(ambient music) >> Good morning, everyone. Lisa Martin with theCUBE, live at the eighth Annual Women in Data Science Conference. This is one of my absolute favorite events of the year. We engage with tons of great inspirational speakers, men and women, and what's happening with WiDS is a global movement. I've got two fabulous co-hosts with me today that you're going to be hearing and meeting. Please welcome Tracy Zhang and Hannah Freitag, who are both from the sata journalism program, master's program, at Stanford. So great to have you guys. >> So excited to be here. >> So data journalism's so interesting. Tracy, tell us a little bit about you, what you're interested in, and then Hannah we'll have you do the same thing. >> Yeah >> Yeah, definitely. I definitely think data journalism is very interesting, and in fact, I think, what is data journalism? Is definitely one of the big questions that we ask during the span of one year, which is the length of our program. And yeah, like you said, I'm in this data journalism master program, and I think coming in I just wanted to pivot from my undergrad studies, which is more like a traditional journalism, into data. We're finding stories through data, so that's why I'm also very excited about meeting these speakers for today because they're all, they have different backgrounds, but they all ended up in data science. So I think they'll be very inspirational and I can't wait to talk to them. >> Data in stories, I love that. Hannah, tell us a little bit about you. >> Yeah, so before coming to Stanford, I was a research assistant at Humboldt University in Berlin, so I was in political science research. And I love to work with data sets and data, but I figured that, for me, I don't want this story to end up in a research paper, which is only very limited in terms of the audience. And I figured, okay, data journalism is the perfect way to tell stories and use data to illustrate anecdotes, but to make it comprehensive and accessible for a broader audience. So then I found this program at Stanford and I was like, okay, that's the perfect transition from political science to journalism, and to use data to tell data-driven stories. So I'm excited to be in this program, I'm excited for the conference today and to hear from these amazing women who work in data science. >> You both brought up great points, and we were chatting earlier that there's a lot of diversity in background. >> Tracy: Definitely. >> Not everyone was in STEM as a young kid or studied computer science. Maybe some are engineering, maybe some are are philosophy or economic, it's so interesting. And what I find year after year at WiDS is it brings in so much thought diversity. And that's what being data-driven really demands. It demands that unbiased approach, that diverse, a spectrum of diverse perspectives, and we definitely get that at WiDS. There's about 350 people in person here, but as I mentioned in the opening, hundreds of thousands will engage throughout the year, tens of thousands probably today at local events going on across the globe. And it just underscores the importance of every organization, whether it's a bank or a grocer, has to be data-driven. We have that expectation as consumers in our consumer lives, and even in our business lives, that I'm going to engage with a business, whatever it is, and they're going to know about me, they're going to deliver me a personalized experience that's relevant to me and my history. And all that is powered by data science, which is I think it's fascinating. >> Yeah, and the great way is if you combine data with people. Because after all, large data sets, they oftentimes consist of stories or data that affects people. And to find these stories or advanced research in whatever fields, maybe in the financial business, or in health, as you mentioned, the variety of fields, it's very powerful, powerful tool to use. >> It's a very power, oh, go ahead Tracy. >> No, definitely. I just wanted to build off of that. It's important to put a face on data. So a dataset without a name is just some numbers, but if there's a story, then I think it means something too. And I think Margot was talking about how data science is about knowing or understanding the past, I think that's very interesting. That's a method for us to know who we are. >> Definitely. There's so many opportunities. I wanted to share some of the statistics from AnitaB.org that I was just looking at from 2022. We always talk at events like WiDS, and some of the other women in tech things, theCUBE is very much pro-women in tech, and has been for a very long, since the beginning of theCUBE. But we've seen the numbers of women technologists historically well below 25%, and we see attrition rates are high. And so we often talk about, well, what can we do? And part of that is raising the awareness. And that's one of the great things about WiDS, especially WiDS happening on International Women's Day, today, March 8th, and around event- >> Tracy: A big holiday. >> Exactly. But one of the nice things I was looking at, the AnitaB.org research, is that representation of tech women is on the rise, still below pre-pandemic levels, but it's actually nearly 27% of women in technical roles. And that's an increase, slow increase, but the needle is moving. We're seeing much more gender diversity across a lot of career levels, which is exciting. But some of the challenges remain. I mean, the representation of women technologists is growing, except at the intern level. And I thought that was really poignant. We need to be opening up that pipeline and going younger. And you'll hear a lot of those conversations today about, what are we doing to reach girls in grade school, 10 year olds, 12 year olds, those in high school? How do we help foster them through their undergrad studies- >> And excite them about science and all these fields, for sure. >> What do you think, Hannah, on that note, and I'll ask you the same question, what do you think can be done? The theme of this year's International Women's Day is Embrace Equity. What do you think can be done on that intern problem to help really dial up the volume on getting those younger kids interested, one, earlier, and two, helping them stay interested? >> Yeah. Yeah, that's a great question. I think it's important to start early, as you said, in school. Back in the day when I went to high school, we had this one day per year where we could explore as girls, explore a STEM job and go into the job for one day and see how it's like to work in a, I dunno, in IT or in data science, so that's a great first step. But as you mentioned, it's important to keep girls and women excited about this field and make them actually pursue this path. So I think conferences or networking is very powerful. Also these days with social media and technology, we have more ability and greater ways to connect. And I think we should even empower ourselves even more to pursue this path if we're interested in data science, and not be like, okay, maybe it's not for me, or maybe as a woman I have less chances. So I think it's very important to connect with other women, and this is what WiDS is great about. >> WiDS is so fantastic for that network effect, as you talked about. It's always such, as I was telling you about before we went live, I've covered five or six WiDS for theCUBE, and it's always such a day of positivity, it's a day of of inclusivity, which is exactly what Embrace Equity is really kind of about. Tracy, talk a little bit about some of the things that you see that will help with that hashtag Embrace Equity kind of pulling it, not just to tech. Because we're talking and we saw Meta was a keynote who's going to come to talk with Hannah and me in a little bit, we see Total Energies on the program today, we see Microsoft, Intuit, Boeing Air Company. What are some of the things you think that can be done to help inspire, say, little Tracy back in the day to become interested in STEM or in technology or in data? What do you think companies can and should be doing to dial up the volume for those youngsters? >> Yeah, 'cause I think somebody was talking about, one of the keynote speakers was talking about how there is a notion that girls just can't be data scientists. girls just can't do science. And I think representation definitely matters. If three year old me see on TV that all the scientists are women, I think I would definitely have the notion that, oh, this might be a career choice for me and I can definitely also be a scientist if I want. So yeah, I think representation definitely matters and that's why conference like this will just show us how these women are great in their fields. They're great data scientists that are bringing great insight to the company and even to the social good as well. So yeah, I think that's very important just to make women feel seen in this data science field and to listen to the great woman who's doing amazing work. >> Absolutely. There's a saying, you can't be what you can't see. >> Exactly. >> And I like to say, I like to flip it on its head, 'cause we can talk about some of the negatives, but there's a lot of positives and I want to share some of those in a minute, is that we need to be, that visibility that you talked about, the awareness that you talked about, it needs to be there but it needs to be sustained and maintained. And an organization like WiDS and some of the other women in tech events that happen around the valley here and globally, are all aimed at raising the profile of these women so that the younger, really, all generations can see what they can be. We all, the funny thing is, we all have this expectation whether we're transacting on Uber ride or we are on Netflix or we're buying something on Amazon, we can get it like that. They're going to know who I am, they're going to know what I want, they're going to want to know what I just bought or what I just watched. Don't serve me up something that I've already done that. >> Hannah: Yeah. >> Tracy: Yeah. >> So that expectation that everyone has is all about data, though we don't necessarily think about it like that. >> Hannah: Exactly. >> Tracy: Exactly. >> But it's all about the data that, the past data, the data science, as well as the realtime data because we want to have these experiences that are fresh, in the moment, and super relevant. So whether women recognize it or not, they're data driven too. Whether or not you're in data science, we're all driven by data and we have these expectations that every business is going to meet it. >> Exactly. >> Yeah. And circling back to young women, I think it's crucial and important to have role models. As you said, if you see someone and you're younger and you're like, oh I want to be like her. I want to follow this path, and have inspiration and a role model, someone you look up to and be like, okay, this is possible if I study the math part or do the physics, and you kind of have a goal and a vision in mind, I think that's really important to drive you. >> Having those mentors and sponsors, something that's interesting is, I always, everyone knows what a mentor is, somebody that you look up to, that can guide you, that you admire. I didn't learn what a sponsor was until a Women in Tech event a few years ago that we did on theCUBE. And I was kind of, my eyes were open but I didn't understand the difference between a mentor and a sponsor. And then it got me thinking, who are my sponsors? And I started going through LinkedIn, oh, he's a sponsor, she's a sponsor, people that help really propel you forward, your recommenders, your champions, and it's so important at every level to build that network. And we have, to your point, Hannah, there's so much potential here for data drivenness across the globe, and there's so much potential for women. One of the things I also learned recently , and I wanted to share this with you 'cause I'm not sure if you know this, ChatGPT, exploding, I was on it yesterday looking at- >> Everyone talking about it. >> What's hot in data science? And it was kind of like, and I actually asked it, what was hot in data science in 2023? And it told me that it didn't know anything prior to 2021. >> Tracy: Yes. >> Hannah: Yeah. >> So I said, Oh, I'm so sorry. But everyone's talking about ChatGPT, it is the most advanced AI chatbot ever released to the masses, it's on fire. They're likening it to the launch of the iPhone, 100 million-plus users. But did you know that the CTO of ChatGPT is a woman? >> Tracy: I did not know, but I learned that. >> I learned that a couple days ago, Mira Murati, and of course- >> I love it. >> She's been, I saw this great profile piece on her on Fast Company, but of course everything that we're hearing about with respect to ChatGPT, a lot on the CEO. But I thought we need to help dial up the profile of the CTO because she's only 35, yet she is at the helm of one of the most groundbreaking things in our lifetime we'll probably ever see. Isn't that cool? >> That is, yeah, I completely had no idea. >> I didn't either. I saw it on LinkedIn over the weekend and I thought, I have to talk about that because it's so important when we talk about some of the trends, other trends from AnitaB.org, I talked about some of those positive trends. Overall hiring has rebounded in '22 compared to pre-pandemic levels. And we see also 51% more women being hired in '22 than '21. So the data, it's all about data, is showing us things are progressing quite slowly. But one of the biggest challenges that's still persistent is attrition. So we were talking about, Hannah, what would your advice be? How would you help a woman stay in tech? We saw that attrition last year in '22 according to AnitaB.org, more than doubled. So we're seeing women getting into the field and dropping out for various reasons. And so that's still an extent concern that we have. What do you think would motivate you to stick around if you were in a technical role? Same question for you in a minute. >> Right, you were talking about how we see an increase especially in the intern level for women. And I think if, I don't know, this is a great for a start point for pushing the momentum to start growth, pushing the needle rightwards. But I think if we can see more increase in the upper level, the women representation in the upper level too, maybe that's definitely a big goal and something we should work towards to. >> Lisa: Absolutely. >> But if there's more representation up in the CTO position, like in the managing level, I think that will definitely be a great factor to keep women in data science. >> I was looking at some trends, sorry, Hannah, forgetting what this source was, so forgive me, that was showing that there was a trend in the last few years, I think it was Fast Company, of more women in executive positions, specifically chief operating officer positions. What that hasn't translated to, what they thought it might translate to, is more women going from COO to CEO and we're not seeing that. We think of, if you ask, name a female executive that you'd recognize, everyone would probably say Sheryl Sandberg. But I was shocked to learn the other day at a Women in Tech event I was doing, that there was a survey done by this organization that showed that 78% of people couldn't identify. So to your point, we need more of them in that visible role, in the executive suite. >> Tracy: Exactly. >> And there's data that show that companies that have women, companies across industries that have women in leadership positions, executive positions I should say, are actually more profitable. So it's kind of like, duh, the data is there, it's telling you this. >> Hannah: Exactly. >> Right? >> And I think also a very important point is work culture and the work environment. And as a woman, maybe if you enter and you work two or three years, and then you have to oftentimes choose, okay, do I want family or do I want my job? And I think that's one of the major tasks that companies face to make it possible for women to combine being a mother and being a great data scientist or an executive or CEO. And I think there's still a lot to be done in this regard to make it possible for women to not have to choose for one thing or the other. And I think that's also a reason why we might see more women at the entry level, but not long-term. Because they are punished if they take a couple years off if they want to have kids. >> I think that's a question we need to ask to men too. >> Absolutely. >> How to balance work and life. 'Cause we never ask that. We just ask the woman. >> No, they just get it done, probably because there's a woman on the other end whose making it happen. >> Exactly. So yeah, another thing to think about, another thing to work towards too. >> Yeah, it's a good point you're raising that we have this conversation together and not exclusively only women, but we all have to come together and talk about how we can design companies in a way that it works for everyone. >> Yeah, and no slight to men at all. A lot of my mentors and sponsors are men. They're just people that I greatly admire who saw raw potential in me 15, 18 years ago, and just added a little water to this little weed and it started to grow. In fact, theCUBE- >> Tracy: And look at you now. >> Look at me now. And theCUBE, the guys Dave Vellante and John Furrier are two of those people that are sponsors of mine. But it needs to be diverse. It needs to be diverse and gender, it needs to include non-binary people, anybody, shouldn't matter. We should be able to collectively work together to solve big problems. Like the propaganda problem that was being discussed in the keynote this morning with respect to China, or climate change. Climate change is a huge challenge. Here, we are in California, we're getting an atmospheric river tomorrow. And Californians and rain, we're not so friendly. But we know that there's massive changes going on in the climate. Data science can help really unlock a lot of the challenges and solve some of the problems and help us understand better. So there's so much real-world implication potential that being data-driven can really lead to. And I love the fact that you guys are studying data journalism. You'll have to help me understand that even more. But we're going to going to have great conversations today, I'm so excited to be co-hosting with both of you. You're going to be inspired, you're going to learn, they're going to learn from us as well. So let's just kind of think of this as a community of men, women, everything in between to really help inspire the current generations, the future generations. And to your point, let's help women feel confident to be able to stay and raise their hand for fast-tracking their careers. >> Exactly. >> What are you guys, last minute, what are you looking forward to most for today? >> Just meeting these great women, I can't wait. >> Yeah, learning from each other. Having this conversation about how we can make data science even more equitable and hear from the great ideas that all these women have. >> Excellent, girls, we're going to have a great day. We're so glad that you're here with us on theCUBE, live at Stanford University, Women in Data Science, the eighth annual conference. I'm Lisa Martin, my two co-hosts for the day, Tracy Zhang, Hannah Freitag, you're going to be seeing a lot of us, we appreciate. Stick around, our first guest joins Hannah and me in just a minute. (ambient music)

(upbeat intro music) >> Hello everyone. Welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier, here in Palo Alto, California. Got a special remote guest coming in. Teresa Carlson, President and Chief Commercial Officer at Flexport, theCUBE alumni, one of the first, let me go back to 2013, Teresa, former AWS. Great to see you. Thanks for coming on. >> Oh my gosh, almost 10 years. That is unbelievable. It's hard to believe so many years of theCUBE. I love it. >> It's been such a great honor to interview you and follow your career. You've had quite the impressive run, executive level woman in tech. You've done such an amazing job, not only in your career, but also helping other women. So I want to give you props to that before we get started. Thank you. >> Thank you, John. I, it's my, it's been my honor and privilege. >> Let's talk about Flexport. Tell us about your new role there and what it's all about. >> Well, I love it. I'm back working with another Amazonian, Dave Clark, who is our CEO of Flexport, and we are about 3,000 people strong globally in over 90 countries. We actually even have, we're represented in over 160 cities and with local governments and places around the world, which I think is super exciting. We have over 100 network partners and growing, and we are about empowering the global supply chain and trade and doing it in a very disruptive way with the use of platform technology that allows our customers to really have visibility and insight to what's going on. And it's a lot of fun. I'm learning new things, but there's a lot of technology in this as well, so I feel right at home. >> You quite have a knack from mastering growth, technology, and building out companies. So congratulations, and scaling them up too with the systems and processes. So I want to get into that. Let's get into your personal background. Then I want to get into the work you've done and are doing for empowering women in tech. What was your journey about, how did it all start? Like, I know you had a, you know, bumped into it, you went Microsoft, AWS. Take us through your career, how you got into tech, how it all happened. >> Well, I do like to give a shout out, John, to my roots and heritage, which was a speech and language pathologist. So I did start out in healthcare right out of, you know, university. I had an undergraduate and a master's degree. And I do tell everyone now, looking back at my career, I think it was super helpful for me because I learned a lot about human communication, and it has done me very well over the years to really try to understand what environments I'm in and what kind of individuals around the world culturally. So I'm really blessed that I had that opportunity to work in healthcare, and by the way, a shout out to all of our healthcare workers that has helped us get through almost three years of COVID and flu and neurovirus and everything else. So started out there and then kind of almost accidentally got into technology. My first small company I worked for was a company called Keyfile Corporation, which did workflow and document management out of Nashua, New Hampshire. And they were a Microsoft goal partner. And that is actually how I got into big tech world. We ran on exchange, for everybody who knows that term exchange, and we were a large small partner, but large in the world of exchange. And those were the days when you would, the late nineties, you would go and be in the same room with Bill Gates and Steve Ballmer. And I really fell in love with Microsoft back then. I thought to myself, wow, if I could work for a big tech company, I got to hear Bill on stage about saving, he would talk about saving the world. And guess what my next step was? I actually got a job at Microsoft, took a pay cut and a job downgrade. I tell this story all the time. Took like three downgrades in my role. I had been a SVP and went to a manager, and it's one of the best moves I ever made. And I shared that because I really didn't know the world of big tech, and I had to start from the ground up and relearn it. I did that, I just really loved that job. I was at Microsoft from 2000 to 2010, where I eventually ran all of the U.S. federal government business, which was a multi-billion dollar business. And then I had the great privilege of meeting an amazing man, Andy Jassy, who I thought was just unbelievable in his insights and knowledge and openness to understanding new markets. And we talked about government and how government needed the same great technology as every startup. And that led to me going to work for Andy in 2010 and starting up our worldwide public sector business. And I pinch myself some days because we went from two people, no offices, to the time I left we had over 10,000 people, billions in revenue, and 172 countries and had done really amazing work. I think changing the way public sector and government globally really thought about their use of technology and Cloud computing in general. And that kind of has been my career. You know, I was there till 2020, 21 and then did a small stint at Splunk, a small stint back at Microsoft doing a couple projects for Microsoft with CEO, Satya Nadella, who is also an another amazing CEO and leader. And then Dave called me, and I'm at Flexport, so I couldn't be more honored, John. I've just had such an amazing career working with amazing individuals. >> Yeah, I got to say the Amazon One well-documented, certainly by theCUBE and our coverage. We watched you rise and scale that thing. And like I said at a time, this will when we look back as a historic run because of the build out. I mean as a zero to massive billions at a historic time where government was transforming, I would say Microsoft had a good run there with Fed, but it was already established stuff. Federal business was like, you know, blocking and tackling. The Amazon was pure build out. So I have to ask you, what was your big learnings? Because one, you're a Seattle big tech company kind of entrepreneurial in the sense of you got, here's some working capital seed finance and go build that thing, and you're in DC and you're a woman. What did you learn? >> I learned that you really have to have a lot of grit. You, my mom and dad, these are kind of more southern roots words, but stick with itness, you know. you can't give up and no's not in your vocabulary. I found no is just another way to get to yes. That you have to figure out what are all the questions people are going to ask you. I learned to be very patient, and I think one of the things John, for us was our secret sauce was we said to ourselves, if we're going to do something super transformative and truly disruptive, like Cloud computing, which the government really had not utilized, we had to be patient. We had to answer all their questions, and we could not judge in any way what they were thinking because if we couldn't answer all those questions and prove out the capabilities of Cloud computing, we were not going to accomplish our goals. And I do give so much credit to all my colleagues there from everybody like Steve Schmidt who was there, who's still there, who's the CISO, and Charlie Bell and Peter DeSantis and the entire team there that just really helped build that business out. Without them, you know, we would've just, it was a team effort. And I think that's the thing I loved about it was it was not just sales, it was product, it was development, it was data center operations, it was legal, finance. Everybody really worked as a team and we were on board that we had to make a lot of changes in the government relations team. We had to go into Capitol Hill. We had to talk to them about the changes that were required and really get them to understand why Cloud computing could be such a transformative game changer for the way government operates globally. >> Well, I think the whole world and the tech world can appreciate your work and thank you later because you broke down those walls asking those questions. So great stuff. Now I got to say, you're in kind of a similar role at Flexport. Again, transformative supply chain, not new. Computing wasn't new when before Cloud came. Supply chain, not a new concept, is undergoing radical change and transformation. Online, software supply chain, hardware supply chain, supply chain in general, shipping. This is a big part of our economy and how life is working. Similar kind of thing going on, build out, growth, scale. >> It is, it's very much like that, John, I would say, it's, it's kind of a, the model with freight forwarding and supply chain is fairly, it's not as, there's a lot of technology utilized in this global supply chain world, but it's not integrated. You don't have a common operating picture of what you're doing in your global supply chain. You don't have easy access to the information and visibility. And that's really, you know, I was at a conference last week in LA, and it was, the themes were so similar about transparency, access to data and information, being able to act quickly, drive change, know what was happening. I was like, wow, this sounds familiar. Data, AI, machine learning, visibility, common operating picture. So it is very much the same kind of themes that you heard even with government. I do believe it's an industry that is going through transformation and Flexport has been a group that's come in and said, look, we have this amazing idea, number one to give access to everyone. We want every small business to every large business to every government around the world to be able to trade their goods, think about supply chain logistics in a very different way with information they need and want at their fingertips. So that's kind of thing one, but to apply that technology in a way that's very usable across all systems from an integration perspective. So it's kind of exciting. I used to tell this story years ago, John, and I don't think Michael Dell would mind that I tell this story. One of our first customers when I was at Keyfile Corporation was we did workflow and document management, and Dell was one of our customers. And I remember going out to visit them, and they had runners and they would run around, you know, they would run around the floor and do their orders, right, to get all those computers out the door. And when I think of global trade, in my mind I still see runners, you know, running around and I think that's moved to a very digital, right, world that all this stuff, you don't need people doing this. You have machines doing this now, and you have access to the information, and you know, we still have issues resulting from COVID where we have either an under-abundance or an over-abundance of our supply chain. We still have clogs in our shipping, in the shipping yards around the world. So we, and the ports, so we need to also, we still have some clearing to do. And that's the reason technology is important and will continue to be very important in this world of global trade. >> Yeah, great, great impact for change. I got to ask you about Flexport's inclusion, diversity, and equity programs. What do you got going on there? That's been a big conversation in the industry around keeping a focus on not making one way more than the other, but clearly every company, if they don't have a strong program, will be at a disadvantage. That's well reported by McKinsey and other top consultants, diverse workforces, inclusive, equitable, all perform better. What's Flexport's strategy and how are you guys supporting that in the workplace? >> Well, let me just start by saying really at the core of who I am, since the day I've started understanding that as an individual and a female leader, that I could have an impact. That the words I used, the actions I took, the information that I pulled together and had knowledge of could be meaningful. And I think each and every one of us is responsible to do what we can to make our workplace and the world a more diverse and inclusive place to live and work. And I've always enjoyed kind of the thought that, that I could help empower women around the world in the tech industry. Now I'm hoping to do my little part, John, in that in the supply chain and global trade business. And I would tell you at Flexport we have some amazing women. I'm so excited to get to know all. I've not been there that long yet, but I'm getting to know we have some, we have a very diverse leadership team between men and women at Dave's level. I have some unbelievable women on my team directly that I'm getting to know more, and I'm so impressed with what they're doing. And this is a very, you know, while this industry is different than the world I live in day to day, it's also has a lot of common themes to it. So, you know, for us, we're trying to approach every day by saying, let's make sure both our interviewing cycles, the jobs we feel, how we recruit people, how we put people out there on the platforms, that we have diversity and inclusion and all of that every day. And I can tell you from the top, from Dave and all of our leaders, we just had an offsite and we had a big conversation about this is something. It's a drum beat that we have to think about and live by every day and really check ourselves on a regular basis. But I do think there's so much more room for women in the world to do great things. And one of the, one of the areas, as you know very well, we lost a lot of women during COVID, who just left the workforce again. So we kind of went back unfortunately. So we have to now move forward and make sure that we are giving women the opportunity to have great jobs, have the flexibility they need as they build a family, and have a workplace environment that is trusted for them to come into every day. >> There's now clear visibility, at least in today's world, not withstanding some of the setbacks from COVID, that a young girl can look out in a company and see a path from entry level to the boardroom. That's a big change. A lot than even going back 10, 15, 20 years ago. What's your advice to the folks out there that are paying it forward? You see a lot of executive leaderships have a seat at the table. The board still underrepresented by most numbers, but at least you have now kind of this solidarity at the top, but a lot of people doing a lot more now than I've seen at the next levels down. So now you have this leveled approach. Is that something that you're seeing more of? And credit compare and contrast that to 20 years ago when you were, you know, rising through the ranks? What's different? >> Well, one of the main things, and I honestly do not think about it too much, but there were really no women. There were none. When I showed up in the meetings, I literally, it was me or not me at the table, but at the seat behind the table. The women just weren't in the room, and there were so many more barriers that we had to push through, and that has changed a lot. I mean globally that has changed a lot in the U.S. You know, if you look at just our U.S. House of Representatives and our U.S. Senate, we now have the increasing number of women. Even at leadership levels, you're seeing that change. You have a lot more women on boards than we ever thought we would ever represent. While we are not there, more female CEOs that I get an opportunity to see and talk to. Women starting companies, they do not see the barriers. And I will share, John, globally in the U.S. one of the things that I still see that we have that many other countries don't have, which I'm very proud of, women in the U.S. have a spirit about them that they just don't see the barriers in the same way. They believe that they can accomplish anything. I have two sons, I don't have daughters. I have nieces, and I'm hoping someday to have granddaughters. But I know that a lot of my friends who have granddaughters today talk about the boldness, the fortitude, that they believe that there's nothing they can't accomplish. And I think that's what what we have to instill in every little girl out there, that they can accomplish anything they want to. The world is theirs, and we need to not just do that in the U.S., but around the world. And it was always the thing that struck me when I did all my travels at AWS and now with Flexport, I'm traveling again quite a bit, is just the differences you see in the cultures around the world. And I remember even in the Middle East, how I started seeing it change. You've heard me talk a lot on this program about the fact in both Saudi and Bahrain, over 60% of the tech workers were females and most of them held the the hardest jobs, the security, the architecture, the engineering. But many of them did not hold leadership roles. And that is what we've got to change too. To your point, the middle, we want it to get bigger, but the top, we need to get bigger. We need to make sure women globally have opportunities to hold the most precious leadership roles and demonstrate their capabilities at the very top. But that's changed. And I would say the biggest difference is when we show up, we're actually evaluated properly for those kind of roles. We have a ways to go. But again, that part is really changing. >> Can you share, Teresa, first of all, that's great work you've done and I wan to give you props of that as well and all the work you do. I know you champion a lot of, you know, causes in in this area. One question that comes up a lot, I would love to get your opinion 'cause I think you can contribute heavily here is mentoring and sponsorship is huge, comes up all the time. What advice would you share to folks out there who were, I won't say apprehensive, but maybe nervous about how to do the networking and sponsorship and mentoring? It's not just mentoring, it's sponsorship too. What's your best practice? What advice would you give for the best way to handle that? >> Well yeah, and for the women out there, I would say on the mentorship side, I still see mentorship. Like, I don't think you can ever stop having mentorship. And I like to look at my mentors in different parts of my life because if you want to be a well-rounded person, you may have parts of your life every day that you think I'm doing a great job here and I definitely would like to do better there. Whether it's your spiritual life, your physical life, your work life, you know, your leisure life. But I mean there's, and there's parts of my leadership world that I still seek advice from as I try to do new things even in this world. And I tried some new things in between roles. I went out and asked the people that I respected the most. So I just would say for sure have different mentorships and don't be afraid to have that diversity. But if you have mentorships, the second important thing is show up with a real agenda and questions. Don't waste people's time. I'm very sensitive today. If you're, if you want a mentor, you show up and you use your time super effectively and be prepared for that. Sponsorship is a very different thing. And I don't believe we actually do that still in companies. We worked, thank goodness for my great HR team. When I was at AWS, we worked on a few sponsorship programs where for diversity in general, where we would nominate individuals in the company that we felt that weren't, that had a lot of opportunity for growth, but they just weren't getting a seat at the table. And we brought 'em to the table. And we actually kind of had a Chatham House rules where when they came into the meetings, they had a sponsor, not a mentor. They had a sponsor that was with them the full 18 months of this program. We would bring 'em into executive meetings. They would read docs, they could ask questions. We wanted them to be able to open up and ask crazy questions without, you know, feeling wow, I just couldn't answer this question in a normal environment or setting. And then we tried to make sure once they got through the program that we found jobs and support and other special projects that they could go do. But they still had that sponsor and that group of individuals that they'd gone through the program with, John, that they could keep going back to. And I remember sitting there and they asked me what I wanted to get out of the program, and I said two things. I want you to leave this program and say to yourself, I would've never had that experience if I hadn't gone through this program. I learned so much in 18 months. It would probably taken me five years to learn. And that it helped them in their career. The second thing I told them is I wanted them to go out and recruit individuals that look like them. I said, we need diversity, and unless you all feel that we are in an inclusive environment sponsoring all types of individuals to be part of this company, we're not going to get the job done. And they said, okay. And you know, but it was really one, it was very much about them. That we took a group of individuals that had high potential and a very diverse with diverse backgrounds, held 'em up, taught 'em things that gave them access. And two, selfishly I said, I want more of you in my business. Please help me. And I think those kind of things are helpful, and you have to be thoughtful about these kind of programs. And to me that's more sponsorship. I still have people reach out to me from years ago, you know, Microsoft saying, you were so good with me, can you give me a reference now? Can you talk to me about what I should be doing? And I try to, I'm not pray 100%, some things pray fall through the cracks, but I always try to make the time to talk to those individuals because for me, I am where I am today because I got some of the best advice from people like Don Byrne and Linda Zecker and Andy Jassy, who were very honest and upfront with me about my career. >> Awesome. Well, you got a passion for empowering women in tech, paying it forward, but you're quite accomplished and that's why we're so glad to have you on the program here. President and Chief Commercial Officer at Flexport. Obviously storied career and your other jobs, specifically Amazon I think, is historic in my mind. This next chapter looks like it's looking good right now. Final question for you, for the few minutes you have left. Tell us what you're up to at Flexport. What's your goals as President, Chief Commercial Officer? What are you trying to accomplish? Share a little bit, what's on your mind with your current job? >> Well, you kind of said it earlier. I think if I look at my own superpowers, I love customers, I love partners. I get my energy, John, from those interactions. So one is to come in and really help us build even a better world class enterprise global sales and marketing team. Really listen to our customers, think about how we interact with them, build the best executive programs we can, think about new ways that we can offer services to them and create new services. One of my favorite things about my career is I think if you're a business leader, it's your job to come back around and tell your product group and your services org what you're hearing from customers. That's how you can be so much more impactful, that you listen, you learn, and you deliver. So that's one big job. The second job for me, which I am so excited about, is that I have an amazing group called flexport.org under me. And flexport.org is doing amazing things around the world to help those in need. We just announced this new funding program for Tech for Refugees, which brings assistance to millions of people in Ukraine, Pakistan, the horn of Africa, and those who are affected by earthquakes. We just took supplies into Turkey and Syria, and Flexport, recently in fact, just did sent three air shipments to Turkey and Syria for these. And I think we did over a hundred trekking shipments to get earthquake relief. And as you can imagine, it was not easy to get into Syria. But you know, we're very active in the Ukraine, and we are, our goal for flexport.org, John, is to continue to work with our commercial customers and team up with them when they're trying to get supplies in to do that in a very cost effective, easy way, as quickly as we can. So that not-for-profit side of me that I'm so, I'm so happy. And you know, Ryan Peterson, who was our founder, this was his brainchild, and he's really taken this to the next level. So I'm honored to be able to pick that up and look for new ways to have impact around the world. And you know, I've always found that I think if you do things right with a company, you can have a beautiful combination of commercial-ity and giving. And I think Flexport does it in such an amazing and unique way. >> Well, the impact that they have with their system and their technology with logistics and shipping and supply chain is a channel for societal change. And I think that's a huge gift that you have that under your purview. So looking forward to finding out more about flexport.org. I can only imagine all the exciting things around sustainability, and we just had Mobile World Congress for Big Cube Broadcast, 5Gs right around the corner. I'm sure that's going to have a huge impact to your business. >> Well, for sure. And just on gas emissions, that's another thing that we are tracking gas, greenhouse gas emissions. And in fact we've already reduced more than 300,000 tons and supported over 600 organizations doing that. So that's a thing we're also trying to make sure that we're being climate aware and ensuring that we are doing the best job we can at that as well. And that was another thing I was honored to be able to do when we were at AWS, is to really cut out greenhouse gas emissions and really go global with our climate initiatives. >> Well Teresa, it's great to have you on. Security, data, 5G, sustainability, business transformation, AI all coming together to change the game. You're in another hot seat, hot roll, big wave. >> Well, John, it's an honor, and just thank you again for doing this and having women on and really representing us in a big way as we celebrate International Women's Day. >> I really appreciate it, it's super important. And these videos have impact, so we're going to do a lot more. And I appreciate your leadership to the industry and thank you so much for taking the time to contribute to our effort. Thank you, Teresa. >> Thank you. Thanks everybody. >> Teresa Carlson, the President and Chief Commercial Officer of Flexport. I'm John Furrier, host of theCUBE. This is International Women's Day broadcast. Thanks for watching. (upbeat outro music)

>>Welcome back here on the Cube. I'm John Walls. We are in Las Vegas at the Venetian, and this is Reinvent 22 in the Executive Summit sponsored by Accenture. Glad to have you with us here as we continue our conversations. I'm joined by Paul Puckett, who's the former director of the Enterprise Cloud Management Services at the US Army. Paul, good to see you sir. Hey, you as well, John. Thank you. And Justin, she who is managing director and cloud go to market lead at Accenture Federal Services. Justin, good morning to you. Good morning, John. Yeah, glad to have you both here on the cube. First time too, I believe, right? Yes sir. Well, welcome. I wish we had some kind of baptism or indoctrination, but I'll see what I can come up with in the next 10 minutes for you. Let's talk about the Army, Paul. So enterprise cloud management, US Army. You know, I can't imagine the scale we're talking about here. I can't imagine the solutions we're talking about. I can't imagine the users we're talking about. Just for our folks at home, paint the picture a little bit of what kind of landscape it is that you have to cover with that kind of title. >>Sure. The United States Army, about 1.4 million people. Obviously a global organization responsible for protecting and defending the United States as part of our sister services in the Department of Defense. And scale often comes up a lot, right? And we talk about any capability to your solution for the United States Army scale is the, the number one thing, but oftentimes people overlook quality first. And actually when you think of the partnership between the Army and Accenture Federal, we thought a lot when it came to establishing the enterprise Cloud management agency that we wanted to deliver quality first when it came to adopting cloud computing and then scale that quality and not so much be afraid of the, the scale of the army and the size that forces us to make bad decisions. Cuz we wanted to make sure that we proved that there was opportunity and value in the cloud first, and then we wanted to truly scale that. And so no doubt, an immense challenge. The organization's been around for now three years, but I think that we've established irreversible momentum when it comes to modernization, leveraging cloud computing >>For the army. So let's back up. You kind of threw it in there, the ecma. So this agency was, was your a collaboration, right? To create from the ground up and it's in three years in existence. So let's just talk about that. What went into that thinking? What went into the planning and then how did you actually get it up and run into the extent that it is today? >>Sure. Well, it was once the enterprise cloud management office. It was a directorate within the, the CIO G six of the United States Army. So at the headquarters, the army, the chief information Officer, and the G six, which is essentially the military arm for all IT capability were once a joint's organization and the ECMO was created to catalyze the adoption of cloud computing. The army had actually been on a, a cloud adoption journey for many years, but there wasn't a lot of value that was actually derived. And so they created the ecma, well, the ECMO at the time brought me in as the director. And so we were responsible for establishing the new strategy for the adoption of cloud. One of the components of that strategy was essentially we needed an opportunity to be able to buy cloud services at scale. And this was part of our buy secure and build model that we had in place. And so part of the buy piece, we put an acquisition strategy together around how we wanted to buy cloud at scale. We called it the cloud account management optimization. OTA >>Just rolls right off the >>Tongue, it just rolls right off the tongue. And for those that love acronyms, camo, >>Which I liked it when I was say cama, I loved that. That was, that was, >>You always have to have like a tundra, a little >>Piece of that. Very good. It was good. >>But at the time it was novetta, no, Nevada's been bought up by afs, but Novea won that agreement. And so we've had this partnership in place now for just about a year and a half for buying cloud computing net scale. >>So let's talk about, about what you deal with on, on the federal services side here, Justin, in terms of the army. So obviously governance, a major issue, compliance, a major issue, security, you know, paramount importance and all that STEM leads up to quality that Paul was talking about. So when you were looking at this and keeping all those factors in, in your mind, right? I mean, how many, like, oh my God, what kind of days did you have? Oh, well, because this was a handful. >>Well, it was, but you could see when we were responding to the acquisition that it was really, you know, forward thinking and forward leaning in terms of how they thought about cloud acquisition and cloud governance and cloud management. And it's really kind of a sleepy area like cloud account acquisition. Everyone's like, oh, it's easy to get in the cloud, you know, run your credit card on Amazon and you're in, in 30 seconds or less. That's really not the case inside the federal government, whether it's the army, the Air Force or whoever, right? Those, those are, they're real challenges in procuring and acquiring cloud. And so it was clear from, you know, Paul's office that they understood those challenges and we were excited to really meet them with them. >>And, and how, I guess from an institutional perspective, before this was right, I I assume very protective, very tight cloistered, right? You, you, in terms of being open to or, or a more open environment, there might have been some pushback was they're not. Right? So dealing with that, what did you find that to be the case? Well, so >>There's kind of a few pieces to unpacking that. There's a lot of fear in trepidation around something you don't understand, right? And so part of it is the teaching and training and the, and the capability and the opportunity in the cloud and the ability to be exceptionally secure when it comes to no doubt, the sensitivity of the information of the Department of Defense, but also from an action acquisition strategy perspective, more from a financial perspective, the DOD is accustomed to buying hardware. We make these big bets of these big things to, to live in today's centers. And so when we talk about consuming cloud as a utility, there's a lot of fear there as well, because they don't really understand how to kind of pay for something by the drink, if you will, because it incentivizes them to be more efficient with their utilization of resources. >>But when you look at the budgeting process of the d od, there really is not that much of incentive for efficiency. The p PPE process, the planning program, budgeting, execution, they care about execution, which is spending money and you can spend a lot of money in the cloud, right? But how are you actually utilizing that? And so what we wanted to do is create that feedback loop and so the utilization is actually fed into our financial systems that help us then estimate into the future. And that's the capability that we partnered with AFS on is establishing the closing of that feedback loop. So now we can actually optimize our utilization of the cloud. And that's actually driving better incentives in the PPE >>Process. You know, when you think about these keywords here, modernized, digitized, data driven, so on, so forth, I, I don't think a lot of people might connect that to the US government in general just because of, you know, it's a large intentionally slow moving bureaucratic machine, right? Is that fair to characterize it that way? It >>Is, but not in this case. Right? So what we done, >>You you totally juxtapose that. Yeah. >>Yeah. So what we've done is we've really enabled data driven decision making as it relates to cloud accounts and cloud governance. And so we have a, a tool called Cloud Tracker. We deployed for the army at a number of different classifications, and you get a full 360 view of all of your cloud utilization and cloud spend, you know, really up to date within 24 hours of it occurring, right? And there a lot of folks, you know, they didn't never went into the console, they never looked at what they were spending in cloud previously. And so now you just go to a simple web portal and see the entire entirety of the army cloud spend right there at your fingertips. So that really enables like better decision making in terms of like purchasing savings plans and reserved instances and other sorts of AWS specific tools to help you save money. >>So Paul, tell me about Cloud Tracker then. Yeah, I mean from the client side then, can you just say this dashboard lays it out for you right? In great detail about what kind of usage, what kind of efficiencies I assume Yeah. What's working, what's not? >>Absolutely. Well, and, and I think a few things to unpack that's really important here is listen, any cloud service provider has a concept. You can see what you're actually spending. But when it comes to money in the United States government, there are different colors of money. There's regulations when it comes to how money is identified for different capabilities or incentives. And you've gotta be very explicit in how you track and how you spend that money from an auditability perspective. Beyond that, there is a move when it comes to the technology business management, which is the actual labeling of what we actually spend money on for different services or labor or software. And what Cloud Tracker allows us to do is speak the language of the different colors of money. It allows us to also get very fine grain in the actual analysis of, from a TBM perspective, what we're spending on. >>But then also it has real time hooks into our financial systems for execution. And so what that really does for us is it allows us to complete the picture, not just be able to see our spend in the cloud, but also be able to able to see that spending context of all things in the P P P E process as well as the execution process that then really empowers the government to make better investments. And all we're seeing is either cost avoidance or cost savings simply because we're able to close that loop, like I said. Yep. And then we're able to redirect those funds, retag them, remove them through our actual financial office within the headquarters of the army, and be able to repurpose that to other modernization efforts that Congress is essentially asking us to invest >>In. Right. So you know how much money you have, basically. Exactly. Right. You know how much you've already spent, you know how you're spending it, and now you how much you have left, >>You can provide a reliable forecast for your spend. >>Right. You know, hey, we're, we're halfway through this quarter, we're halfway through the, the fiscal year, whatever the case might be. >>Exactly. And the focus on expenditures, you know, the government rates you on, you know, how much have you spent, right? So you have a clear total transparency into what you're going to spend through the rest of the fiscal. Sure. >>All right. Let's just talk about the relationship quickly then about going forward then in terms of federal services and then what on, on the, the US Army side. I mean, what now you've laid this great groundwork, right? You have a really solid foundation where now what next? >>We wanna be all things cloud to the army. I mean, we think there's tremendous opportunity to really aid the modernization efforts and governance across the holistic part of the army. So, you know, we just, we want to, we wanna do it all with the Army as much as we can. It's, it's, it's a fantastic >>Opportunity. Yeah. AFS is, is in a very kind of a strategic role. So as part of the ecma, we own the greater strategy and execution for adoption of cloud on behalf of the entire army. Now, when it comes to delivery of individual capabilities for mission here and there, that's all specific to system owners and different organizations. AFS plays a different role in this instance where they're able to more facilitate the greater strategy on the financial side of the house. And what we've done is we've proven the ability to adopt cloud as a utility rather than this fixed thing, kind of predict the future, spend a whole bunch of money and never use the resource. We're seeing the efficiency for the actual utilization of cloud as a utility. This actually came out as one of the previous NDAs. And so how we actually address nda, I believe it was 2018 in the adoption of cloud as a utility, really is now cornerstone of modernization across all of the do d and really feeds into the Jo Warfighting cloud capability, major acquisition on behalf of all of the D O D to establish buying cloud as just a common service for everyone. >>And so we've been fortunate to inform that team of some of our lessons learned, but when it comes to the partnership, we just see camo moving into production. We've been live for now a year and a half. And so there's another two and a half years of runway there. And then AFS also plays a strategic role at part of our cloud enablement division, which is essentially back to that teaching part, helping the Army understand the opportunity of cloud computing, align the architectures to actually leverage those resources and then deliver capabilities that save soldier's >>Lives. Well, you know, we've, we've always known that the Army does its best work on the ground, and you've done all this groundwork for the military, so I'm not surprised, right? It's, it's a winning formula. Thanks to both of you for being with us here in the executive summit. Great conversation. Awesome. Thanks for having us. A good deal. All right. Thank you. All right. You are watching the executive summit sponsored by Accenture here at Reinvent 22, and you're catching it all on the cube, the leader in high tech coverage.

>>Welcome back everyone to Cube's live coverage, VMware Explorer, 2022 formerly world. I've been saying now I gotta get that out. Dave, I've been sayingm world. It just kind of comes off the tongue when I'm tired, but you know, wall to wall coverage, again, back to back interviews all day two sets. This is a wrap up here with the analyst discussion. Got one more interview after this really getting the analyst's perspective around what we've been hearing and seeing, observing, and reporting on the cube. Again, two sets blue and green. We call them here on the show floor on Moscone west with the sessions upstairs, two floors of, of amazing content sessions, keynote across ed Moscone, north and south SBI here, cloud strategists with the cube. And of course, what event wouldn't be complete without SBE weighing in on the analysis. And, and, and I'm, you know, all kidding aside. I mean that because we've had great interactions around, you know, digging in you, you're like a roving analyst out there. And what's great about what you do is you're social. You're communicating, you're touching everybody out there, but you're also picking up the puzzle pieces. And we, you know, of course we recognize that cuz that's what we do, but you're out, we're on the set you're out on the floor and you know your stuff and, and you know, clouds. So how you, this is your wheelhouse. Great to see you. Good to >>See you. I'm good guys. Thank you. Thank you for having >>Me. So I mean, Dave and I were riffing going back earlier in this event and even before, during our super cloud event, we're reminded of the old OpenStack days. If you remember, Dave OpenStack was supposed to be the open source version of cloud. And that was a great ambition. And the cloud AATI at that time was very into it because it made a lot of sense. And the vision, all the infrastructure was code. Everything was lined up. Everything was religiously was on the table. Beautiful cloud future. Okay. 20 2009, 2010, where was Amazon? Then they just went off like a rocket ship. So cloud ended up becoming AWS in my opinion. Yeah. OpenStax then settled in, did some great things, but also spawns Kubernetes. Okay. So, you know, we've lived through thiss we've seen this movie. We were actually in the trenches on the front lines present at creation for cloud computing. >>Yeah. I was at Rackspace when the open stack was open sourced. I was there in, in the rooms and discussions and all that. I think OpenStack was given to the open source like prematurely. I usually like we left a toddler on the freeway. No, the toddler >>Got behind the wheel. Can't see over the dashboard. >>So we have learned over the years in last two decades, like we have seen the open source rise of open source and we have learned quite a few lessons. And one lesson we learned from there was like, don't let a project go out in the open, tell it mature enough with one vendor. So we did that prematurely with NASA, NASA and Rackspace gave the, the code from two companies to the open source community and then likes of IBM and HPE. No. Now HPE, they kind of hijacked the whole thing and then put a lot of developers on that. And then lot of us sort of second tier startup. >>But, but, but I remember not to interject, but at that time there wasn't a lot of pushback for letting them it wasn't like they infiltrated like a, the vendors always tried to worry about vendors coming in open source, but at that time was pretty people accepted them. And then it got off the rails. Then you remember the great API debate. You >>Called it a hail Mary to against AWS, which is, is what it was, what it was. >>It's true. Yeah. Ended up being right. But the, the battle started happening when you started seeing the network perimeters being discussed, you starting to see some of the, in the trenches really important conversations around how to make essentially cross cloud or super cloud work. And, and again, totally premature it continue. And, and what does that mean today? So, okay. Is VMware too early on their cross cloud? Are they, is multi-cloud ready? >>No >>For, and is it just vaporware? >>No, they're not too early, actually on, on, on, on that side they were premature to put that out there, but this is like very mature company, like in the ops area, you know, we have been using, we VMware stuff since 2000 early 2000. I, I was at commerce one when we started using it and yeah, it was for lab manager, you know, like, you know, put the labs >>Out desktop competition. >>Yeah, yeah. Kind of thing. So it, it matured pretty fast, but now it it's like for all these years they focused on the op site more. Right. And then the challenge now in the DevOps sort of driven culture, which is very hyped, to be honest with you, they have try and find a place for developers to plug in on the left side of the sort of whole systems, life cycle management sort of line, if you will. So I think that's a, that's a struggle for, for VMware. They have to figure that out. And they are like a tap Tansu application platform services. They, they have released a new version of that now. So they're trying to do that, but still they are from the sort of get ups to the, to the right, from that point to the right on the left side. They're lot more tooling to helpers use as we know, but they are very scattered kind of spend and scattered technology on the left side. VMware doesn't know how to tackle that. But I think, I think VMware should focus on the right side from the get ups to the right and then focus there. And then how in the multi-cloud cross cloud. >>Cause my sense is, they're saying, Hey, look, we're not gonna own the developers. I think they know that. And they think they're saying do develop in whatever world you want to develop in will embrace it. And then the ops guys, we, we got you covered, we got the standards, we have the consistency and you're our peeps. You tend then take it, you know, to, to the market. Is that not? I mean, it seems like a viable strategy. I >>Mean, look at if you're VMware Dave and start, you know, this where they are right now, the way they missed the cloud. And they had to reboot that with jazzy and, and, and Raghu to do the databases deal. It's essentially VMware hosted on AWS and clients love it cuz it's clarity. Okay. It's not vCloud air. So, so if you're them right now, you seeing yourself, wow. We could be the connective tissue between all clouds. We said this from day one, when Kubernetes was hitting in the scene, whoever can make this, the interoperability concept of inter clouding and connect clouds so that there could be spanning of applications and data. We didn't say data, but we said, you know, creating that nice environment of multiple clouds. Okay. And again, in concept, that sounds simple, but if you're VMware, you could own that abstraction layer. So do you own it or do you seed the base and let it become a defacto organization? Like a super layer, super pass layer and then participate in it? Or are you the middleware yourself? We heard AJ Patel say that. So, so they could be the middleware for at all. >>Aren't they? The infrastructure super cloud. I mean, that's what they're trying to be. >>Yeah. I think they're trying, trying to do that. It's it's I, I, I have said that many times VMware is bridged to the cloud, right? >>The sorry. Say bridge to >>The cloud. Yeah. Right. For, for enterprises, they have virtualized environments, mostly on VMware stacks. And another thing is I wanna mention touch on that is the number of certified professionals on VMware stack. There it's a huge number it's in tens of thousands. Right? So people who have got these certifications, they want to continue that sort of journey. They wanna leverage that. It's like, it's a Sunco if they don't use that going forward. And that was my question to, to during the press release yesterday, like are there new certifications coming into the, into the limelight? I, I think the VMware, if they're listening to me here somewhere, they will listen. I guess they should introduce a, a cross cloud certification for their stack because they want to be cross cloud or multi-cloud sort of vendor with one sort of single pane. So does actually Cisco and so do many others. But I think VMware is in a good spot. It's their market to lose. I, I, I call it when it comes to the multi-cloud for enterprise, especially for the legacy applications. >>Well, they're not, they have the enterprise they're super cloud enabler, Dave for the, for the enterprise, cuz they're not hyperscaler. Okay. They have all the enterprise customers who come here, we see them, we speak to them. We know them will mingle, but >>They have really good relationships with all the >>Hyperscale. And so those, those guys need a way to the cloud in a way that's cloud operation though. So, so if you say enterprises need their own super cloud, I would say VMware might wanna raise their hands saying we're the vendor to provide that. Yes, totally. And then that's the middleware role. So middleware isn't your classic stack middleware it's middle tissue. So you got, it's not a stack model anymore. It's completely different. >>Maybe, maybe my, my it's >>Not a stack >>Industry. Maybe my industry super cloud is too aspirational, but so let's assume for a second. You're not gonna have everybody doing their own clouds, like Goldman Sachs and, and capital one, even though we're seeing some evidence of that, even in that case, connecting my on-prem to the cloud and modernizing my application stack and, and having some kind of consistency between your on-prem and it's just call it hybrid, like real hybrid, true hybrid. They should dominate that. I mean, who is who, if it's not it's VMware and it's what red hat who else? >>I think red hat wants it too. >>Yeah. Well, red hat and red, hat's doing it with IBM consulting and they gotta be, they have great advantage there for all the banks. Awesome. But what, what about the other 500,000 customers that are >>Out there? If VMware could do what they did with the hypervisor, with virtualization and create the new thing for super cloud, AKA connecting clouds together. That's a, that's a holy grail move right >>There. But what about this PA layer? This Tansu and area which somebody on Twitter, there was a little SNAR come that's V realized just renamed, which is not. I mean, it's, it's from talking to Raghu unless he's just totally BSing us, which I don't think he is. That's not who he is. It's this new federated architecture and it's this, their super PAs layer and, and, and it's purpose built for what they're trying to do across clouds. This is your wheelhouse. What, what do you make of that? >>I think Tansu is a great effort. They have put in lot of other older products under that one umbrella Tansu is not a product actually confuses the heck out of the market. That it's not a product. It's a set of other products put under one umbrella. Now they have created another umbrella term with the newer sort of, >>So really is some yeah. >>Two >>Umbrella on there. So it's what it's pivotal. It's vRealize it's >>Yeah. We realize pivotal and, and, and older stack, actually they have some open source components in there. So, >>So they claim that this ragus claim, it's this new architecture, this new federated architecture graph database, low latency, real time ingestion. Well, >>AJ, AJ that's AJ's department, >>It sounded good. I mean, this is that >>Actually I think the newer, newer stuff, what they announced, that's very promising because it seems like they're building something from scratch. So, >>And it won't be, it won't be hardened for, but, but >>It won't be hardened for, but, >>But those, but they have a track record delivering. I mean, they gotta say that about yeah. >>They're engineering focus company. They have engineering culture. They're their software engineers are top. Not top not, >>Yes. >>What? >>Yeah. It's all relatives. If they, if the VMware stays the way they are. Well, >>Yeah, >>We'll get to that a second. What >>Do you mean? What are you talking >>About? They don't get gutted >>The elephant in the room if they don't get gutted and then, then we'll see it happens there. But right now I love, we love VMware. We've been covering them for 12 years and we've seen the trials, not without their own issues to work on. I mean, everyone needs to work on stuff, but you know, world class, they're very proud of their innovation, but I wanna ask you, what was your observations walking around the floor, talking to people? What was the sense of the messaging? Is it real in their minds? Are they leaning in, are they like enthused? Are they nervous, apprehensive? How would you categorize the attitude of the folks here that you've talked to or observed? >>Yeah. It at the individual product level, like the people are very confident what they're building, what they're delivering, but when it comes to the telling a cohesive story, if you go to all the VMware booth there, like it's hard to find anybody who can tell what, what are all the services under tens and how they are interconnected and what facilities they provide or they can't. They, I mean, most of the people who are there, they can are walking through the economic side of things, like how it will help you save money or, or how the TCR ROI will improve. They are very focused on because of the nature of the company, right. They're very focused on the technology only. So I think that that's the, that's what I learned. And another sort of gripe or negative I have about VMware is that they have their product portfolio is so vast and they are even spreading more thinly. And they're forced to go to the left towards developers because of the sheer force of hyperscalers. On one side on the, on the right side, they are forced to work with hyperscalers to do more like ops related improvements. They didn't mention AI or, or data. >>Yeah. Data storage management. >>That that was weak. That's true. During the, the keynote as well. >>And they didn't mention security and their security story, strong >>Security. I think they mentioned it briefly very briefly, very briefly. But I think their SCO story is good actually, but no is they didn't mention it properly, I guess. >>Yeah. There wasn't prominent in the keynote. It was, you know, and again, I understand why data wasn't P I, they wanted to say about data, >>Didn't make room for the developer story. I think this was very much a theatrical maneuver for Hawk and the employee morale and the ecosystem morale, Dave, then it had to do with the nuts bolt of security. They can come back to get that security. In my opinion, you know, I, I don't think that was as bad of a call as bearing the vSphere, giving more demos, which they did do later. But the keynote I thought was, was well done as targeted for all the negative sentiment around Broadcom and Broadcom had this, the acquisition agreement that they're, they are doing, they agree >>Was well done. I mean, >>You know, if I VMware, I would've done the same thing, look at this is a bright future. We're given that we're look at what we got. If you got this, it's on you. >>And I agree with you, but the, the, again, I don't, I don't see how you can't make security front and center. When it is the number one issue for CIOs, CSOs, CSOs boards or directors, they just, it was a miss. They missed it. Yeah. Okay. And they said, oh, well, there's only so much time, but, and they had to put the application development focus on there. I get that. But >>Another thing is, I think just keynote is just one sort of thing. One moment in this whole sort of continuous period, right. They, I think they need to have that narrative, like messaging done periodically, just like Amazon does, you know, like frequent events tapping into the practitioners on regional basis. They have to do that. Maybe it's a funding issue. Maybe it is some weakness on the, no, >>I think they planning, I talked to, we talked to the CMO and she said, Explorer is gonna be a road show. They're gonna go international with, it's gonna take a global, they're gonna have a lot of wood behind the arrow. They're gonna spend a lot of money on Explorer is what, they're, what we're seeing. And that's a good thing. You got a new brand, you gotta build it. >>You know, I would've done, I would've had, I would've had a shorter keynote on day one and doing, and then I would've done like a security day, day two. I would've dedicated the whole morning, day two keynote to security cuz their stories I think is that strong? >>Yeah. >>Yeah. And I don't know the developers side of things. I think it's hard for VMware to go too much to the left. The spend on the left is very scattered. You know, if you notice the tools, developers change their tools on freaking monthly basis, right? Yeah. Yeah. So it's hard to sustain that they on the very left side and the, the, the >>It's hard for companies like VMware to your point. And then this came up in super cloud and ins Rayme mentioned that developers drive everything, the patterns, what they like and you know, the old cliche meet them where they are. You know, honestly, this is kind of what AJ says is the right they're doing. And it's the right strategy meeting that develops where they are means give them something that they like. They like self-service they like to try stuff. They like to, they don't like it. They'll throw it away. Look at the success that comes like data, dog companies like that have that kind of offering with freemium and self-service to, to continue the wins versus jamming the tooling down their throat and selling >>Totally self-serve infrastructure for the, in a way, you know, you said they missed cloud, which they did V cloud air. And then they thought of got it. Right. It kind of did the same thing with pivotal. Right. It was almost like they forced to take pivotal, you know, by pivotal, right. For 2 billion or whatever it was. All right. Do something with it. Okay. We're gonna try to do something with it and they try to go out and compete. And now they're saying, Hey, let's just open it up. Whatever they want to use, let 'em use it. So unlike and I said this yesterday, unlike snowflake has to attract developers to build on their unique platform. Okay. I think VMware's taken a different approach saying use whatever you want to use. We're gonna help the ops guys. And that, to me, a new op >>Very sensitive, >>The new ops, the new ops guys. Yes. Yes. >>I think another challenge on the right right. Is on, on the op site is like, if, if you are cloud native, you are a new company. You just, when you're a startup, you are cloud native, right. Then it's hard for VMware to convince them to, Hey, you know, come to us and use this. Right. It's very hard. It is. They're a good play for a while. At least they, they can prolong their life by innovating along the way because of the, the skills gravity, I call it of the developers and operators actually that's their, they, they have a loyal community they have and all that stuff. And by the way, the name change for the show. I think they're trying to get out of that sort of culty kind of nature of the, their communities that they force. The communities actually can force the companies, not to do certain things certain way. And I've seen that happening. And >>Well, I think, I think they're gonna learn and they already walked back their messaging. Not that they said anything overtly, but you know, the Lori, the CMO clarified this significantly, which was, they never said that they wanted to replace VM world. Although the name change implies that. And what they re amplified after the fact is that this is gonna be a continuation of the community. And so, you know, it's nuanced, they're splitting hairs, but that's, to me walking back the, you know, the, the loyalty and, and look at let's face it. Anytime you have a loyal community, you do anything of change. People are gonna be bitching and moaning. Yeah. >>But I mean, knew, worked, explore, >>Work. It wasn't bad at all. It was not a bad look. It wasn't disastrous call. Okay. Not at all. I'm critical of the name change at first, but the graphics are amazing. They did an exceptional job on the branding. They did, did an exceptional job on how they handled the new logo, the new name, the position they, and a lot of people >>Showed >>Up. Yeah. It worked >>A busy busier than all time >>It worked. And I think they, they threaded the needle, given everything they had going on. I thought the event team did an exceptional job here. I mean, just really impressive. So hats up to the event team at, at VMware pulling off now, did they make profit? I don't know. It doesn't matter, you know, again, so much going on with Broadcom, but here being in Moscone west, we see people coming down the stairs here, Dave's sessions, you know, lot of people, a lot of buzz on the content sold out sessions. So again, that's the ecosystem. The people giving the talks, you know, the people in the V brown bag, you know, got the, the V tug. They had their meeting, you know, this week here, >>Actually the, the, the red hat, the, the integration with the red hat is another highlight of, of, they announced that, that you can run that style >>OpenShift >>And red hats, not here, >>Red hat now here, but yeah, but, but, but >>It was more developers, more, you know, >>About time. I would say, why, why did it take so long? That should >>Have happened. All right. Final question. So what's the bottom line. Give us the summary. What's your take, what's your analysis of VMware explore the event, what they did, what it means, what it's gonna mean when the event's over, what's gonna happen. >>I think VMware with the VMware Explorer have bought the time with the messaging. You know, they have promised certain things with newer announcements and now it, it, it is up to them to deliver that in a very sort of fast manner and build more hooks into other sort of platforms. Right? So that is very important. You cannot just be closed system people. Don't like those systems. You have to be part of the ecosystem. And especially when you are sitting on top of the actually four or four or more public clouds, Alibaba cloud was, they were saying that they're the only VMware is only VMware based offering in mainland China on top of the Alibaba. And they, they can go to other ones as well. So I think, especially when they're sitting on top of other cloud providers, they have to build hooks into other platforms. And if they can build a marketplace of their own, that'll be even better. I think they, >>And they've got the ecosystem for it. I mean, you saw it last night. I mean, all the, all the parties were hopping. I mean, there was, there's >>A lot of buzz. I mean, I pressed, I pressed them Dave hard. I had my little, my zingers. I wanted to push the buttons on one question that was targeted towards the answer of, are they gonna try to do much more highly competitive maneuvering, you know, get that position in the middleware. Are they gonna be more aggressive with frontal competitiveness or are they gonna take the, the strategy of open collaborative and every single data point points to collaborative totally hit Culbert. I wanna do out in the open. We're not just not, we're not one company. So I think that's the right play. If they came out and said, we're gonna be this, you know? >>Yeah. The one, the last thing, actually, the, the one last little idea I'm putting out out there since I went to the Dell world, was that there's a economics of creation of software. There's economics of operations of software. And they are very good on the operation economics of operations side of things that when I say economics, it doesn't mean money only. It also means a productivity practitioner, growth. Everything is in there. So I think these vendors who are not hyperscalers, they have to distinguish these two things and realize that they're very good on the right side economics of operations. And, and that will go a long way. Actually. I think they muddy the waters by when DevOps, DevOps, and then it's >>Just, well, I think Dave, we always we've had moments in time over the past 12 years covering VMware's annual conference, formally world now floor, where there were moments of that's pat Gelsinger, spinal speech. Yeah. And I remember he was under a siege of being fired. Yeah. There was a point in time where it was touch and go, and then everything kind of came together. That was a moment. I think we're at a moment in time here with VMware Dave, where we're gonna see what Broadcom does, because I think what hop 10 and Broadcom saw this week was an EBI, a number on the table that they know they can probably get or squeeze. And then they saw a future value and net present value of future state that you could, you gotta roll back and do the analysis saying, okay, how much is it worth all this new stuff worth? Is that gonna contribute to the EBITDA number that they want on the number? So this is gonna be a very interesting test because VMware did it, an exceptional job of laying out that they got some jewels in the oven. You >>Think about how resilient this company has been. I mean, em, you know, EMC picked them up for a song. It was 640 million or whatever it was, you know, about the public. And then you, another epic moment you'll recall. This was when Joe Tuchi was like the mafia Don up on stage. And Michael Dell was there, John Chambers with all the ecosystem CEOs and there was Tucci. And then of course, Michael Dell ends up owning this whole thing, right? I mean, when John Chambers should have owned the whole thing, I mean, it's just, it's been incredible. And then Dell uses VMware as a piggy bank to restructure its balance sheet, to pay off the EMC debt and then sells the thing for $60 billion. And now it's like, okay, we're finally free of all this stuff. Okay. Now Broadcom's gonna buy you. And, >>And if Michael Dell keeps all in stock, he'll be the largest shareholder of Broadcom and own it off. >>Well, and that's probably, you know, that's a good question is, is it's gonna, it probably a very tax efficient transaction. If he takes all stock and then he can, you know, own against it. I mean, that's, that's, >>That's what a history we're gonna leave it there. Start be great to have you Dave great analysis. Okay. We'll be back with more coverage here. Day two, winding down after the short break.

(upbeat music) >> Hi everybody. We're back at VeeamON 2022, we're winding down coverage to The Cube day two. We've done a lot of VeeamON. We're at the Aria hotel, smaller physical audience, huge hybrid audience, little different program. Great keynotes, really loved the keynote yesterday and today kind of product day today. Sean Smith is here with myself and David Nicholson. He's the staff Solution Architect at VMware. Sean, thanks for coming on the Cube, taking some time with us. >> Hey guys. Great to be here and great to be in person again. >> Yeah, it sure is. Hoping to see VMworld is no longer VMworld, right? >> It's VMware Explore now. Yep. >> Okay. Awesome. Looking forward to that. That was one of the first shows we ever did. It's kind of got that same vibe, I hope you don't lose that, the core of VMware. >> What we've been told is it's still going to be, the core of what we do and it's going to be the showcase of VMware. >> Which is the ecosystem, great vibe. You always know a million people there, which is great fun. How's it going at VMware today? I mean, let's start there. It's been a while since we've talked physically with... >> Yeah. VMware is, we've come through the pandemic, fairly well, relative speaking to what others have done. I'm part of the VCPP Program, the VMware Cloud Provider Program, and I look after cloud service providers, cloud builders, people who are actually building out networks for customers and environments that are very specialized and focusing on their needs and VMware is forefront with cloud service providers these days, doing really well. >> The last time we were physically proximate to VMware executives, I think Pat Gelsinger was still the CEO, Dell still owned the majority of VMware. So that spin happened. So that's good. I think the ecosystem in particular is probably really happy about that. Does it have any effect on your world? >> From a day to day business perspective, not really, right. Obviously we still have a very tight relationship with Dell. We still do a lot of innovative solutions and products with the Dell team. We have a tight integration there. It really gives us the opportunity to also work with many other vendors as well. And focus on solutions that our customers are looking for really, is where VMware is tryna focus. >> Yeah. It's funny, we were at Red Hat Summit last week. IBM Think was right across the street there was very little mention, if any, I think they talked about an IBM mainframe at Red Hat Summit. That was it. I mean IBM fully owns Red Hat, but a lot of people said, we hope that it's going to be like VMware and you guys have always had that independent culture. >> Fiercely independent. >> Fiercely independent. Yes. >> Yes. It's like when you coach, I don't know me anyway, when I coach my kids baseball, I'm a tougher on them than am with the other kids. I think you guys were sometimes tougher on your own or... And rightly so, you have a huge ecosystem. >> We do. >> That is epic. And so you have to look out for that. VMware has always done that. VCPP the V is for a VMware what's what's the acronym. >> So the CPP is Cloud Provider Program. It's a program that's specifically aimed at our cloud service providers. There's several solutions within the program, which are really focused on helping them build business, helping them go to market, helping them with being able to, for certain part of it compete with the hyperscalers and our support several cloud providers, mostly out of the Northeast, and they're doing really well. They're doing well against the hyperscalers, they very often provide solutions that are not easy to get on a hyperscaler. When you want to have customer interaction and things like that. So the VCP Program as I said, is really tailored, it has solutions which are very much focused on allowing them to build their businesses as a cloud service provider. >> Just a follow up if I may. >> Yeah. >> So the history of VMware Cloud has been really interesting. At one point vCloud Air, we know what happened there. This is not vCloud Air. >> This is not vCloud Air. It's got nothing to do with vCloud Air. It's really a program where we provide solutions that the cloud builders build with, right? So it's software solutions. There's no hardware involved. There's no VMware having the environment, it's really cloud providers building solutions. >> So it's interesting, Dave, this has come full circle, you used to work at Virtustream. There was point Rodney was like, bring it on AWS, correlation and back said, we can't lose to a book seller and all that was just, fun marketing talk for media people like us. But the interesting thing is, well, so VMware Cloud on AWS. Huge success of VMware Cloud Foundation. Doing really well. And obviously you've got momentum. Everybody thought, not everybody. >> It's in Google's, in Azure, it's in Oracle. >> Yeah, yeah. Sorry. >> It's an IBM. >> IBM a... >> It's an IBM. >> Number one in IBM. Yeah. >> And so a lot of people thought, I shouldn't say everybody, but a lot of people thought, MSPs, the cloud service providers, non-hyperscalers are cooked through 2010, 2011. The exact opposite happened. >> It's 100%. >> It's growing like crazy. We want to understand why, but it's come full circle. >> Yeah, it certainly has. I mean, the industry has changed considerably and especially over the last few years with COVID, I will say that the cloud service providers that are support and by the way, Virtustream was one of them, when I first joined VMware, I supported Virtustream. And they have had to adapt their businesses, the hyperscalers have come at them with everything that they've got and honesty, the cloud service providers that I support are phenomenal growth. They they're growing on a par with what some of the hyperscalers are doing. So there's definitely a place for cloud service providers, they've got great business, they've got great customers, great relationships. And it's as I said, it's growing a huge business. >> So we've talked a lot about theme from the perspective of the idea of a Supercloud. Something that can overlay a variety of on-premises and off-premises providers and provide sort of a unified view, unified management methodology. How much is what at least was formerly known as the SDDC stack, the Software Defined Data Center stack, still a part of VMwares vision that is right in line with that, from what Veeam is doing. How much of your business is deploying SDDC stacks that are then customized in one way or another. >> 100% of it. >> 100% of it. Right, okay. >> Yeah. So, when you're talking about having that single view of everything in the cloud provider program, there's a product called VMware Cloud Director. and it is the multi-tenant view of the infrastructure and the environment that the cloud providers are building. Right. So VMware Cloud Director has gone through many iterations and we've recently launched Cloud Director Service, which is a SaaS offering of the product. But what it actually does is you put it on top of VMC on AWS. you put it on top of GCVE, you put it on top of the cloud service providers, SDDCs, right. All of these are SDDCs underneath. >> AVS and Azure. >> AVS and Azure. >> I was associated with that. So I must have it mentioned. >> Exactly. >> They're all SDDC's. >> SDDC's, yeah, yeah, exactly. And as well as your on premise environment. Right. So all of these federate together through the VMware Cloud Director, and you end up having a single pane of glass across all of those environments. So whether it's running in the hyperscale, or running on your premises, running in a cloud service provider's environment, you have a single view, a single interface that you log into and you can see everything that's going on inside your environment. So it really brings that holistic, single view of everything to reality. >> How about from a licensing perspective? >> So from a licensing perspective... >> I'm a non-premises customer, I'm running VMware on-prem, I have been, I was at world VMworld 2004 and enjoyed BattleBots. So hopefully you'll start bringing BattleBots back. >> We will have to. >> And now I'm dealing with a service provider. That is one of the partners that you're working with. How does that licensing work? >> So the Cloud Provider Program actually has a slightly different licensing model to what you would have on premises, right? They have a rental model with VMware, it's a PAYGo model, right. One of the great things about the program is that it's consumption based. So it makes it easy for cloud service providers to build a consumption based business, which is kind of where everything is moving, right? >> Yeah, for sure. >> So whether you have an on-premise environment that's licensed through what we call perpetual or ELA licensing, from a VMware perspective, you can still layer on top, that cloud service provider solution VCD, right? And you would obviously have a financial relationship with the cloud service provider in terms of the environment that you have with them. And they will be able to hook up that environment to your on-premises environment and get that single view. So the licensing is not a restriction, right, you can still continue to have your traditional licensed environment in your data center, as well as being able to connect into these seamlessly, right. That's the great thing about it. And that's where VMC, AVS, GCVE, the OCVS, the Oracle version, the RBM one, you can bring all of these together and really look at it from a holistic perspective, bring in things like NSX-T and other solutions like that VM as well, it works seamlessly across all these environments. >> I am talking about Supercloud, I asked Raghu last year, who's virtually at VMworld, I kind of explained that concept of hiding the complexity, the abstraction layer, being able to hide the underlying primitives and APIs, seems like it's evolving. One of the things he said was yes, but if developers want to go there, we let them. And that was a key point, because you're getting more into that DevOps. >> Correct 100%. >> And I would imagine the cloud service providers really oftentimes need for their reasons to get to those underlying primitives and APIs. >> And actually VCD is the enabler, right? So VCD allows you to provide a container based service sitting right alongside your IAS in the same SDDC, right? We're not even talking about segregating them out, you can have it inside the exact same SDDC, all linked together, all taking a common security approach to what's going on and providing you with that ease of use. So from an end user perspective, the DevOps type of people, VCD is an awesome solution, because they can go in fire up a new VM, or fire up a new container or whatever, without having to go through the rigmarole of asking IT for a VM, or asking somebody's permission, as a organization, you would give your DevOps teams certain amount of resources, how they use it's up to them, right? Whether they put containers in there or they bring VMs, it's all there. And it's all in one single solution. >> You mentioned that your community is doing very well growing it let's call it 35, 40% a year. And it's a market that's quite large worldwide. Because it's a lot of local, regional CSPs, a lot of big country CSPs and you said... >> It's four and a 1/2 thousand of them. So, it's huge. >> There you >> Versus four hyperscalers. >> Yeah, exactly. >> Include Alibaba. So, they might be individually smaller, but collectively they're larger. But you said that the hyperscalers coming after them with everything they had was a comment that you made, are customers choosing CSPs over hyperscalers? If so, when and why. >> Sometimes they are choosing CSPs over hyperscalers, but not always, very often they're choosing CSPs and hyperscalers, right. And it really depends on what their needs are. So historically speaking, it's been everybody rushing to the hyperscalers because that's the flavor of the day let's move out of our data center. It's much cheaper to run everything in these hyperscalers, and they do it. And then the bill comes in and reality suddenly hits. And it's definitely not as cheap as they thought it was going to be, right. So there's many aspects that cause tenants to not only rethink that, but also repatriate, right. Repatriation is a big thing for our cloud service providers. Things like egress costs, most cloud service providers have no egress costs, right? They encourage movement of things amongst themselves and for their tenants, because that's what they want, right? So egress costs are a huge problem for many tenants who come into these environments and that's sometimes why they would choose a CSP over a hyperscaler. But really, it's more about choosing the right place for your workload. There are workloads that belong in hyperscalers, right? And if you have a solution with a CSP like VCD, that allows you not only to be able to connect your on premises and the CSP, but also the hyperscalers and actually have a much more holistic solution where you can determine where you want to put stuff and put it in the right place. It's more about that, than it is about choosing one over the other really. >> Yeah, and sometimes it's more of a business differentiation than a technical one. Is it a hyperscale or is it a CSP? If you're licensing the SDDC stack and you're running it on IAS in Amazon or in Google or Azure? >> I think the other thing too is the CSPs oftentimes they manage service providers, right? Is that true? >> The relationship, right? And that's one of the things if you talk to a cloud service provider and yesterday I was, I had a session and I was talking to a bunch of people about VMware stuff. And I said to them, how many of you have tried to pick up a phone and talk to somebody at AWS? And there was laughter, because the reality is that what AWS does is a kind of one size fits all approach, right? There isn't somebody on the end of the phone that you can pick up and call, if they have a major outage that outage is affecting 1000s of different customers and you one of those thousands really means nothing to them, right? Whereas a cloud service provider, generally speaking, has a very tight one-on-one relationship with both from an engineering perspective, right. With their tenants, but also at a higher managerial level. So they create those relationships and those relationships often drive these things. It's not always financial, there is a financial component to it, but very often it's the relationship, have they got somebody that they can talk to? If they getting many different solutions, can they get all those solutions from one provider? And if they can, it's much easier for them to manage from a... >> And I think so does that manage service... There's also a lot of things that despite their breadth and portfolio that the cloud service providers don't support, you can't do Oracle rack in the cloud, right? But you can in a service provider. >> Exactly. >> And Oracle, look you can negotiate with Oracle, so you can get similar pricing AWS, but this price is two x. They're either on-prem or in Oracle. So I could take my Oracle instance, stick it into a managed service provider or cloud service provider, do whatever I need to, and there are I'm sure 1000s of configurations like that, that aren't necessarily identically supported, security edicts that aren't necessarily exactly the same, so many specials that managed service say welcome to your point. AWS is as long as it's black, it's good. >> Yeah, exactly. And that's the thing, right? Those cloud service providers are doing exactly that. They have Oracle racks in there, they have all sorts of those solutions that are there in their data centers. And proximity is also an issue, right? Very often the people who are using those systems need their ancillary things to be close by, they can't be 10s or 20s or 30 milliseconds away, they need to be sub millisecond connectivity. And those are the areas where the cloud service providers really shine, they can offer those solutions that really enable their tenants to get what they want at the end of the day. Again to your point, you can negotiate with Oracle, but these cloud service providers do it day in and day out. Who wants their business? >> Who wants to do that with Oracle anyway, their lawyers are smarter than yours. Veeam, what are you doing with Veeam, in resilient architectures and cyber recovery? >> Yeah, we are a sponsor here at the event and Veeam is a great partner with VMware and we're great partner to them. A lot of cloud service providers actually use Veeam as their primary backup solution for their tenants, right. VMware Cloud Director that I was talking about just now, the thing that gives you a view of everything over the top, Veeam was actually one of the very first vendors to integrate with VCD. And you can use your Veeam environment directly from the screen, you right click, and you say do a backup and that's as easy as that from a Veeam perspective. So we have a lot of integrations with Veeam. We help the cloud service providers, ransomware is a big talking thing around this event, but all over the place, right? So a lot of the solutions that Veeam brings to the party, these cloud service providers are also deploying into their environments to help with ransomware. They have so many solutions that help those cloud service providers provide a holistic solution. >> Well, Veeam was basically founded saying, Hey, we're going to better our business on VMware. I first saw Veeam at a V mug, I think in Boston, and I was like, who is Veeam? VMware is that their product? It was just so you guys have had a long relationship, even though initially VMware was probably saying the same thing, who the heck are these guys? Well, how do you like them now? Sean, thanks so much for... >> Thank you. It's been great to be here. Appreciate it. Thank you for watching. Keep it right there. We'll be back shortly. We'll get a couple more segments left. Dave and I are going to wrap up later in the day, you watching The Cube at VeeamON 2022, be right back. (upbeat music)

(upbeat music) >> Lately Infinidat has been on a bit of a Super cycle of product announcements. Adding features, capabilities, and innovations to its core platform that are applied across its growing install base. CEO, Phil Bollinger has brought in new management and really emphasized a strong and consistent cadence of product releases, a hallmark of successful storage companies. And one of those new executives is a CMO with a proven product chops, who seems to bring an energy and an acceleration of product output, wherever he lands. Eric Herzog joins us on "theCUBE". Hey, man. Great to see you. Awesome to have you again. >> Dave. Thank you. And of course, for "theCUBE", of course, I had to put on a Hawaiian shirt as always. >> They're back. All right, I love it.(laughs) Watch out for those Hawaiian shirt police, Eric. (both laughing) All right. I want to have you start by. Maybe you can make some comments on the portfolio over the past year. You heard my intro, InfiniBox is the core, the InfiniBox SSA, which announced last year. InfiniGuard you made some substantial updates in February of this year. Real focus on cyber resilience, which we're going to talk about with Infinidat. Give us the overview. >> Sure. Well, what we've got is it started really 11 years ago with the InfiniBox. High end enterprise solution, hybrid oriented really incredible magic fairy dust around the software and all the software technology. So for example, the Neural Cache technology, which has multiple patents on it, allowed the original InfiniBox to outperform probably 85% of the All-Flash Arrays in the industry. And it still does that today. We also of course, had our real, incredible ease-of-use the whole point of the way it was configured and set up from the beginning, which we continued to make sure we do is if you will a set it and forget it model. For example, When you install, you don't create lungs and raid groups and volumes it automatically and autonomously configures. And when you add new solutions, AKA additional applications or additional servers and point it at the InfiniBox. It automatically, again in autonomously, adjust to those new applications learning what it needs to configure everything. So you're not setting cash size and Q depth, or Stripes size, anything you would performance to you don't have to do any of that. So that entire set of software is on the InfiniBox. The InfiniBox SSA II, which we're of course launching today and then inside of the InfiniGuard platform, there's a actually an InfiniBox. So the commonality of snapshots replication, ease of use. All of that is identical across the platform of all-flash array, hybrid array and purpose-built backup secondary storage and no other vendor has that breadth of product that has the same exact software. Some make a similar GUI, but we're talking literally the same exact software. So once you learn it, all three platforms, even if you don't have them, you could easily buy one of the other platforms that you don't have yet. And once you've got it, you already know how to use it. 'Cause you've had one platform to start as an example. So really easy to use from a customer perspective. >> So ever since I've been following the storage business, which has been a long time now, three things that customers want. They want something that is rock solid, dirt cheap and super fast. So performance is something that you guys have always emphasized. I've had some really interesting discussions over the years with Infinidat folks. How do you get performance? If you're using this kind of architecture, it's been quite amazing. But how does this launch extend or affect performance? Why the focus on performance from your standpoint? >> Well, we've done a number of different things to bolster the performance. We've already been industry-leading performance again. The regular InfiniBox outperforms 80, 85% of the All-Flash Arrays. Then, when the announcement of the InfiniBox SSA our first all-flash a year ago, we took that now to the highest demanding workloads and applications in the industry. So what did it add to the super high end Oracle app or SAP or some custom app that someone's created with Mongo or Cassandra. We can absolutely meet the performance between either the InfiniBox or the InfiniBox all-flash with the InfiniBox SSA. However, we've decided to extend the performance even farther. So we added a whole bunch of new CPU cores into our tri part configuration. So we don't have two array controllers like many companies do. We actually have three everything's in threes, which gives us the capability of having our 100% availability guarantee. So we've extended that now we've optimized. We put a additional InfiniBand interconnects between the controllers, we've added the CPU core, we've taken if you will the InfiniBox operating system, Neural Cache and everything else we've had. And what we have done is we have optimized that to take advantage of all those additional cores. This has led us to increase performance in all aspects, IOPS bandwidth and in fact in latency. In latency we now are at 35 mikes of latency. Real world, not a hero number, but real-world on an array. And when you look end to end, if I Mr. Oracle, or SAP sitting in the server and I'll look across that bridge, of course the sand and over to the other building the storage building that entire traversing can be as fast as a 100 microseconds of latency across the entire configuration, not just the storage. >> Yeah. I think that's best in class for an external array. Well, so what's the spectrum you can now hit with the performance ranges. Can you hit all the aspects of the market with the two InfiniBoxes, your original, and then the SSA? >> Yes, even with the original SSA. In fact, we've had one of our end users, who's been first InfiniBox customer, then InfiniBox SSA actually has been running for the last two months. A better version of the SSA II. So they've had a better version and this customer's running high end Oracle rack configurations. So they decided, you know what? We're not going to run storage benchmarks. We're going to run only Oracle benchmarks. And in every benchmark IOPS, latency and bandwidth oriented, we outperformed the next nearest competition. So for example, 57% faster in IOPS, 58% faster in bandwidth and on the latency side using real-world Oracle apps, we were three times better performance on the latency aspect, which of course for a high end high performance workload, that's heavily transactional. Latency is the most important, but when you look across all three of those aspects dramatically outperform. And by the way, that was a beta unit that didn't of course have final code on it yet. So incredible performance angle with the InfiniBox SSA II. >> So I mean you earlier, you were talking about the ease of use. You don't have to provision lungs and all that sort of nonsense, and you've always emphasized ease-of-use. Can you double click on that a little bit? How do you think about that capability? And I'm really interested in why you think it's different from other vendors? >> Well, we make sure that, for example, when you install you don't have to do anything, you have to rack and stack, yes and cable. And of course, point the servers at the storage, but the storage just basically comes up. In fact, we have a customer and it's a public reference that bought a couple units many years ago and they said they were up and going in about two hours. So how many high-end enterprise storage array can be up and going in two hours? Almost I mean, basically nobody about us. So we wanted to make sure that we maintain that when we have customers, one of our big plays, particularly helping with CapEx and OpEx is because we are so performant. We can consolidate, we have a large customer in Europe that took 57 arrays from one of our competitors and consolidate it to five of the original InfiniBox. 57 to 5. They saved about $25 million in capital expense and they're saving about a million and a half a year in operational expense. But the whole point was as they kept adding more and more servers that were connected to those competitive arrays and pointing them at the InfiniBox, there's no performance tuning. Again, that's all ease-of-use, not only saving on operational expense, but obviously as we know, the headcount for storage admins is way down from its peak, which was probably in 2007. Yet every admin is managing what 25 to 50 times the amount of storage between 2007 and 2022. So the reality is the easier it is to use. Not only does of course the CIO love it because both the two of us together probably been storage, doing storage now for close to 80 years would be my guess I've been doing it for 40. You're a little younger. So maybe we're at 75 to 78. Have you ever met a CIO used to be a storage admin ever? >> No. >> And I can't think of one either so guess what? The easier it is to use the CIOs know that they need storage. They don't like it. They're all these days are all software guys. There used to be some mainframe guys in the old days, but they're long gone too. It's all about software. So when you say, not only can we help reduce your CapEx at OpEx, but the operational manpower to run the storage, we can dramatically reduce that because of our ease-of-use that they get and ease-of-use has been a theme on the software side ever since the Mac came out. I mean, Windows used to be a dog. Now it's easy to use and you know, every time the Linux distribution come out, someone's got something that's easier and easier to use. So, the fact that the storage is easy to use, you can turn that directly into, we can help you save on operational manpower and OPEX and CIOs. Again, none of which ever met are storage guys. They love that message. Of course the admins do too 'cause they're managing 25 to 50 times more storage than they had to manage back in 2007. So the easier it is for them at the tactical level, the storage admin, the storage manager, it's a huge deal. And we've made sure we've maintained that as you've added the SSA, as we brought up the InfiniGuard, as we've continue to push new feature function. We always make it easy to use. >> Yeah. Kind of a follow up on that. Just focus on software. I mean, I would think every storage company today, every modern storage company is going to have more software engineers than hardware engineers. And I think Infinidat obviously is no different. You got a strong set of software, it's across the portfolio. It's all included kind of thing. I wonder if you could talk about your software approach and how that is different from your competitors? >> Sure, so we started out 11 years ago when in Infinidat first got started. That was all about commodity hardware. So while some people will use custom this and custom that, yeah and I having worked at two of the biggest storage companies in the world before I came here. Yes, I know it's heavily software, but our percentage of hardware engines, softwares is even less hardware engineering than our competitors have. So we've had that model, which is why this whole what we call the set it and forget it mantra of ease-of-use is critical. We make sure that we've expanded that. For example, we're announcing today, our InfiniOps focus and Infini Ops all software allows us to do AIOps both inside of our storage system with our InfiniVerse and InfiniMetrics packages. They're easy to use. They come pre-installed and they manage capacity performance. We also now have heavy integration with AI, what I'll call data center, AIOps vendors, Vetana ServiceNow, VMware and others. And in that case, we make sure that we expose all of our information out to those AIOps data center apps so that they can report on the storage level. So we've made sure we do that. We have incredible support for the Ansible framework again, which is not only a software statement, but an ease-of-use statement as well. So for the Ansible framework, which is trying to allow an even simpler methodology for infrastructure deployment in companies. We support that extensively and we added some new features. Some more, if you will, what I'll say are more scripts, but they're not really scripts that Ansible hides all that. And we added more of that, whether that be configuration installations, that a DevOps guy, which of course just had all the storage guys listening to this video, have a heart attack, but the DevOps guy could actually configure storage. And I guess for my storage buddies, they can do it without messing up your storage. And that's what Ansible delivers. So between our AIOps focus and what we're doing with InfiniOps, that extends of course this ease-of-use model that we've had and includes that. And all this again, including we already talked about a little bit cyber resilience Dave, within InfiniSafe. All this is included when you buy it. So we don't piecemeal, which is you get this and then we try to upcharge you for that. We have the incredible pricing that delivers this CapEx and an OpEx. Not just for the array, but for the associated software that goes with it, whether that be Neural Cache, the ease-of-use, the InfiniOps, InfiniSafes. You get all of that package together in the way we deploy from a business now perspective, ease of doing business. You don't cut POS for all kinds of pieces. You cut APO and you just get all the pieces on the one PO when we deliver it. >> I was talking yesterday to a VC and we were chatting about AI And of course, everybody's chasing AI. It's a lot of investments go in there, but the reality is, AI is like containers. It's just getting absorbed into virtually every thing. And of course, last year you guys made a pretty robust splash into AIOps. And then with this launch, you're extending that pretty substantially. Tell us a little bit more about the InfiniOps announcement news. >> So the InfiniOps includes our existing in the box framework InfiniVerse and what we do there, by the way, InfiniVerse has the capability with the telemetry feed. That's how we could able to demo at our demo today and also at our demo for our channel partner pre-briefing. Again a hundred mics of latency across the entire configuration, not just to a hundred mics of latency on storage, which by the way, several of our competitors talk about a hundred mics of latency as their quote hero number. We're talking about a hundred mics of latency from the application through the server, through the SAN and out to the storage. Now that is incredible. But the monitoring for that is part of the InfiniOps packaging, okay. We support again with DevOps with all the integration that we do, make it easy for the DevOps team, such as with Ansible. Making sure for the data center people with our integration, with things like VMware and ServiceNow. The data center people who are obviously often not the storage centric person can also be managing the entire data center. And whether that is conversing with the storage admin on, we need this or that, or whether they're doing it themselves again, all that is part of our InfiniOps framework and we include things like the Ansible support as part of that. So InfiniOps is sort of an overarching theme and then overarching thing extends to AIops inside of the storage system. AIops across the data center and even integration with I'll say something that's not even considered an infrastructure play, but something like Ansible, which is clearly a red hat, software oriented framework that incorporates storage systems and servers or networks in the capability of having DevOps people manage them. And quite honestly have the DevOps people manage them without screwing them up or losing data or losing configuration, which of course the server guys, the network guys and the storage guys hate when the DevOps guys play with it. But that integration with Ansible is part of our InfiniOps strategy. >> Now our shift gears a little bit talk about cyber crime and I mean, it's a topic that we've been on for a long time. I've personally been writing about it now for the last few years. Periodically with my colleagues from ETR, we hit that pretty hard. It's top of mind, and now the house just approved what's called the Better Cybercrime Metrics Act. It was a bipartisan push. I mean, the vote was like 377 to 48 and the Senate approved this bill last year. Once president Biden signs it, it's going to be the law's going to be put into effect and you and many others have been active in this space Infinidat. You announced cyber resilience on your purpose bill backup appliance and secondary storage solution, InfiniGuard with the launch of InfiniSafe. What are you doing for primary storage from InfiniBox around cyber resilience? >> So the goal between the InfiniGuard and secondary storage and the InfiniBox and the InfiniBox SSA II, we're launching it now, but the InfiniSafe for InfiniBox will work on the original InfiniBox. It's a software only thing. So there's no extra hardware needed. So it's a software only play. So if you have an InfiniBox today, when you upgrade to the latest software, you can have the InfiniSafe reference architecture available to you. And the idea is to support the four key legs of the cybersecurity table from a storage perspective. When you look at it from a storage perspective, there's really four key things that the CISO and the CIO look for first is a mutable snapshot technology. An article can't be deleted, right? You can schedule it. You can do all kinds of different things, but the point is you can't get rid of it. Second thing of course, is an air gap. And there's two types of air gap, logical air gap, which is what we provide and physical the main physical air gaping would be either to tape or to course what's left of the optical storage market. But we've got a nice logical air gap and we can even do that logical air gaping remotely. Since most customers often buy for disaster recovery purposes, multiple arrays. We can then put that air gap, not just locally, but we can put the air gap of course remotely, which is a critical differentiator for the InfiniBox a remote logical air gap. Many other players have logical, we're logical local, but we're going remote. And then of course the third aspect is a fenced forensic environment. That fence forensic environment needs to be easily set up. So you can determine a known good copy to a restoration after you've had a cyber incident. And then lastly is rapid recovery. And we really pride ourself on this. When you go to our most recent launch in February of the InfiniGuard within InfiniSafe, we were able to demo live a recovery taking 12 minutes and 12 seconds of 1.5 petabytes of backup data from Veeam. Now that could have been any backup data. Convolt IBM spectrum tech Veritas. We happen to show with Veeam, but in 12 minutes and 12 seconds. Now on the primary storage side, depending on whether you're going to try to recover locally or do it from a remote, but if it's local, we're looking at something that's going to be 1 to 2 minutes recovery, because the way we do our snapshot technology, how we just need to rebuild the metadata tree and boom, you can recover. So that's a real differentiator, but those are four things that a CISO and a CIO look for from a storage vendor is this imutable snapshot capability, the air gaping capability, the fenced environment capability. And of course this near instantaneous recovery, which we have proven out well with the InfiniGuard. And now with the InfiniBox SSA II and our InfiniBox platform, we can make that recovery on primary storage, even faster than what we have been able to show customers with the InfiniGuard on the secondary data sets and backup data sets. >> Yeah. I love the four layer cake. I just want to clarify something on the air gap if I could so you got. You got a local air gap. You can do a remote air gap with your physical storage. And then you're saying there's I think, I'm not sure I directly heard that, but then the next layer is going to be tape with the CTA, the Chevy truck access method, right? >> Well, so while we don't actively support tape and go to that there's basically two air gap solutions out there that people talk about either physical, which goes to tape or optical or logical. We do logical air gaping. We don't do air gaping to tape 'cause we don't sell tape. So we make sure that it's a remote logical air gap going to a secondary DR Site. Now, obviously in today's world, no one has a true DR data center anymore, right. All data centers are both active and DR for another site. And because we're so heavily concentrated in the global Fortune 2000, almost all the InfiniBoxes in the field already are set up as in a disaster recovery configuration. So using a remote logical air gap would be is easy for us to do with our InfiniBox SSA II and the whole InfiniBox family. >> And, I get, you guys don't do tape, but when you say remote, so you've got a local air gap, right? But then you also you call a remote logical, but you've got a physical air gap, right? >> Yeah, they would be physically separated, but when you're not going to tape because it's fully removable or optical, then the security analysts consider that type of air gap, a logical air gap, even though it's physically at a remote. >> I understand, you spent a lot of time with the channel as well. I know, and they must be all over this. They must really be climbing on to the whole cyber resiliency. What do you say, do they set up? Like a lot of the guys, doing managed services as well? I'm just curious. Are there separate processes for the air gap piece than there are for the mainstream production environment or is it sort of blended together? How are they approaching that? >> So on the InfiniGuard product line, it's blended together, okay. On the InfiniBox with our InfiniSafe reference architecture, you do need to have an extra server where you create an scuzzy private VLAN and with that private VLAN, you set up your fenced forensic environment. So it's a slightly more complicated. The InfiniGuard is a 100% automated. On the InfiniBox we will be pushing that in the future and we will continue to have releases on InfiniSafe and making more and more automated. But the air gaping and the fence reference now are as a reference architecture configuration. Not with click on a gooey in the InfiniGuard case are original InfiniSafe. All you do is click on some windows and it just goes does. And we're not there yet, but we will be there in the future. But it's such a top of mind topic, as you probably see. Last year, Fortune did a survey of the Fortune 500 CEOs and the number one cited threat at 66% by the way was cybersecurity. So one of the key things store storage vendors do not just us, but all storage vendors is need to convince the CISO that storage is a critical component of a comprehensive cybersecurity strategy. And by having these four things, the rapid recovery, the fenced forensic environment, the air gaping technology and the immutable snapshots. You've got all of the checkbox items that a CISO needs to see to make sure. That said many CISOs still even today stood on real to a comprehensive cybersecurity strategy and that's something that the storage industry in general needs to work on with the security community from a partner perspective. The value is they can sell a full package, so they can go to their end user and say, look, here's what we have for edge protection. Here's what we've got to track the bad guide down once something's happened or to alert you that something's happened by having tools like IBM's, Q Radar and competitive tools to that product line. That can traverse the servers and the software infrastructure, and try to locate malware, ransomware akin to the way all of us have Norton or something like Norton on our laptop that is trolling constantly for viruses. So that's sort of software and then of course storage. And those are the elements that you really need to have an overall cybersecurity strategy. Right now many companies have not realized that storage is critical. When you think about it. When you talk to people in security industry, and I know you do from original insertion intrusion to solution is 287 days. Well guess what if the data sets thereafter, whether it be secondary InfiniGuard or primary within InfiniBox, if they're going to trap those things and they're going to take it. They might have trapped those few data sets at day 50, even though you don't even launch the attack until day 200. So it's a big deal of why storage is so critical and why CISOs and CIOs need to make sure they include it day one. >> It's where the data lives, okay. Eric. Wow.. A lot of topics we discovered. I love the agile sort of cadence. I presume you're not done for the year. Look forward to having you back and thanks so much for coming on today. >> Great. Thanks you, Dave. We of course love being on "theCUBE". Thanks again. And thanks for all the nice things about Infinidat. You've been saying thank you. >> Okay. Yeah, thank you for watching this cube conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

(bright music) >> In the 2010s, organizations became keenly aware that data would become the key ingredient to driving competitive advantage, differentiation, and growth. But to this day, putting data to work remains a difficult challenge for many, if not most organizations. Now, as the cloud matures, it has become a game changer for data practitioners by making cheap storage and massive processing power readily accessible. We've also seen better tooling in the form of data workflows, streaming, machine intelligence, AI, developer tools, security, observability, automation, new databases and the like. These innovations they accelerate data proficiency, but at the same time, they add complexity for practitioners. Data lakes, data hubs, data warehouses, data marts, data fabrics, data meshes, data catalogs, data oceans are forming, they're evolving and exploding onto the scene. So in an effort to bring perspective to the sea of optionality, we've brought together the brightest minds in the data analyst community to discuss how data management is morphing and what practitioners should expect in 2022 and beyond. Hello everyone, my name is Dave Velannte with theCUBE, and I'd like to welcome you to a special Cube presentation, analysts predictions 2022: the future of data management. We've gathered six of the best analysts in data and data management who are going to present and discuss their top predictions and trends for 2022 in the first half of this decade. Let me introduce our six power panelists. Sanjeev Mohan is former Gartner Analyst and Principal at SanjMo. Tony Baer, principal at dbInsight, Carl Olofson is well-known Research Vice President with IDC, Dave Menninger is Senior Vice President and Research Director at Ventana Research, Brad Shimmin, Chief Analyst, AI Platforms, Analytics and Data Management at Omdia and Doug Henschen, Vice President and Principal Analyst at Constellation Research. Gentlemen, welcome to the program and thanks for coming on theCUBE today. >> Great to be here. >> Thank you. >> All right, here's the format we're going to use. I as moderator, I'm going to call on each analyst separately who then will deliver their prediction or mega trend, and then in the interest of time management and pace, two analysts will have the opportunity to comment. If we have more time, we'll elongate it, but let's get started right away. Sanjeev Mohan, please kick it off. You want to talk about governance, go ahead sir. >> Thank you Dave. I believe that data governance which we've been talking about for many years is now not only going to be mainstream, it's going to be table stakes. And all the things that you mentioned, you know, the data, ocean data lake, lake houses, data fabric, meshes, the common glue is metadata. If we don't understand what data we have and we are governing it, there is no way we can manage it. So we saw Informatica went public last year after a hiatus of six. I'm predicting that this year we see some more companies go public. My bet is on Culebra, most likely and maybe Alation we'll see go public this year. I'm also predicting that the scope of data governance is going to expand beyond just data. It's not just data and reports. We are going to see more transformations like spark jawsxxxxx, Python even Air Flow. We're going to see more of a streaming data. So from Kafka Schema Registry, for example. We will see AI models become part of this whole governance suite. So the governance suite is going to be very comprehensive, very detailed lineage, impact analysis, and then even expand into data quality. We already seen that happen with some of the tools where they are buying these smaller companies and bringing in data quality monitoring and integrating it with metadata management, data catalogs, also data access governance. So what we are going to see is that once the data governance platforms become the key entry point into these modern architectures, I'm predicting that the usage, the number of users of a data catalog is going to exceed that of a BI tool. That will take time and we already seen that trajectory. Right now if you look at BI tools, I would say there a hundred users to BI tool to one data catalog. And I see that evening out over a period of time and at some point data catalogs will really become the main way for us to access data. Data catalog will help us visualize data, but if we want to do more in-depth analysis, it'll be the jumping off point into the BI tool, the data science tool and that is the journey I see for the data governance products. >> Excellent, thank you. Some comments. Maybe Doug, a lot of things to weigh in on there, maybe you can comment. >> Yeah, Sanjeev I think you're spot on, a lot of the trends the one disagreement, I think it's really still far from mainstream. As you say, we've been talking about this for years, it's like God, motherhood, apple pie, everyone agrees it's important, but too few organizations are really practicing good governance because it's hard and because the incentives have been lacking. I think one thing that deserves mention in this context is ESG mandates and guidelines, these are environmental, social and governance, regs and guidelines. We've seen the environmental regs and guidelines and posts in industries, particularly the carbon-intensive industries. We've seen the social mandates, particularly diversity imposed on suppliers by companies that are leading on this topic. We've seen governance guidelines now being imposed by banks on investors. So these ESGs are presenting new carrots and sticks, and it's going to demand more solid data. It's going to demand more detailed reporting and solid reporting, tighter governance. But we're still far from mainstream adoption. We have a lot of, you know, best of breed niche players in the space. I think the signs that it's going to be more mainstream are starting with things like Azure Purview, Google Dataplex, the big cloud platform players seem to be upping the ante and starting to address governance. >> Excellent, thank you Doug. Brad, I wonder if you could chime in as well. >> Yeah, I would love to be a believer in data catalogs. But to Doug's point, I think that it's going to take some more pressure for that to happen. I recall metadata being something every enterprise thought they were going to get under control when we were working on service oriented architecture back in the nineties and that didn't happen quite the way we anticipated. And so to Sanjeev's point it's because it is really complex and really difficult to do. My hope is that, you know, we won't sort of, how do I put this? Fade out into this nebula of domain catalogs that are specific to individual use cases like Purview for getting data quality right or like data governance and cybersecurity. And instead we have some tooling that can actually be adaptive to gather metadata to create something. And I know its important to you, Sanjeev and that is this idea of observability. If you can get enough metadata without moving your data around, but understanding the entirety of a system that's running on this data, you can do a lot. So to help with the governance that Doug is talking about. >> So I just want to add that, data governance, like any other initiatives did not succeed even AI went into an AI window, but that's a different topic. But a lot of these things did not succeed because to your point, the incentives were not there. I remember when Sarbanes Oxley had come into the scene, if a bank did not do Sarbanes Oxley, they were very happy to a million dollar fine. That was like, you know, pocket change for them instead of doing the right thing. But I think the stakes are much higher now. With GDPR, the flood gates opened. Now, you know, California, you know, has CCPA but even CCPA is being outdated with CPRA, which is much more GDPR like. So we are very rapidly entering a space where pretty much every major country in the world is coming up with its own compliance regulatory requirements, data residents is becoming really important. And I think we are going to reach a stage where it won't be optional anymore. So whether we like it or not, and I think the reason data catalogs were not successful in the past is because we did not have the right focus on adoption. We were focused on features and these features were disconnected, very hard for business to adopt. These are built by IT people for IT departments to take a look at technical metadata, not business metadata. Today the tables have turned. CDOs are driving this initiative, regulatory compliances are beating down hard, so I think the time might be right. >> Yeah so guys, we have to move on here. But there's some real meat on the bone here, Sanjeev. I like the fact that you called out Culebra and Alation, so we can look back a year from now and say, okay, he made the call, he stuck it. And then the ratio of BI tools to data catalogs that's another sort of measurement that we can take even though with some skepticism there, that's something that we can watch. And I wonder if someday, if we'll have more metadata than data. But I want to move to Tony Baer, you want to talk about data mesh and speaking, you know, coming off of governance. I mean, wow, you know the whole concept of data mesh is, decentralized data, and then governance becomes, you know, a nightmare there, but take it away, Tony. >> We'll put this way, data mesh, you know, the idea at least as proposed by ThoughtWorks. You know, basically it was at least a couple of years ago and the press has been almost uniformly almost uncritical. A good reason for that is for all the problems that basically Sanjeev and Doug and Brad we're just speaking about, which is that we have all this data out there and we don't know what to do about it. Now, that's not a new problem. That was a problem we had in enterprise data warehouses, it was a problem when we had over DoOP data clusters, it's even more of a problem now that data is out in the cloud where the data is not only your data lake, is not only us three, it's all over the place. And it's also including streaming, which I know we'll be talking about later. So the data mesh was a response to that, the idea of that we need to bait, you know, who are the folks that really know best about governance? It's the domain experts. So it was basically data mesh was an architectural pattern and a process. My prediction for this year is that data mesh is going to hit cold heart reality. Because if you do a Google search, basically the published work, the articles on data mesh have been largely, you know, pretty uncritical so far. Basically loading and is basically being a very revolutionary new idea. I don't think it's that revolutionary because we've talked about ideas like this. Brad now you and I met years ago when we were talking about so and decentralizing all of us, but it was at the application level. Now we're talking about it at the data level. And now we have microservices. So there's this thought of have we managed if we're deconstructing apps in cloud native to microservices, why don't we think of data in the same way? My sense this year is that, you know, this has been a very active search if you look at Google search trends, is that now companies, like enterprise are going to look at this seriously. And as they look at it seriously, it's going to attract its first real hard scrutiny, it's going to attract its first backlash. That's not necessarily a bad thing. It means that it's being taken seriously. The reason why I think that you'll start to see basically the cold hearted light of day shine on data mesh is that it's still a work in progress. You know, this idea is basically a couple of years old and there's still some pretty major gaps. The biggest gap is in the area of federated governance. Now federated governance itself is not a new issue. Federated governance decision, we started figuring out like, how can we basically strike the balance between getting let's say between basically consistent enterprise policy, consistent enterprise governance, but yet the groups that understand the data and know how to basically, you know, that, you know, how do we basically sort of balance the two? There's a huge gap there in practice and knowledge. Also to a lesser extent, there's a technology gap which is basically in the self-service technologies that will help teams essentially govern data. You know, basically through the full life cycle, from develop, from selecting the data from, you know, building the pipelines from, you know, determining your access control, looking at quality, looking at basically whether the data is fresh or whether it's trending off course. So my prediction is that it will receive the first harsh scrutiny this year. You are going to see some organization and enterprises declare premature victory when they build some federated query implementations. You going to see vendors start with data mesh wash their products anybody in the data management space that they are going to say that where this basically a pipelining tool, whether it's basically ELT, whether it's a catalog or federated query tool, they will all going to get like, you know, basically promoting the fact of how they support this. Hopefully nobody's going to call themselves a data mesh tool because data mesh is not a technology. We're going to see one other thing come out of this. And this harks back to the metadata that Sanjeev was talking about and of the catalog just as he was talking about. Which is that there's going to be a new focus, every renewed focus on metadata. And I think that's going to spur interest in data fabrics. Now data fabrics are pretty vaguely defined, but if we just take the most elemental definition, which is a common metadata back plane, I think that if anybody is going to get serious about data mesh, they need to look at the data fabric because we all at the end of the day, need to speak, you know, need to read from the same sheet of music. >> So thank you Tony. Dave Menninger, I mean, one of the things that people like about data mesh is it pretty crisply articulate some of the flaws in today's organizational approaches to data. What are your thoughts on this? >> Well, I think we have to start by defining data mesh, right? The term is already getting corrupted, right? Tony said it's going to see the cold hard light of day. And there's a problem right now that there are a number of overlapping terms that are similar but not identical. So we've got data virtualization, data fabric, excuse me for a second. (clears throat) Sorry about that. Data virtualization, data fabric, data federation, right? So I think that it's not really clear what each vendor means by these terms. I see data mesh and data fabric becoming quite popular. I've interpreted data mesh as referring primarily to the governance aspects as originally intended and specified. But that's not the way I see vendors using it. I see vendors using it much more to mean data fabric and data virtualization. So I'm going to comment on the group of those things. I think the group of those things is going to happen. They're going to happen, they're going to become more robust. Our research suggests that a quarter of organizations are already using virtualized access to their data lakes and another half, so a total of three quarters will eventually be accessing their data lakes using some sort of virtualized access. Again, whether you define it as mesh or fabric or virtualization isn't really the point here. But this notion that there are different elements of data, metadata and governance within an organization that all need to be managed collectively. The interesting thing is when you look at the satisfaction rates of those organizations using virtualization versus those that are not, it's almost double, 68% of organizations, I'm sorry, 79% of organizations that were using virtualized access express satisfaction with their access to the data lake. Only 39% express satisfaction if they weren't using virtualized access. >> Oh thank you Dave. Sanjeev we just got about a couple of minutes on this topic, but I know you're speaking or maybe you've always spoken already on a panel with (indistinct) who sort of invented the concept. Governance obviously is a big sticking point, but what are your thoughts on this? You're on mute. (panelist chuckling) >> So my message to (indistinct) and to the community is as opposed to what they said, let's not define it. We spent a whole year defining it, there are four principles, domain, product, data infrastructure, and governance. Let's take it to the next level. I get a lot of questions on what is the difference between data fabric and data mesh? And I'm like I can't compare the two because data mesh is a business concept, data fabric is a data integration pattern. How do you compare the two? You have to bring data mesh a level down. So to Tony's point, I'm on a warpath in 2022 to take it down to what does a data product look like? How do we handle shared data across domains and governance? And I think we are going to see more of that in 2022, or is "operationalization" of data mesh. >> I think we could have a whole hour on this topic, couldn't we? Maybe we should do that. But let's corner. Let's move to Carl. So Carl, you're a database guy, you've been around that block for a while now, you want to talk about graph databases, bring it on. >> Oh yeah. Okay thanks. So I regard graph database as basically the next truly revolutionary database management technology. I'm looking forward for the graph database market, which of course we haven't defined yet. So obviously I have a little wiggle room in what I'm about to say. But this market will grow by about 600% over the next 10 years. Now, 10 years is a long time. But over the next five years, we expect to see gradual growth as people start to learn how to use it. The problem is not that it's not useful, its that people don't know how to use it. So let me explain before I go any further what a graph database is because some of the folks on the call may not know what it is. A graph database organizes data according to a mathematical structure called a graph. The graph has elements called nodes and edges. So a data element drops into a node, the nodes are connected by edges, the edges connect one node to another node. Combinations of edges create structures that you can analyze to determine how things are related. In some cases, the nodes and edges can have properties attached to them which add additional informative material that makes it richer, that's called a property graph. There are two principle use cases for graph databases. There's semantic property graphs, which are use to break down human language texts into the semantic structures. Then you can search it, organize it and answer complicated questions. A lot of AI is aimed at semantic graphs. Another kind is the property graph that I just mentioned, which has a dazzling number of use cases. I want to just point out as I talk about this, people are probably wondering, well, we have relation databases, isn't that good enough? So a relational database defines... It supports what I call definitional relationships. That means you define the relationships in a fixed structure. The database drops into that structure, there's a value, foreign key value, that relates one table to another and that value is fixed. You don't change it. If you change it, the database becomes unstable, it's not clear what you're looking at. In a graph database, the system is designed to handle change so that it can reflect the true state of the things that it's being used to track. So let me just give you some examples of use cases for this. They include entity resolution, data lineage, social media analysis, Customer 360, fraud prevention. There's cybersecurity, there's strong supply chain is a big one actually. There is explainable AI and this is going to become important too because a lot of people are adopting AI. But they want a system after the fact to say, how do the AI system come to that conclusion? How did it make that recommendation? Right now we don't have really good ways of tracking that. Machine learning in general, social network, I already mentioned that. And then we've got, oh gosh, we've got data governance, data compliance, risk management. We've got recommendation, we've got personalization, anti money laundering, that's another big one, identity and access management, network and IT operations is already becoming a key one where you actually have mapped out your operation, you know, whatever it is, your data center and you can track what's going on as things happen there, root cause analysis, fraud detection is a huge one. A number of major credit card companies use graph databases for fraud detection, risk analysis, tracking and tracing turn analysis, next best action, what if analysis, impact analysis, entity resolution and I would add one other thing or just a few other things to this list, metadata management. So Sanjeev, here you go, this is your engine. Because I was in metadata management for quite a while in my past life. And one of the things I found was that none of the data management technologies that were available to us could efficiently handle metadata because of the kinds of structures that result from it, but graphs can, okay? Graphs can do things like say, this term in this context means this, but in that context, it means that, okay? Things like that. And in fact, logistics management, supply chain. And also because it handles recursive relationships, by recursive relationships I mean objects that own other objects that are of the same type. You can do things like build materials, you know, so like parts explosion. Or you can do an HR analysis, who reports to whom, how many levels up the chain and that kind of thing. You can do that with relational databases, but yet it takes a lot of programming. In fact, you can do almost any of these things with relational databases, but the problem is, you have to program it. It's not supported in the database. And whenever you have to program something, that means you can't trace it, you can't define it. You can't publish it in terms of its functionality and it's really, really hard to maintain over time. >> Carl, thank you. I wonder if we could bring Brad in, I mean. Brad, I'm sitting here wondering, okay, is this incremental to the market? Is it disruptive and replacement? What are your thoughts on this phase? >> It's already disrupted the market. I mean, like Carl said, go to any bank and ask them are you using graph databases to get fraud detection under control? And they'll say, absolutely, that's the only way to solve this problem. And it is frankly. And it's the only way to solve a lot of the problems that Carl mentioned. And that is, I think it's Achilles heel in some ways. Because, you know, it's like finding the best way to cross the seven bridges of Koenigsberg. You know, it's always going to kind of be tied to those use cases because it's really special and it's really unique and because it's special and it's unique, it's still unfortunately kind of stands apart from the rest of the community that's building, let's say AI outcomes, as a great example here. Graph databases and AI, as Carl mentioned, are like chocolate and peanut butter. But technologically, you think don't know how to talk to one another, they're completely different. And you know, you can't just stand up SQL and query them. You've got to learn, know what is the Carl? Specter special. Yeah, thank you to, to actually get to the data in there. And if you're going to scale that data, that graph database, especially a property graph, if you're going to do something really complex, like try to understand you know, all of the metadata in your organization, you might just end up with, you know, a graph database winter like we had the AI winter simply because you run out of performance to make the thing happen. So, I think it's already disrupted, but we need to like treat it like a first-class citizen in the data analytics and AI community. We need to bring it into the fold. We need to equip it with the tools it needs to do the magic it does and to do it not just for specialized use cases, but for everything. 'Cause I'm with Carl. I think it's absolutely revolutionary. >> Brad identified the principal, Achilles' heel of the technology which is scaling. When these things get large and complex enough that they spill over what a single server can handle, you start to have difficulties because the relationships span things that have to be resolved over a network and then you get network latency and that slows the system down. So that's still a problem to be solved. >> Sanjeev, any quick thoughts on this? I mean, I think metadata on the word cloud is going to be the largest font, but what are your thoughts here? >> I want to (indistinct) So people don't associate me with only metadata, so I want to talk about something slightly different. dbengines.com has done an amazing job. I think almost everyone knows that they chronicle all the major databases that are in use today. In January of 2022, there are 381 databases on a ranked list of databases. The largest category is RDBMS. The second largest category is actually divided into two property graphs and IDF graphs. These two together make up the second largest number databases. So talking about Achilles heel, this is a problem. The problem is that there's so many graph databases to choose from. They come in different shapes and forms. To Brad's point, there's so many query languages in RDBMS, in SQL. I know the story, but here We've got cipher, we've got gremlin, we've got GQL and then we're proprietary languages. So I think there's a lot of disparity in this space. >> Well, excellent. All excellent points, Sanjeev, if I must say. And that is a problem that the languages need to be sorted and standardized. People need to have a roadmap as to what they can do with it. Because as you say, you can do so many things. And so many of those things are unrelated that you sort of say, well, what do we use this for? And I'm reminded of the saying I learned a bunch of years ago. And somebody said that the digital computer is the only tool man has ever device that has no particular purpose. (panelists chuckle) >> All right guys, we got to move on to Dave Menninger. We've heard about streaming. Your prediction is in that realm, so please take it away. >> Sure. So I like to say that historical databases are going to become a thing of the past. By that I don't mean that they're going to go away, that's not my point. I mean, we need historical databases, but streaming data is going to become the default way in which we operate with data. So in the next say three to five years, I would expect that data platforms and we're using the term data platforms to represent the evolution of databases and data lakes, that the data platforms will incorporate these streaming capabilities. We're going to process data as it streams into an organization and then it's going to roll off into historical database. So historical databases don't go away, but they become a thing of the past. They store the data that occurred previously. And as data is occurring, we're going to be processing it, we're going to be analyzing it, we're going to be acting on it. I mean we only ever ended up with historical databases because we were limited by the technology that was available to us. Data doesn't occur in patches. But we processed it in patches because that was the best we could do. And it wasn't bad and we've continued to improve and we've improved and we've improved. But streaming data today is still the exception. It's not the rule, right? There are projects within organizations that deal with streaming data. But it's not the default way in which we deal with data yet. And so that's my prediction is that this is going to change, we're going to have streaming data be the default way in which we deal with data and how you label it and what you call it. You know, maybe these databases and data platforms just evolved to be able to handle it. But we're going to deal with data in a different way. And our research shows that already, about half of the participants in our analytics and data benchmark research, are using streaming data. You know, another third are planning to use streaming technologies. So that gets us to about eight out of 10 organizations need to use this technology. And that doesn't mean they have to use it throughout the whole organization, but it's pretty widespread in its use today and has continued to grow. If you think about the consumerization of IT, we've all been conditioned to expect immediate access to information, immediate responsiveness. You know, we want to know if an item is on the shelf at our local retail store and we can go in and pick it up right now. You know, that's the world we live in and that's spilling over into the enterprise IT world We have to provide those same types of capabilities. So that's my prediction, historical databases become a thing of the past, streaming data becomes the default way in which we operate with data. >> All right thank you David. Well, so what say you, Carl, the guy who has followed historical databases for a long time? >> Well, one thing actually, every database is historical because as soon as you put data in it, it's now history. They'll no longer reflect the present state of things. But even if that history is only a millisecond old, it's still history. But I would say, I mean, I know you're trying to be a little bit provocative in saying this Dave 'cause you know, as well as I do that people still need to do their taxes, they still need to do accounting, they still need to run general ledger programs and things like that. That all involves historical data. That's not going to go away unless you want to go to jail. So you're going to have to deal with that. But as far as the leading edge functionality, I'm totally with you on that. And I'm just, you know, I'm just kind of wondering if this requires a change in the way that we perceive applications in order to truly be manifested and rethinking the way applications work. Saying that an application should respond instantly, as soon as the state of things changes. What do you say about that? >> I think that's true. I think we do have to think about things differently. It's not the way we designed systems in the past. We're seeing more and more systems designed that way. But again, it's not the default. And I agree 100% with you that we do need historical databases you know, that's clear. And even some of those historical databases will be used in conjunction with the streaming data, right? >> Absolutely. I mean, you know, let's take the data warehouse example where you're using the data warehouse as its context and the streaming data as the present and you're saying, here's the sequence of things that's happening right now. Have we seen that sequence before? And where? What does that pattern look like in past situations? And can we learn from that? >> So Tony Baer, I wonder if you could comment? I mean, when you think about, you know, real time inferencing at the edge, for instance, which is something that a lot of people talk about, a lot of what we're discussing here in this segment, it looks like it's got a great potential. What are your thoughts? >> Yeah, I mean, I think you nailed it right. You know, you hit it right on the head there. Which is that, what I'm seeing is that essentially. Then based on I'm going to split this one down the middle is that I don't see that basically streaming is the default. What I see is streaming and basically and transaction databases and analytics data, you know, data warehouses, data lakes whatever are converging. And what allows us technically to converge is cloud native architecture, where you can basically distribute things. So you can have a node here that's doing the real-time processing, that's also doing... And this is where it leads in or maybe doing some of that real time predictive analytics to take a look at, well look, we're looking at this customer journey what's happening with what the customer is doing right now and this is correlated with what other customers are doing. So the thing is that in the cloud, you can basically partition this and because of basically the speed of the infrastructure then you can basically bring these together and kind of orchestrate them sort of a loosely coupled manner. The other parts that the use cases are demanding, and this is part of it goes back to what Dave is saying. Is that, you know, when you look at Customer 360, when you look at let's say Smart Utility products, when you look at any type of operational problem, it has a real time component and it has an historical component. And having predictive and so like, you know, my sense here is that technically we can bring this together through the cloud. And I think the use case is that we can apply some real time sort of predictive analytics on these streams and feed this into the transactions so that when we make a decision in terms of what to do as a result of a transaction, we have this real-time input. >> Sanjeev, did you have a comment? >> Yeah, I was just going to say that to Dave's point, you know, we have to think of streaming very different because in the historical databases, we used to bring the data and store the data and then we used to run rules on top, aggregations and all. But in case of streaming, the mindset changes because the rules are normally the inference, all of that is fixed, but the data is constantly changing. So it's a completely reversed way of thinking and building applications on top of that. >> So Dave Menninger, there seem to be some disagreement about the default. What kind of timeframe are you thinking about? Is this end of decade it becomes the default? What would you pin? >> I think around, you know, between five to 10 years, I think this becomes the reality. >> I think its... >> It'll be more and more common between now and then, but it becomes the default. And I also want Sanjeev at some point, maybe in one of our subsequent conversations, we need to talk about governing streaming data. 'Cause that's a whole nother set of challenges. >> We've also talked about it rather in two dimensions, historical and streaming, and there's lots of low latency, micro batch, sub-second, that's not quite streaming, but in many cases its fast enough and we're seeing a lot of adoption of near real time, not quite real-time as good enough for many applications. (indistinct cross talk from panelists) >> Because nobody's really taking the hardware dimension (mumbles). >> That'll just happened, Carl. (panelists laughing) >> So near real time. But maybe before you lose the customer, however we define that, right? Okay, let's move on to Brad. Brad, you want to talk about automation, AI, the pipeline people feel like, hey, we can just automate everything. What's your prediction? >> Yeah I'm an AI aficionados so apologies in advance for that. But, you know, I think that we've been seeing automation play within AI for some time now. And it's helped us do a lot of things especially for practitioners that are building AI outcomes in the enterprise. It's helped them to fill skills gaps, it's helped them to speed development and it's helped them to actually make AI better. 'Cause it, you know, in some ways provide some swim lanes and for example, with technologies like AutoML can auto document and create that sort of transparency that we talked about a little bit earlier. But I think there's an interesting kind of conversion happening with this idea of automation. And that is that we've had the automation that started happening for practitioners, it's trying to move out side of the traditional bounds of things like I'm just trying to get my features, I'm just trying to pick the right algorithm, I'm just trying to build the right model and it's expanding across that full life cycle, building an AI outcome, to start at the very beginning of data and to then continue on to the end, which is this continuous delivery and continuous automation of that outcome to make sure it's right and it hasn't drifted and stuff like that. And because of that, because it's become kind of powerful, we're starting to actually see this weird thing happen where the practitioners are starting to converge with the users. And that is to say that, okay, if I'm in Tableau right now, I can stand up Salesforce Einstein Discovery, and it will automatically create a nice predictive algorithm for me given the data that I pull in. But what's starting to happen and we're seeing this from the companies that create business software, so Salesforce, Oracle, SAP, and others is that they're starting to actually use these same ideals and a lot of deep learning (chuckles) to basically stand up these out of the box flip-a-switch, and you've got an AI outcome at the ready for business users. And I am very much, you know, I think that's the way that it's going to go and what it means is that AI is slowly disappearing. And I don't think that's a bad thing. I think if anything, what we're going to see in 2022 and maybe into 2023 is this sort of rush to put this idea of disappearing AI into practice and have as many of these solutions in the enterprise as possible. You can see, like for example, SAP is going to roll out this quarter, this thing called adaptive recommendation services, which basically is a cold start AI outcome that can work across a whole bunch of different vertical markets and use cases. It's just a recommendation engine for whatever you needed to do in the line of business. So basically, you're an SAP user, you look up to turn on your software one day, you're a sales professional let's say, and suddenly you have a recommendation for customer churn. Boom! It's going, that's great. Well, I don't know, I think that's terrifying. In some ways I think it is the future that AI is going to disappear like that, but I'm absolutely terrified of it because I think that what it really does is it calls attention to a lot of the issues that we already see around AI, specific to this idea of what we like to call at Omdia, responsible AI. Which is, you know, how do you build an AI outcome that is free of bias, that is inclusive, that is fair, that is safe, that is secure, that its audible, et cetera, et cetera, et cetera, et cetera. I'd take a lot of work to do. And so if you imagine a customer that's just a Salesforce customer let's say, and they're turning on Einstein Discovery within their sales software, you need some guidance to make sure that when you flip that switch, that the outcome you're going to get is correct. And that's going to take some work. And so, I think we're going to see this move, let's roll this out and suddenly there's going to be a lot of problems, a lot of pushback that we're going to see. And some of that's going to come from GDPR and others that Sanjeev was mentioning earlier. A lot of it is going to come from internal CSR requirements within companies that are saying, "Hey, hey, whoa, hold up, we can't do this all at once. "Let's take the slow route, "let's make AI automated in a smart way." And that's going to take time. >> Yeah, so a couple of predictions there that I heard. AI simply disappear, it becomes invisible. Maybe if I can restate that. And then if I understand it correctly, Brad you're saying there's a backlash in the near term. You'd be able to say, oh, slow down. Let's automate what we can. Those attributes that you talked about are non trivial to achieve, is that why you're a bit of a skeptic? >> Yeah. I think that we don't have any sort of standards that companies can look to and understand. And we certainly, within these companies, especially those that haven't already stood up an internal data science team, they don't have the knowledge to understand when they flip that switch for an automated AI outcome that it's going to do what they think it's going to do. And so we need some sort of standard methodology and practice, best practices that every company that's going to consume this invisible AI can make use of them. And one of the things that you know, is sort of started that Google kicked off a few years back that's picking up some momentum and the companies I just mentioned are starting to use it is this idea of model cards where at least you have some transparency about what these things are doing. You know, so like for the SAP example, we know, for example, if it's convolutional neural network with a long, short term memory model that it's using, we know that it only works on Roman English and therefore me as a consumer can say, "Oh, well I know that I need to do this internationally. "So I should not just turn this on today." >> Thank you. Carl could you add anything, any context here? >> Yeah, we've talked about some of the things Brad mentioned here at IDC and our future of intelligence group regarding in particular, the moral and legal implications of having a fully automated, you know, AI driven system. Because we already know, and we've seen that AI systems are biased by the data that they get, right? So if they get data that pushes them in a certain direction, I think there was a story last week about an HR system that was recommending promotions for White people over Black people, because in the past, you know, White people were promoted and more productive than Black people, but it had no context as to why which is, you know, because they were being historically discriminated, Black people were being historically discriminated against, but the system doesn't know that. So, you know, you have to be aware of that. And I think that at the very least, there should be controls when a decision has either a moral or legal implication. When you really need a human judgment, it could lay out the options for you. But a person actually needs to authorize that action. And I also think that we always will have to be vigilant regarding the kind of data we use to train our systems to make sure that it doesn't introduce unintended biases. In some extent, they always will. So we'll always be chasing after them. But that's (indistinct). >> Absolutely Carl, yeah. I think that what you have to bear in mind as a consumer of AI is that it is a reflection of us and we are a very flawed species. And so if you look at all of the really fantastic, magical looking supermodels we see like GPT-3 and four, that's coming out, they're xenophobic and hateful because the people that the data that's built upon them and the algorithms and the people that build them are us. So AI is a reflection of us. We need to keep that in mind. >> Yeah, where the AI is biased 'cause humans are biased. All right, great. All right let's move on. Doug you mentioned mentioned, you know, lot of people that said that data lake, that term is not going to live on but here's to be, have some lakes here. You want to talk about lake house, bring it on. >> Yes, I do. My prediction is that lake house and this idea of a combined data warehouse and data lake platform is going to emerge as the dominant data management offering. I say offering that doesn't mean it's going to be the dominant thing that organizations have out there, but it's going to be the pro dominant vendor offering in 2022. Now heading into 2021, we already had Cloudera, Databricks, Microsoft, Snowflake as proponents, in 2021, SAP, Oracle, and several of all of these fabric virtualization/mesh vendors joined the bandwagon. The promise is that you have one platform that manages your structured, unstructured and semi-structured information. And it addresses both the BI analytics needs and the data science needs. The real promise there is simplicity and lower cost. But I think end users have to answer a few questions. The first is, does your organization really have a center of data gravity or is the data highly distributed? Multiple data warehouses, multiple data lakes, on premises, cloud. If it's very distributed and you'd have difficulty consolidating and that's not really a goal for you, then maybe that single platform is unrealistic and not likely to add value to you. You know, also the fabric and virtualization vendors, the mesh idea, that's where if you have this highly distributed situation, that might be a better path forward. The second question, if you are looking at one of these lake house offerings, you are looking at consolidating, simplifying, bringing together to a single platform. You have to make sure that it meets both the warehouse need and the data lake need. So you have vendors like Databricks, Microsoft with Azure Synapse. New really to the data warehouse space and they're having to prove that these data warehouse capabilities on their platforms can meet the scaling requirements, can meet the user and query concurrency requirements. Meet those tight SLS. And then on the other hand, you have the Oracle, SAP, Snowflake, the data warehouse folks coming into the data science world, and they have to prove that they can manage the unstructured information and meet the needs of the data scientists. I'm seeing a lot of the lake house offerings from the warehouse crowd, managing that unstructured information in columns and rows. And some of these vendors, Snowflake a particular is really relying on partners for the data science needs. So you really got to look at a lake house offering and make sure that it meets both the warehouse and the data lake requirement. >> Thank you Doug. Well Tony, if those two worlds are going to come together, as Doug was saying, the analytics and the data science world, does it need to be some kind of semantic layer in between? I don't know. Where are you in on this topic? >> (chuckles) Oh, didn't we talk about data fabrics before? Common metadata layer (chuckles). Actually, I'm almost tempted to say let's declare victory and go home. And that this has actually been going on for a while. I actually agree with, you know, much of what Doug is saying there. Which is that, I mean I remember as far back as I think it was like 2014, I was doing a study. I was still at Ovum, (indistinct) Omdia, looking at all these specialized databases that were coming up and seeing that, you know, there's overlap at the edges. But yet, there was still going to be a reason at the time that you would have, let's say a document database for JSON, you'd have a relational database for transactions and for data warehouse and you had basically something at that time that resembles a dupe for what we consider your data life. Fast forward and the thing is what I was seeing at the time is that you were saying they sort of blending at the edges. That was saying like about five to six years ago. And the lake house is essentially on the current manifestation of that idea. There is a dichotomy in terms of, you know, it's the old argument, do we centralize this all you know in a single place or do we virtualize? And I think it's always going to be a union yeah and there's never going to be a single silver bullet. I do see that there are also going to be questions and these are points that Doug raised. That you know, what do you need for your performance there, or for your free performance characteristics? Do you need for instance high concurrency? You need the ability to do some very sophisticated joins, or is your requirement more to be able to distribute and distribute our processing is, you know, as far as possible to get, you know, to essentially do a kind of a brute force approach. All these approaches are valid based on the use case. I just see that essentially that the lake house is the culmination of it's nothing. It's a relatively new term introduced by Databricks a couple of years ago. This is the culmination of basically what's been a long time trend. And what we see in the cloud is that as we start seeing data warehouses as a check box items say, "Hey, we can basically source data in cloud storage, in S3, "Azure Blob Store, you know, whatever, "as long as it's in certain formats, "like, you know parquet or CSP or something like that." I see that as becoming kind of a checkbox item. So to that extent, I think that the lake house, depending on how you define is already reality. And in some cases, maybe new terminology, but not a whole heck of a lot new under the sun. >> Yeah. And Dave Menninger, I mean a lot of these, thank you Tony, but a lot of this is going to come down to, you know, vendor marketing, right? Some people just kind of co-op the term, we talked about you know, data mesh washing, what are your thoughts on this? (laughing) >> Yeah, so I used the term data platform earlier. And part of the reason I use that term is that it's more vendor neutral. We've tried to sort of stay out of the vendor terminology patenting world, right? Whether the term lake houses, what sticks or not, the concept is certainly going to stick. And we have some data to back it up. About a quarter of organizations that are using data lakes today, already incorporate data warehouse functionality into it. So they consider their data lake house and data warehouse one in the same, about a quarter of organizations, a little less, but about a quarter of organizations feed the data lake from the data warehouse and about a quarter of organizations feed the data warehouse from the data lake. So it's pretty obvious that three quarters of organizations need to bring this stuff together, right? The need is there, the need is apparent. The technology is going to continue to converge. I like to talk about it, you know, you've got data lakes over here at one end, and I'm not going to talk about why people thought data lakes were a bad idea because they thought you just throw stuff in a server and you ignore it, right? That's not what a data lake is. So you've got data lake people over here and you've got database people over here, data warehouse people over here, database vendors are adding data lake capabilities and data lake vendors are adding data warehouse capabilities. So it's obvious that they're going to meet in the middle. I mean, I think it's like Tony says, I think we should declare victory and go home. >> As hell. So just a follow-up on that, so are you saying the specialized lake and the specialized warehouse, do they go away? I mean, Tony data mesh practitioners would say or advocates would say, well, they could all live. It's just a node on the mesh. But based on what Dave just said, are we gona see those all morphed together? >> Well, number one, as I was saying before, there's always going to be this sort of, you know, centrifugal force or this tug of war between do we centralize the data, do we virtualize? And the fact is I don't think that there's ever going to be any single answer. I think in terms of data mesh, data mesh has nothing to do with how you're physically implement the data. You could have a data mesh basically on a data warehouse. It's just that, you know, the difference being is that if we use the same physical data store, but everybody's logically you know, basically governing it differently, you know? Data mesh in space, it's not a technology, it's processes, it's governance process. So essentially, you know, I basically see that, you know, as I was saying before that this is basically the culmination of a long time trend we're essentially seeing a lot of blurring, but there are going to be cases where, for instance, if I need, let's say like, Upserve, I need like high concurrency or something like that. There are certain things that I'm not going to be able to get efficiently get out of a data lake. And, you know, I'm doing a system where I'm just doing really brute forcing very fast file scanning and that type of thing. So I think there always will be some delineations, but I would agree with Dave and with Doug, that we are seeing basically a confluence of requirements that we need to essentially have basically either the element, you know, the ability of a data lake and the data warehouse, these need to come together, so I think. >> I think what we're likely to see is organizations look for a converge platform that can handle both sides for their center of data gravity, the mesh and the fabric virtualization vendors, they're all on board with the idea of this converged platform and they're saying, "Hey, we'll handle all the edge cases "of the stuff that isn't in that center of data gravity "but that is off distributed in a cloud "or at a remote location." So you can have that single platform for the center of your data and then bring in virtualization, mesh, what have you, for reaching out to the distributed data. >> As Dave basically said, people are happy when they virtualized data. >> I think we have at this point, but to Dave Menninger's point, they are converging, Snowflake has introduced support for unstructured data. So obviously literally splitting here. Now what Databricks is saying is that "aha, but it's easy to go from data lake to data warehouse "than it is from databases to data lake." So I think we're getting into semantics, but we're already seeing these two converge. >> So take somebody like AWS has got what? 15 data stores. Are they're going to 15 converge data stores? This is going to be interesting to watch. All right, guys, I'm going to go down and list do like a one, I'm going to one word each and you guys, each of the analyst, if you would just add a very brief sort of course correction for me. So Sanjeev, I mean, governance is going to to be... Maybe it's the dog that wags the tail now. I mean, it's coming to the fore, all this ransomware stuff, which you really didn't talk much about security, but what's the one word in your prediction that you would leave us with on governance? >> It's going to be mainstream. >> Mainstream. Okay. Tony Baer, mesh washing is what I wrote down. That's what we're going to see in 2022, a little reality check, you want to add to that? >> Reality check, 'cause I hope that no vendor jumps the shark and close they're offering a data niche product. >> Yeah, let's hope that doesn't happen. If they do, we're going to call them out. Carl, I mean, graph databases, thank you for sharing some high growth metrics. I know it's early days, but magic is what I took away from that, so magic database. >> Yeah, I would actually, I've said this to people too. I kind of look at it as a Swiss Army knife of data because you can pretty much do anything you want with it. That doesn't mean you should. I mean, there's definitely the case that if you're managing things that are in fixed schematic relationship, probably a relation database is a better choice. There are times when the document database is a better choice. It can handle those things, but maybe not. It may not be the best choice for that use case. But for a great many, especially with the new emerging use cases I listed, it's the best choice. >> Thank you. And Dave Menninger, thank you by the way, for bringing the data in, I like how you supported all your comments with some data points. But streaming data becomes the sort of default paradigm, if you will, what would you add? >> Yeah, I would say think fast, right? That's the world we live in, you got to think fast. >> Think fast, love it. And Brad Shimmin, love it. I mean, on the one hand I was saying, okay, great. I'm afraid I might get disrupted by one of these internet giants who are AI experts. I'm going to be able to buy instead of build AI. But then again, you know, I've got some real issues. There's a potential backlash there. So give us your bumper sticker. >> I'm would say, going with Dave, think fast and also think slow to talk about the book that everyone talks about. I would say really that this is all about trust, trust in the idea of automation and a transparent and visible AI across the enterprise. And verify, verify before you do anything. >> And then Doug Henschen, I mean, I think the trend is your friend here on this prediction with lake house is really becoming dominant. I liked the way you set up that notion of, you know, the data warehouse folks coming at it from the analytics perspective and then you get the data science worlds coming together. I still feel as though there's this piece in the middle that we're missing, but your, your final thoughts will give you the (indistinct). >> I think the idea of consolidation and simplification always prevails. That's why the appeal of a single platform is going to be there. We've already seen that with, you know, DoOP platforms and moving toward cloud, moving toward object storage and object storage, becoming really the common storage point for whether it's a lake or a warehouse. And that second point, I think ESG mandates are going to come in alongside GDPR and things like that to up the ante for good governance. >> Yeah, thank you for calling that out. Okay folks, hey that's all the time that we have here, your experience and depth of understanding on these key issues on data and data management really on point and they were on display today. I want to thank you for your contributions. Really appreciate your time. >> Enjoyed it. >> Thank you. >> Thanks for having me. >> In addition to this video, we're going to be making available transcripts of the discussion. We're going to do clips of this as well we're going to put them out on social media. I'll write this up and publish the discussion on wikibon.com and siliconangle.com. No doubt, several of the analysts on the panel will take the opportunity to publish written content, social commentary or both. I want to thank the power panelists and thanks for watching this special CUBE presentation. This is Dave Vellante, be well and we'll see you next time. (bright music)

>>Welcome back to the cubes coverage here in Washington D. C. For a W. S. Public sector summit. I'm john fraser host of the queues and in person event but of course we have remote guests. It's a hybrid event as well. Amazon is streaming amazon web services, streaming all the teams, some of the key notes of course all the cube interviews are free and streaming out there as well on the all the cube channels and all the social coordinates. Our next guest is Melissa Pavlik President and Ceo POV con joining me here to talk about predictive maintenance, bringing that to life for the U. S. Air Force melissa. Thanks for coming in remotely on our virtual cube here at the physical event. >>Excellent, thank you. Good morning >>Show. People have been been um face to face for the first time since 2019. A lot of people remote calling in checking things out kind of an interesting time, right? We're living in so uh what's your, what's your take on all this? >>Sure. I mean it's a new way of doing business, right? Um I will say, I guess for us as a company we always have been remote so it's not too much of a change but it is definitely challenging, especially trying to engage with such a large user community such as the United States Air Force who isn't always used to working as remotely. So it's definitely a unique challenge for sure. >>Well let's get into, I love this topic. You had a real success story. There is a case study with the U. S. Air Force, what's the relationship take us through what you guys are doing together? >>Sure. Absolutely. So we started working with the Air Force now about five years ago on this subject and predictive maintenance. Sometimes you might hear me catch myself and say CBM plus condition based maintenance. They're synonymous. They mean the exact same thing basically. But about five years ago the Air Force was contemplating how do we get into a space of getting ahead of unscheduled maintenance events? Um if the military they're big push always his readiness how do we improve readiness? So to do that it was a big ask of do we have the data to get ahead of failures? So we started on this journey about five years ago as I said and frankly we started under the radar we weren't sure if it was going to work. So we started with two platforms. And of course when I think a lot of people here predictive maintenance, they immediately think of sensor data and sensors are wonderful data but unfortunately especially in an entity such as the Air Force not all assets are censored. So it also opened up a whole other avenue of how do we use the data that they have today to be able to generate and get ahead of failures. So it did start a really great partnership working not only with the individual, I'll say Air Force entities that Air Force Lifecycle Management Center but we also worked across all the major commands, the individual units, supply control, logistics and everyone else. So it's been a really great team effort to bring together all of those but typically would be rather segregated operations together. >>Yeah, they're getting a lot of props lately on a lot of their projects across the board and this one particular, how did you guys specifically help them modernize and with their and get this particular maintenance thing off the ground? >>Absolutely. I think quite simply it was what really we put their existing data to work. We really wanted to get in there and think about they already had a ton of data. There wasn't a need to generate more. We're talking about petabytes of information. So how do we use that and put it into a focus of getting ahead of failure? We said we established basically three key performance parameters right from the beginning it was, we knew we wanted to increase availability which was going to directly improve readiness. We needed to make sure we were reducing mission aborts and we wanted to get ahead of any kind of maintenance costs. So for us it was really how do we leverage and embrace machine learning and ai paired with just big data analytics and how do we take frankly what is more of a World War Two era architecture and turn it into something that is in the information age. So our modernization really started with how do we take their existing data and turn it into something that is useful and then simultaneously how do we educate the workforce and helping them understand what truly machine learning and AI offer because I think sometimes there's everyone has their own opinions of what that means, but when you put it into action and you need to make sure that it's something that they can take action on, right, it's not just pushing a dot moving numbers around, it's really thinking about and considering how their operations are done and then infusing that with the data on the back end, >>it's awesome. You know the old workflows in the cloud, this is legit, I mean physical assets, all kinds of things and his legacy is also but you want the modernization, I was gonna ask you about the machine learning and ai component, you brought that up. What specifically are you leveraging their from the ai side of the machine learning side? >>Absolutely for us, most and foremost we're talking about responsible a i in this case because unfortunately a lot of the data in the Air Force is human entry, so it's manual, which basically means it's open and rife for a lot of error into that data. So we're really focused heavily on the data integrity, we're really focused on utilizing different types of machine learning because I think on the surface the general opinion is there's a lot of data here. So it would open itself naturally into a lot of potential machine learning techniques, but the reality situation is this data is not human understandable unless you are a prior maintainer, frankly, it's a lot of codes, there's not a whole lot of common taxonomy. So what we've done is we've looked at those supervised and unsupervised models, we've taken a whole different approach to infusing it with truly, what I would say arguably is the most important key element, domain expertise. You know, someone who actually understands what this data means. So that way we can in in End up with actionable output something that the air force can actually put into use, see the results coming out of it. And thus far it's been great. Air mobility command has come back and said we've been able to reduce their my caps, which are parts waiting for maintenance by 18%. That's huge in this space. >>Yeah, it's interesting about unsupervised and supervised machine learning. That's a big distinct because you mentioned there's a lot of human error going on. That's a big part. Can you explain a little bit more because that was that to solve the human error part or was it the mix and match because the different data sets, but why the why both machine learning modes. >>So really it was to address both items frankly. When we started down this path, we weren't sure we were going to find right, We went in with some hypotheses and some of those ended up being true and others were not. So it was a way for us to quickly adjust as we needed to again put the data into actionable use and make sure we were responsibly doing that. So for us a lot of it, because it's human understanding and human error that goes into this natural language processing is a really big area in this space. So for us, adjusting between and trying different techniques is really where we were able to discover and find out what was going to be the most effective and useful in this particular space as well as cost effective. Because for us there's also this resistance, you have to have resist the urge to want to monitor everything. In this case we're talking about really focusing on those top drivers and depending on the type of data that we had, depending on the users that we knew were going to get involved with it as well as I would say, the historical information, it really would help us dictate on supervised versus supervised and going the unsupervised route. In some cases there's just still not ready for that because the data is just so manual. Once we get to a point where there is more automation and more automated data collection, unsupervised will definitely no doubt become more valuable right now though, in order to get those actionable. That supervised modeling was really what we found to be the most valuable >>and that makes total sense. You've got a lot of head room to grow into with Unsupervised, which is actually harder as you as you know, everyone, everyone everyone knows that. But I mean that's really the reality. Congratulations. I gotta ask you on the AWS side what part do they play in all this? Obviously the cloud um their relationship with the Air Force as well, what's their what's their role in this particular maintenance solution? >>Sure, absolutely. And I'll just say, I mean we're really proud to be a partner network with them and so when we started this there was no cloud, so today a lot of opportunity or things we hear about in the Air Force where like cloud one platform one, those weren't in existence, you know, five years ago or so. So for us when we started down this path and we had to identify very quickly a format and a host location that would allow us not only handle large amounts of data but do all of the deep analysis we needed to AWS GovCloud is where that came in. Plus it also is awesome that they were already approved at I. L. Five to be able to host that we in collaboration with them host a nist 801 +71 environment. And so it's really allowed us to to grow and deliver this this impact out over 6000 users today on the Air Force side. So for us with a W. S. Has been a great partnership. They obviously have some really great native services that are inside their cloud as well as the pairing and easy collaboration among not only licensed products but also all that free and open source that's out there because again, arguably that's the best community to pull from because they're constantly evolving and working in the space. But a W has been a really great partner for us and of course we have some of our very favorite services I'm happy to talk about, but they've been really great to work with >>what's the top services. >>So for us, a lot of top services are like ec two's work spaces, of course S three and Glacier um are right up there, but you really enjoy working across glue Athena were really big on, we find a commercial service we're looking for that's not yet available in Govcloud. And we pull in our AWS partners and ask, hey, you know when it's going to get into the gulf cloud space and they move pretty quickly to get those in there. So recent months are definitely a theme in blue. Well, >>congratulations, great solution, I love this application because it highlights the power of the cloud, What's the future in store for the U. S. Air Force when it comes to predictive maintenance. >>Sure. I mean, I think at this point they are just going to continue adding additional top driver analyses you through our work for the past couple years. We've identified a lot of operational and functional opportunities for them. So there's gonna be some definitely foundational changing coming along, some enabling new technologies to get that data integrity more automated as well so that there isn't such a heavy lift on the downstream, we're talking about data cleansing, but I think as far as predictive maintenance goes, we're definitely going to see more and more improvements across the readiness level, getting rid of and eliminating that unscheduled event that drives a lot of the readiness concerns that are out there. And we're also hoping to see a lot more improvement and I'd say enhancement across the supply chain because we know that's also an area that really they could get ahead on your part of our other work as we developed a five year long range supply forecast and it's really been opening some eyes to see how they can better plan, not only on the maintenance side but also supporting maintenance from a logistics and supply, >>great stuff melissa. Great to have you on President Ceo Path Con, you're also the business owner. Um how's things going with the business? The pandemic looks like I'm gonna come out of it stronger. Got the tailwind with cloud technology. The modernization boom is here in, in Govcloud, 10 years celebrating Govcloud birthday here at this event. How's business house? How are you doing >>good. Everything has actually been, we were, I guess fortunate, as I mentioned the very beginning, we were remote companies. So fortunately for us the pandemic did not have that much of an operational hiccup and being that a lot of our clients are in the federal space, we were able to continue working and amazingly we actually grew during the pandemic. We added quite a bit of a personnel to the team and so we're looking forward to doing some more predictive maintenance across, not only explaining the Air Force but the other services as well. >>You know, the people who were Agile had some cloud action going on, we're productive and they came out stronger melissa. Great to have you on the cube. Thank you for coming in remotely and joining our face to face event from the interwebs. Thank you so much for coming on cuba >>All right, thank you, john have a great rest of your day. >>Okay. I'm john for here at the cube with a W. S. Public sector summit in person and remote bringing guest on. We've got the new capability of bringing remotes in. We do in person. I'll see you face to face hear the cube and it's like to be here at the public sector summit. Thanks for watching. Mhm. Mhm >>robert, Herjavec

(high intensity music) >> Everyone, welcome back to theCUBE's coverage of AWS Public Sector Summit live in Washington, D.C. Two days of wall-to-wall coverage. I'm John Furrier, your host of theCUBE. Finally, great to be in-person. We had a remote interviews. We have a hybrid event going on. We're streaming everything all over the place. Next guest is Matt Mandrgoc, who's the Head of Public Sector at Zoom. The company that everyone loves and have happy meetings, happening events. Great to see you. >> Thank you for having me today. >> So, I'll say Zoom is in the center of all the action pandemic. Everyone knows what's going on with Zoom. Household name. Company's exceptionally well on the performance side, what's going on in Public Sector? >> It's exciting. You know, over the last 18 months, we've just exploded across all the marketplace, both in federal state, local government and education. And what's exciting is we've just scratched the surface for our customers. So, if you look at what we've done in getting in front of inaugural events, courts, legislation, all kinds of other types of meetings and webinars, getting the message out around the pandemic. It's exciting to know that we have that opportunity to make a difference. Now, part of this whole thing around Public Sector, since we just scratched the surface, what's exciting is how do we start to look forward to the next 12, 24, 36 months in helping our customers? How do we really add value in accelerating that mission value for them? >> You know, Matt, it's interesting. There's two things that happened during the pandemic that I point to and I talk about all the time. The internet didn't break. So, all those service providers that had the pipes, good job, packets from moving around, And Zoom, you guys really saved society and educate, so many use this. Education, government, meetings, courtrooms, I never thought about the speeding tickets. People have to go free Zoom. All this stuff's happening. Now, you've got a partnership with AWS. What's the next level? I'm assuming more immersion, more connections, more integration. What's the next? What's the plan? >> Great question. So, our next step is we looked at this relationship and we were going to customers and go in there, we go in there and then they go in there. There's wasn't any synergy. So, what we decided to do is come together. So, think about this, Zoom and AWS going into our public sector customers, bringing solutions and helping them evolve, innovate, and transform. As they're evolving through this people-centric hybrid network or workplace journey that they're going through. And then the best part about this is these ecosystem of partners that help both of us, and be a part of that process as well. >> Not to toot your own horn, but we just had a remote interview on Zoom connected to our gear here. Here with a guest sitting right here, just now, that's the kind of impact. How is that transformed some of the government agencies, like military for instance? >> Great question. So, we had, one of the things that the, even back in April 2020, the Air force was recognized by military.com for recruiting and how they use to keep their numbers up, to get in front of recruits. And think about this, if I'm a recruiter, I can't drive three hours to go see somebody, find out if they can join or not and come back. Now they could use Zoom, something that people were comfortable with. Ease of use, simple, ingrained in the fabric of people's lives. Now they could have that, keeping their numbers up and being recognized by a two star general for what they did around the recruiting and keeping the numbers up. >> All right. So I'll ask you cause I know you have a federal background with one. You know the industry pretty well, over the years you've stunned. You've seen the old way now, the new way, what's it like at Zoom? Because you guys exploded onto the scene. Been around for a while, but once you hit the tipping point, it was a rocket ship plus the pandemic. Now you come into federal. You've got FedRAMP issues, what do you do? How do you get through all that? >> We were excited about the fact that we're really catapulted us. We were at FedRAMP Impact Level 2, Moderate back in April of 2019. So, what set the groundwork? So when the pandemic occurred, we were able to explode forward, help our customers. Now, we've even looked past that and go, "What do we do next?" DOD Impact Level 4. We have an authorization to operate with conditions from the Department of the Air Force. And it was set as we go through our provisional process with DISA. The exciting part is, our customers can use this. Now, they have a set of conditions. Those conditions are basically guidelines of how to use and set up an IL-4 call. >> So, just Impact Level 4 is just below top secret if I understand that correct, right? >> So, Impact Level 4 allows our customers and the DOD to use it for a CUI, which is Controlled Unclassified Information or FOUO, For Official Use only conversations. >> Got it. And there's six levels, right? >> Yes. >> Five, six is like the ultimate, like- >> yes. >> super top secret, secret. >> Yes. >> Okay, cool. All right. So four is good? >> It's very good. >> So this is interesting, in 2019, you've mentioned that stuff. That kind of highlights the whole Cloud way before the pandemic. The winners and losers tend to see who was winning and who's losing. And I think a lot of agencies realize the ones that were in the cloud early before the pandemic and the ones that didn't get there fast enough are really lagging behind. What's your reaction to that? >> Well, you're absolutely right. And the interesting thing about the pandemic, what it brought forth is a horrible event, but what it brought forth was transformation that customers had to go through. So think of it this way. If a customer, you know, they were at all this equipment sitting on staff, on site and they had to go home. And all of a sudden when they went home, legacy systems could not transform and allow them to evolve into this work from home environment. So, what it brought forth of these systems that were just not capable of being able to scale. And all of a sudden, as they went forward, they were able to go ahead and us. For us, it was easy because ease of use, scalability, innovation, extensibility and security, allowed us to really jump right in there. And as people I mentioned earlier, it became ingrained in the fabric of people's lives. So, the ease of use for everybody made it easy for them to move home. >> Yeah. And that's a big impact. All right. Let me ask about the Amazon Marketplace, AWS Marketplace. News there? Share. >> Yeah. We're excited we announced over the last two days, we've announced our relationship with AWS, and the AWS Marketplace via Kairosoft. So, Kairosoft is a world-class public sector distributor. The great relationship we have there that help us really accelerate this relationship was Amazon already had that AWS Marketplace distributor. We had Kairosoft as our main distributor for all Public Sector, solar suburb. So, the relationship already there and with the integration with Tackle.io, allowed us to really accelerate this relationship and be able to transact for our customers. And you think about the transaction, now our customers can start to leverage AWS contracts and accelerate the pieces that they have across there. >> Talk about the Tackle.io piece, how does that fit in? Cause you've got Kairosoft, Distributor, Zoom, what's Tackle do? They integrate? >> Tackle was just the integration piece allowed us to get these transactions going for back and forth. So, the transaction you think about, a customer will buy through AWS contract. They'll get transacted through the AWS Marketplace at Kairosoft, and it come to Zoom from there. Tackle.io was just the integration piece allowed that to happen. >> Yeah. And just a plug for Tackle.io. Those guys are start-up that's growing really fast. They make it easy. The Marketplace is not that easy. (laughs) Dave McCain would argue with me, but yeah, it's can be unwieldy, but they manage it and make it easier. >> Matt: Well, if you think about typically, if you had direct integration, it would take you many months to get through that process and a lot of times. This helped us, with the Marketplace being at Kairosoft, and Tackle.io, allowed us to really accelerate this relationship. >> I mean, that's a consumption model in the future. I mean, you're looking at, from a Zoom standpoint, you look at the marketplace, that's just more distribution. That's a selling vehicle for you, right? >> Exactly. But it's also, you think, but it's selling people for us. But you think about it from the customer side. If they have a contract already in place and they have consumption, you know, minimums they have to hit and they can be a part of the solution set now that we come together. It really becomes that, "Hey yeah, it's easy to use as a great way." But now we're giving, as we mentioned earlier, an acceleration point for our customers to drive that innovation and quickly procure it. >> Now, you've been around the block on Public Sector. You've seen the waves of innovation over the years. Now, it's kind of like the perfect storm. Multiple waves colliding into a big wave with cloud and with the new normal that's coming. From telemedicine to education, to military, to top secret, to distribution via marketplaces cloud scale, where there's now a new stack emerging, horizontal and vertical. What is your take on that as a industry participant? You're like, "We're putting perspective." Like how big is this compared to what was once other waves? >> Well, you know, what the pandemic brought forth was, as Max mentioned earlier today in his keynote, it really accelerated transformation of people how to do it, which would may take three to five years. Took weeks and months. Now we have the opportunity to go forward and really push this and say, "How do we transform while this pandemic happened?" People are now, the governments are, in education are now looking at transformation on how they accelerate this for the next five to seven years. Because the decisions are making, the money they're settling, and the investments they're making are transforming how they're going to do that. And they realize they cannot do it the way they did it before. >> Well, congratulations in all the success that Zoom, for you and your teammates. Eric, over there as CEO and Collin, and the rest of the team, Ross Mayfield, amongst others. We love you guys. I think you're great company. You really made a dent in the universe in a positive way. I'm looking forward to seeing what's on the roadmap. IOT devices, edge, what's happening? >> Actually, it's great timing of that because we just had our Zoomtopia. So we announced a number of different innovative things that we've done out there, white boarding and such. That really is going to come forward. So I would encourage everybody to go to the Zoom website, look at some of the videos we had from Zoomtopia. Talked about some of the actual, really cool innovative things that we've done. >> John: Yeah. Yeah. I mean, almost imagined was the camera technology, the collaboration technology, things are going to be a little bit different. It's not going to be what people think it's going to be. It might look different. What's your view on that? >> I think it's going to look different than it was a year ago. I think it's going to look different than two years from now. And so, with innovation, we look at, we have hundreds of different innovative things that occurred out there. So we look at, you know, virtual classrooms, things that they have out there to change the environment, to make that feel like it's a real life experience. And that's what makes the difference on us. >> You know, I watched companies like Facebook saying, they're going to drop 50 million into metaverse for the next two years. They're throwing engineers at it. But all it points down to is a better user experience. That's the goal, right? To make that user experience immersive, clean, elegant, simple but effective. >> Yeah. It's intuitive. It's the number one thing I hear form every single person. They want something easy to use when the send them home, they want to be able to turn it on for it to work. And we had one department, one agency has sent people home. They found the productivity was doing so well that they actually have decided to hire people in different parts of the country. It's very specialized group around, it moved the D.C. area. Now it's changed the whole scope of how you bring people in with these different skillsets, how not having a move to an area. We'll be able to leverage them at a remote location, but really embrace that expertise. >> Matt, thank you for coming on theCUBE, Matt Mandrgoc, Head of Public Sector. U.S. Public Sector for Zoom. A name you're going to keep hearing about more and more. It's not going away. Establish themselves as the leader in collaboration, certainly video meetings, conferences, events. Thanks for coming on. >> Matt: Thanks for having me on theCUBE. >> Okay. Well, more coverage from a live personal in-person event with remote Zoom's coming in as hybrid. It's theCUBE coverage of AWS Summit 2021, here in Washington, DC. I'm John Furrier. Thanks for watching. (soft music)

>> Welcome back to theCUBE's covering of AWS Public Sector Summit. In-person here in Washington, DC. I'm John Furrier, your host, great to be back face to face. We've got a great, special guest Clint Crosier, who is the Director of AWS' Aerospace & Satellite. Major General of The Air Force/Space Force. Retired. Great to see you in person again. Thanks for coming on theCUBE. >> Thank you for having me. I appreciate that. >> First of all, props to you for doing a great job at Amazon, bringing all your knowledge from Space Force and Air Force into the cloud. >> Thank you. >> So that's great, historical context. >> It's been valuable and it's provided a whole lot of insight into what we're building with the AWS space team, for sure. >> So number one question I get a lot is: We want more space content. What's the coolest thing going on in space? Is there a really a satellite behind the moon there, hidden there somewhere? What's the coolest thing going on in space? >> Well, the coolest thing that's going on in space, I think is you're seeing the rapid growth of the space industry, I mean, to me. I've been in the space industry for 34 years now, and there have been periods where we projected lots of growth and activity and it just didn't really come about, especially in the 80's and the 90's. But what we're seeing today is that growth is taking place. Whether it's the numbers of satellites that are being launched around the globe every year, there's some 3,000 objects on orbit today. Estimates are that there'll be 30,000 objects at the end of the decade, or the number of new companies, or the number of global spinning. It is just happening right now, and it's really exciting. >> So, when people say or hear space, there's a lot of economic changes in terms of the cost structures of how to get things deployed into space. That brings up the question of: Is space an opportunity? Is it a threat vector? What about congestion and security? >> Yeah, well three great things, absolutely an opportunity. We're seeing the rapid growth of the space industry, and we're seeing more commercialization than ever before. In my whole career, The Air Force or, NASA, or the NRO would sort of, hold things and do them themselves Today, you're seeing commercial contracts going out from the National Reconnaissance Office, NASA, from The Air Force, from the Space Force. So lots of opportunity for commercial companies. Security. Absolutely, priority number one should be security is baked into everything we do at AWS. And our customers, our Government classified customers tell us the reason they came to AWS is our security is top notch and certified for all their workloads. And as you well know, we have from unclassified all the way up to top secret capabilities on the AWS cloud. So just powerful opportunities for our customers. >> Yeah. And a lot of competitors will throw foot on that. I know, I've reported on some of that and not a lot of people have that same credential. >> Sure. >> Compared to the competition. >> Sure. >> Now I have to ask you, now that you have the top secret, all these clouds that are very tailorable, flexible with space: How are you helping customers with this Aerospace Division? Is it is a commercial? In the public sector together? What's the... >> All of the above. >> Take us through the value proposition. >> Yeah, happy to do this. So what we recognized over the last two years or so we, at AWS, recognized all this rapid growth that we're talking about within the space industry. Every sector from launch to on-orbit activities, to space exploration, all of it. And so AWS saw that and we looked at ourselves and said: "Do we have the right organization and expertise in place really to help our customers lean into that?" And the answer was: we decided to build a team that had deep experience in space, and that was the team that we grew because our thesis was: If you have a deep experience in space, a deep experience in cloud, you bring those two together and it's a powerful contribution. And so we've assembled a team with more than 500 years of collective hands-on experience, flying satellites, launching rockets. And when we sit down with our customers to innovate on their behalf, we're able to come up with some incredible solutions and I'm happy to talk about those. >> I'd love to, but tell you what, first of all, there's a lot of space nerds out there. I love space. I love space geeking out on the technology, but take us through the year you had, you've had a pretty incredible year with some results. You have that brain trust there. I know you're hiring. I know that people want to work for you. I'm sure the resumes are flying in, a lot of action. >> There is. >> What are the highlights from this year? >> So the highlights I think is, we've built a team that the industry is telling us was needed. Again, there was no organization that really served the space cloud industry. And so we're kind of building this industry within the industry, the space cloud industry. And so number one, just establishing that team and leaning into that industry has been valuable. The other thing that we're real proud of is we built a global team, because space is a global enterprise. We have teams in Europe and in Asia and South America here in the U.S., so we built a global team. One of the things that we did right up front, we weren't even six months old, when we envisioned the idea of doing the AWS Space Accelerator. And some of the folks told me: "Clint, six months under your belt, maybe you ought to get your feet under you." And I said: "No, no. We move fast to support our customers." And so we made a call for any space startup that wanted to come on board with AWS and go through our four week Space Accelerator. We partnered with Sarah from Capital. And the idea was: if you're a small company that wants to grow and build and learn how you can use the cloud to gain competitive advantage, come with us. And so John, I would have been happy if we had 50 companies applied, we had 194 companies across 44 countries that applied to our accelerator. We had to down select a 10, but that was a tremendous accomplishment, two of those are speaking this afternoon, where they met each other at our accelerator and now have formed a partnership: Ursa Space and HawkEye 360 on how they build on the cloud together. Fascinating. >> Well, I love that story. First of all, I love the military mindset. No, we're not going to wait. >> Move it out. >> It's not take that hill, it's take that planet. >> Our customers won't wait, innovation, doesn't wait, the future doesn't wait. We have to move out. >> So, this brings up the entrepreneurship angle. We got there a little early, but I want to talk about it because it's super important. There's an entrepreneurial culture happening right now in the space community >> There is. At large, and it's getting bigger and wider. >> Bigger every day. >> What is that? What if someone says: "Hey, what's going on with entrepreneurship in this space? What are the key dynamics? What's the power dynamics?" It's not money, there's money out there, but like what's the structural thing happening? >> The key dynamic, I think, is we're seeing that we can unlock things that we could never do before. And one of our goals is: the more space data we can make more accessible to more people around the world. It unlocks things we couldn't do. We're working with space companies who are using space data to track endangered whales off the coast of California. We're working with companies that are using space data to measure thermal and greenhouse emissions for climate change and climate management. We're working with one company, Edgybees, who has a small satellite constellation, and they're using it to build satellite based, augmented reality, to provide it to first responders as they go into a disaster response area. And they get a 3D-view of what they're going into. None of those workloads were possible five years ago. And the cloud and cloud-based technologies are really what opens those kinds of workloads up. >> What kind of higher level services do you see emerging from space cloud? Because you know, obviously you have to have some infrastructure. >> Absolutely. Got to put some stuff into space. That's a supply chain, reliability, also threat. I mean, I can have a satellite attack, another satellite, or I'm just making that up, but I'm sure there's other scenarios that the generals are thinking about. >> So space security and cyberspace security is critical. And as I said, it's built into everything we do in all of our platforms, so you're absolutely right about that, but when we think about the entrepreneurship, you know, what we're seeing is, and I'll give you a good example of why the industry is growing so fast and why cloud. So one company we work with, LeoLabs. So Leo identified the growth in the LEO: Low Earth Orbit segment. 3,000 objects on orbit today, 30,000 tomorrow. Who's going to do the space traffic management for 30,000 objects in space that are all in the same orbital regime? And so LeoLabs built a process to do space traffic management, collision avoidance. They were running it on premises. It took them eight hours to do a single run for a single satellite conjunction. We got them to help understand how to use the cloud. They moved all that to AWS. Now that same run they do in 10 seconds. Eight hours to 10 seconds. Those are the kind of workloads as space proliferates in and we grow, that we just can't execute without cloud and cloud-based technologies. >> It's interesting, you know, the cloud has that same kind of line: move your workloads to the cloud and then refactor. >> Yeah. So space workloads are coming to the cloud. >> They are. >> Just changing the culture. So I have to ask you, I know there's a lot of young people out there looking for careers and interests. I mean, Cal poly is going into the high school now offering classes. >> Yeah So high school, there's so much interest in space and technology. What is the cultural mindset to be successful? Andy Jassy last year, reading and talk about the mindset of the builder and the enterprise CXO: "Get off your butt and start building" There's a space ethos going on. What is the mindset? Would you share your view on it? >> The mindset is innovation and moving fast, right? We, we lived, most of my career, in the time where we had an unlimited amount of money and unlimited amount of time. And so we were really slow and deliberate about how we built things. The future won't wait, whether it's commercial application, or military application, we have to move fast. And so the culture is: the faster we can move, The more we'll succeed, and there's no way to move faster than when you're building on the AWS cloud. Ground station is a good example. You know, the proposition of the cloud is: Don't invest your limited resources in your own infrastructure that doesn't differentiate your capability. And so we did that same thing with ground station. And we've said to companies: "Don't spend millions of dollars on developing your own ground station infrastructure, pay by the minute to use AWS's and focus your limited resources back in your product, which differentiate your space mission." and that's just been power. >> How is that going from customer perspective? >> Great. It's going great. We continue to grow. We added another location recently. And just in the last week we announced a licensed accelerator. One of the things our customers told us is it takes too long to work with global governments to get licensed, to operate around the world. And we know that's been the case. So we put together a team that leaned in to solve that problem, and we just announced the licensed accelerator, where we will work with companies to walk them through that process, and we can shave an 18 month process into a three or four month process. And that's been... we've gotten great response on that from our company. >> I've always said: >> I remember when you were hired and the whole space thing was happening. I remember saying to myself: "Man, if democratization can bring, come to space" >> And we're seeing that happening >> You guys started it and you guys, props to your team. >> Making space available to more and more people, and they'll dazzle us with the innovative ways we use space. 10 years ago, we couldn't have envisioned those things I told you about earlier. Now, we're opening up all sorts of workloads and John, real quick, one of the reasons is, in the past, you had to have a specific forte or expertise in working with space data, 'cause it was so unique and formatted and in pipeline systems. We're making that democratized. So it's just like any other data, like apps on your phone. If you can build apps for your phone and manage data, we want to make it that easy to operate with space data, and that's going to change the way the industry operates. >> And that's fundamentally, that's great innovation because you're enabling that. That's why I have to ask you on that note Of the innovation trends that you see or activities: What excites you the most? >> So a lot of things, but I'll give you two examples very quickly: One is high-performance compute. We're seeing more and more companies really lean in to understanding how fast they can go on AWS. I told you about LeoLabs, eight hours to 10 seconds. But that high-performance computes going to be a game changer. The other thing is: oh, and real quick, I want to tell you, Descartes Labs. So Descartes Labs came to us and said: "We want to compete in the Annual Global Top 500 supercomputer challenge" And so we worked with them for a couple of weeks. We built a workload on the AWS standard platform. We came in number 40 in the globe for the Top 500 super computer lists, just by building some workloads on our standard platform. That's powerful, high-performance compute. But the second example I wanted to give you is: digital modeling, digital simulation, digital engineering. Boom Aerospace is a company, Boom, that we work with. Boom decided to build their entire supersonic commercial, supersonic aircraft, digital engineering on the AWS cloud. In the last three years, John, they've executed 6,000 years of high-performance compute in the last three years. How do you do 6,000 years in compute in three years? You spin up thousands of AWS servers simultaneously, let them do your digital management, digital analysis, digital design, bring back a million different perturbations of a wing structure and then pick the one that's best and then come back tomorrow and run it again. That's powerful. >> And that was not even possible, years ago. >> Not at that speed, no, not at that speed. And that's what it's really opening up in terms of innovation. >> So now you've done it so much in your career, okay? Now you're here with Amazon. Looking back on this past year or so, What's the learnings for you? >> The learning is, truly how valuable cloud can be to the space industry, I'll admit to you most people in the space industry and especially in the government space industry. If you ask us a year ago, two years ago: "Hey, what do you think about cloud?" We would have said: "Well, you know, I hear people talk about the cloud. There's probably some value. We should probably look at that" And I was in the same boat, but now that I've dug deeply into the cloud and understand the value of artificial intelligence, machine learning, advanced data analytics, a ground station infrastructure, all those things, I'm more excited than ever before about what the space industry can benefit from cloud computing, and so bringing that, customer by customer is just a really fulfilling way to continue to be part of the space industry. Even though I retired from government service. >> Is there a... I'm just curious because you brought it up. Is there a lot of people coming in from the old, the space industry from public sector? Are they coming into commercial? >> Absolutely. >> Commercial rising up and there's, I mean, I know there's a lot of public/private partnerships, What's the current situation? >> Yeah, lots of partnerships, but we're seeing an interesting trend. You know, it used to be that NASA led the way in science and technology, or the military led the way in science and technology, and they still do in some areas. And then the commercial industry would follow along. We're seeing that's reversed. There's so much growth in the commercial industry. So much money, venture capital being poured in and so many innovative solutions being built, for instance, on the cloud that now the commercial industry is leading technology and building new technology trends that the military and the DOD and their government are trying to take advantage of. And that's why you're seeing all these commercial contracts being led from Air Force, Space Force, NASA, and NRO. To take advantage of that commercialization. >> You like your job. >> I love my job. (laughing) -I can tell, >> I love my job. >> I mean, it is a cool job. I kind of want to work for you. >> So John, space is cool. That's our tagline: space is cool. >> Space is cool. Space equals ratings in the digital TV realm, it is really, super exciting a lot of young people are interested, I mean, robotics clubs in high schools are now varsity sports, eSports, all blend together. >> Space, robotics, artificial intelligence, machine learning, advanced analytics. It's all becoming a singular sector today and it's open to more people than ever before, for the reasons we talked about. >> Big wave and you guys are building the surf boards, everyone a ride it, congratulations. Great to see you in person. >> Thank you. Again, thanks for coming on theCUBE, appreciate that. >> Thanks for having us. >> Clint Crosier is the Director of AWS Aerospace & Satellite. Legend in the industry. Now at AWS. I'm John Furrier with theCUBE. Thanks for watching.

(upbeat music) >> Live in Washington, DC. This is day two of two days of coverage. I'm John Furr, your host. We're in person face-to-face event it's kicking off day two. Dave Levy's here, Vice President of US government Nonprofit and healthcare businesses for AWS Public Sector. Dave, great to see you again, welcome back. >> Dave: Great to see you, John. >> So, great time last time we were in person, 2019, looks like the event, the last year was virtual, what's new? >> Well, first of all, I think it's just exciting. I mean, I'm excited to be back and in-person and so much has happened in our personal lives in our communities and so I'm really glad that we can all be together and it's been great so far. >> I was talking yesterday with some folks and I saw people doing some networking. I heard someone, "Hey, I'm want to hire someone." So, the face-to-face is back, we're also streaming. Max Peterson told me they're pushing it everywhere on Facebook, LinkedIn, Twitter, everywhere, Twitch, so free content, but still a lot of registrations here in person, good stuff. >> Yeah, great registrations. We're thrilled with the support from partners and customers. And also too, like you said, the connections that people are making, so it does feel good that things are flowing and people are having conversations and- >> Well, you got healthcare, nonprofits, US government, healthcare has been a big focus so far in this show. A lot of action, local governments, governments and healthcare seem to be like pandemic enabled to change. What's the update? What's the highlights so far for you? >> Well, I think the highlights are in those areas that, what we've been able to help our customers with is the ability to respond and that's what Cloud is all about and their ability to react and to respond to things that they don't necessarily know is going to happen and the big thing that none of us knew was going to happen was the pandemic. And so that ability and agility and preparedness to respond has really been great to see from a lot of those customers. >> You know, Max Peterson had the CIO from the Air Force up on stage and she's known for her comments about data and data's our data, the US Air Force and so data's big part of it. They are having a transformation and the how's that project going? What's the update there? What's your impression on that? >> Yeah, well, it was great to see the Air Force on stage and great to see Laura up there and we're really proud to support the DOD and the Air Force. And the Air Force has a lot to be proud of in their transformation journey and what they're doing with Cloud One is pretty substantial and amazing transformation for them. And then they've got 35 applications running on AWS. And so we think their progress is really good and they're thinking the right way in terms of their software factories and other types of projects. >> What's interesting is it's watching like who's adopting, it's like you look at like the pandemic has really opened up the view of the projects, which ones are doing well. And how do I say this politely? The projects that were being blocked or hidden, or the KPIs camouflaging the value were exposed because I mean, once that pulled back the curtain, people realized, "Oh my God, we're stuck," Or "we're inadequate, we are antiquated. We need to change," because now the pressure to deliver shifted to digital. I mean, this literally exposed the good, bad, and the ugly. >> It did and some were more prepared than others. There are great examples. We worked with the SBA to help expand the portal for the payroll protection program to get more lenders access faster. And that was a great project. They were able to respond really quickly and we were able to support them in that. Others, not so much. I think it you're right, it did expose that there's an opportunity. There's an opportunity to accelerate some of the things that they were doing already in terms of digital transformation. >> How about the GovCloud and the federal customers that you have, what's the traction point? How has that going? Is there a new generation here? >> GovCloud has been a great success. GovCloud it's our- >> John: 10-year anniversary. >> It's our 10-year anniversary, so we're thrilled to celebrate that. I can't believe it's 2011. >> EC2 is 15. Is that 315? I guess 15, too is SQS, the original building blocks. >> So, we've got a lot of great success through GovCloud and GovCloud was really something that was born out of what customers wanted, primarily federal customers. But we've also seen over the last few years, real adoption from regulated industry, real adoption from partners that are going into GovCloud that really want to take advantage of the security and compliance that federal customers need and the larger defense industrial base organizations need. So, GovCloud's been a fabulous success and expect I expect a lot of growth going forward. >> Yeah, is there a cultural shift in the federal government now? I can imagine some countries have been exploring this. I did talk briefly about it with Ms. Shannon Kellogg and John Wood, about how, if you're under the age of 40 and you work in the federal government, you got to be like, "Why aren't we doing this?" Like there seems to be like a cultural shift, younger generation coming in and be like, looking at the old way and be like, "Why are we still doing that?" >> Well, I think look bipartisan support for digital transformation, for making sure that we have the competitive edge for generations and generations to come in the US both in business and in defense and national security, I think is an imperative. I mean nobody I've talked to disagrees that we need to do this. And I think that younger workforce coming in behind I'm jealous of the 40-year olds, I wish I was under 40, but none of workforce really sees the obstacles that maybe previous generation saw these emerging technologies are becoming, the basic unit of computer's getting smaller, the cost to do these things is coming way down and I think that younger workforce says, "Why aren't we doing this?" >> Yeah and I think the Air Force projects are interesting too because that shows us not just about the CIA or the DOD that you have, they're leaning into production workloads, and the mission critical workloads too, the DOD is also now continuing to adopt. What else are you guys doing with the DOD? >> Well, we're partnering with GDIT on milCloud and that's going to give DOD mission owners access to a whole suite of AWS services. So, we're really excited about that. And those are available now. We're the only Cloud provider that's making that accessible to them on milCloud. And so this is going to open up the opportunity for them to start doing that mission work that you described. A good example of that are programs like ABMS, Air Force's Advanced Battle Management System. It's part of their effort around JADC2 and a great set of capabilities that they're delivering there. We're happy to have participated. We did some testing and some show intel, if you will at Ramstein Air Force Base and we're really proud to support that effort and we're excited about what the Air Force is doing. >> You know, I've always been impressed with the DOD when the tactical edge concept came out, that was very impressive because they're really using the data properly and I know Amazon has been doing well in this area because you've got things like Outpost, Wavelength, Snowball products. How's that edge piece developing? Do you see that becoming more critical now? >> It's absolutely critical. It's not becoming critical, it is critical and I think if you look at what the DOD and all of their partners are trying to accomplish, it's really moving all of that data around from the very edge in theater, back home to where it needs to be analyzed, doing it fast, doing it secure, being able to deliver on their missions and that's what this is all about. So, we see huge, huge opportunities to really innovate around the edge. >> Yeah, the data equation really is fascinating to me. Just when you think about things like words, highly available versus high availability means something 'cause you're going to want real time, not just on available data, you got to have it real time so the pressure around these projects are high. And so technically, you've got to have low latency on all this stuff. >> That's true, that's true. You've got to either have near real time or real-time availability and in many cases there's high stakes. So, the ability the DOD to pull this off is really, really important and we're a big supporter of that. >> Dave, I want to get your perspective because you've been in the industry, you've seen that the ways, we talked before cameras about the '90s and data centers and stuff. 10 years of GovCloud, look at public sector, just to look at the 10 years, interesting evolution. I mean, you couldn't give Cloud a wait 15 years ago. They weren't moving, glacier speed of adoption, now, massive adoption, uptakes there, the transformations are happening, migrations are huge, healthcare, which is like silo the data, HIPAA compliance lock everything down, everything's opening up. This is causing a lot of change. What's your reaction to that? >> Well, my reaction to that is I think customers are starting to connect what their outcomes are, whether it's a business outcome or a mission outcome or both to what Cloud can actually do. And I think that's freeing them up to make decisions about enabling Cloud in their environment, enabling experimentation, because that's what you want. You don't know what you're going to be faced with. We don't know what the threats are. We don't know if there's going to be another major pandemic. We hope there's not, but we don't know and if you set goals around your outcomes for mission and tie those, Cloud becomes such an enabler for that. And I see customers embracing that. Customers across the spectrum, nonprofit, healthcare providers, everybody, Homeland Security, VA, they're all thinking about, "What are the mission outcomes we're trying to drive?" >> Yeah, what's interesting too on that is that, just to point out is that the applications now aren't as complex to build relatively to the speed. In other words, you can get the time to value. So, the pandemic showed people that if you were in the Cloud and had that agility or optionality to be agile, you could write software 'cause software is the key in this, and not let's do the waterfall, 12-weeks assessment, 10-month rollout. Now people are doing it in 10 days, new applications. >> Sure, sure. Well, I tell customers a lot, "Think about McDonald's during the pandemic and think about customers like that who had to react to a new environment of delivery and your fast food fresh and how quickly companies like that are able to roll out capabilities." And I don't know that federal customers will be able to do it in a week or two weeks, but it's certainly possible. And it certainly will shorten that lead time that they have now in their software development. >> Well, great to see you, Dave. Is there any customers you want to highlight and you want to talk about, get a plug in for? >> Yeah, a lot of great customers here representing today and we're really appreciative also just want to say it was really great to see Max on stage for his first summit and think it was great to see Laura and others as well too. We've got some great customers coming here, The Veteran's affairs is going to be here as well as the Navy presenting on a lot of their capabilities today. So, I'm really excited about that. >> Yeah, a lot of action and education, healthcare, really blooming, really changing and modernizing. Big-wave migration, modernization, all kinds of the big wave. >> Yeah, it is. Yeah, big things coming and some of these systems are ready, so these systems are 40 and 50 years old and we're here to help these customers deliver on the agility and the extensibility of these systems to really serve citizens. >> What's your outlook for next year? What are you seeing next year so happening? How do you see everything unfolding? So you mentioned the pandemic, we're still in it, Delta Virus, who knows what's going to happen next, the world stage is changing, the global economy, space. >> I see customers really leaning in and starting to see the benefits of moving their data to the Cloud, number one, and then also to getting the insights using AI and ML to really drive the insights that they need to make the decisions on that data and I see more and more customers doing that. I did a panel this week, moderated a panel with some great customers around that and getting started is probably the biggest thing that I see and we're going to have more and more customers getting started. >> Yeah, getting into the Cloud. Congratulations to milCloud by the way, too. That was a good call out. All right, thanks for coming, I appreciate it. >> John: Yeah, thanks, Sean. >> Okay, keep coverage here. The Public Sector Summit, live in Washington, D.C. in-person event also hybrid we're streaming out. We're doing remote interviews and Amazon is streaming all the keynotes and key sessions for the digital folks out there. Thanks for watching. (upbeat music)

(upbeat music) >> We're back. This is Dave Vellante of theCUBE, and we're here with Ray Wang, who just wrote a book reminiscent of the famous Tears for Fears song, Everybody Wants to Rule the World: Surviving and Thriving in a World of Digital Giants. Ray, great to see again, man. >> What's going on, man, how are you? >> Oh great, thanks for coming on. You know, it was crazy, been crazy, but it's good to see you face-to-face. >> Ray: This is, we're in the flesh, it's live, we're having conversations, and the information that we're getting is cut right. >> Dave: Yeah, so why did you write this book and how did you find the time? >> Hey, we're in the middle of pandemic. No, I wrote the book because what was happening was digital transformation efforts, they're starting to pop up, but companies weren't always succeeding. And something was happening with digital giants that was very different. They were winning in the marketplace. And never in the form of, if you think about extreme capitalism, if we think about capitalism in general, never in the history of capitalism have we seen growth of large companies. They get large, they fall apart, they don't have anything to build, they can't scale. Their organizations are in shambles. But what happened? If you look at 2017, the combined market cap of the FAANGs and Microsoft was 2 trillion. Today, it is almost 10.2 trillion. It's quintupled. That's never happened. And there's something behind that business model that they put into place that others have copied, from the Airbnbs to the Robloxes to what's going to happen with like a Starlink, and of course, the Robinhoods and you know, Robinhoods and Coinbases of the world. >> And the fundamental premise is all around data, right? Putting data at the core, if you don't do that, you're going to fly blind. >> It is and the secret behind that is the long-term platforms called data-driven digital networks. These platforms take the ability, large memberships, our large devices, they look at that effect. Then they look at figuring out how to actually win on data supremacy. And then of course, they monetize off that data. And that's really the secret behind that is you've got to build that capability and what they do really well is they dis-intermediate customer account control. They take the relationships, aggregate them together. So food delivery app companies are great example of that. You know, small businesses are out there that hundreds and thousands of customers. Today, what happens? Well, they've been aggregated. Millions of customers together into food delivery app. >> Well, I think, you know, this is really interesting what you're saying, because if you think about how we deal with Netflix, we don't call the Netflix sales department or the marketing department of the service, just one interface, the Netflix. So they've been able to put data at their core. Can incumbents do that? How can they do that? >> Incumbents can definitely do that. And it's really about figuring out how to automate that capture. What you really want to do is you start in the cloud, you bring the data together, and you start putting the three A's, analytics, automation, and AI are what you have to be able to put into place. And when you do do that, you now have the ability to go out and figure out how to create that flywheel effect inside those data-driven digital networks. These DDDNS are important. So in Netflix, what are they capturing? They're looking at sentiment, they're looking at context. Like why did you interact with, you know, one title versus another? Did you watch Ted Lasso? Did you switch out of Apple TV to Netflix? Well, I want to know why, right? Did you actually jump into another category? You switched into genres. After 10:00 p.m., what are you watching? Maybe something very different than what you're watching at 2:00 p.m.. How many members are in the home, right? All these questions are being answered and that's the business graph behind all this. >> How much of this is kind of related to the way organizations or companies are organized? In other words, you think about, historically, they would maybe put the process at the core or the, in a bottling plant, the manufacturing facility at the core and the data's all dispersed. Everybody talks about silos. So will AI be the answer to that? Will some new database, Snowflake? Is that the answer? What's the answer to sort of bringing that data together and how do you deal with the organizational inertia? >> Well, the trick to it is really to have a single plane to be able to access that data. I don't care where the data sits, whether it's on premise, whether it's in the cloud, whether it's in the edge, it makes no difference. That's really what you want to be able to do is bring that information together. But the glue is the context. What time was it? What's the weather outside? What location are you in? What's your heart rate? Are you smiling, right? All of those factors come into play. And what we're trying to do is take a user, right? So it could be a customer, a supplier, a partner, or an employee. And how do they interact with an order doc, an invoice, an incident, and then apply the context. And what we're doing is mining that context and information. Now, the more, back to your other point on self service and automation, the more you can actually collect those data points, the more you can capture that context, the more you're able to get to refine that information. >> Context, that's interesting, because if you think about our operational systems, we've contextualized most of them, whether it's sales, marketing, logistics, but we haven't really contextualized our data systems, our data architecture. It's generally run by a technical group. They don't necessarily have the line of business context. You see what HPE is doing today is trying to be inclusive of data on prem. I mentioned Snowflake, they're saying no way. Frank Slootman says we're not going on prem. So that's kind of interesting. So how do you see sort of context evolving with the actually the business line? Not only who has the context actually can, I hate to use the word, but I'm going to, own the data. >> You have to have a data to decisions pathway. That data decisions pathway is you start with all types of data, structured, unstructured, semi-structured, you align it to a business process as an issue, issue to resolution, order to cash, procure to pay, hire to retire. You bring that together, and then you start mining and figuring out what patterns exist. Once you have the patterns, you can then figure out the next best action. And when you get the next best action, you can compete on decisions. And that becomes a very important part. That decision piece, that's going to be automated. And when we think about that, you and I make a decision one per second, how long does it get out of management committee? Could be a week, two weeks, a quarter, a year. It takes forever to get anything out of management committee. But these new systems, if you think about machines, can make decisions a hundred times per second, a thousand times per second. And that's what we're competing against. That asymmetry is the decision velocity. How quickly you can make decisions will be a competitive weapon. >> Is there a dissonance between the fact that you just mentioned, speed, compressing, that sort of time to decision, and the flip side of that coin, quality, security, governance. How do you see squaring that circle? >> Well, that's really why we're going to have to make that, that's the automated, that's the AI piece. Just like we have all types of data, we got to spew up automated ontologies, we got to spit them up, we got to be using, we've got to put them back into play, and then we got to be able to take back into action. And so you want enterprise class capabilities. That's your data quality. That's your security. That's the data governance. That's the ability to actually take that data and understand time series, and actually make sure that the integrity of that data is there. >> What do you think about this sort of notion that increasingly, people are going to be building data products and services that can be monetized? And that's kind of goes back to context, the business lines kind of being responsible for their own data, not having to get permission to add another data source. Do you see that trend? Do you see that decentralization trend? Two-part question. And where do you see HPE fitting into that? >> I see, one, that that trend is definitely going to exist. I'll give you an example. I can actually destroy the top two television manufacturers in the world in less than five years. I could take them out of the business and I'll show you how to do it. So I'm going to make you an offer. $15 per month for the next five years. I'm going to give you a 72 inch, is it 74? 75 inch, 75 inch smart TV, 4k, big TV, right? And it comes with a warranty. And if anything breaks, I'm going to return it to you in 48 hours or less with a brand new one. I don't want your personal information. I'm only going to monitor performance data. I want to know the operations. I want to know which supplier lied to me, which components are working, what features you use. I don't need to know your personal viewing habits, okay? Would you take that deal? >> TV is a service, sure, of course I would. >> 15 bucks and I'm going to make you a better deal. For $25 a month, you get to make an upgrade anytime during that five-year period. What would happen to the two largest TV manufacturers if I did that? >> Yeah, they'd be disrupted. Now, you obviously have a pile of VC money that you're going to do that. Will you ever make money at that model? >> Well, here's why I'll get there and I'll explain. What's going to happen is I lock them out of the market for four to five years. I'm going to take 50 to 60% of the market. Yes, I got to raise $10 billion to figure out how to do that. But that's not really what happens at the end. I become a data company because I have warranty data. I'm going to buy a company that does, you know, insurance like in Asurion. I'm going to get break/fix data from like a Best Buy or a company like that. I'm going to get at safety data from an underwriter's lab. It's a competition for data. And suddenly, I know those habits better than anyone else. I'm going to go do other things more than the TV. I'm not done with the TV. I'm going to do your entire kitchen. For $100 a month, I'll do a mid range. For like $500 a month, I'm going to take your dish washer, your washer, your dryer, your refrigerator, your range. And I'll do like Miele, Gaggenau, right? If you want to go down Viking, Wolf, I'll do it for $450 a month for the next 10 years. By year five, I have better insurance information than the insurance companies from warranty. And I can even make that deal portable. You see where we're going? >> Yeah so each of those are, I see them as data products. So you've got your TV service products, you've got your kitchen products, you've got your maintenance, you know, data products. All those can be monetized. >> And I went from TV manufacturer to underwriter overnight. I'm competing on data, on insurance, and underwriting. And more importantly, here's the green initiative. Here's why someone would give me $10 billion to do it. I now control 50% of all power consumption in North America because I'm also going to do HVAC units, right? And I can actually engineer the green capabilities in there to actually do better power purchase consumption, better monitoring, and of course, smart capabilities in those, in those appliances. And that's how you actually build a model like that. And that's how you can win on a data model. Now, where does HPE fit into that? Their job is to bring that data together at the edge. They bring that together in the middle. Then they have the ability to manage that on a remote basis and actually deliver those services in the cloud so that someone else can consume it. >> All right, so if you, you're hitting on something that some people have have talked about, but it's, I don't think it's widely sort of discussed. And that is, historically, if you're in an industry, you're in that industry's vertical stack, the sales, the marketing, the manufacturing, the R&D. You become an expert in insurance or financial services or whatever, you know, automobile manufacturing or radio and television, et cetera. Obviously, you're seeing the big internet giants, those 10 trillion, you know, some of the market caps, they're using data to traverse industries. We've never seen this before. Amazon in content, you're seeing Apple in finance, others going into the healthcare. So they're technology companies that are able to traverse industries. Never seen this before, and it's because of data. >> And it's the collapsing value chains. Their data value chains are collapsing. Comms, media, entertainment, tech, same business. Whether you sell me a live stream TV, a book, a video game, or some enterprise software, it's the same data value stream on multi-sided networks. And once you understand that, you can see retail, right? Distribution, manufacturing collapsed in the same kind of way. >> So Silicon Valley broadly defined, if I can include, you know, Microsoft and Amazon in there, they seem to have a dual disruption agenda, right? One is on the technology front, disrupting, you know, the traditional enterprise business. The other is they're disrupting industries. How do you see that playing out? >> Well the problem is, they're never going to be able to get into new industries going forward because of the monopoly power that people believe they have, and that's what's going on, but they're going to invest in creating joint venture startups in other industries, as they power the tools to enable other industries to jump and leap frog from where they are. So healthcare, for example, we're going to have AI in monitoring in ways that we never seen before. You can see devices enter healthcare, but you see joint venture partnerships between a big hyperscaler and some of the healthcare providers. >> So HPE transforming into a cloud company as a service, do you see them getting into insurance as you just described in your little digital example? >> No, but I see them powering the folks that are in insurance, right? >> They're not going to compete with their customers maybe the way that Amazon did. >> No, that's actually why you would go to them as opposed to a hyperscale that might compete with you, right? So is Google going to get into the insurance business? Probably not. Would Amazon? Maybe. Is Tesla in the business? Yeah, they're definitely in insurance. >> Yeah, big time, right. So, okay. So tell me more about your book. How's it being received? What's the reaction? What's your next book? >> So the book is doing well. We're really excited. We did a 20 city book tour. We had chances to meet everybody across the board. Clients we couldn't see in a while, partners we didn't see in a while. And that was fun. The reaction is, if you read the book carefully, there are $3 trillion market cap opportunities, $1000 billion unicorns that can be built right there. >> Is, do you have a copy for me that's signed? (audience laughing) >> Ray: Sorry (coughs) I'm choking on my makeup. I can get one actually, do you want one? >> Dave: I do, I want, I want one. >> Can someone bring my book bag? I actually have one, I can sign it right here. >> Dave: Yeah, you know what? If we have a book, I'd love to hold it. >> Ray: Do you have any here as well? >> So it's obviously you know, Everybody Wants to Rule the World: Surviving and Thriving in a world of Digital Giants, available, you know, wherever you buy books. >> Yeah, so, oh, are we still going? >> Dave: Yeah, yeah, we're going. >> Okay. >> Dave: What's the next book? >> Next book? Well, it's about disrupting those digital giants and it's going to happen in the metaverse economy. If we think about where the metaverse is, not just the hardware platforms, not just the engines, not just what's going on with the platforms around defy decentralization and the content producers, we see those as four different parts today. What we're going to actually see is a whole comp, it's a confluence of events that's going to happen where we actually bring in the metaverse economy and the stuff that Neal Stephenson was writing about ages ago in Snow Crash is going to come out real. >> So, okay. So you're laying out a scenario that the big guys, the disruptors, could get disrupted. It sounds like crypto is possibly a force in that disruption. >> Ray: Decentralized currencies, crypto plays a role, but it's the value exchange mechanisms in an Algorand, in an Ether, right, in a Cardano, that actually enables that to happen because the value exchange in the smart contracts power that capability, and what we're actually seeing is the reinvention of the internet. So you think, see things like SIOM pop-up, which actually is creating the new set of the internet standards, and when those things come together, what we're actually going to move from is the seller is completely transparent, the buyer's completely anonymous and it's in a trust framework that actually allows you to do that. >> Well, you think about those protocols, the internet protocols that were invented whenever, 30 years ago, maybe more, TCP/IP, wow. I mean, okay. And they've been co-opted by the internet giants. It's the crypto guys, some of the guys you've mentioned that are actually innovating and putting, putting down new innovation really and have been well-funded to do so. >> I mean, I'll give you another example of how this could happen. About four years ago, five years ago, I wanted to buy Air Canada's mileage program, $400 million, 10 million users, 40 bucks a user. What do I want them in a mileage program? Well think about it. It's funded, a penny per mile. It's redeemed at 1.6 cents a mile. It's 2 cents if you buy magazines, 2 1/2 cents if you want, you know, electronics, jewelry, or sporting equipment. You don't lose money on these. CFOs hate them, they're just like (groans) liability on the books, but they mortgage the crap out of them in the middle of an ish problem and banks pay millions of dollars a year pour those mileage points. But I don't want it for the 10 million flyers in Canada. What I really want is the access to 762 million people in Star Alliance. What would happen if I turned that airline mileage program into cryptocurrency? One, I would be the world's largest cryptocurrency on day one. What would happen on day two? I'd be the world's largest ad network. Cookie apocalypse, go away. We don't need that anymore. And more importantly, on day three, what would I do? My ESG here? 2.2 billion people are unbanked in the world. All you need is a mobile device and a connection, now you have a currency without any government regulation around, you know, crayon banking, intermediaries, a whole bunch of people like taking cuts, loansharking, that all goes away. You suddenly have people that are now banked and you've unbanked, you've banked the unbanked. And that creates a whole very different environment. >> Not a lot of people thinking about how the big giants get disintermediated. Get the book, look into it, big ideas. Ray Wang, great to see you, man. >> Ray: Hey man, thanks a lot. >> Hey, thank you. All right and thank you for watching. Keep it right there for more great content from HPE's big GreenLake announcements. Be right back. (bright music)

>>AWS public sector summit here in person in Washington, D. C. For two days live. Finally a real event. I'm john for your host of the cube. Got a great guest Howard Levinson from data bricks, regional vice president and general manager of the federal team for data bricks. Uh Super unicorn. Is it a decade corn yet? It's uh, not yet public but welcome to the cube. >>I don't know what the next stage after unicorn is, but we're growing rapidly. >>Thank you. Our audience knows David bricks extremely well. Always been on the cube many times. Even back, we were covering them back when big data was big data. Now it's all data everything. So we watched your success. Congratulations. Thank you. Um, so there's no, you know, not a big bridge for us across to see you here at AWS public sector summit. Tell us what's going on inside the data bricks amazon relationship. >>Yeah. It's been a great relationship. You know, when the company got started some number of years ago we got a contract with the government to deliver the data brooks capability and they're classified cloud in amazon's classified cloud. So that was the start of a great federal relationship today. Virtually all of our businesses in AWS and we run in every single AWS environment from commercial cloud to Govcloud to secret top secret environments and we've got customers doing great things and experiencing great results from data bricks and amazon. >>The federal government's the classic, I call migration opportunity. Right? Because I mean, let's face it before the pandemic even five years ago, even 10 years ago. Glacier moving speed slow, slow and they had to get modernized with the pandemic forced really to do it. But you guys have already cleared the runway with your value problems. You've got lake house now you guys are really optimized for the cloud. >>Okay, hardcore. Yeah. We are, we only run in the cloud and we take advantage of every single go fast feature that amazon gives us. But you know john it's The Office of Management and Budget. Did a study a couple of years ago. I think there were 28,000 federal data centers, 28,000 federal data centers. Think about that for a minute and just think about like let's say in each one of those data centers you've got a handful of operational data stores of databases. The federal government is trying to take all of that data and make sense out of it. The first step to making sense out of it is bringing it all together, normalizing it. Fed aerating it and that's exactly what we do. And that's been a real win for our federal clients and it's been a real exciting opportunity to watch people succeed in that >>endeavour. We have another guest on. And she said those data center huggers tree huggers data center huggers, majority of term people won't let go. Yeah. So but they're slowly dying away and moving on to the cloud. So migrations huge. How are you guys migrating with your customers? Give us an example of how it's working. What are some of the use cases? >>So before I do that I want to tell you a quick story. I've I had the luxury of working with the Air Force Chief data officer Ailene vedrine and she is commonly quoted as saying just remember as as airmen it's not your data it's the Air Force's data. So people were data center huggers now their data huggers but all of that data belongs to the government at the end of the day. So how do we help in that? Well think about all this data sitting in all these operational data stores they're getting it's getting updated all the time. But you want to be able to Federated this data together and make some sense out of it. So for like an organization like uh us citizenship and immigration services they had I think 28 different data sources and they want to be able to pull that data basically in real time and bring it into a data lake. Well that means doing a change data capture off of those operational data stores transforming that data and normalizing it so that you can then enjoy it. And we've done that I think they're now up to 70 data sources that are continually ingested into their data lake. And from there they support thousands of users doing analysis and reports for the whole visa processing system for the United States, the whole naturalization environment And their efficiency has gone up I think by their metrics by 24 x. >>Yeah. I mean Sandy carter was just on the cube earlier. She's the Vice president partner ecosystem here at public sector. And I was coming to her that federal game has changed, it used to be hard to get into you know everybody and you navigate the trip wires and all the subtle hints and and the people who are friends and it was like cloak and dagger and so people were locked in on certain things databases and data because now has to be freely available. I know one of the things that you guys are passionate about and this is kind of hard core architectural thing is that you need horizontally scalable data to really make a I work right. Machine learning works when you have data. How far along are these guys in their thinking when you have a customer because we're seeing progress? How far along are we? >>Yeah, we still have a long way to go in the federal government. I mean, I tell everybody, I think the federal government's probably four or five years behind what data bricks top uh clients are doing. But there are clearly people in the federal government that have really ramped it up and are on a par were even exceeding some of the commercial clients, U. S. C. I. S CBP FBI or some of the clients that we work with that are pretty far ahead and I'll say I mentioned a lot about the operational data stores but there's all kinds of data that's coming in at U S. C. I. S. They do these naturalization interviews, those are captured in real text. So now you want to do natural language processing against them, make sure these interviews are of the highest quality control, We want to be able to predict which people are going to show up for interviews based on their geospatial location and the day of the week and other factors the weather perhaps. So they're using all of these data types uh imagery text and structure data all in the Lake House concept to make predictions about how they should run their >>business. So that's a really good point. I was talking with keith brooks earlier directive is development, go to market strategy for AWS public sector. He's been there from the beginning this the 10th year of Govcloud. Right, so we're kind of riffing but the jpl Nasa Jpl, they did production workloads out of the gate. Yeah. Full mission. So now fast forward today. Cloud Native really is available. So like how do you see the the agencies in the government handling Okay. Re platform and I get that but now to do the reef acting where you guys have the Lake House new things can happen with cloud Native technologies, what's the what's the what's the cross over point for that point. >>Yeah, I think our Lake House architecture is really a big breakthrough architecture. It used to be, people would take all of this data, they put it in a Hadoop data lake, they'd end up with a data swamp with really not good control or good data quality. And uh then they would take the data from the data swamp where the data lake and they curate it and go through an E. T. L. Process and put a second copy into their data warehouse. So now you have two copies of the data to governance models. Maybe two versions of the data. A lot to manage. A lot to control with our Lake House architecture. You can put all of that data in the data lake it with our delta format. It comes in a curated way. Uh there's a catalogue associated with the data. So you know what you've got. And now you can literally build an ephemeral data warehouse directly on top of that data and it exists only for the period of time that uh people need it. And so it's cloud Native. It's elastically scalable. It terminates when nobody's using it. We run the whole center for Medicaid Medicare services. The whole Medicaid repository for the United States runs in an ephemeral data warehouse built on Amazon S three. >>You know, that is a huge call out, I want to just unpack that for a second. What you just said to me puts the exclamation point on cloud value because it's not your grandfather's data warehouse, it's like okay we do data warehouse capability but we're using higher level cloud services, whether it's governance stuff for a I to actually make it work at scale for those environments. I mean that that to me is re factoring that's not re platform Ng. Just re platform that's re platform Ng in the cloud and then re factoring capability for on uh new >>advantages. It's really true. And now you know at CMS, they have one copy of the data so they do all of their reporting, they've got a lot of congressional reports that they need to do. But now they're leveraging that same data, not making a copy of it for uh the center for program integrity for fraud. And we know how many billions of dollars worth of fraud exist in the Medicaid system. And now we're applying artificial intelligence and machine learning on entity analytics to really get to the root of those problems. It's a game >>changer. And this is where the efficiency comes in at scale. Because you start to see, I mean we always talk on the cube about like how software is changed the old days you put on the shelf shelf where they called it. Uh that's our generation. And now you got the cloud, you didn't know if something is hot or not until the inventory is like we didn't sell through in the cloud. If you're not performing, you suck basically. So it's not working, >>it's an instant Mhm. >>Report card. So now when you go to the cloud, you think the data lake and uh the lake house what you guys do uh and others like snowflake and were optimized in the cloud, you can't deny it. And then when you compare it to like, okay, so I'm saving you millions and millions if you're just on one thing, never mind the top line opportunities. >>So so john you know, years ago people didn't believe the cloud was going to be what it is. Like pretty much today, the clouds inevitable. It's everywhere. I'm gonna make you another prediction. Um And you can say you heard it here first, the data warehouse is going away. The Lake house is clearly going to replace it. There's no need anymore for two separate copies, there's no need for a proprietary uh storage copy of your data and people want to be able to apply more than sequel to the data. Uh Data warehouses, just restrict. What about an ocean house? >>Yeah. Lake is kind of small. When you think about this lake, Michigan is pretty big now, I think it's I >>think it's going to go bigger than that. I think we're talking about Sky Computer, we've been a cloud computing, we're going to uh and we're going to do that because people aren't gonna put all of their data in one place, they're going to have, it spread across different amazon regions or or or amazon availability zones and you're going to want to share data and you know, we just introduced this delta sharing capability. I don't know if you're familiar with it but it allows you to share data without a sharing server directly from picking up basically the amazon, you RLS and sharing them with different organizations. So you're sharing in place. The data actually isn't moving. You've got great governance and great granularity of the data that you choose to share and data sharing is going to be the next uh >>next break. You know, I really loved the Lake House were fairly sing gateway. I totally see that. So I totally would align with that and say I bet with you on that one. The Sky net Skynet, the Sky computing. >>See you're taking it away man, >>I know Skynet got anything that was computing in the Sky is Skynet that's terminated So but that's real. I mean I think that's a concept where it's like, you know what services and functions does for servers, you don't have a data, >>you've got to be able to connect data, nobody lives in an island. You've got to be able to connect data and more data. We all know more data produces better results. So how do you get more data? You connect to more data sources, >>Howard great to have you on talk about the relationship real quick as we end up here with amazon, What are you guys doing together? How's the partnership? >>Yeah, I mean the partnership with amazon is amazing. We have, we work uh, I think probably 95% of our federal business is running in amazon's cloud today. As I mentioned, john we run across uh, AWS commercial AWS GovCloud secret environment. See to us and you know, we have better integration with amazon services than I'll say some of the amazon services if people want to integrate with glue or kinesis or Sagemaker, a red shift, we have complete integration with all of those and that's really, it's not just a partnership at the sales level. It's a partnership and integration at the engineering level. >>Well, I think I'm really impressed with you guys as a company. I think you're an example of the kind of business model that people might have been afraid of which is being in the cloud, you can have a moat, you have competitive advantage, you can build intellectual property >>and, and john don't forget, it's all based on open source, open data, like almost everything that we've done. We've made available to people, we get 30 million downloads of the data bricks technology just for people that want to use it for free. So no vendor lock in. I think that's really important to most of our federal clients into everybody. >>I've always said competitive advantage scale and choice. Right. That's a data bricks. Howard? Thanks for coming on the key, appreciate it. Thanks again. Alright. Cube coverage here in Washington from face to face physical event were on the ground. Of course, we're also streaming a digital for the hybrid event. This is the cubes coverage of a W. S. Public sector Summit will be right back after this short break.

(high intensity music) >> Everyone, welcome back to theCube coverage of AWS, Amazon Web Services, Public Sector Summit live in D.C. We're in-person, I'm John Furrier, the host of theCube. I'm here with Max Peterson, the Head of Public Sector, Vice President. Max, great to see you in in-person event. >> Great to be here. We're in-person and we're also live streaming. So, we're here, however customers, however partners want to participate. >> I got to say, I'm very impressed with the turnout. The attendance is strong. People excited to be here. We're not wearing our masks cause we're on stage right now, but great turnout. But it's a hybrid event. >> It is. >> You've got engagement here physically, but also digitally as well with theCube and other live streams everywhere. You're putting it everywhere. >> It's been a great event so far. We did a pre-day yesterday. We had great participation, great results. It was about imagining education. And then today, from the executive track to the main tent, to all of the learning, live streaming 'em, doing things in person. Some things just don't translate. So, they'll won't be available, but many things will be available for viewing later as well. So all of the breakout sessions. >> The asynchronous consumption, obviously, the new normal, but I got to say, I was just on a break. I was just walking around. I heard someone, two people talking, just cause I over walk pass them, over hear 'em, "Yeah, we're going to hire this person." That's the kind of hallway conversations that you get. You got the programs, you got people together. It's hard to do that when you're on a virtual events. >> Max: It's hard. The customers that we had up on stage today, the same sort of spontaneity and the same sort of energy that you get from being in-person, it's hard to replicate. Lisa from State of Utah, did a great job and she got an opportunity to thank the team back home who drove so much of the innovation and she did it spontaneously and live. You know, it's a great motivator for everybody. And then Lauren from Air force was phenomenal. And Suchi, our "Imagine Me and You" artist was just dynamite. >> I want to unpack some of that, but I want to just say, it's been a really change of a year for you guys at Public Sector. Obviously, the pandemic has changed the landscape of Public Sector. It's made it almost like Public-Private Sector. It's like, it seems like it's all coming together. Incredible business performance on your end. A lot of change, a lot of great stuff. >> We had customers we talked today with SBA, with VA, with NASA, about how they just embraced the challenge and embraced digital and then drove amazing things out onto AWS. From the VA, we heard that they took tele-health consultations. Get this from 25,000 a month to 45,000 a day using AWS and the Cloud. We heard SBA talk about how they were able to turn around the unemployment benefits programs, you know, for the unemployed, as a result of the traumatic impact of the COVID-19 pandemic in a matter of weeks. And then, scaled their systems up just to unbelievable heights as President Biden announced the news. >> You had a lot of announcement. I want to get to a couple of them. One of them was the health equity thing. What is that about? Take us through that announcement. >> So the pandemic, it was hard. It was traumatic in a lot of different ways. It also turned into this little innovation laboratory, but one of the things that it laid bare more than anything else where the inequities associated with some of these systems that had to spring into action. And in particular, in the space of health, healthcare equity. We saw simply communities that didn't have access and weren't included in the same sorts of responses that the rest of the community may have been included in. And so we launched this global initiative today to power health equity solutions. It's a $40 million program. Lasts for three years. And it's open to customers or it's open to partners. Anybody who can contribute to three different areas of health equity. It's people who are leveraging data to build more equal, more sustainable health systems. Is people that are using analytics to do greater study of socioeconomic and social situational conditions that contribute to health inequities. And then finally, it's about building systems that deliver more equitable care to those who are underserved around the world. >> So, just to get this right, 40 million. Is that going to go towards the program for three years and are you going to dolo that out or as funding, or is that just a fund the organization? >> It's actually very similar to the development diagnostic initiative that we ran when COVID hit. We've launched the program. We're welcoming applications from anybody who is participating in those three developmental areas. They'll get Cloud credits. They'll get technical consulting. They may need professional services. They'll get all manner of assistance. And all you have to do is put in an application between now and November 15th for the first year. >> That's for the health equity? >> For the health equity. >> Got it. Okay, cool. So, what's the other news? You guys had some baseline data, got a lot of rave reviews from ACORE. I interviewed Constance and Thompson on the Cube earlier. That's impressive. You guys really making a lot of change. >> Well, you're hundred percent right. Sustainability is a key issue from all of our customers around the world. It's a key issue for us, frankly, as inhabitants of planet earth, right? >> John: Yeah. >> But what's really interesting is we've now got governments around the world who are starting to evaluate whether they're not their vendors have the same values and sustainability. And so that the AWS or the Amazon Climate Pledge is a game changer in terms of going carbon zero by 2040, 10 years ahead of most sort of other programs of record. And then with ACORE, we announced the ability to actually start effecting sustainability in particular parts around the world. This one's aim at that. >> But the key there is that, from what I understand is that, you guys are saying a baseline on the data. So, that's an Amazonian kind of cultural thing, right? Like you got to measure, you can't know what you're doing. >> The world is full of good intentions, but if you want to drive change at scale, you've got to figure out a way to measure the change. And then you've got to set aggressive goals for yourself. >> That's really smart. Congratulations! That's a good move. Real quick on the announcement at re:Invent, you've talked about last re:Invent, you're going to train 29 million people. Where are you on that goal? >> Well, John, we've been making tremendous progress and I'm going to use theCube here to make a small teaser. You know, stay tuned for our re:Invent conference that comes up shortly because we're actually going to be sharing some more information about it. But we've done digital trainings, self-training, online skills workshops. We just took a program called re/Start, which serves an unemployed or underemployed individuals. We launched that around the world and we're really excited. Today, we announced we're bringing it to Latin America too. So we're expanding into Colombia, Mexico, Peru, Brazil, and Argentina. And the amazing thing about that re/Start program, it's a 12 week intensive program. Doesn't require skills in advance. And after 12 weeks, 90% of the people graduating from that course go right onto a job interview. And that's the real goal, not just skills, but getting people in jobs. >> Yeah. The thing about the Cloud. I keep on banging the drum. I feel like I'm beating a dead horse here, but the level up, you don't need to have a pedigree from some big fancy school. The Cloud, you can be like top tier talent from anywhere. >> And you heard it from some of our speakers today who said they literally helped their teams bootstrap up from old skills like COBOL, you know, to new skills, like Cloud. And I will tell you, you know, right now, Cloud skills are still in a critical shortage. Our customers tell us all the time they can use every single person we can get to 'em. >> I'm going to tell my son, who's a sophomore in CS. I'm like, "Hey, work on COBOL Migration to AWS. You'll be a zillionaire." (John and Max laughs) No one knows what the passwords of the COBOL. I love that 80s jazzy jokes from two re:Invents ago. (John laughs) I got to ask you about the National-Local Governments, how they're monetizing Cloud of the past 18 months. What have you seeing at that level? >> Yeah. National and Local Governments, of course, were tremendously impacted first by the pandemic itself and the health concerns around it, but then all of the secondary effects, you know, unemployment. And immediately, you needed to put into action unemployment benefits systems. We work with the U.S. Small Business Administration, 15 other States across the U.S. You know, to have those systems in place in like weeks to be able to serve the unemployed as a result of the COVID-19 pandemic. Then you saw things progress, to the point where we had States across the country, standing up call centers on Amazon Connect. Instantly, they could have a high scalable volume call center that was situated for their instantly remote workforce, as opposed to their old call center technology. So, across the U.S. we saw those. And in fact, around the world, as governments mobilized to be able to respond to citizens. But the final thing that I think is really incredible, is though is the way that the AWS teams and partners sprung into action to work with National Governments around the world. Over 26 National Governments run their vaccine management scheduling systems on AWS. The largest to date, being in India, where in a single day, the vaccine management system scheduled and conducted 22.5 million vaccinations. Which is more than the population of New York State in one week and one day. >> Wow. That's good. That's great progress. I got to say, I mean, that kind of impact is interesting. And we had Shannon Kellogg on earlier, talking about the Virginia impact with the Amazon $220 million being spread over a few Counties just in one year. The partnership between business... and governments with the Cloud, so much more agility. This really strikes at the core of the future of government. >> Max: I think so. People have talked about private-public partnerships for a long time. I'm really proud of some of the work that Amazon and the whole team is doing around the world in those types of public private partnerships. Whether they're in skilling and workforce with partnerships, like eight different States across the U.S. to deliver skills, training through community college based systems. Whether it's with healthcare systems. Like NHS or GEL over in the UK, to really start applying cloud-scale analytics and research to solve the problems that eventually you're going to get us to personalized healthcare. >> That's a great stuff. Cloud benefits are always good. I always say the old joke is, "You hang around the barbershop long enough, you'll get a haircut." And if you get in the Cloud, you can take advantage of the wave. If you don't get on the wave, your driftwood. >> And States found that out, in fact. You'd have customers who were well on their journey. They were really able to turn on a dime. They pivoted quickly. They delivered new mission systems with customers. Those who hadn't quite progressed to the same state, they found out their legacy. IT systems were just brittle and incapable of pivoting so quickly to the new needs. And what we found, John, was that almost overnight, a business, government, which was largely in-person and pretty high touch had to pivot to the point where their only interaction was now a digital system. And those who- >> John: Middle of the day, they could have race car on the track, like quickly. >> Well, we've got it. We do have race cars on the track, right? Every year we've got the artificial intelligence powered Amazon DeepRacer and Red River on the track. >> I can see it. Always a good showing. Final question. I know you got to go on and I appreciate you coming on- >> It's been great. >> with all your busy schedule. Looking ahead. What tech trends should we be watching as Public Sector continues to be powered by this massive structural change? >> Well, I think there's going to be huge opportunity in healthcare. In fact, this afternoon at four o'clock Eastern, we're talking with Dr. Shafiq Rab from Wellforce. He and folks at Veterans Affairs to tell you telehealth and telemedicine are two, the areas where there's still the greatest potential. The number of people who now are serviced, and the ability to service a population far more broadly dispersed, I think has dramatic potential in terms of simply making the planet more healthy. >> Like you said, the pandemics have exposed the right path and the wrong path. And agility, speed, new ways of doing things, telemedicine. Another example, I interviewed a great company that's doing a full stack around healthcare with all kinds of home, agents, virtual agents, really interesting stuff. >> It is. I think it's going to change the world. >> John: Max Peterson, Head of Public Sector. Thank you for coming on theCube, as always. >> John, it's my pleasure. Love the cube. We've always had a good time. >> Yeah. Great stuff. >> Peter: We'll keep on making this difference. >> Hey, there's too many stories. We need another Cube here. So many stories here, impacting the world. Here at the Amazon Web Services Public Sector Summit. I'm John Furrier, your host. Thanks for watching. (soft music)