>Redesign of work. Yes, they, they, they probably need to be the catalyst. And as a board member, you want to be asking what is the CFO's strategic imperative for the next year? And if it doesn't include this, it's just got to get on the agenda. >>Well, curve ball here is his CFO question and you know, three years or two years ago, you wouldn't have even thought, I mean, let me set it up better. One of the industries that is highly automated is crypto. Yeah. You wouldn't even thought about crypto in your balance sheet a couple of years ago, but I'm not sure it's a widespread board level discussion, but as a CFO, what do you make of the trend to put Bitcoin on balance sheets? >>Yeah, I'm probably not the right person to ask because I'm a conservative guy. >>If somebody supported me and he said, Hey, why don't we put crypto on the balance sheet? >>I would get much more educated. I wouldn't shut it down. I would put it into, let's get more educated. Let's get the experts in here. Let's understand what's really happening with it. Let's understand what the risks are, what the rewards are. And can we absorb any sort of risk or reward with it? And when you say put it on the balance sheet, you can put it on in a small way to test it out. I wouldn't put the whole, I wouldn't make the whole balance sheet for Dell on day one. So that's why I would think about it. Just tell, tell me more, get me educated. How did you think about it? How can it help our business? How can I help our shareholders? How does it grow the bottom line? And then, then you start making decisions. >>Cause CFOs, let me find nature often conservative and most CFOs that I talked to just say no way, not a chance, but you're, maybe you're not as conservative as you think. Well, >>No, but I will never say go away on anything. I mean, cause I want to learn. I want to know. I mean, um, if you like all this stuff, that's new, it's easy to say go away, right? Yeah. But all of a sudden, three years later, the go away, all your competitors are doing it at a competitive advantage. So never say go away, get yourself educated before you jump into it. >>That's good advice. Yeah. In any walk of life question for you, or have you talked about the education aspect there? I'm curious from a risk mitigation perspective, especially given the last 18, 19 months, so tumultuous, so scary for all those organizations that were very digital, they're either gone or they accelerated very quickly. How much of an education do you have to provide certain industries? And are you seeing certain industries? I think healthcare manufacturing, financial services as being leaders in the uptake? >>Well, I think the financial service industries, for sure, they, they, they get this and then they need to, uh, cause they, you know, they're, they're a transaction and based, uh, industry. Uh, so they get it completely. Um, you know, I think maybe some manufacturing distribution, some of the old line businesses are, you know, they may not be thinking of this as progressively as they should. Um, but they'll get there. They're going to have to get there eventually. Um, you know, when you think about the education, my, I thought you were gonna ask a question about the education of the workforce. And I think as a board member, I would be really focused on, uh, how am I educating my workforce of the future? And do I have the workforce of the future today? Do I have to educate them to have to bring in hiring for it? Do I have to bring third-party service providers to get us there? So as a board member really focus on, do I have the right workforce to get us to this next stage? And if not, what do I need to do to get there? Because >>We'll allocate a percentage of their budgets to training and education. And the question is where do they put it >>In? Is it the right training and education, right? >>Where do they focus though? Right now we hear you iPad talking about they're a horizontal play, but James, when you and Lisa, we were asking about industry, when you go to market, are you, are you more focused on verticals? Are you thinking, >>No, it's on two things. So which often find is regardless of the sector with some nuanced variation, the back office functions are regionally the procure to pay process as the same fundamentals, regardless of the sector where the differentiation comes in at a sector of service is when you start going to the middle of the front office, I mean a mining has only one customer. They sold their product to image the retailer has an endless number of them. So when you get to the middle and front office and really start engaging with a customer and external vendors, then a differentiation is very unique and you'd have a lot of sort of customers having sector specific nuances and variations in how you use the platform. And that's where the shift now is happening as well is the back office functions that are largely driven by the CFO. If now getting good, robust value out of it, there's pivot to make it a differentiator in the market, comes in the front and middle office. And that's where we starting to say, sector specific genres solutions, nuances really come to the fall >>Deep industry expertise. Do you think digital at all changes that the reason I ask it because I see Amazon as a retail and then they're in cloud and they're in grocery other in content Apple's in, in financial services and you're seeing these internet giants with a dual agenda, they're disrupting horizontal technology and then there's disruptive industries. And my premise is it's because of data and digital. Do you ever see that industry specialization changing that value chain >>Without a doubt? And I think it's happens initially. It starts off. When people have started looking at the process, they realize there's such key dependencies on the upstream and downstream components of the value chain that they want to control it. So they actually start bridging out of what the core practices or the core business to own a broader agenda. And with digital, you can do it. You can actively interact more systemically that installs triggering, well, maybe I have a different product offering. Maybe I can own this. Could I monetize the information I had at my disposal today in a completely new line. And that really what gets truly innovative and starts creating a revenue increase as opposed as the cost saving. And that's what they're really going after. It's how do I, >>The vertical integration is not new. The plenty of ended up Koch industries, Tyson foods, but now it's digital. So presumably you can do it faster with greater greater scale >>Without a doubt. And you don't have to move your big ERP and things like that. Cause that's the only way it takes five years to move my technology backbone with digital. I can do the interaction tomorrow and we can build up enough to be able to sustain that in the short term. >>Right. And speaking of speed, unfortunately, guys, we are out of time, but thank you. Fantastic conversation automation as a board imperative guys, that's been great James or >>Thank you for your time. Thank you so much >>For Dave a long day. I'm Lisa Martin. You're watching the queue. We are live in Las Vegas at the Bellagio at UI path forward for stick around Dave and I will be right back. Okay.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to theCUBE's live coverage of ServiceNow Knowledge18 here in Las Vegas, Nevada. I'm your host Rebecca Knight, along with my co-host Dave Vellante. We're joined by Michael D'Ippolito. He is the VP of Run Services at Nationwide Insurance. He's coming to us straight from Columbus, Ohio. So thanks so much for joining us. >> Thanks for having me, appreciate it. >> So tell our viewers a little bit about what you do. What is Run Services? What do you do at Nationwide? >> Sure, yes. We are a part of what we call our infrastructure and operations group and we're really an enterprise services group. Basically in my resposibility, I have resposibility over our data centers, over what we call our enterprise command centers. Pretty much the eyes on glass, 24 by 7 operations that kind of keeps everything running. Also, I have resposibility for all our run processes. So our ITSM processes, both from a process ownership and a process management. So that's where ServiceNow really comes in. >> So we've talked about this before, Mike. It's just in terms of the insurance business. Some of the things that are driving that business. We always talk about digital disruption but it's really, the insurance business hasn't really been digitally disrupted. Maybe it's coming. Not maybe, I'm sure it's coming. But what's driving your business today and how important, important is the wrong word. How much of a factor is digital in terms of the decisions that you make on a day-to-day basis? >> Well, it's huge. You know, as you probably heard we're really at a big inflection point in the world today and we are going to be disrupted and we actually focus on how can we disrupt ourselves because somebody else is going to. It's just a matter of time until Amazon wants to get into the insurance business. >> Dave: That's right. (Rebecca and Dave laugh) >> We laugh but you know. >> No, I know they're planning it. >> They're selling groceries. You're not really competing with other insurance carriers anymore. You're competing with Amazon and Google for that experience, that user experience, that ease of use, that direct interaction. You know, when you think about it, home and auto insurance, it's kind of a commodity. It's like buying your gas and electric. So you've got to be able to create that direct experience to our members, to our consumers just like an Amazon would. >> We hear so much of these buzzwords at this conference but also just in general in the technology industry. Automation, streamlining, this emphasis on customer experience. How do these play in to your digital transformation in terms of what you're thinking about at Nationwide? >> Yeah, right now one of our big drivers is what we call the need for speed. Speed is everything right now in terms of staying competitive, coming out with features as fast as possible. And when you think about it, the only way to really get fast is you have to be automated, right? You can't be manual and fast. So really now we have to look at, how can we automate everything and how do we treat infrastructure like software, basically, like code. And we can roll out changes any time, any day, any hour, versus the old days when you had these big releases once a month of your applications. Those days are kind of gone. >> So I got to ask you about, I mean, one of the things that cloud brought was this notion of self-service. There's certainly pressure for customers to do self-service. You see that, they're going to comparison shop, they're going to pick their package, et cetera. So that's part of the disruption and then the other part is potentially on the actuarial side, the actuarial robots. What do you see happening there and how is that affecting your business? >> That actually is an interesting use case. That's probably where big data is really coming into play. So for example, in auto insurance, your rates change every six months and what we do is we look backwards and say how did you drive over those last six months? Did you have accidents? Did you have tickets? You know, et cetera, and then we price you accordingly. Well, now with the information, the data we can get out of your vehicle 24 by 7, we can price you every day. So we can look at basically what's called metered insurance or insurance by the mile that we use the technology to enable that kind of a pricing model. >> And I would imagine you're at the point where you can begin to predict riskier situations. >> Absolutely, and anticipate it just like they do in health care, right, so, you know, not much different but yeah, that's definitely a new thing coming. >> You're collecting all of this data. I mean and this is the thing about the collection of the data is the easy part really but it's really knowing what the data is telling you and then how to act on the data in the right way. >> Yes. >> So is it a lot of trial and error or how are you determining what insights are the actionable ones? >> Well, as you know, a very popular skill out there are data scientists. Data and analytics, that's huge right now. So getting people who have that skill to understand the so what from the data and to be able to make good decisions on it, and then how do you even automate that? That's a big field right now actually. >> We're obvioulsy ways away but you see it in the news pretty much every day. You go to Silicon Valley, you can't miss it. What's the conversation like around autonomous vehicles? Because everybody says, well the problem is who's liable if something goes wrong and then you see that big accident, the Uber situation. What's the conversation like internally around that? >> It's going to be here sooner than you think. It's already here. You're seeing it more and more. You're seeing every car getting smarter now. It's getting closer and closer. It's an inevitable future. We are going to have those. And so now we have to look at what is going to be the actual model around that? We'll figure that out. But as you know, in a lot of these industries, the technology has really been ahead of the regulation. When Uber came out, there were basically discussions about coverage and liability and all those kinds of things. So normally in any fast-paced technology, usually it leads and then the rest follows. It'll get figured out. >> And I think you will figure it out because you guys are good with numbers. (laughs) Insurance companies can always figure out the cost of insuring something, right? >> Right. >> Should we envision kind of a hybrid shared risk model between the consumer and the technology supplier? Or do you think it's all going to be in the consumer? >> Well, it's hard to say exactly but we know there will be some compression in insurance because of it. And really, you might get to the point where the software is what gets insured and not the person. >> Right. >> Right. So we're already talking to automakers about how do you insure the actual vehicle versus the person driving it because they're not driving it anymore. >> That's a shock to the 100-plus-year-old system, isn't it? (laughs) >> Absolutely. Again, it was a shock when people said, you mean we're not going to use horses anymore? >> (Rebecca laughs) Good point. Point taken. >> So you go through time and there's these big revolutions that happen and I think we're approaching one. >> Talk about the ServiceNow situation. We've talked about your journey before but maybe remind us of that, where you are, what you thought of the new announcements today, maybe give us an update. >> Yeah, we're excited. We've been on ServiceNow for almost three years. Over the last year, we've made tremendous progress in terms of, we have a program now called IT Simplification and a little shout out to my partner Rick Schnierer who is my AVP who runs the platform for us. They do a great job. I'm kind of like the business partner to them. Right now what we're doing is it's a focus on configuration management and we're slowly retiring legacy systems and repositories across the company into the one single source which is in ServiceNow. We're also really focused on hardware and software asset management. Getting an understanding of all the assets we own and constantly scanning the network to understand who's connecting in and if it's a threat, if it's a good guy or a bad guy, that's important. Very important right now. And then lastly, like I said, the need for speed. How can our operations side support this need for increased pace of development? Because once you put it in, it's got to operate, right? And it's go to run. >> So where are you at today? Mostly, so ITSM, doing SecOps or did I infer that or no? >> Yeah, we have all the ITSM in. Actually we're moving to Kingston this weekend. We're doing that upgrade. We are involved with the HR module. We're bringing in Workday as our platform in July and ServiceNow will integrate with that. We're looking at the portfolio management. So now that we have the ITSM under control, we're slowly looking at where else can ServiceNow play for us? Cloud's a big play for us so, you know, we're right now working with a cloud provider and then there's a lot of APIs and interfacing back into ServiceNow. So that's going to be important for us. >> And you're saying for infrastructure? Cloud for infrastructure? >> Correct. >> Or infrastructure's a service? >> Correct, right now, well, we focus on SaaS first. Anything that can be SaaS, we want to go SaaS. ServiceNow is a perfect example. Salesforce.com, all those kinds of SaaS solutions. Then IaaS and PaaS are also important, right? So right now, by the end of 2018, we'll only be about probably 10% external cloud and 90% on-prem, but three years from now, it'll be the other way around. We'll probably be 90% cloud. >> Awesome. >> What keeps you coming back to Knowledge? >> You know, it's just the, look at this crowd. >> I know, it's true. >> I mean, the networking, the peers you meet. It's been so great because you have that time of year where you can share ideas, share stories, and all that. Where ServiceNow is going with the platform is always so interesting and appealing. We're really interested in hearing and getting to that agent workspace which I think would be great for internal, like our help desk services. So, more automation inline with where we're going. We think it's a great platform for that. >> Rebecca: Great, well Michael, thank you so much for coming on theCUBE. It was great talking to you. >> Great, thank you. >> Thanks, enjoyed it, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from theCUBE's coverage of ServiceNow Knowledge18 just after this.

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to AWS re:Invent 2017. I am Lisa Martin with theCUBE, our day two of continuing coverage of this event that has attracted 44,000 people. Keith Townsend is my cohost, and we are very excited to welcome to theCUBE family Simon West, the CMO of Cyxtera. Welcome, Simon. >> Thank you, great to be here. >> Cyxtera, a six-month-old company. Tell us about it, what do you guys do? >> Sure, so as you said we are just six months old. It feels longer than that now, born at the intersection of five simultaneous acquisitions. One part of that was the acquisition of 57 data centers and a global co-location business that was formerly owned and operated by Century Link. Into that we've added the security and analytics capabilities of four modern startup software companies, and the vision is to provide a secure infrastructure solution both within our data centers, but interestingly even though I've got 57 data centers around the world, I want to be location agnostic. We recognize that today's enterprises are running multi-clouds, running hybrid environments, so we extend our security solutions on prem and into public clouds which is why we are here at AWS re:Invent. >> Fantastic. >> One of the big challenges that we hear from the enterprise perspective, hybrid IT is that the control that we have internally are very different from the controls that exist in AWS. How do you guys help even that out? >> You are exactly right, we would go so far as to gently suggest that the core method by which we protect access to infrastructure and applications which is still predicated on a physical perimeter is just fundamentally flawed in a 2017 world where your applications are everywhere, your users are everywhere connecting on a myriad of devices. You can't build a wall around that which doesn't exist. You have also obviously, as you say, you've got that problem of hydrogenous platforms, each with their own method of control. Our flagship product in that area is a product called AppGate SDP. SDP stands for software defined perimeter which is an emerging specification born out of the US government's disarm. Now a number of companies are offering software defined perimeter solutions. The basic premise that we hold is that security should be user centric rather than IP centric. A firewall is still predicated on granting access from one IP block to another IP block. The VPN may capture who is coming in, but once you are in, we give you basically unfettered access to flat corporate internal networks and we track you as an IP address rather than as a user. We think we should get more user centric. The user should be at the center of our policy. We think it should be more like cloud in the way we run security so rather than these hardware-based static central chokepoints, we think security should be real-time, it should be adaptive and intelligent, and it should be as agile as the cloud. You build cloud applications that are capable of spawning multiple copies of themselves, auto scaling up and down, moving from availability zone to availability zone yet our typical network security posture is still highly static. When you have some of the high profile attacks that we have seen over the last few months, our ability to change policy, immediately we recognize a problem. A particular operating system, apps in a particular service pack, is incredibly out of step with how agile the rest of our IT is. So more like cloud in terms of the way it operates, and finally we think, and so does the software defined perimeter spec, we think that access needs to be thought of as conditional rather than just a X, Y, yes or no. Jim has access to sensitive financial systems should be dependent on what operating system Jim is using whether Jim is on a coffee shop Wi-Fi network or on a structured corporate network, the time of day, the day of week, our overall security posture. The way AppGate works is when a user tries to access a system, the policy can ingest any one of these different conditional items. It can interrogate the device the user is using for the right software revisions. You can look at environmental variables. It can even look at internal business systems and check anything it can get to via an API, and only if those conditions are met will it provide access to a specific system, and then it can monitor that real time, so if your context changes, you move from a trusted network to an untested network, we can alter access. We can prime for a one time multifactor authentication or take any other steps the user wants. We offer that in cloud, on premise, integrated into our data centers to provide one central policy mechanism no matter what platform you are running on. In the case of AWS, we integrate with features like security groups, like AMI machine tagging, so you can build policy natively out of those Amazon features as well. >> Talk about that transition to this user based approach. I would imagine that a user can migrate their legacy systems into one of your 56, 57 data centers, and then as they start to expand out to the cloud, they have to change their operating model from they may migrate their traditional big firewall into your data center. What does that migration process look like? Is that an application by application spec, network by network? How do I transition? >> You know, it really varies. It feels a lot like I'm an old cloud guy, so it feels a lot like cloud did in the late 00s, in 2008, 2009. We think the software defined perimeter is going to have that big of an impact, a cloudlike impact on network and application security, but the way in which organizations will choose to implement it is going to vary. One of the things we did very early on was to integrate AppGate as a service into the data centers. If you think about co-location environments, when you bring new gear into a data center, you racket and stack it, the very next thing you do after that is drag a VPN back to the corporate office so you can access it remotely, which we would respectfully suggest is not necessarily the best way to do it in 2017 out of the chute. We've then integrated AppGate so organizations can just avail themselves of that as a service, and instantly have a kind of easy on-ramp. One of the big areas we see, and we've seen with customers here at re:Invent is customers who are moving workloads to cloud, and want to make sure that they can have that same sense of fine-grained access control common to those on premises and off premises environments, whether that's at migration or that's just an extension of an app into cloud environments, so it's kind of all over the place. >> Sorry Simon, what differentiates Cyxtera's approach to the software defined perimeter from your competitors? >> A couple of things, it's extremely robust in terms of one, being able to run in multiple environments, so a native AWS version, versions that run natively in other public cloud environments. Obviously we think the ability to offer it deeply integrated into the data centers is important. It's also capable of granting access to more than just web applications. You've got some solutions out there that are really web proxies and that are built for SAS apps and born on the cloud apps. This is more of a fundamental network platform by which you can gain access to any system or application you choose, and finally was introduced the concept of what we call scriptable entitlements which is the ability to interrogate third-party systems via API, and bring back those results as part of the building policy. An example there is we've got service provider customers who are running large multitenant environments. You then have a technical support organization who needs to support a huge multi thousands of servers environment with multiple customers running in multiple VLANs and typically the way you have to do that is a jam box in the middle and then giving these technical support folks access to that entire backend management network which is a security risk. With AppGate, you can actually integrate into a ticketing system and when John in support asks for access to a customer database server, at runtime, we can find out whether there is a trouble ticket open on that box assigned to that rep, and only then will we grant access. We don't grant level network access. We grant access to that specific application. We call it a segment of one, secure and cryptic connection between the user's device and the application or the applications they have access to but to nothing else. Everything else on the network is literally dark. It cannot be port scanned. It doesn't show up at all, so it's a much narrower sense of control, a much narrower sense of access, and again it's dynamic. If that trouble ticket that shut off, the access goes away automatically. We think the integration into business systems is a critical piece of the puzzle and an area where I think we have innovated with AppGate. >> Let's talk about security in depth. Obviously you guys are putting the software security perimeter around the data center, what we would classify as the data center which is kind of disappearing in a sense, and the edge. You talked about end-user protection. Where do you guys pickup and drop off when it comes to MDM, mobile device management, which is much more important now with mobile, and then laptops, desktops, et cetera, and you mentioned third parties, pieces of data center equipment that's not in your data center, like a wind farm. >> Sure, so you are right. We are absolutely moving to the edge. I think we continue to think that the data center will be as important as it ever was. The more cloud we have, the more data centers it needs to run in. The more public cloud we have the more people want to move some of their machines that might have historically run on prem to cloud data centers with low latency direct connect to public cloud environments. If you look at our data center footprint with regard to the edge, we are not just in the major markets, although in major metropolitan markets I've got half a dozen data centers all linked together, but I'm also in markets started across the country, so I've got half a dozen in New York and New Jersey, half a dozen in DC, half a dozen in the Bay Area, but I'm in Tampa, I'm in Columbus Ohio, I'm in Dallas, I'm in Denver, and so that distribution becomes particularly important as more customers move data to the edge. From a security perspective, again, we think of that data center as the nexus of enterprise at IT and the cloud. The data center is where our conversation about security in terms of access control starts. It's a physical security message of biometrics, and ID checks, and so forth, but there, we think is the missing piece of the puzzle. The principal point of ingress and egress into a data center today is not to the front door, the back door, or the loading dock. It's the massively clustered multicarrier network core, so if you are not providing some level of access control in and out of the network, I'd offer you are not providing a truly secure infrastructure solution. We start there. We are focused mainly at this point with AppGate at controlling the conversation between the user device and the system applications themselves. One of our other acquisitions, a company called Cat Bird has done some innovative work in terms of east/west segmentation in virtual environments, which is notoriously difficult otherwise to see, to stop the spread of how machines can talk to each other in a large virtualized forms as well, and so it's the infrastructure where we principally focus. >> Where are we, or maybe where are you guys in this revolution of information security? Are we at the forefront of massive change? What is Cyxtera's view on that? >> I think we are at the beginnings of a revolution that's about 20 years late. If you can kind of carbon date year zero of modern IT at around 1996, which is the advent of the Internet as a commercial and consumer force, that was the revolution for enterprise IT. That was the moment that we had to move IT outside the four walls of the machine room on the corporate campus. Prior to that, the applications all ran on big beige boxes in one room. The users were largely tethered to them by smaller beige boxes in other rooms, and the notion of perimeter security worked. It was a valid construct. As soon as enterprises had to start thinking about an increasingly global user base, as soon as users started to connect from all over the place, the concept of this perimeter goes away. Over the last 20 years, you've seen revolution after revolution and the way in which we design, provision, deploy, manage and operate our business applications, our development frameworks, and our infrastructure. We've revolutionized for availability. We've revolutionized agility. We've turned IT into a real-time API driven motion, and we've revolutionized for scalability with platforms like AWS just industrializing this real time IT on a global scale, and if you took a systems administrator from '96, and you showed them IT today, I think you have some explaining to do. If you took a security administrator from 1996 and showed him 2017, I think the construct would be familiar. We are still hardware driven in a software defined world. We are still assuming that access is static, that it's never changing, that it's predicated on the users being someplace, the applications being another, and again, in a world of real time IT, a world in which our underlying application footprint changes without any human intervention whatsoever, and I think you see with WannaCry, with NotPetya, with all of these attacks, the commonalities that they have in the terms of the reason they were so devastating is one, they take advantage of lateral spread. They take advantage of riding an authorized access into a corporate network where port scans show up 10,000s of ports where you can rattle the handles, break the locks, and spread like wildfire, and two, in the case of something like WannaCry, days after we realized what the problem was, we were unable to simply alter as an institution, as an industry, or as an enterprise access policy at the press of a button until we could get things patched. We had to sit, and wait, and watch the fires continue to burn, so it's a question of security being insufficiently agile, insufficiently automated and adaptive, and insufficiently software driven. We think that is just starting. I think on the SDP side, we've noticed in the last six months the conversation changing. We've noticed customers who now have SDP mandates internally who are seriously starting to evaluate these technologies. >> Wow, it sounds like Cyxtera is at the beginning of being potentially a great leader in this security revolution. We wish you, Simon, and the entire company the best of luck. We thank you so much for joining us on theCUBE, and we look forward to hearing great things from you guys down the road. >> Much appreciated, thank you both. >> Absolutely, for my cohost, Keith Townsend, I'm Lisa Martin. You are watching theCUBE's continuous coverage of AWS re:Invent 2017. Stick around guys, we will be right back.

>> Narrator: Live from Midtown Manhattan it's theCUBE! Covering Big Data, New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsor. >> Okay, welcome back everyone. Live here in New York this is theCUBE's coverage of Big Data NYC, our event. We've been doing it for five years, it's our event in conjunction with Strata Data, which is the O'Reilly Media that we run, it's a separate event. But we've been covering the Big Data for eight years since 2010, Hadoop World. This is theCUBE. Of course theCUBE is never going to change, they might call it Strata AI next year, whatever trend that they might see. But we're going to keep it theCUBE. This is in New York City, our eighth year of coverage. Guys, welcome to theCUBE. Our next two guests is Andrew Burt, Chief Privacy Officer and Andrew Gillman, Chief Customer Officer and CMO. It's a start-up so you got all these fancy titles, but you're on the A-team from Immuta. Hot start-up. Welcome to theCUBE. Great to see you again. >> Thanks for having us, appreciate it. >> Okay, so you guys are the start-up feature here this week on theCUBE, our little segment here. I think you guys are the hottest start-up that is out there and that people aren't really talking a lot about. So you guys are brand new, you guys have got a really good reputation. Getting a lot of props inside the community. Especially in the people who know data, data science, and know some of the intelligence organizations. But respectful people like Dan Hutchin says you guys are rockstars and doing great. So why all the buzz inside the community? Now you guys are just starting to go to the market? What's the update on the company? >> So great story. Founded in 2014, (mumbles) Investment, it was announced earlier this year. And the team, group of serial entrepreneurs sold their last company CSC, ran the public sector business for them for a while. Really special group of engineers and technologists and data scientists. Headquartered out of D.C. Customer success organization out of Columbus, Ohio, and we're servicing Fortune 100 companies. >> John: So Immuta, I-M-M-U-T-A. >> Immuta.com we just launched the new website earlier this week in preparation for the show. And the easiest way-- >> Immuta, immutable, I mean-- >> Immutable, I'm sure there's a backstory. >> Immutable, yeah. We do not ever touch the raw data. So we're all about managing risk and managing the integrity of the data. And so risk and integrity and security are baked into everything we do. We want our customers to know that their data will be immutable, and that in using us they'll never pose an additional risk to that underlying data. >> I think of blockchain when I think of immutability, like I'm so into blockchaining these dayS as you guys know, I've been totally into it. >> There's no blockchain in their technology. >> I know, but let's get down to why the motivation to enter the market. There's a lot of noisy stuff out there. Why do we need another unified platform? >> The big opportunity that we saw was, organizations had spent basically the past decade refining and upgrading their application infrastructure. But in doing so under the guise of digital transformation. We've really built that organization's people processes to support monolithic applications. Now those applications are moving to the cloud, they're being rearchitected in a microsurfaces architecture. So we have all this data now, how do we manage it for the new application, which we see is really algorithm-centric? The Amazons of the world have proven, how do you compete against anyone? How do you disrupt any industry? That's operationalize your data in a new way. >> Oh, they were developer-centric right? They were very focused on the developer. You guys are saying you're algorithm-centric, meaning the software within the software kind of thing. >> It's really about, we see the future enterprise to compete. You have to build thousands of algorithms. And each one of those algorithms is going to do something very specific, very precise, but faster than any human can do. And so how do you enable an application, excuse me, an algorithm-centric infrastructure to support that? And today, as we go and meet with our customers and other groups, the people, the processes, the data is everywhere. The governance folks who have to control how the data is used, the laws are dynamic. The tooling is complex. So this whole world looks very much like pre-DevOps IT, or pre-cloud IT. It takes on average between four to six months to get a data scientist up and running on a project. >> Let's get into the company. I wanted to just get that gist out, put some context. I see the problem you solve: a lot of algorithms out there, more and more open sources coming up to the scene. With the Linux Foundation, having their new event Rebrand the Open Source summit, shows exponential growth in open source. So no doubt about it, software's going to be new guys coming on, new gals. Tons of software. What is the company positioning? What do you guys do? How many employees? Let's go down by the numbers and then talk about the problem that you solve. >> Okay, cool. So, company. We'll be about 40 people by Q1. Heavy engineering, go to market. We're operating and working with, as I mentioned, Fortune 100 clients. Highly regulated industries. Financial services, healthcare, government, insurance, et cetera. So where you have lots of data that you need to operationalize, that's very sensitive to use. What else? Company positioning. So we are positioned as data management for data science. So the opportunity that we saw, again, managing data for applications is very different than managing data for algorithm development, data sciences. >> John: So you're selling to the CDO, Chief Data Officer? Are you selling to the analytics? >> In a lot of our customers, like in financial services, we're going right into the line of business. We're working with managing directors who are building next generation analytics infrastructure that need to unify and connect the data in a new way that's dynamic. It's not just the data that they have within their organization, they're looking to bring data in from outside. They want to also work collaboratively with governance professionals and lawyers who in financial services, they are, you know, we always jest in the company that different organizations have these cool new tools, like data scientists have all their new tools. And the data owners have flash disks and they have all this. But the governance people still have Microsoft Word. And maybe the newer tools are like Wikis. So now we can get it off of Word and make it shareable. But what we allow them to do is, and what Andrew Burt has really driven, is the ability for you to take internal logic, internal policies, external regulations, and put them into code that becomes dynamically enforceable as you're querying the data, as you're using it, to train algorithms, and to drive, mathematical decision-making in the enterprise. >> Let's jump into some of the privacy. You're the Chief Privacy Officer, which is codeword for you're doing all the governance stuff. And there's a lot of stuff business-wise that's going on around GDPR which is actually relevant. There's a lot of dollars on table for that too, so it's probably good for business. But there's a lot of policy stuff going on. What's going on with you guys in this area? >> So I think policy is really catching up to the world of big data. We've known for a very long time that data is incredibly important. It's the lifeblood of an increasingly large number of organizations, and because data is becoming more important, laws are starting to catch up. I think GDPR is really, it's hot to talk about. I think it is just the beginning of a larger trend. >> People are scared. People are nervous. It's like they don't know, this could be a blank check that they're signing away. The enforcement side is pretty outrageous. >> So I mean-- >> Is that right? I mean people are scared, or do you think? >> I think people are terrified because they know that its important, and they're also terrified because data scientists, and folks in IT have never really had to think very seriously about implementing complex laws. I think GDPR is the first example of laws, forcing technology to basically blend software and law. The only way, I mean one of our theses is, the only way to actually solve for GDPR is to invent laws within the software you're using. And so, we're moving away from this meetings and memos type approach to governing data, which is very slow and can take months, and we need it to happen dynamically. >> This is why I wanted to bring you guys in. Not only, Andrew, we knew each other from another venture, but what got my attention for you guys was really this intersection between law and society and tech. And this is just the beginning. You look at the tell-signs there. Peter Burris who runs research for Wikibon coined the term programming the real world. Life basically. You've got wearables, you've got IOT, this is happening. Self-driving cars. Who decides what side of the street people walk on now? Law and code are coming together. That's algorithm. There'll be more of them. Is there an algorithm for the algorithms? Who teaches the data set, who shares the data set? Wait a minute, I don't want to share my data set because I have a law that says I can't. Who decides all this stuff? >> Exactly. We're starting to enter a world where governments really, really care about that stuff. Just in-- >> In Silicon Valley, that's not in their DNA. You're seeing it all over the front pages of the news, they can't even get it right in inclusion and diversity. How can they work with laws? >> Tension is brewing. In the U.S. our regulatory environment is a little more lax, we want to see innovation happen first and then regulate. But the EU is completely different. Their laws in China and Russia and elsewhere around the world. And it's basically becoming impossible to be a global organization and still take that approach where you can afford to be scared of the law. >> John: I don't know how I feel about this because I get all kinds of rushes of intoxication to fear. Look at what's going on with Bitcoin and Blockchain, underbelly is a whole new counterculture going on around in-immutable data. Anonymous cultures, where they're complete anonymous underbellies going on. >> I think the risk-factors going up, when you mentioned IOTs, so its where you are and your devices and your home. Now think about 23 and Me, Verily, Freenome, where you're digitizing your DNA. We've already started to do that with MRIs and other operations that we've had. You think about now, I'm handing over my DNA to an organization because I want find out my lineage. I want to learn about where I came from. How do I make sure that the derived data off of that digital DNA is used properly? Not just for me, as Andrew, but for my progeny. That introduces some really interesting ethical issues. It's an intersection of this new wave of investment, to your point, like in Silicon Valley, of bringing healthcare into data science, into technology and the intersection. And the underpinning of the whole thing is the data. How do we manage the data, and what do we do-- >> And AI really is the future here. Even though machine-learning is the key part of AI, we just put out an article this morning on SiliconANGLE from Gina Smith, our new writer. Google Brain Chief: AI tops humans in computer vision, and healthcare will never be the same. They talk about little things, like in 2011 you can barely do character recognition of pictures, now you can 100%. Now you take that forward, in Heidelberg, Germany, the event this week we were covering the Heidelberg Laureate Forum, or HLF 2017. All the top scientists were there talking about this specific issue of, this is society blending in with tech. >> Absolutely. >> This societal impact, legal impact, kind of blending. Algorithms are the only thing that are going to scale in this area. This is what you guys are trying to do, right? >> Exactly, that's the interesting thing. When you look at training models and algorithms in AI, right, AI is the new cloud. We're in New York, I'm walking down the street, and there's the algorithm you're writing, and everything is Ernestine Young. Billboards on algorithms, I mean who would have thought, right? An AI. >> John: theCUBE is going to be an AI pretty soon. "Hey, we're AI! "Brought to you by, hey, Siri, do theCUBE interview." >> But the interesting part of the whole AI and the algorithm is you have n number of models. We have lots of data scientists and AI experts. Siri goes off. >> Sorry Siri, didn't mean to do that. >> She's trying to join the conversation. >> Didn't mean to insult you, Siri. But you know, it's applied math by a different name. And you have n number of models, assuming 90% of all algorithms are single linear regression. What ultimately drives the outcome is going to be how you prepare and manage the data. And so when we go back to the governance story. Governance in applications is very different than governance in data science because how we actually dynamically change the data is going to drive the outcome of that algorithm directly. If I'm in Immuta, we connect the data, we connect the data science tools. We allow you to control the data in a unique way. I refer to that as data personalization. It's not just, can I subscribe to the data? It's what does the data look like based on who I am and what those internal and external policies are? Think about this for example, I'm training a model that doesn't mask against race, and doesn't generalize against age. What do you think is going to happen to that model when it goes to start to interact? Either it's delivered as-- >> Well context is critical. And the usability of data, because it's perishable at this point. Data that comes in quick is worth more, but historically the value goes down. But it's worth more when you train the machine. So it's two different issues. >> Exactly. So it's really about longevity of the model. How can we create and train a model that's going to be able to stay in? It's like the new availability, right? That it's going to stay, it's going to be relevant, and it's going to keep us out of jail, and keep us from getting sued as long as possible. >> Well Jeff Dean, I just want to quote one more thing to add context. I want to ask Andrew over here about his view on this. Jeff Dean, the Google Brain Chief behind all of the stuff is saying AI-enabled healthcare. The sector's set to grow at an annual rate of 40% through 2021, when it's expected to hit 6.6 billion spent on AI-enabled healthcare. 6.6 billion. Today it's around 600 million. That's the growth just in AI healthcare impact. Just healthcare. This is going to go from a policy privacy issue, One, healthcare data has been crippled with HIPPA slowing us down. But where is the innovation going to come from? Where's the data going to be in healthcare? And other verticals. This is one vertical. Financial services is crazy too. >> I mean, honestly healthcare is one of the most interesting examples of applied AI, and it's because there's no other realm, at least now, where people are thinking about AI, and the risk is so apparent. If you get a diagnosis and the doctor doesn't understand why it's very apparent. And if they're using a model that has a very low level of transparency, that ends up being really important. I think healthcare is a really fascinating sector to think about. But all of these issues, all of these different types of risks that have been around for a while are starting to become more and more important as AI takes-- >> John: Alright, so I'm going to wrap up here. Give you guys both a chance, and you can't copy each other's answer. So we'll start with you Andrew over here. Explain Immuta in a simple way. Someone who's not in the industry. What do you guys do? And then do a version for someone in the industry. So elevator pitch for someone who's a friend, who's not in the industry, and someone who is. >> So Immuta is a data management platform for data science. And what that actually gives you is, we take the friction out of trying to access data, and trying to control data, and trying to comply with all of the different rules that surround the use of that data. >> John: Great, now do the one for normal people. >> That was the normal pitch. >> Okay! (laughing) I can't wait to hear the one for the insiders. >> And then for the insiders-- >> Just say, "It's magic". >> It's magic. >> We're magic, you know. >> Coming from the infrastructure role, I like to refer to it as a VMWare for data science. We create an abstraction layer than sits between the data and the data science tools, and we'll dynamically enforce policies based on the values of the organization. But also, it drives better outcomes. Because today, the data owners aren't confident that you're going to do with the data what you say you're going to do. So they try to hold it. Like the old server-huggers, the data-huggers. So we allowed them to unlock that and make it universally available. We allow the governance people to get off those memos, that have to be interpreted by IT and enforced, and actually allow them to write code and have it be enforced as the policy mandates. >> And the number one problem you solve is what? >> Accelerate with confidence. We allow the data scientists to go and build models faster by connecting to the data in a way that they're confident that when they deploy their model, that it's going to go into production, and it's going to stay into production for as long as possible. >> And what's the GDPR angle? You've got the legal brain over here, in policy. What's going on with GDPR? How are you guys going to be a solution for that? >> We have the most, I'd say, robust option of policy enforcement on data, I think, available. We make it incredibly easy to comply with GDPR. We actually put together a sample memo that says, "Here's what it looks like to comply with GDPR." It's written from a governance department, sent to the internal data science department. It's about a page and a half long. We actually make that very onerous process-- >> (mumbles) GDPR, you guys know the size of that market? In terms of spend that's going to be coming around the corner? I think it's like the Y2K problem that's actually real. >> Exactly, it feels the same way. And actually Andrew and his team have taken apart the regulation article by article and have actually built-in product features that satisfy that. It's an interesting and unique--- >> John: I think it's really impressive that you guys bring a legal and a policy mind into the product discussion. I think that's something that I think you guys are doing a little bit different than I see anyone out there. You're bringing legal and policy into the software fabric, which is unique, and I think it's going to be the standard in my opinion. Hopefully this is a good trend, hopefully you guys keep in touch. Thanks for coming on theCUBE, thanks for-- >> Thanks for having us. >> For making time to come over. This is theCUBE, breaking out the start-up action sharing the hot start-ups here, that really are a good position in the marketplace, as the generation of the infrastructure changes. It's a whole new ballgame. Global development platform, called the Internet. The new Internet. It's decentralized, we even get into Blockchain, we want to try that a little later, maybe another segment. It's theCUBE in New York City. More after this short break.

>> Announcer: Live from the Washington D.C. It's the CUBE covering AWS Public Sector Summit 2017. Brought to you be Amazon Web Services and it's partner Ecosystem. >> Welcome back here on the CUBE as we continue our coverage of the AWS Public Sector Summit 2017. Along with John Furrier, I'm John Walls we're in the Walter E. Washington Convention Center. For the sixth show, of almost 10,000 attending. somewhere in that ball park. It's come along way in a very short period of time. AWS has a lot to feel good about. >> It's a good reinvent for Public Sector. It's huge. >> And not just to think about government. We think about education as well. We had a couple of segments about that. We are going to talk about government with our next guest. If we get a name wrong on this segment shame on us, John Stephenson with John Walls and John Furrier. John's a senior manage at Public Policy at AWS. John nice to have you with us we appreciate that. >> Thank you for having me. >> Thank you for your time. So your focus primarily state and local governments. What exactly as the conduit do you want to bring to their table from of AWS? >> Well I'm Senior Manager, of Public Policy for Amazon Web Services in the Eastern United States. I handle state and local government relations in the Eastern U.S. from Texas to Main and then South Florida. I help our business and also our partners in government to understand how public policy can enable cloud and modern technologies. It's a very exciting place to be because there's a lot going on in state and local government when it comes to IT modernization and cloud right now. >> I think about government too. There's that big umbrella we can put on (mumbles). It's public service. But federal government has a place and state and local. I think much more responsive, much more grass roots. So those applications are much more immediate. I would think. Does that come into play with you? That you need to be a little more nimble. Or you're helping your clients to be a litter more nimble or more agile? >> Absolutely, if you look at what state and local governments are doing. Essential services from delivering health care to taking out the trash, providing public safety, providing education it's handled at the state and local government. If you look at the number of times you touch government. It is state and local. Think about renewing a driver license. Think about paying a parking ticket. Think about getting a zoning permit for remodeling of your house. You're dealing with state and local government. The demands on state and local government are also higher. They're holding more data on citizens than the Federal government. They are undergoing massive population changes. It's either positive or negative. State and local governments which have budget constraints. Need to be more nimble, more innovative. They are natural early adopters and first movers of technology. If you look at some of the more exciting things about technology that are happening in the government space. I think it's happening at state and local government in the U.S. >> Smart cities by the way is the hottest trend. Intel one of the key sponsors of this show. We had two folks on here. AI is going to be a real nice gateway for some of these innovations on their side. They have 5G opportunities. They have transformation. Lot of technology going on under the covers, under the hood if you will. One of them is smart cities and that is something that is just mind blowing. Just from a technology stand point but even more mind blowing from a policy perspective. Who sets the rules? What side does the car run on? What digital services are the citizens going to get? Who pays for them? What does the government do? What does the private sector do? These are issues that need to be grappled with. Your thoughts on how you guys look at that? And how are your constituents engaging with that and thinking about it? >> I'm glad you mentioned smart cities because there's a lot of activity going on in that space. If you look at the internet of things technologies alone. One of the enablers of smart cities. As many as 53% of state and local government according to NASCIO are looking at these technologies or deploying them. It's great to see that because that will enable a lot of potential from smarter government services, better government services, improving service delivery and improving constituent fulfillment. Which resonates with us, as part of Amazon. We're all about our customer fulfillment and delighting our customer. >> Lower prices and ship things faster that's Bezos' ethos. That's Amazon's culture. >> Exactly. >> And you could deliver services any digital service. >> Everything we do starts with the customer and we work backwards. In the conversations I've had with policy makers in the state and local governments. They see smart cities as a way to do that. Everything from improving transportation in places like Columbus, Ohio. To improving connectivity and engagement with the internet in places Kansas City, Missouri. And new ways of delivering services in places like New York and Los Angeles. It's very exciting stuff. Policy makers are coming to us and others in the industry. What are the policies? What are the best practices that can enable these technologies? We've been working with them. Providing information on what we're seeing around the world. How open data can be made (mumbles). How security and compliance can be built into applications. And we're happy to provide that because we know from working in the cloud ourselves. The potential that's there for state and local government. >> You want to foster innovation but at the same time you don't want to create this restrictive environment. Or have legacy be the baggage that holds things back. In fact you look at some of the best smart cities implementation. It's Singapore. It's Dubai. It's areas all over the world. In some cases it didn't have real strong infrastructure. So now come back to your role. As you look at the U.S. which has great infrastructure. Except for broadband connectivity, we'd be faster. They have some pre-existing conditions. They're under pressure. The cloud is a prefect vehicle for them. Because they can come in with their existing stuff. Get apps and services online quicker. How are you dealing with the challenge of? OK, calm down we're not going to take over the world. No, skynet's not coming. You know terminator reference. That's a concern, privacy. Lot of in policy issues, to be dealt with. How do you handle those? >> I think with any policy issue. I've been in public policy for a while now. It really starts with education. Understanding in really simple layman's terms. What the cloud is. And what it is not. It is a very transformative technology. It is not an end all one size fits all technology. What we've done is help educate policy makers by understanding the potential of cloud. What it can do in terms of cost savings, improved security, and being more agile. And to tell that story, we don't use PowerPoints at Amazon. We're not coming in and giving PowerPoint presentations. >> Good ole flesh pounding, hand shakes, and hit the streets. >> We'll more importantly it's sharing the customer's stories We're talking with them about what's happening at the New York City Department of Transportation. We're talking with them about what's happening at the city of Los Angeles with their emergency operation center. About how cities are using cloud technologies to deliver far superior products and services faster. >> So what is New York doing and what is L.A. doing specifically? >> New York city they have their iRide application to help citizens get from one point to the other much more quickly and safely as part of their Vision Zero campaign. Anyone who's been in New York, and I've been in New York quite a few times. Knows that traffic and be a real pain getting from part of Manhattan to the other. So what iRide does, is it helps people navigate Manhattan and the other boroughs much more quickly and efficiently using all the modes of transportation available to them. The city of New York was able to deploy that much more quickly, to many more people. They're able to update it, keep it secure thanks to cloud technology offered by AWS. The city of Los Angeles. They face cyber attacks everyday. Then there are the huge cost of maintaining that security. But with cloud they're able to build out event management systems and integrate those with their Homeland Security technologies and practices. And to be able to do it for a fraction of the cost using traditional systems, traditional IT, and traditional practices. It's very exciting. Suddenly local government can move at the speed and agility of a startup. Which has made Amazon very innovative. Last year we launched over a thousand new services and features. Local governments are seeing that. They want to be more like us and others in the industry. That are using cloud to deliver new products and services. And be better at their job. >> And the education, I say it probably patience in the educational role. You think about just the civil liberties of the citizens. That's really job one. Because I think most people get spooked. Whoa all this surveillance. The thing about it, just watching Patriots Day with my family. You know the Boston bombing, Boston strong with Mark Wahlberg. These things actually happen all the time. And we take for granted the some of the things we have in the surveillance community for the kinds of data that's out there. The same time that's the balance. Can you bring me value with my liberties. It's the same compliance scheme. Same governance game. This is the public sector. >> Well, that's where I think cloud has a great story to tell With cloud you get the benefits of economies of scale. Of Amazon with security and also with privacy. We have multiple compliance frameworks. Everything from HIPPA, FERPA, CJIS, Criminal Justice Information Systems. We are zealous guardians of security and our customer's privacy. We don't look at data. We don't share data about with out our customer's permission. We have very strong safeguards. That's why if you look a the customer base of Amazon from banks to government agencies, health care companies. Even companies like Netflix and you would think they're a competitor of ours. They're running their IT in AWS. They trust us even though with Amazon video and Amazon prime. You would think they're a competitor. But they've put that level of trust in us and our systems and our practices that they can put their data there. And we're hearing it from customer after customer. That they feel more safer and more secure with their data in the cloud offered by AWS. And we've shared that with government officials. And they take great comfort in those statements. >> You hit on something earlier. When you said that state governments and local governments have more data at their disposal than the federal government has about their consumers. Because of that, how much higher do find their concerns to be, in terms of cyber security, in terms of hack proof secured networks and systems as opposed to what might happen at the federal level. Cause we think federal. We think big. About what happened with the U.S. government's payment systems last year OPM. State and local they've got a lot more data they're protecting >> I've had a great opportunity in my current job to talk with a lot of IT officials and policy makers in the state. And, often times a meeting will start. And they'll say I've read about this. I've heard about this. And we're often able to say that's not an issue with the cloud offered the AWS. Or that's something we've already addressed through our security and compliance frame works. For example, I was in one meeting and a state policy maker asked me, well what do you do about HIPPA compliance. We have HIPPA compliance in AWS. And then he tried to ask questions, well what about this, what about that. And each time our team was able to tell the state policy maker. We meet that. We exceed that. We actually help write the standard for that compliance frame work. What we've been able to show that policy maker and others. The cloud just offers a far superior security posture than what they can do on their own. It's taken some time because the cloud is new. And as we like to say, it's still day one in this field. But we are very confident as word gets out. More and more people will be trusting particularly in state government their data to the cloud. Because of the superiority it offers on so many different levels. >> Well certainly the words getting out. This event here is just as big as it's ever been (mumbles). Use to be a little summit, now it's grown. There's a lot of interest. >> It's very exciting for me. I've been to reinvent now twice. And this is just so delightful to see so many people from government from the U.S. from internationally here to learn about the cloud share their stories. It's really inspirational to see what's possible. >> That's a testament to Teresa Carlson. Who was just years ago knocking on doors. That was before cloud was cloud. Now it's just come a long way. Congratulations to the whole team. >> Thank you. It's really to delightful to see. And I can't wait to see what's in store for next year and after that. >> We still got a little bit here to go John Don't kick us out. John Stephenson, Public Policy at AWS. Thanks for being with us we appreciate that. >> Thank you. >> Thank you. With John Furrier, I'm John Walls and we'll be back with more here on the CUBE from Washington D.C. right after this. (upbeat music)

>> Narrator: Live, from Washington, DC, it's the Cube. Covering AWS Public Sector Summit 2017. Brought to you by Amazon Web Services, and its partner ecosystem. >> Well welcome back to our nations' capitol, Washington, DC, hosting this week's AWS Public Sector Summit 2017. You're live, here on the Cube, which of course is the flagship broadcast of the Siliconangle TV, where my partner in crime John Fourier always likes to say, we extract the single from the noise, don't we John? >> That's right, we're here. >> Yeah, we are. >> In D.C. >> In DC and it's a little warm, it's a little toasty inside but outside especially. 95 and humidity, Jeff Raleigh could attest to that. He just pulled into town from Columbus, Ohio. Jeff, good to see you, the Senior VP and GM of Cloud at Ellucian, so thank you for being with us Jeff. >> Absolutely, John and John, happy to be here. >> You bet, so Ellucian, a leader in higher education software, we've talked a little bit about the company. 2,400 institutions around the world with which you work. Most of those, about 2,000 here in the US. Let's talk about that work, the kind of nature of the work first and then we'll jump into a little bit about how they're playing in the Cloud these days. >> Sure absolutely happy to, so the Ellucian's got a sole focus in higher education. So it's really the only industry that we serve. We serve the industry really from a software, enterprise software prospective. So that's really helping from an ERP perspective, HR finance, but really our bread and butter is the student system and it's really the systems around helping students achieve success. As they, go to a community college or go to a four year public or four year private. It's really about helping those students drive success. And actually get the successful outcomes. And we do that with registration, with advisement, with recruiting systems, so there's a full breadth of software that an institution needs in order to help a student successfully go through that process of getting a degree and ultimately getting a job. >> Well John and I can both relate to that. He's got a daughter who's transferring over to Cal Berkeley. Going to be going to school there. I've got a niece starting at UNC Wilmington that I'm helping out, I love the registration help. So, you and I need to talk about it. >> Absolutely. >> A question is how do you get the kids into the schools they want, is there a back door Trojan horse? >> We can't manipulate that much. But you talk about your company does data rich inside pour, which I thought that was an interesting way to kind of look at things. Like we have this huge treasure trove of information and data but yet maybe there's somewhat of a disconnect in interpreting that data and then putting it value, putting it to use. What do you see with regard to that in the higher education space? >> You know, I think John, that's a great question. That's actually a really big focus of ours in terms of unlocking that data. If you think about the systems that have been on campus for 30 years right. You've got all kinds of information about the students that have attended, the classes that they take and how well they've succeeded, the types of advising that they needed. But how do you unlock all of the rich information so that you can take that information, drive some insight and then just drive better outcomes? We've been working on a platform, we call it Ethos and what we basically built is a new data model for higher education where we've looked at all of those different systems and we've basically harmonized to a new data model that really sits above all of those systems. And we begin now to extract all of that information out from those systems, into a data model that's really designed around bringing role based or persona based insight. And we call it role based analytics. That basically is designed around answering the top five to seven questions that all of the people that are on campus have. So if you're a registrar and you want to know what classes should I be adding that I need extras of. Well, that's a tough question to answer, we unlock the answer to that through the Ethos platform and the new persona based analytics that we're developing. Cause when we sit down and we talk to presidents of a school or we talk to the provost, one of the things that they want is they want to know that the people that they have working on campus for student outcomes are getting access to the information that they need to do their jobs better. And so that's been a clear mandate from our customers to help them do a better job of using the information that they're collecting. >> How do you guys deal with the data science side of this Because it's interesting is that you're using data aggressively, Cloud's perfect for that. You got a lot of compute available, how are you guys taking that legacy environment and kind of putting overlay on top of a really high, functional analytic system? >> That's a great question John. So what we do is we enable all of our software, whether it be on premise software, most of our customers still run a lot of their software on premise. And what we've built for those systems is a set of restful APIs that we deliver wherever that software runs to push that data into an AWS cloud environment where we begin putting that data in the columnar databases that are really built and constructed to help get insight very, very quickly from that data. The most important part of doing that is really sitting down and talking to the person that has the question to understand, what's the question that you're trying to answer that you haven't been able to answer? And then building the visualization that they need that actually helps them answer that question. But we took it one step further, and what we did is we basically said, we know through our research that that first question really just always yields another question. Which then yields another question and so what we did is we built a heuristic capability into the analytic platform that based on the user, based on who they are, based on the role that they had at a school and based on other people that look like them and act like them and have that role. The system begins to learn the questions that are being asked and then where are they navigating to? What are the next questions, so that we actually begin presenting the users not just with the answer to the first question that they have, but actually to, we believe that now that you've got the answer to this, that this is where you're going to go next from an inside perspective. The next types of questions so we begin to guide the users and that's really where that guided nature comes from. >> So what's the next question John's going to ask then? >> This brings up the whole cognitive computing thing. The idea that predictive analytics are one thing, you've got prescription analytics also you've got the notion of recommendation engines. All kinds of cool things that are just sitting out there waiting to be applied, the question is how do you get the data, that's the number one problem. >> That's a good one, so we've got, one of the solutions that we have in our CR Import folio is called Advise. And what we do with that product is we actually bring all of the student data, so we bring their attendance data, we bring their health records, we bring all of the grades that they have. And we then build cohorts where we have like students. And what we begin to do is we begin to build a predictive model to find students that are at risk. That based on these attendance patters in these classes, we know that this set of students is likely to have a poor outcome. And so what we want to do is not just identify that, well, now they're at risk but it's the predictive side of, well what should you do, what is the actual intervention that you need to take that's going to drive a better outcome? So the solution actually takes all the data and does two things. First, it identifies who are the students that we want to be working with, could be at risk, could be hypos right, could by high potential students that we want to accelerate. But then it's about driving the actual actions and the interactions with those students. It is not just about identifying well, Johnny's going to be in trouble, it's well, okay, what should we do for Johnny to help him get out of trouble? And so it's both sides of that. So, it is about polling all of the data which means you need to understand where the data lives. We have an advantage there over, pretty much everyone else in higher education because those 2,400 institutions that we have, they are running a massive amount of our software from a portfolio perspective. So we know where the data is, so we know how to go out and get it. And then if you look at our partner, ecosystem we have over 130 partners that also serve higher education with us. And we know what data they have and we are enabling all of those partners to leverage the Ethos platform. To be able to share that data, both from an integration and interoperability perspective. But also to feed that cloud analytic solution as well. >> One of the cool things you're doing with AWS, I'll say, they pretty much run the table on public cloud, we see the numbers there. They're in the chapter of their company or divisions, like the way a company, I call the team period. I call it the enterprise years. Govnow is like really going, it's like reinvent size. It's getting to that level, what's the impact that that's having and what are some of the things that you're doing with AWS inside the public sector that's notable. >> That's a great question, I think one of the big things is we have a really, really strong go to market partnership with AWS. And I say the go to market side because we've had a really strong technical partnership with them for many years. Where we've been working with them as they've developed new services and we've been able to leverage those services to build micro applications, to build elastic applications, all of that. And that's great form a technical perspective but now it's about bringing all of that to market. We have a very strong joint partnership with. >> John: How many years has it gone back? >> About two and a half, three years. So our enterprise agreement is two and half years old. We were doing work with them before that. But it's about two and a half years old and when I look at that, we deploy all of our cloud applications solely on AWS. So they are the sole cloud provider for us. We've expanded our cloud offering outside of the United States, we're in Dublin, we have a data center in Sydney, Australia. And we are just expanded into their new data center in the eastern Canada area in Montreal. And that's helped us from a go to market because what they bring for us, is they bring that credibility of delivering cloud infrastructure. We bring credibility of delivering higher education solutions that solve specific problems that only exist in higher education. It's that combination when you go to market to basically say the world's leading infrastructure cloud provider partnered with the world's leading solution provider in higher education. That's an unbeatable solution for us. >> So I got to ask you the question that people might ask. Hey, I've not been following AWS public sector. I see the Wall Street Journal articles, they're killing it. How would you describe their current state of innovation, their current presence in the public sector market as of right now? >> I think the lens that I really have is really around that higher education, so community colleges, public four year schools and they are highly focused on it. They have a team of dedicated people that are just focused on higher education. They work with us kind of from a joint perspective and I know that my cloud business that I'm responsible for, it is the fastest growing part of Ellucian today. So in June of 2016, we actually surpassed, form a growth perspective we started growing much faster than the on premise side of our business. And that's in large part because of what AWS has enabled us to do, so from a training perspective, from a sales motion perspective, from a marketing and positioning perspective. It's a big focus for them. >> Would you consider them, like the perception of them would be they're getting traction, they've cleared the runway, they're at cruising altitude. Where are they in the mind share of higher eds? >> I definitely think, they've cleared the runway. They are clearly going past that 10,000 foot and up there. For us, one of the main reasons we chose AWS was that factor, they already had traction. They were well known and well understood and that really helps us. Prior to that, we were doing a co location where we were managing a bunch of infrastructure, that was a hard sell, cause let's face it, we're software people, not infrastructure people. When we started bringing AWS to the table and basically talking about that's where we deploy. That took a lot of questions around scale, security, elasticity and it basically put it all to rest. So we no longer have to contend with those questions because AWS is well known in the higher education space. So it really worked well for us. >> So when you sit down with a new client or new perspective client, the two of you, you come in with this great resume and I think is where it's kind of interesting to me, universities are these fountains of innovation and creative thinking. IT, maybe not so much, because it's very institutional. There's a lot of legacy baggage they're bringing along. So what are the impediments that you run into in terms of talking to folks who might be, not doubters, but maybe a little resistant to change or maybe have a little change aversion. I mean how do you go about bringing them along on that journey? >> What's interesting in terms of higher education is there's actually a couple things that are happening that really help us with that, that are happening. But to answer the first question John which was when we get into that, not really a battle. But when we get into that dialogue, where they're like well I'm not really sure that moving to the cloud is the right thing. There's an analyst that covers higher education and she's made a statement that basically is, by 2020, a no cloud policy on campus is going to be much like a no internet policy on campus. Just not going to be a thing. And a lot of that is because a lot of providers are only building cloud solutions. That's all you're going to have access to. One of the things that's happening in higher education is in the IT space particularly, they're having a hard time finding those IT professionals. Because higher education isn't seen IT wise as a sexy place to go. And so a lot of those people that have been working in higher education for 25, 30 years, they're reaching that retirement age, and so. >> John: The main frame guys. >> Right, the main frame guys, the Unix guys. And where do you go find replacements for those. And so, they're recognizing that, okay, well that's going to be a problem for us. And right there's a lot of the infrastructure, on premise infrastructure is getting old. So does it make sense to put that capital investment into infrastructure or I got other capital investment for research and research equipment that I'd much rather put, if I'm a president, I'd much rather put the money there. That also leads to an easier conversation around that journey to the cloud, that journey of taking your enterprise systems and moving them to cloud environments. The other thing that we find is, the conversation is never really around cost savings. What it's really around is the redeployment of those IT resources to be better business partners, to be business analysts, to be people that can actually be change agents at the university to bring about change cause they're no longer managing operating systems or writing network patches or security patches. They've offloaded that to us and we've offloaded part of that work to AWS. >> Well, we appreciate the perspective. Like you said, it sounds like you've got quite a corner on the market, 2,400 partners, if you will out there. Many of those overseas, so congratulations on that front. >> Thank you. >> And I wish you continued success and thanks for joining us on The Cube, first time I think right? >> Yep, first time. >> We have rookies across the board. >> But you're now a Cube alumni. >> I appreciate it. >> Look forward to having you back. >> Thanks John and John, appreciate it. >> Back with more from Washington, DC at the AWS Public Sector Summit, 2017. You're watching live on the Cube. (upbeat music)