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

>>Hello and welcome today's cube presentation of eight of us startup showcase. I'm john for your host highlighting the hottest companies and devops data analytics and cloud management lisa martin and David want are here to kick it off. We've got a great program for you again. This is our, our new community event model where we're doing every quarter, we have every new episode, this is quarter three this year or episode three, season one of the hottest cloud startups and we're gonna be featured. Then we're gonna do a keynote package and then 15 countries will present their story, Go check them out and then have a closing keynote with a practitioner and we've got some great lineups, lisa Dave, great to see you. Thanks for joining me. >>Hey guys, >>great to be here. So David got to ask you, you know, back in events last night we're at the 14 it's event where they had the golf PGA championship with the cube Now we got the hybrid model, This is the new normal. We're in, we got these great companies were showcasing them. What's your take? >>Well, you're right. I mean, I think there's a combination of things. We're seeing some live shows. We saw what we did with at mobile world Congress. We did the show with AWS storage day where it was, we were at the spheres, there was no, there was a live audience, but they weren't there physically. It was just virtual and yeah, so, and I just got pained about reinvent. Hey Dave, you gotta make your flights. So I'm making my flights >>were gonna be at the amazon web services, public sector summit next week. At least a lot, a lot of cloud convergence going on here. We got many companies being featured here that we spoke with the Ceo and their top people cloud management, devops data, nelson security. Really cutting edge companies, >>yes, cutting edge companies who are all focused on acceleration. We've talked about the acceleration of digital transformation the last 18 months and we've seen a tremendous amount of acceleration in innovation with what these startups are doing. We've talked to like you said, there's, there's C suite, we've also talked to their customers about how they are innovating so quickly with this hybrid environment, this remote work and we've talked a lot about security in the last week or so. You mentioned that we were at Fortinet cybersecurity skills gap. What some of these companies are doing with automation for example, to help shorten that gap, which is a big opportunity >>for the job market. Great stuff. Dave so the format of this event, you're going to have a fireside chat with the practitioner, we'd like to end these programs with a great experienced practitioner cutting edge in data february. The beginning lisa are gonna be kicking off with of course Jeff bar to give us the update on what's going on AWS and then a special presentation from Emily Freeman who is the author of devops for dummies, she's introducing new content. The revolution in devops devops two point oh and of course jerry Chen from Greylock cube alumni is going to come on and talk about his new thesis castles in the cloud creating moats at cloud scale. We've got a great lineup of people and so the front ends can be great. Dave give us a little preview of what people can expect at the end of the fireside chat. >>Well at the highest level john I've always said we're entering that sort of third great wave of cloud. First wave was experimentation. The second big wave was migration. The third wave of integration, Deep business integration and what you're >>going to hear from >>Hello Fresh today is how they like many companies that started early last decade. They started with an on prem Hadoop system and then of course we all know what happened is S three essentially took the knees out from, from the on prem Hadoop market lowered costs, brought things into the cloud and what Hello Fresh is doing is they're transforming from that legacy Hadoop system into its running on AWS but into a data mess, you know, it's a passionate topic of mine. Hello Fresh was scaling they realized that they couldn't keep up so they had to rethink their entire data architecture and they built it around data mesh Clements key and christoph Soewandi gonna explain how they actually did that are on a journey or decentralized data >>measure it and your posts have been awesome on data measure. We get a lot of traction. Certainly you're breaking analysis for the folks watching check out David Landes, Breaking analysis every week, highlighting the cutting edge trends in tech Dave. We're gonna see you later, lisa and I are gonna be here in the morning talking about with Emily. We got Jeff Barr teed up. Dave. Thanks for coming on. Looking forward to fireside chat lisa. We'll see you when Emily comes back on. But we're gonna go to Jeff bar right now for Dave and I are gonna interview Jeff. Mm >>Hey Jeff, >>here he is. Hey, how are you? How's it going really well. So I gotta ask you, the reinvent is on, everyone wants to know that's happening right. We're good with Reinvent. >>Reinvent is happening. I've got my hotel and actually listening today, if I just remembered, I still need to actually book my flights. I've got my to do list on my desk and I do need to get my >>flights. Uh, >>really looking forward >>to it. I can't wait to see the all the announcements and blog posts. We're gonna, we're gonna hear from jerry Chen later. I love the after on our next event. Get your reaction to this castle and castles in the cloud where competitive advantages can be built in the cloud. We're seeing examples of that. But first I gotta ask you give us an update of what's going on. The ap and ecosystem has been an incredible uh, celebration these past couple weeks, >>so, so a lot of different things happening and the interesting thing to me is that as part of my job, I often think that I'm effectively living in the future because I get to see all this really cool stuff that we're building just a little bit before our customers get to, and so I'm always thinking okay, here I am now, and what's the world going to be like in a couple of weeks to a month or two when these launches? I'm working on actually get out the door and that, that's always really, really fun, just kind of getting that, that little edge into where we're going, but this year was a little interesting because we had to really significant birthdays, we had the 15 year anniversary of both EC two and S three and we're so focused on innovating and moving forward, that it's actually pretty rare for us at Aws to look back and say, wow, we've actually done all these amazing things in in the last 15 years, >>you know, it's kind of cool Jeff, if I may is is, you know, of course in the early days everybody said, well, a place for startup is a W. S and now the great thing about the startup showcases, we're seeing the startups that >>are >>very near, or some of them have even reached escape velocity, so they're not, they're not tiny little companies anymore, they're in their transforming their respective industries, >>they really are and I think that as they start ups grow, they really start to lean into the power of the cloud. They as they start to think, okay, we've we've got our basic infrastructure in place, we've got, we were serving data, we're serving up a few customers, everything is actually working pretty well for us. We've got our fundamental model proven out now, we can invest in publicity and marketing and scaling and but they don't have to think about what's happening behind the scenes. They just if they've got their auto scaling or if they're survivalists, the infrastructure simply grows to meet their demand and it's it's just a lot less things that they have to worry about. They can focus on the fun part of their business which is actually listening to customers and building up an awesome business >>Jeff as you guys are putting together all the big pre reinvented, knows a lot of stuff that goes on prior as well and they say all the big good stuff to reinvent. But you start to see some themes emerged this year. One of them is modernization of applications, the speed of application development in the cloud with the cloud scale devops personas, whatever persona you want to talk about but basically speed the speed of of the app developers where other departments have been slowing things down, I won't say name names, but security group and I t I mean I shouldn't have said that but only kidding but no but seriously people want in minutes and seconds now not days or weeks. You know whether it's policy. What are some of the trends that you're seeing around this this year as we get into some of the new stuff coming out >>So Dave customers really do want speed and for we've actually encapsulate this for a long time in amazon in what we call the bias for action leadership principle >>where >>we just need to jump in and move forward and and make things happen. A lot of customers look at that and they say yes this is great. We need to have the same bias fraction. Some do. Some are still trying to figure out exactly how to put it into play. And they absolutely for sure need to pay attention to security. They need to respect the past and make sure that whatever they're doing is in line with I. T. But they do want to move forward. And the interesting thing that I see time and time again is it's not simply about let's adopt a new technology. It's how do we >>how do we keep our workforce >>engaged? How do we make sure that they've got the right training? How do we bring our our I. T. Team along for this. Hopefully new and fun and exciting journey where they get to learn some interesting new technologies they've got all this very much accumulated business knowledge they still want to put to use, maybe they're a little bit apprehensive about something brand new and they hear about the cloud, but there by and large, they really want to move forward. They just need a little bit of >>help to make it happen >>real good guys. One of the things you're gonna hear today, we're talking about speed traditionally going fast. Oftentimes you meant you have to sacrifice some things on quality and what you're going to hear from some of the startups today is how they're addressing that to automation and modern devoPS technologies and sort of rethinking that whole application development approach. That's something I'm really excited to see organization is beginning to adopt so they don't have to make that tradeoff anymore. >>Yeah, I would >>never want to see someone >>sacrifice quality, >>but I do think that iterating very quickly and using the best of devoPS principles to be able to iterate incredibly quickly and get that first launch out there and then listen with both ears just >>as much >>as you can, Everything. You hear iterate really quickly to meet those needs in, in hours and days, not months, quarters or years. >>Great stuff. Chef and a lot of the companies were featuring here in the startup showcase represent that new kind of thinking, um, systems thinking as well as you know, the cloud scale and again and it's finally here, the revolution of deVOps is going to the next generation and uh, we're excited to have Emily Freeman who's going to come on and give a little preview for her new talk on this revolution. So Jeff, thank you for coming on, appreciate you sharing the update here on the cube. Happy >>to be. I'm actually really looking forward to hearing from Emily. >>Yeah, it's great. Great. Looking forward to the talk. Brand new Premier, Okay, uh, lisa martin, Emily Freeman is here. She's ready to come in and we're going to preview her lightning talk Emily. Um, thanks for coming on, we really appreciate you coming on really, this is about to talk around deVOPS next gen and I think lisa this is one of those things we've been, we've been discussing with all the companies. It's a new kind of thinking it's a revolution, it's a systems mindset, you're starting to see the connections there she is. Emily, Thanks for coming. I appreciate it. >>Thank you for having me. So your teaser video >>was amazing. Um, you know, that little secret radical idea, something completely different. Um, you gotta talk coming up, what's the premise behind this revolution, you know, these tying together architecture, development, automation deployment, operating altogether. >>Yes, well, we have traditionally always used the sclc, which is the software delivery life cycle. Um, and it is a straight linear process that has actually been around since the sixties, which is wild to me um, and really originated in manufacturing. Um, and as much as I love the Toyota production system and how much it has shown up in devops as a sort of inspiration on how to run things better. We are not making cars, we are making software and I think we have to use different approaches and create a sort of model that better reflects our modern software development process. >>It's a bold idea and looking forward to the talk and as motivation. I went into my basement and dusted off all my books from college in the 80s and the sea estimates it was waterfall. It was software development life cycle. They trained us to think this way and it came from the mainframe people. It was like, it's old school, like really, really old and it really hasn't been updated. Where's the motivation? I actually cloud is kind of converging everything together. We see that, but you kind of hit on this persona thing. Where did that come from this persona? Because you know, people want to put people in buckets release engineer. I mean, where's that motivation coming from? >>Yes, you're absolutely right that it came from the mainframes. I think, you know, waterfall is necessary when you're using a punch card or mag tape to load things onto a mainframe, but we don't exist in that world anymore. Thank goodness. And um, yes, so we, we use personas all the time in tech, you know, even to register, well not actually to register for this event, but a lot events. A lot of events, you have to click that drop down. Right. Are you a developer? Are you a manager, whatever? And the thing is personas are immutable in my opinion. I was a developer. I will always identify as a developer despite playing a lot of different roles and doing a lot of different jobs. Uh, and this can vary throughout the day. Right. You might have someone who has a title of software architect who ends up helping someone pair program or develop or test or deploy. Um, and so we wear a lot of hats day to day and I think our discussions around roles would be a better, um, certainly a better approach than personas >>lease. And I've been discussing with many of these companies around the roles and we're hearing from them directly and they're finding out that people have, they're mixing and matching on teams. So you're, you're an S R E on one team and you're doing something on another team where the workflows and the workloads defined the team formation. So this is a cultural discussion. >>It absolutely is. Yes. I think it is a cultural discussion and it really comes to the heart of devops, right? It's people process. And then tools deVOps has always been about culture and making sure that developers have all the tools they need to be productive and honestly happy. What good is all of this? If developing software isn't a joyful experience. Well, >>I got to ask you, I got you here obviously with server list and functions just starting to see this kind of this next gen. And we're gonna hear from jerry Chen, who's a Greylock VC who's going to talk about castles in the clouds, where he's discussing the moats that could be created with a competitive advantage in cloud scale. And I think he points to the snowflakes of the world. You're starting to see this new thing happening. This is devops 2.0, this is the revolution. Is this kind of where you see the same vision of your talk? >>Yes, so DeVOps created 2000 and 8, 2000 and nine, totally different ecosystem in the world we were living in, you know, we didn't have things like surveillance and containers, we didn't have this sort of default distributed nature, certainly not the cloud. Uh and so I'm very excited for jerry's talk. I'm curious to hear more about these moz. I think it's fascinating. Um but yeah, you're seeing different companies use different tools and processes to accelerate their delivery and that is the competitive advantage. How can we figure out how to utilize these tools in the most efficient way possible. >>Thank you for coming and giving us a preview. Let's now go to your lightning keynote talk. Fresh content. Premier of this revolution in Devops and the Freemans Talk, we'll go there now. >>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. I am really excited to share with you a kind of a wild idea, a complete re imagining of the S DLC and I want to be clear, I need your feedback. I want to know what you think of this. You can always find me on twitter at editing. Emily, most of my work centers around deVOps and I really can't overstate what an impact the concept of deVOPS has had on this industry in many ways it built on the foundation of Agile to become a default a standard we all reach for in our everyday work. When devops surfaced as an idea in 2008, the tech industry was in a vastly different space. AWS was an infancy offering only a handful of services. Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented applications adhered to a monolithic architecture, databases were almost exclusively relational and serverless wasn't even a concept. Everything from the application to the engineers was centralized. Our current ecosystem couldn't be more different. Software is still hard, don't get me wrong, but we continue to find novel solutions to consistently difficult, persistent problems. Now, some of these end up being a sort of rebranding of old ideas, but others are a unique and clever take to abstracting complexity or automating toil or perhaps most important, rethinking challenging the very premises we have accepted as Cannon for years, if not decades. In the years since deVOps attempted to answer the critical conflict between developers and operations, engineers, deVOps has become a catch all term and there have been a number of derivative works. Devops has come to mean 5000 different things to 5000 different people. For some, it can be distilled to continuous integration and continuous delivery or C I C D. For others, it's simply deploying code more frequently, perhaps adding a smattering of tests for others. Still, its organizational, they've added a platform team, perhaps even a questionably named DEVOPS team or have created an engineering structure that focuses on a separation of concerns. Leaving feature teams to manage the development, deployment, security and maintenance of their siloed services, say, whatever the interpretation, what's important is that there isn't a universally accepted standard. Well, what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. A framework people can utilize to configure and customize their specific circumstances to modern development practices. The characteristic of deVOPS that I think we can all agree on though, is that an attempted to capture the challenges of the entire software development process. It's that broad umbrella, that holistic view that I think we need to breathe life into again, The challenge we face is that DeVOps isn't increasingly outmoded solution to a previous problem developers now face. Cultural and technical challenge is far greater than how to more quickly deploy a monolithic application. Cloud native is the future the next collection of default development decisions and one the deVOPS story can't absorb in its current form. I believe the era of deVOPS is waning and in this moment as the sun sets on deVOPS, we have a unique opportunity to rethink rebuild free platform. Even now, I don't have a crystal ball. That would be very handy. I'm not completely certain with the next decade of tech looks like and I can't write this story alone. I need you but I have some ideas that can get the conversation started, I believe to build on what was we have to throw away assumptions that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S. D. L. C. has been in use since the 1960s and it's remained more or less the same since before color television and the touch tone phone. Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different with agile and deVOps we sort of looped it into a circle and then an infinity loop we've added pretty colors. But the sclc is more or less the same and it has become an assumption. We don't even think about it anymore, universally adopted constructs like the sclc have an unspoken permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a construct was popularized. Nearly everything around us is a construct, a model, an artifact of a human idea. The chair you're sitting in the desk, you work at the mug from which you drink coffee or sometimes wine, buildings, toilets, plumbing, roads, cars, art, computers, everything. The sclc is a remnant an artifact of a previous era and I think we should throw it away or perhaps more accurately replace it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed complexity of modern socio technical systems. It just can't. Mhm. And these two ideas aren't mutually exclusive that the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time, showing respect for the past while envisioning the future. Now, I don't know about you, I've never had a software project goes smoothly in one go. No matter how small. Even if I'm the only person working on it and committing directly to master software development is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations of agile and devops and represent the iterative nature of continuous innovation. Now, when I was thinking about this, I was inspired by ideas like extreme programming and the spiral model. I I wanted something that would have layers, threads, even a way of visually representing multiple processes happening in parallel. And what I settled on is the revolution model. I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario. And I'm going to dive into all the discrete elements. But I want to give you a moment to have a first impression, to absorb my idea. I call it revolution because well for one it revolves, it's circular shape reflects the continuous and iterative nature of our work, but also because it is revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow, but that would be super cool. And you should call me my mission with. This is to challenge the status quo to create a model that I think more accurately reflects the complexity of modern cloud native software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, automating, deploying and operating intersecting each loop are six spokes that describe the production considerations every engineer has to consider throughout any engineering work and that's test, ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed are not all encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model. We have long used personas as the default way to do divide audiences and tailor messages to group people. Every company in the world right now is repeating the mantra of developers, developers, developers but personas have always bugged me a bit because this approach typically either oversimplifies someone's career are needlessly complicated. Few people fit cleanly and completely into persona based buckets like developers and operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor messages as to call out the difference between a devops engineer and a release engineer or a security administrator versus a security engineer but perhaps most critically, I believe personas are immutable. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ, but they're probably still selecting the same persona on that ubiquitous drop down. We all have to choose from when registering for an event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai Ops and Deverell in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach roles are very different. Roles are temporary, inconsistent, constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied, but the persona I would identify as would remain an actress and artist lesbian. Your work isn't confined to a single set of skills. It may have been a decade ago, but it is not today in any given week or sprint, you may play the role of an architect. Thinking about how to design a feature or service, developer building out code or fixing a bug and on automation engineer, looking at how to improve manual processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers or in operations. Engineer ensuring an application functions inconsistent expected ways and no matter what role we play. We have to consider a number of issues. The first is test ability. All software systems require testing to assure architects that designs work developers, the code works operators, that infrastructure is running as expected and engineers of all disciplines that code changes won't bring down the whole system testing in its many forms is what enables systems to be durable and have longevity. It's what reassures engineers that changes won't impact current functionality. A system without tests is a disaster waiting to happen, which is why test ability is first among equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most part are high impact, low probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting for a year. They don't happen super frequently and then goodness because you know that there are endless small vulnerabilities lurking in our systems. Security is something we all know we should dedicate time to but often don't make time for. And let's be honest, it's hard and complicated and a little scary def sec apps. The first derivative of deVOPS asked engineers to move security left this approach. Mint security was a consideration early in the process, not something that would block release at the last moment. This is also the consideration under which I'm putting compliance and governance well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. I'm kidding. But in all seriousness, these three concepts are really about risk management, identity, data, authorization. It doesn't really matter what specific issue you're speaking about, the question is who has access to what win and how and that is everyone's responsibility at every stage site reliability engineering or sorry, is a discipline job and approach for good reason. It is absolutely critical that applications and services work as expected. Most of the time. That said, availability is often mistakenly treated as a synonym for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. The system is not reliable, reliability has five key components, availability, latency, throughput. Fidelity and durability, reliability is the end result. But resiliency for me is the journey the action engineers can take to improve reliability, observe ability is the ability to have insight into an application or system. It's the combination of telemetry and monitoring and alerting available to engineers and leadership. There's an aspect of observe ability that overlaps with reliability, but the purpose of observe ability isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner workings of that system. The concept of observe ability actually originates and linear dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs. If it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared responsibility model of cloud storage compute and managed services require that engineering teams be able to quickly be alerted to identify and remediate issues as they arise. Flexible systems are capable of adapting to meet the ever changing needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns. Are partitioned into small components or classes and architected to enable the now as well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas accommodate change well components, communicate via a standardized and well documented A. P. I. The only thing constant in our industry is change and every role we play, creating flexibility and solutions that can be flexible that will grow as the applications grow is absolutely critical. Finally, scalability scalability refers to more than a system's ability to scale for additional load. It implies growth scalability and the revolution model carries the continuous innovation of a team and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles to consider everyone around us, our customers who use the system or rely on its services, our colleagues current and future with whom we collaborate and even our future selves. Mhm. Software development isn't a straight line, nor is it a perfect loop. It is an ever changing complex dance. There are twirls and pivots and difficult spins forward and backward. Engineers move in parallel, creating truly magnificent pieces of art. We need a modern model for this modern era and I believe this is just the revolution to get us started. Thank you so much for having me. >>Hey, we're back here. Live in the keynote studio. I'm john for your host here with lisa martin. David lot is getting ready for the fireside chat ending keynote with the practitioner. Hello! Fresh without data mesh lisa Emily is amazing. The funky artwork there. She's amazing with the talk. I was mesmerized. It was impressive. >>The revolution of devops and the creative element was a really nice surprise there. But I love what she's doing. She's challenging the status quo. If we've learned nothing in the last year and a half, We need to challenge the status quo. A model from the 1960s that is no longer linear. What she's doing is revolutionary. >>And we hear this all the time. All the cube interviews we do is that you're seeing the leaders, the SVP's of engineering or these departments where there's new new people coming in that are engineering or developers, they're playing multiple roles. It's almost a multidisciplinary aspect where you know, it's like going into in and out burger in the fryer later and then you're doing the grill, you're doing the cashier, people are changing roles or an architect, their test release all in one no longer departmental, slow siloed groups. >>She brought up a great point about persona is that we no longer fit into these buckets. That the changing roles. It's really the driver of how we should be looking at this. >>I think I'm really impressed, really bold idea, no brainer as far as I'm concerned, I think one of the things and then the comments were off the charts in a lot of young people come from discord servers. We had a good traction over there but they're all like learning. Then you have the experience, people saying this is definitely has happened and happening. The dominoes are falling and they're falling in the direction of modernization. That's the key trend speed. >>Absolutely with speed. But the way that Emily is presenting it is not in a brash bold, but it's in a way that makes great sense. The way that she creatively visually lined out what she was talking about Is amenable to the folks that have been doing this for since the 60s and the new folks now to really look at this from a different >>lens and I think she's a great setup on that lightning top of the 15 companies we got because you think about sis dig harness. I white sourced flamingo hacker one send out, I oh, okay. Thought spot rock set Sarah Ops ramp and Ops Monte cloud apps, sani all are doing modern stuff and we talked to them and they're all on this new wave, this monster wave coming. What's your observation when you talk to these companies? >>They are, it was great. I got to talk with eight of the 15 and the amount of acceleration of innovation that they've done in the last 18 months is phenomenal obviously with the power and the fuel and the brand reputation of aws but really what they're all facilitating cultural shift when we think of devoPS and the security folks. Um, there's a lot of work going on with ai to an automation to really kind of enabled to develop the develops folks to be in control of the process and not have to be security experts but ensuring that the security is baked in shifting >>left. We saw that the chat room was really active on the security side and one of the things I noticed was not just shift left but the other groups, the security groups and the theme of cultural, I won't say war but collision cultural shift that's happening between the groups is interesting because you have this new devops persona has been around Emily put it out for a while. But now it's going to the next level. There's new revolutions about a mindset, a systems mindset. It's a thinking and you start to see the new young companies coming out being funded by the gray locks of the world who are now like not going to be given the we lost the top three clouds one, everything. there's new business models and new technical architecture in the cloud and that's gonna be jerry Chen talk coming up next is going to be castles in the clouds because jerry chant always talked about moats, competitive advantage and how moats are key to success to guard the castle. And then we always joke, there's no more moz because the cloud has killed all the boats. But now the motor in the cloud, the castles are in the cloud, not on the ground. So very interesting thought provoking. But he's got data and if you look at the successful companies like the snowflakes of the world, you're starting to see these new formations of this new layer of innovation where companies are growing rapidly, 98 unicorns now in the cloud. Unbelievable, >>wow, that's a lot. One of the things you mentioned, there's competitive advantage and these startups are all fueled by that they know that there are other companies in the rear view mirror right behind them. If they're not able to work as quickly and as flexibly as a competitor, they have to have that speed that time to market that time to value. It was absolutely critical. And that's one of the things I think thematically that I saw along the eighth sort of that I talked to is that time to value is absolutely table stakes. >>Well, I'm looking forward to talking to jerry chan because we've talked on the queue before about this whole idea of What happens when winner takes most would mean the top 3, 4 cloud players. What happens? And we were talking about that and saying, if you have a model where an ecosystem can develop, what does that look like and back in 2013, 2014, 2015, no one really had an answer. Jerry was the only BC. He really nailed it with this castles in the cloud. He nailed the idea that this is going to happen. And so I think, you know, we'll look back at the tape or the videos from the cube, we'll find those cuts. But we were talking about this then we were pontificating and riffing on the fact that there's going to be new winners and they're gonna look different as Andy Jassy always says in the cube you have to be misunderstood if you're really going to make something happen. Most of the most successful companies are misunderstood. Not anymore. The cloud scales there. And that's what's exciting about all this. >>It is exciting that the scale is there, the appetite is there the appetite to challenge the status quo, which is right now in this economic and dynamic market that we're living in is there's nothing better. >>One of the things that's come up and and that's just real quick before we bring jerry in is automation has been insecurity, absolutely security's been in every conversation, but automation is now so hot in the sense of it's real and it's becoming part of all the design decisions. How can we automate can we automate faster where the keys to automation? Is that having the right data, What data is available? So I think the idea of automation and Ai are driving all the change and that's to me is what these new companies represent this modern error where AI is built into the outcome and the apps and all that infrastructure. So it's super exciting. Um, let's check in, we got jerry Chen line at least a great. We're gonna come back after jerry and then kick off the day. Let's bring in jerry Chen from Greylock is he here? Let's bring him in there. He is. >>Hey john good to see you. >>Hey, congratulations on an amazing talk and thesis on the castles on the cloud. Thanks for coming on. >>All right, Well thanks for reading it. Um, always were being put a piece of workout out either. Not sure what the responses, but it seemed to resonate with a bunch of developers, founders, investors and folks like yourself. So smart people seem to gravitate to us. So thank you very much. >>Well, one of the benefits of doing the Cube for 11 years, Jerry's we have videotape of many, many people talking about what the future will hold. You kind of are on this early, it wasn't called castles in the cloud, but you were all I was, we had many conversations were kind of connecting the dots in real time. But you've been on this for a while. It's great to see the work. I really think you nailed this. I think you're absolutely on point here. So let's get into it. What is castles in the cloud? New research to come out from Greylock that you spearheaded? It's collaborative effort, but you've got data behind it. Give a quick overview of what is castle the cloud, the new modes of competitive advantage for companies. >>Yeah, it's as a group project that our team put together but basically john the question is, how do you win in the cloud? Remember the conversation we had eight years ago when amazon re event was holy cow, Like can you compete with them? Like is it a winner? Take all? Winner take most And if it is winner take most, where are the white spaces for Some starts to to emerge and clearly the past eight years in the cloud this journey, we've seen big companies, data breaks, snowflakes, elastic Mongo data robot. And so um they spotted the question is, you know, why are the castles in the cloud? The big three cloud providers, Amazon google and Azure winning. You know, what advantage do they have? And then given their modes of scale network effects, how can you as a startup win? And so look, there are 500 plus services between all three cloud vendors, but there are like 500 plus um startups competing gets a cloud vendors and there's like almost 100 unicorn of private companies competing successfully against the cloud vendors, including public companies. So like Alaska, Mongo Snowflake. No data breaks. Not public yet. Hashtag or not public yet. These are some examples of the names that I think are winning and watch this space because you see more of these guys storm the castle if you will. >>Yeah. And you know one of the things that's a funny metaphor because it has many different implications. One, as we talk about security, the perimeter of the gates, the moats being on land. But now you're in the cloud, you have also different security paradigm. You have a different um, new kinds of services that are coming on board faster than ever before. Not just from the cloud players but From companies contributing into the ecosystem. So the combination of the big three making the market the main markets you, I think you call 31 markets that we know of that probably maybe more. And then you have this notion of a sub market, which means that there's like we used to call it white space back in the day, remember how many whites? Where's the white space? I mean if you're in the cloud, there's like a zillion white spaces. So talk about this sub market dynamic between markets and that are being enabled by the cloud players and how these sub markets play into it. >>Sure. So first, the first problem was what we did. We downloaded all the services for the big three clowns. Right? And you know what as recalls a database or database service like a document DB and amazon is like Cosmo dB and Azure. So first thing first is we had to like look at all three cloud providers and you? Re categorize all the services almost 500 Apples, Apples, Apples # one number two is you look at all these markets or sub markets and said, okay, how can we cluster these services into things that you know you and I can rock right. That's what amazon Azure and google think about. It is very different and the beauty of the cloud is this kind of fat long tail of services for developers. So instead of like oracle is a single database for all your needs. They're like 20 or 30 different databases from time series um analytics, databases. We're talking rocks at later today. Right. Um uh, document databases like Mongo search database like elastic. And so what happens is there's not one giant market like databases, there's a database market And 30, 40 sub markets that serve the needs developers. So the Great News is cloud has reduced the cost and create something that new for developers. Um also the good news is for a start up you can find plenty of white speeds solving a pain point, very specific to a different type of problem >>and you can sequence up to power law to this. I love the power of a metaphor, you know, used to be a very thin neck note no torso and then a long tail. But now as you're pointing out this expansion of the fat tail of services, but also there's big tam's and markets available at the top of the power law where you see coming like snowflake essentially take on the data warehousing market by basically sitting on amazon re factoring with new services and then getting a flywheel completely changing the economic unit economics completely changing the consumption model completely changing the value proposition >>literally you >>get Snowflake has created like a storm, create a hole, that mode or that castle wall against red shift. Then companies like rock set do your real time analytics is Russian right behind snowflakes saying, hey snowflake is great for data warehouse but it's not fast enough for real time analytics. Let me give you something new to your, to your parallel argument. Even the big optic snowflake have created kind of a wake behind them that created even more white space for Gaza rock set. So that's exciting for guys like me and >>you. And then also as we were talking about our last episode two or quarter two of our showcase. Um, from a VC came on, it's like the old shelf where you didn't know if a company's successful until they had to return the inventory now with cloud you if you're not successful, you know it right away. It's like there's no debate. Like, I mean you're either winning or not. This is like that's so instrumented so a company can have a good better mousetrap and win and fill the white space and then move up. >>It goes both ways. The cloud vendor, the big three amazon google and Azure for sure. They instrument their own class. They know john which ecosystem partners doing well in which ecosystems doing poorly and they hear from the customers exactly what they want. So it goes both ways they can weaponize that. And just as well as you started to weaponize that info >>and that's the big argument of do that snowflake still pays the amazon bills. They're still there. So again, repatriation comes back, That's a big conversation that's come up. What's your quick take on that? Because if you're gonna have a castle in the cloud, then you're gonna bring it back to land. I mean, what's that dynamic? Where do you see that compete? Because on one hand is innovation. The other ones maybe cost efficiency. Is that a growth indicator slow down? What's your view on the movement from and to the cloud? >>I think there's probably three forces you're finding here. One is the cost advantage in the scale advantage of cloud so that I think has been going for the past eight years, there's a repatriation movement for a certain subset of customers, I think for cost purposes makes sense. I think that's a tiny handful that believe they can actually run things better than a cloud. The third thing we're seeing around repatriation is not necessary against cloud, but you're gonna see more decentralized clouds and things pushed to the edge. Right? So you look at companies like Cloudflare Fastly or a company that we're investing in Cato networks. All ideas focus on secure access at the edge. And so I think that's not the repatriation of my own data center, which is kind of a disaggregated of cloud from one giant monolithic cloud, like AWS east or like a google region in europe to multiple smaller clouds for governance purposes, security purposes or legacy purposes. >>So I'm looking at my notes here, looking down on the screen here for this to read this because it's uh to cut and paste from your thesis on the cloud. The excellent cloud. The of the $38 billion invested this quarter. Um Ai and ml number one, um analytics. Number two, security number three. Actually, security number one. But you can see the bubbles here. So all those are data problems I need to ask you. I see data is hot data as intellectual property. How do you look at that? Because we've been reporting on this and we just started the cube conversation around workflows as intellectual property. If you have scale and your motives in the cloud. You could argue that data and the workflows around those data streams is intellectual property. It's a protocol >>I believe both are. And they just kind of go hand in hand like peanut butter and jelly. Right? So data for sure. I. P. So if you know people talk about days in the oil, the new resource. That's largely true because of powers a bunch. But the workflow to your point john is sticky because every company is a unique snowflake right? Like the process used to run the cube and your business different how we run our business. So if you can build a workflow that leverages the data, that's super sticky. So in terms of switching costs, if my work is very bespoke to your business, then I think that's competitive advantage. >>Well certainly your workflow is a lot different than the cube. You guys just a lot of billions of dollars in capital. We're talking to all the people out here jerry. Great to have you on final thought on your thesis. Where does it go from here? What's been the reaction? Uh No, you put it out there. Great love the restart. Think you're on point on this one. Where did we go from here? >>We have to follow pieces um in the near term one around, you know, deep diver on open source. So look out for that pretty soon and how that's been a powerful strategy a second. Is this kind of just aggregation of the cloud be a Blockchain and you know, decentralized apps, be edge applications. So that's in the near term two more pieces of, of deep dive we're doing. And then the goal here is to update this on a quarterly and annual basis. So we're getting submissions from founders that wanted to say, hey, you missed us or he screwed up here. We got the big cloud vendors saying, Hey jerry, we just lost his new things. So our goal here is to update this every single year and then probably do look back saying, okay, uh, where were we wrong? We're right. And then let's say the castle clouds 2022. We'll see the difference were the more unicorns were there more services were the IPO's happening. So look for some short term work from us on analytics, like around open source and clouds. And then next year we hope that all of this forward saying, Hey, you have two year, what's happening? What's changing? >>Great stuff and, and congratulations on the southern news. You guys put another half a billion dollars into early, early stage, which is your roots. Are you still doing a lot of great investments in a lot of unicorns. Congratulations that. Great luck on the team. Thanks for coming on and congratulations you nailed this one. I think I'm gonna look back and say that this is a pretty seminal piece of work here. Thanks for sharing. >>Thanks john thanks for having us. >>Okay. Okay. This is the cube here and 81 startup showcase. We're about to get going in on all the hot companies closing out the kino lisa uh, see jerry Chen cube alumni. He was right from day one. We've been riffing on this, but he nails it here. I think Greylock is lucky to have him as a general partner. He's done great deals, but I think he's hitting the next wave big. This is, this is huge. >>I was listening to you guys talking thinking if if you had a crystal ball back in 2013, some of the things Jerry saying now his narrative now, what did he have a crystal >>ball? He did. I mean he could be a cuBA host and I could be a venture capital. We were both right. I think so. We could have been, you know, doing that together now and all serious now. He was right. I mean, we talked off camera about who's the next amazon who's going to challenge amazon and Andy Jassy was quoted many times in the queue by saying, you know, he was surprised that it took so long for people to figure out what they were doing. Okay, jerry was that VM where he had visibility into the cloud. He saw amazon right away like we did like this is a winning formula and so he was really out front on this one. >>Well in the investments that they're making in these unicorns is exciting. They have this, this lens that they're able to see the opportunities there almost before anybody else can. And finding more white space where we didn't even know there was any. >>Yeah. And what's interesting about the report I'm gonna dig into and I want to get to him while he's on camera because it's a great report, but He says it's like 500 services I think Amazon has 5000. So how you define services as an interesting thing and a lot of amazon services that they have as your doesn't have and vice versa, they do call that out. So I find the report interesting. It's gonna be a feature game in the future between clouds the big three. They're gonna say we do this, you're starting to see the formation, Google's much more developer oriented. Amazon is much more stronger in the governance area with data obviously as he pointed out, they have such experience Microsoft, not so much their developer cloud and more office, not so much on the government's side. So that that's an indicator of my, my opinion of kind of where they rank. So including the number one is still amazon web services as your long second place, way behind google, right behind Azure. So we'll see how the horses come in, >>right. And it's also kind of speaks to the hybrid world in which we're living the hybrid multi cloud world in which many companies are living as companies to not just survive in the last year and a half, but to thrive and really have to become data companies and leverage that data as a competitive advantage to be able to unlock the value of it. And a lot of these startups that we talked to in the showcase are talking about how they're helping organizations unlock that data value. As jerry said, it is the new oil, it's the new gold. Not unless you can unlock that value faster than your competition. >>Yeah, well, I'm just super excited. We got a great day ahead of us with with all the cots startups. And then at the end day, Volonte is gonna interview, hello, fresh practitioners, We're gonna close it out every episode now, we're going to do with the closing practitioner. We try to get jpmorgan chase data measures. The hottest area right now in the enterprise data is new competitive advantage. We know that data workflows are now intellectual property. You're starting to see data really factoring into these applications now as a key aspect of the competitive advantage and the value creation. So companies that are smart are investing heavily in that and the ones that are kind of slow on the uptake are lagging the market and just trying to figure it out. So you start to see that transition and you're starting to see people fall away now from the fact that they're not gonna make it right, You're starting to, you know, you can look at look at any happens saying how much ai is really in there. Real ai what's their data strategy and you almost squint through that and go, okay, that's gonna be losing application. >>Well the winners are making it a board level conversation >>And security isn't built in. Great to have you on this morning kicking it off. Thanks John Okay, we're going to go into the next set of the program at 10:00 we're going to move into the breakouts. Check out the companies is three tracks in there. We have an awesome track on devops pure devops. We've got the data and analytics and we got the cloud management and just to run down real quick check out the sis dig harness. Io system is doing great, securing devops harness. IO modern software delivery platform, White Source. They're preventing and remediating the rest of the internet for them for the company's that's a really interesting and lumbago, effortless acres land and monitoring functions, server list super hot. And of course hacker one is always great doing a lot of great missions and and bounties you see those success continue to send i O there in Palo alto changing the game on data engineering and data pipe lining. Okay. Data driven another new platform, horizontally scalable and of course thought spot ai driven kind of a search paradigm and of course rock set jerry Chen's companies here and press are all doing great in the analytics and then the cloud management cost side 80 operations day to operate. Ops ramps and ops multi cloud are all there and sunny, all all going to present. So check them out. This is the Cubes Adria's startup showcase episode three.

>>Hi, I'm Emily Freeman, I'm the author of devops for dummies and the curator of 97 things every cloud engineer should know. I am thrilled to be here with you all today. >>I'm really excited to share with you a kind of a wild idea. A complete re imagining >>of the S DLC >>and I want to be clear, I need your feedback. I want to >>know what you think of this. You can always find me >>on twitter at editing. Emily, >>most of my work centers around devops and I really >>can't overstate what an impact >>the concept of devoPS has had on this industry >>in many ways it built on the foundation of agile to become a default a standard we all reach for in our everyday work. >>When devops surfaced as an idea in 2000 >>and eight, the tech industry was in a vastly different space. >>AWS was an infancy >>offering. Only a handful >>of services, >>Azure and G C P didn't exist yet. The majority's majority of companies maintained their own infrastructure. >>Developers wrote code and relied on sys admins to deploy new code at scheduled intervals. Sometimes months apart, container technology hadn't been invented. >>Applications adhered >>to a monolithic architecture, databases were almost exclusively relational >>and serverless wasn't even a concept. Everything from the application to the engineers >>was centralized. >>Our current ecosystem couldn't >>be more different. Software is still hard. Don't get me wrong, >>but we continue to find novel solutions to consistently difficult, persistent problems. >>Now, some of these end up being a sort of rebranding of old ideas >>but others are a unique and clever take to abstracting complexity >>or >>automating toil or >>perhaps most important, >>rethinking challenging the very >>premises we have accepted as Cannon for years, if not decades. >>In the years since deVOps attempted to answer the critical conflict between developers and operations engineers. Devops has become a catch all term >>and there have been a number of >>derivative works. DeVos has come to mean 5000 different things to 5000 different people. For some, it can be distilled >>to continuous integration and continuous delivery or C I C D. For others, it's >>simply deploying code more frequently, perhaps adding a smattering of tests >>for others. Still its organizational, they've added a platform team, perhaps even a >>questionably named DevoPS team or have created an engineering structure that focuses on a separation of concerns, leaving feature teams to manage the development, >>deployment, security and maintenance of their siloed services. Whatever >>the interpretation, what's important is that there isn't a universally accepted >>standard, well what deVOPS is or what it looks like an execution, it's a philosophy more than anything else. >>A framework people can utilize to configure >>and customize >>their specific circumstances >>to modern development practices. The characteristic of DEVOPS that I think we can all >>agree on though, is that an attempted to capture the challenges of the entire >>software development process. It's that broad >>umbrella, that holistic view that I think we need to breathe life into again, The challenge we face >>is that devops isn't >>increasingly outmoded solution to a >>previous problem developers now face >>cultural and technical challenge is far greater than how to more quickly deploy a monolithic application >>cloud native is the future. The next collection of default development decisions >>and one the deVOps story can't absorb in its current form. >>I believe the era of devops is waning and in this moment as the sun sets on >>deVOps, we have a unique opportunity to rethink >>rebuild free platform. Even now, I don't have a crystal ball that would be >>very handy. >>I'm not completely certain with the next decade of tech looks like >>and I can't write this story alone. I need you >>but I have some ideas >>that can get the conversation >>started, I believe to >>build on what was we have to throw away assumptions >>that we've taken for granted all this time in order to move forward. We must first step back. Mhm. The software or systems development life cycle, what we call the S DLC >>has been in use since the 1960s and it's remained more or less the same since before >>color television >>and the touch tone phone >>Over the last 60 or so odd years we've made tweaks, slight adjustments, massaged it. The stages or steps are always a little different >>with agile and devops we sort of looped it into a circle >>and then an infinity loop. >>We've added pretty colors. But the sclc >>is more or less >>the same and it has become an assumption. We don't even think about it anymore, >>universally adopted constructs like the sclc have an unspoken >>permanence. They feel as if they have always been and always will be. I think the impact of that is even more potent. If you were born after a >>construct was popularized, nearly everything around us is a construct. A model, an artifact of >>a human idea. >>The chair you're sitting in the >>desk, you work at the mug from which you drink coffee or sometimes wine, >>buildings, toilets, >>plumbing, roads, cars, art, computers, everything. The splc is a remnant an artifact of a previous era and I think we should throw it away >>or perhaps more accurately replace >>it, replace it with something that better reflects the actual nature of our work. A linear, single threaded model designed for the manufacturer of material goods cannot possibly capture the distributed >>complexity of modern socio technical systems. >>It just can't. Mhm. >>And these two ideas aren't mutually exclusive that >>the sclc was industry changing, valuable and extraordinarily impactful and that it's time for something new. I believe we are strong enough to hold these two ideas at the same time showing respect for the past while envisioning the future. >>No, I don't know about you. I've never had a software project goes smoothly in one >>go, no matter how small, even if I'm the only person working on it and committing directly to master >>Software development >>is chaos. It's a study and entropy and it is not getting any more simple. The model with which we think and talk about software development must capture the multithreaded, non sequential nature of our work. It should embody the roles engineers take on and the considerations they make along the way. It should build on the foundations >>of agile >>and devops and represent the iterative nature of continuous innovation. >>Now when I was thinking about this I was inspired by ideas like extreme programming and the spiral model. Yeah >>I wanted something that would have layers, >>threads, even a way >>of visually representing multiple processes happening in parallel. >>And what I settled on is the revolution model. >>I believe the visualization of revolution is capable of capturing the pivotal moments of any software scenario >>and I'm going to dive into all the discrete elements but I want to give you a moment to have a first impression to absorb >>my idea. >>I call it revolution because well for one it revolves, >>it's circular shape reflects the continuous and iterative nature of our work. >>But also because it is >>revolutionary. I am challenging a 60 year old model that is embedded into our daily language. I don't expect Gartner to build a magic quadrant around this tomorrow but that would be super cool and you should call me my mission with this is to challenge the status quo. To create a model that I think more accurately reflects the complexity of modern cloud. Native >>software development. The revolution model is constructed of five concentric circles describing the critical roles of software development architect. Ng development, >>automating, >>deploying and operating >>intersecting each loop are six >>spokes >>that describe the production considerations every engineer has to consider throughout any engineering work and that's test, >>ability, secure ability, reliability, observe ability, flexibility and scalability. The considerations listed >>are not all >>encompassing. There are of course things not explicitly included. I figured if I put 20 spokes, some of us, including myself, might feel a little overwhelmed. So let's dive into each element in this model, >>we have long used personas as the default way to do divide >>audiences and tailor messages to group people. >>Every company in the world right now is repeating the mantra of developers, developers, developers, but personas have >>always bugged me a bit >>because this approach typically >>either oversimplifies someone's career >>are needlessly complicated. Few people fit cleanly and completely >>into persona based buckets like developers and >>operations anymore. The lines have gotten fuzzy on the other hand, I don't think we need to specifically tailor >>messages >>as to call out the difference between a devops engineer and a release engineer or security administrator versus a security engineer. But perhaps most critically, I believe personas are immutable. Mhm. A persona is wholly dependent on how someone identifies themselves. It's intrinsic not extrinsic. Their titles may change their jobs may differ but they're probably >>still selecting the same persona on that ubiquitous drop down. We all have to choose >>from when registering for an >>event. Probably this one too. I I was a developer and I will always identify as a developer despite doing a ton of work in areas like devops and Ai ops and Deverell >>in my heart. I'm a developer I think about problems from that perspective. First it influences my thinking and my approach. Mhm roles are very different. Roles are temporary, >>inconsistent, >>constantly fluctuating. If I were an actress, the parts I would play would be lengthy and varied but the persona I would identify as would remain an actress and artist >>lesbian. >>Your work isn't confined >>to a single set of skills. It may have been a decade ago but it is not today >>in any given week or sprint. You may play the role of an architect thinking about how to design a feature or service, >>developer, building out code or fixing a bug >>and on automation engineer, looking at how to improve manual >>processes. We often refer to as soil release engineer, deploying code to different environments or releasing it to customers. >>We're in operations. Engineer, ensuring an application functions >>inconsistent expected ways >>and no matter what role we play. We have to consider a number of issues. >>The first is test ability. All software systems require >>testing to assure architects >>that designs work developers that code works operators, that >>infrastructure is running as expected >>and engineers of all disciplines >>that code changes won't >>bring down the whole system testing >>in its many forms >>is what enables >>systems to be durable and have >>longevity. It's what reassures engineers that changes >>won't impact current functionality. A system without tests >>is a disaster waiting to happen. Which is why test ability >>is first among >>equals at this particular roundtable. Security is everyone's responsibility. But if you understand how to design and execute secure systems, I struggle with this security incidents for the most >>part are high impact, low >>probability events. The really big disasters, the one that the ones that end up on the news and get us all free credit reporting >>for a year. They don't happen super frequently and >>then goodness because you know that there are >>endless small >>vulnerabilities lurking in our systems. >>Security is something we all know we should dedicate time to but often don't make time for. >>And let's be honest, it's hard and >>complicated >>and a little scary. The cops. The first derivative of deVOPS asked engineers >>to move >>security left this approach. Mint security was a consideration >>early in the process, not something that would block >>release at the last moment. >>This is also the consideration under which I'm putting compliance >>and governance >>well not perfectly aligned. I figure all the things you have to call lawyers for should just live together. >>I'm kidding. But >>in all seriousness, these three concepts >>are really about >>risk management, >>identity, >>data, authorization. It doesn't really matter what specific issue you're speaking about. The question >>is who has access to what, when and how and that is everyone's responsibility at every stage, site, reliability, engineering or SRE is a discipline and job and approach for good reason, it is absolutely >>critical that >>applications and services work as expected. Most of the time. That said, availability is often mistakenly >>treated as a synonym >>for reliability. Instead, it's a single aspect of the concept if a system is available but customer data is inaccurate or out of sync. >>The system is >>not reliable, reliability has five key components, availability latency through but fidelity and durability, reliability >>is the end result. But resiliency for me is the journey the action engineers >>can take to improve reliability, observe ability is the ability to have insight into an application or >>system. It's the combination of telemetry and monitoring and alerting available to engineers >>and leadership. There's an aspect of observe ability that overlaps with reliability but the purpose of observe ability >>isn't just to maintain a reliable system though, that is of course important. It is the capacity for engineers working on a system to have visibility into the inner >>workings of that system. The concept of observe ability actually >>originates and linear >>dynamic systems. It's defined as how well internal states of a system can be understood based on information about its external outputs when it is critical when companies move systems to the cloud or utilize managed services that they don't lose visibility and confidence in their systems. The shared >>responsibility model >>of cloud storage compute and managed services >>require that engineering teams be able to quickly be alerted to identify and remediate >>issues as they arise, flexible systems are capable of >>adapting to meet the ever changing >>needs of the customer and the market segment, flexible code bases absorb new code smoothly. Embody a clean separation of concerns, are partitioned into small components or classes >>and architected to enable the Now as >>well as the next inflexible systems. Change dependencies are reduced or eliminated. Database schemas, accommodate change well components communicate via a standardized and well documented A. P. I. >>The only thing >>constant in our industry is >>change and every role we play, >>creating flexibility and solutions that can be >>flexible that will grow >>as the applications grow >>is absolutely critical. >>Finally, scalability scalability refers to more than a system's ability to scale for additional >>load. It implies growth >>scalability in the revolution model carries the continuous >>innovation of a team >>and the byproducts of that growth within a system. For me, scalability is the most human of the considerations. It requires each of us in our various roles >>to consider everyone >>around us, our customers who use the system or rely on its services, our colleagues, >>current and future with whom we collaborate and even our future selves. Mhm. >>Software development isn't a straight line, nor is it a perfect loop. >>It isn't ever changing complex dance. >>There are twirls and pivots and difficult spins >>forward and backward engineers move in parallel, creating truly magnificent pieces of art. We need a modern >>model for this modern >>era, and I believe this is just the >>revolution to get us started. Thank you so much for having me. Mm.

>> Narrator: From around the globe its "theCUBE" presenting Adaptive Data Governance, brought to you by Io-Tahoe. >> And we're back with the Data Automation series. In this episode we're going to learn more about what Io-Tahoe is doing in the field of adaptive data governance, how can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin and I'm joined by Ajay Vohora the CEO of Io-Tahoe, and Lester Waters the CTO of Io-Tahoe. Gentlemen it's great to have you on the program. >> Thank you Lisa is good to be back. >> Great to see you Lisa. >> Likewise, very seriously this isn't cautious as we are. Lester were going to start with you, what's going on at Io-Tahoe, what's new? >> Well, I've been with Io-Tahoe for a little over the year, and one thing I've learned is every customer needs are just a bit different. So we've been working on our next major release of the Io-Tahoe product and to really try to address these customer concerns because we want to be flexible enough in order to come in and not just profile the data and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could extend the product without building a new version of the product, we wanted to be able to have pluggable modules. We are also focused a lot on performance, that's very important with the bulk of data that we deal with and we're able to pass through that data in a single pass and do the analytics that are needed whether it's a lineage data quality or just identifying the underlying data. And we're incorporating all that we've learned, we're tuning up our machine learning, we're analyzing on more dimensions than we've ever done before, we're able to do data quality without doing an initial reggie expert for example, just out of the box. So I think it's all of these things are coming together to form our next version of our product and We're really excited about. >> Sounds exciting, Ajay from the CEOs level what's going on? >> Wow, I think just building on that, what Lester just mentioned now it's we're growing pretty quickly with our partners, and today here with Oracle we're excited to explain how that's shaping up lots of collaboration already with Oracle, and government in insurance and in banking. And we're excited because we get to have an impact, it's really satisfying to see how we're able to help businesses transform and redefine what's possible with their data. And having Oracle there as a partner to lean in with is definitely helping. >> Excellent, we're going to dig into that a little bit later. Lester let's go back over to you, explain adaptive data governance, help us understand that. >> Really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data-driven culture and pushing what's traditionally managed in IT out to the business. And to do that, you've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concern system, but they need to understand what kind of data they have, what shape it's in, what's dependent on it upstream and downstream, and so that they can make their educated decisions on what they need to do to achieve those business outcomes. A lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just say, you know, (tapping) the start date of a loan must always be before the end date of a loan, and having that generic rule regardless of the underlying database, and applying it even when a new database comes online and having those rules applied, that's what adaptive data governance about. I like to think of it as the intersection of three circles, really it's the technical metadata coming together with policies and rules, and coming together with the business ontologies that are unique to that particular business. And bringing this all together allows you to enable rapid change in your environment, so, it's a mouthful adaptive data governance, but that's what it kind of comes down to. >> So Ajay help me understand this, is this what enterprise companies are doing now or are they not quite there yet? >> Well, you know Lisa I think every organization is going at his pace, but markets are changing economy and the speed at which some of the changes in the economy happening is compelling more businesses to look at being more digital in how they serve their own customers. So what we're saying is a number of trends here from heads of data, chief data officers, CIO stepping back from a one size fits all approach because they've tried that before and it just hasn't worked. They've spent millions of dollars on IT programs trying to drive value from that data, and they've ended up with large teams of manual processing around data to try and hard-wire these policies to fit with the context and each line of business, and that hasn't worked. So, the trends that we're seeing emerge really relate to how do I as a chief data officer, as a CIO, inject more automation and to allow these common tasks. And we've been able to see that impact, I think the news here is if you're trying to create a knowledge graph, a data catalog, or a business glossary, and you're trying to do that manually, well stop, you don't have to do that manual anymore. I think best example I can give is Lester and I we like Chinese food and Japanese food, and if you were sitting there with your chopsticks you wouldn't eat a bowl of rice with the chopsticks one grain at a time, what you'd want to do is to find a more productive way to enjoy that meal before it gets cold. And that's similar to how we're able to help organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >> And if it was me eating that food with you guys I would be not using chopsticks I would be using a fork and probably a spoon. So Lester how then does Io-Tahoe go about doing this and enabling customers to achieve this? >> Let me show you a little story here. So if you take a look at the challenges that most customers have they're very similar, but every customer is on a different data journey, so, but it all starts with what data do I have, what shape is that data in, how is it structured, what's dependent on it upstream and downstream, what insights can I derive from that data, and how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud, maybe they're doing a migration to Oracle, maybe they're doing some data governance changes, and it's about enabling this. So if you look at these challenges, I'm going to take you through a story here, and I want to introduce Amanda. Amanda is not Latin like anyone in any large organizations, she is looking around and she just sees stacks of data, I mean, different databases the one she knows about, the ones she doesn't know about but should know about, various different kinds of databases, and Amanda is this tasking with understanding all of this so that they can embark on her data journey program. So Amanda goes through and she's great, (snaps finger) "I've got some handy tools, I can start looking at these databases and getting an idea of what we've got." But when she digs into the databases she starts to see that not everything is as clear as she might've hoped it would be. Property names or column names have ambiguous names like Attribute one and Attribute two, or maybe Date one and Date two, so Amanda is starting to struggle even though she's got tools to visualize and look at these databases, she's still knows she's got a long road ahead, and with 2000 databases in her large enterprise, yes it's going to be a long journey. But Amanda is smart, so she pulls out her trusty spreadsheet to track all of her findings, and what she doesn't know about she raises a ticket or maybe tries to track down in order to find what that data means, and she's tracking all this information, but clearly this doesn't scale that well for Amanda. So maybe the organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well 'cause there's still ambiguities in the data. With Io-Tahoe what we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that Attribute one looks very much like a US social security number, and Attribute two looks like a ICD 10 medical code. And we do this by using ontologies, and dictionaries, and algorithms to help identify the underlying data and then tag it. Key to doing this automation is really being able to normalize things across different databases so that where there's differences in column names, I know that in fact they contain the same data. And by going through this exercise with Io-Tahoe, not only can we identify the data, but we also can gain insights about the data. So for example, we can see that 97% of that time, that column named Attribute one that's got US social security numbers, has something that looks like a social security number. But 3% of the time it doesn't quite look right, maybe there's a dash missing, maybe there's a digit dropped, or maybe there's even characters embedded in it, that may be indicative of a data quality issues, so we try to find those kinds of things. Going a step further, we also try to identify data quality relationships. So for example we have two columns, one date one date two, through observation we can see the date one 99% of the time is less than date two, 1% of the time it's not, probably indicative of the data quality issue, but going a step further we can also build a business rule that says date one is actually than date two, and so then when it pops up again we can quickly identify and remediate that problem. So these are the kinds of things that we can do with Io-Tahoe. Going even a step further, we can take your favorite data science solution, productionize it, and incorporate it into our next version as what we call a worker process to do your own bespoke analytics. >> Bespoke analytics, excellent, Lester thank you. So Ajay, talk us through some examples of where you're putting this to use, and also what is some of the feedback from some customers. >> Yeah, what I'm thinking how do you bring into life a little bit Lisa lets just talk through a case study. We put something together, I know it's available for download, but in a well-known telecommunications media company, they have a lot of the issues that lasted just spoke about lots of teams of Amanda's, super bright data practitioners, and are maybe looking to get more productivity out of their day, and deliver a good result for their own customers, for cell phone subscribers and broadband users. So, there are so many examples that we can see here is how we went about auto generating a lot of that old understanding of that data within hours. So, Amanda had her data catalog populated automatically, a business glossary built up, and maybe I would start to say, "Okay, where do I want to apply some policies to the data to set in place some controls, whether I want to adapt how different lines of business maybe tasks versus customer operations have different access or permissions to that data." And what we've been able to do that is to build up that picture to see how does data move across the entire organization, across the state, and monitor that over time for improvement. So we've taken it from being like reactive, let's do something to fix something to now more proactive. We can see what's happening with our data, who's using it, who's accessing it, how it's being used, how it's being combined, and from there taking a proactive approach is a real smart use of the tanons in that telco organization and the folks that work there with data. >> Okay Ajay, so digging into that a little bit deeper, and one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is ROI. How do customers measure ROI, What are they seeing with Io-Tahoe solution? >> Yeah, right now the big ticket item is time to value. And I think in data a lot of the upfront investment costs are quite expensive, they happen today with a lot of the larger vendors and technologies. Well, a CIO, an economic buyer really needs to be certain about this, how quickly can I get that ROI? And I think we've got something that we can show just pull up a before and after, and it really comes down to hours, days, and weeks where we've been able to have that impact. And in this playbook that we put together the before and after picture really shows those savings that committed a bit through providing data into some actionable form within hours and days to drive agility. But at the same time being able to enforce the controls to protect the use of that data and who has access to it, so atleast the number one thing I'd have to say is time, and we can see that on the graphic that we've just pulled up here. >> Excellent, so ostensible measurable outcomes that time to value. We talk about achieving adaptive data governance. Lester, you guys talk about automation, you talk about machine learning, how are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? >> Well, as we see the manual date, the days of manual effort are out, so I think this is a multi-step process, but the very first step is understanding what you have in normalizing that across your data estate. So, you couple this with the ontologies that are unique to your business and algorithms, and you basically go across it and you identify and tag that data, that allows for the next steps to happen. So now I can write business rules not in terms of named columns, but I can write them in terms of the tags. Using that automated pattern recognition where we observed the loan starts should be before the loan (indistinct), being able to automate that is a huge time saver, and the fact that we can suggest that as a rule rather than waiting for a person to come along and say, "Oh wow, okay, I need this rule, I need this rule." These are steps that increase, or I should say decrease that time to value that Ajay talked about. And then lastly, a couple of machine learning, because even with great automation and being able to profile all your data and getting a good understanding, that brings you to a certain point, but there's still ambiguity in the data. So for example I might have two columns date one and date two, I may have even observed that date one should be less than date two, but I don't really know what date one and date two are other than a date. So, this is where it comes in and I'm like, "As the user said, can you help me identify what date one and day two are in this table?" It turns out they're a start date and an end date for a loan, that gets remembered, cycled into machine learning step by step to see this pattern of date one date two. Elsewhere I'm going to say, "Is it start date and end date?" Bringing all these things together with all this automation is really what's key to enable this data database, your data governance program. >> Great, thanks Lester. And Ajay I do want to wrap things up with something that you mentioned in the beginning about what you guys are doing with Oracle, take us out by telling us what you're doing there, how are you guys working together? >> Yeah, I think those of us who worked in IT for many years we've learned to trust Oracle's technology that they're shifting now to a hybrid on-prem cloud generation 2 platform which is exciting, and their existing customers and new customers moving to Oracle are on a journey. So Oracle came to us and said, "Now, we can see how quickly you're able to help us change mindsets," and as mindsets are locked in a way of thinking around operating models of IT that are maybe not agile or more siloed, and they're wanting to break free of that and adopt a more agile API driven approach with their data. So, a lot of the work that we're doing with Oracle is around accelerating what customers can do with understanding their data and to build digital apps by identifying the underlying data that has value. And the time we're able to do that in hours, days, and weeks, rather than many months is opening up the eyes to chief data officers, CIO is to say, "Well, maybe we can do this whole digital transformation this year, maybe we can bring that forward and transform who we are as a company." And that's driving innovation which we're excited about, and I know Oracle keen to drive through. >> And helping businesses transform digitally is so incredibly important in this time as we look to things changing in 2021. Ajay and Lester thank you so much for joining me on this segment, explaining adaptive data governance, how organizations can use it, benefit from it, and achieve ROI, thanks so much guys. >> Thanks you. >> Thanks again Lisa. (bright music)

>>from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>And we're back with the data automation. Siri's. In this episode, we're gonna learn more about what I owe Tahoe is doing in the field of adaptive data governance how it can help achieve business outcomes and mitigate data security risks. I'm Lisa Martin, and I'm joined by a J. Bihar on the CEO of Iot Tahoe and Lester Waters, the CEO of Bio Tahoe. Gentlemen, it's great to have you on the program. >>Thank you. Lisa is good to be back. >>Great. Staley's >>likewise very socially distant. Of course as we are. Listen, we're gonna start with you. What's going on? And I am Tahoe. What's name? Well, >>I've been with Iot Tahoe for a little over the year, and one thing I've learned is every customer needs air just a bit different. So we've been working on our next major release of the I O. Tahoe product. But to really try to address these customer concerns because, you know, we wanna we wanna be flexible enough in order to come in and not just profile the date and not just understand data quality and lineage, but also to address the unique needs of each and every customer that we have. And so that required a platform rewrite of our product so that we could, uh, extend the product without building a new version of the product. We wanted to be able to have plausible modules. We also focused a lot on performance. That's very important with the bulk of data that we deal with that we're able to pass through that data in a single pass and do the analytics that are needed, whether it's, uh, lineage, data quality or just identifying the underlying data. And we're incorporating all that we've learned. We're tuning up our machine learning we're analyzing on MAWR dimensions than we've ever done before. We're able to do data quality without doing a Nen initial rejects for, for example, just out of the box. So I think it's all of these things were coming together to form our next version of our product. We're really excited by it, >>So it's exciting a J from the CEO's level. What's going on? >>Wow, I think just building on that. But let's still just mentioned there. It's were growing pretty quickly with our partners. And today, here with Oracle are excited. Thio explain how that shaping up lots of collaboration already with Oracle in government, in insurance, on in banking and we're excited because we get to have an impact. It's real satisfying to see how we're able. Thio. Help businesses transform, Redefine what's possible with their data on bond. Having I recall there is a partner, uh, to lean in with is definitely helping. >>Excellent. We're gonna dig into that a little bit later. Let's let's go back over to you. Explain adaptive data governance. Help us understand that >>really adaptive data governance is about achieving business outcomes through automation. It's really also about establishing a data driven culture and pushing what's traditionally managed in I t out to the business. And to do that, you've got to you've got Thio. You've got to enable an environment where people can actually access and look at the information about the data, not necessarily access the underlying data because we've got privacy concerns itself. But they need to understand what kind of data they have, what shape it's in what's dependent on it upstream and downstream, and so that they could make their educated decisions on on what they need to do to achieve those business outcomes. >>Ah, >>lot of a lot of frameworks these days are hardwired, so you can set up a set of business rules, and that set of business rules works for a very specific database and a specific schema. But imagine a world where you could just >>say, you >>know, the start date of alone must always be before the end date of alone and having that generic rule, regardless of the underlying database and applying it even when a new database comes online and having those rules applied. That's what adaptive data governance about I like to think of. It is the intersection of three circles, Really. It's the technical metadata coming together with policies and rules and coming together with the business ontology ease that are that are unique to that particular business. And this all of this. Bringing this all together allows you to enable rapid change in your environment. So it's a mouthful, adaptive data governance. But that's what it kind of comes down to. >>So, Angie, help me understand this. Is this book enterprise companies are doing now? Are they not quite there yet. >>Well, you know, Lisa, I think every organization is is going at its pace. But, you know, markets are changing the economy and the speed at which, um, some of the changes in the economy happening is is compelling more businesses to look at being more digital in how they serve their own customers. Eh? So what we're seeing is a number of trends here from heads of data Chief Data Officers, CEO, stepping back from, ah, one size fits all approach because they've tried that before, and it it just hasn't worked. They've spent millions of dollars on I T programs China Dr Value from that data on Bennett. And they've ended up with large teams of manual processing around data to try and hardwire these policies to fit with the context and each line of business and on that hasn't worked. So the trends that we're seeing emerge really relate. Thio, How do I There's a chief data officer as a CEO. Inject more automation into a lot of these common tax. Andi, you know, we've been able toc that impact. I think the news here is you know, if you're trying to create a knowledge graph a data catalog or Ah, business glossary. And you're trying to do that manually will stop you. You don't have to do that manually anymore. I think best example I can give is Lester and I We we like Chinese food and Japanese food on. If you were sitting there with your chopsticks, you wouldn't eat the bowl of rice with the chopsticks, one grain at a time. What you'd want to do is to find a more productive way to to enjoy that meal before it gets cold. Andi, that's similar to how we're able to help the organizations to digest their data is to get through it faster, enjoy the benefits of putting that data to work. >>And if it was me eating that food with you guys, I would be not using chopsticks. I would be using a fork and probably a spoon. So eso Lester, how then does iota who go about doing this and enabling customers to achieve this? >>Let me, uh, let me show you a little story have here. So if you take a look at the challenges the most customers have, they're very similar, but every customers on a different data journey, so but it all starts with what data do I have? What questions or what shape is that data in? Uh, how is it structured? What's dependent on it? Upstream and downstream. Um, what insights can I derive from that data? And how can I answer all of those questions automatically? So if you look at the challenges for these data professionals, you know, they're either on a journey to the cloud. Maybe they're doing a migration oracle. Maybe they're doing some data governance changes on bits about enabling this. So if you look at these challenges and I'm gonna take you through a >>story here, E, >>I want to introduce Amanda. Man does not live like, uh, anyone in any large organization. She's looking around and she just sees stacks of data. I mean, different databases, the one she knows about, the one she doesn't know about what should know about various different kinds of databases. And a man is just tasking with understanding all of this so that they can embark on her data journey program. So So a man who goes through and she's great. I've got some handy tools. I can start looking at these databases and getting an idea of what we've got. Well, as she digs into the databases, she starts to see that not everything is as clear as she might have hoped it would be. You know, property names or column names, or have ambiguous names like Attribute one and attribute to or maybe date one and date to s Oh, man is starting to struggle, even though she's get tools to visualize. And look what look at these databases. She still No, she's got a long road ahead. And with 2000 databases in her large enterprise, yes, it's gonna be a long turkey but Amanda Smart. So she pulls out her trusty spreadsheet to track all of her findings on what she doesn't know about. She raises a ticket or maybe tries to track down the owner to find what the data means. And she's tracking all this information. Clearly, this doesn't scale that well for Amanda, you know? So maybe organization will get 10 Amanda's to sort of divide and conquer that work. But even that doesn't work that well because they're still ambiguities in the data with Iota ho. What we do is we actually profile the underlying data. By looking at the underlying data, we can quickly see that attribute. One looks very much like a U. S. Social Security number and attribute to looks like a I c D 10 medical code. And we do this by using anthologies and dictionaries and algorithms to help identify the underlying data and then tag it. Key Thio Doing, uh, this automation is really being able to normalize things across different databases, so that where there's differences in column names, I know that in fact, they contain contain the same data. And by going through this exercise with a Tahoe, not only can we identify the data, but we also could gain insights about the data. So, for example, we can see that 97% of that time that column named Attribute one that's got us Social Security numbers has something that looks like a Social Security number. But 3% of the time, it doesn't quite look right. Maybe there's a dash missing. Maybe there's a digit dropped. Or maybe there's even characters embedded in it. So there may be that may be indicative of a data quality issues, so we try to find those kind of things going a step further. We also try to identify data quality relationships. So, for example, we have two columns, one date, one date to through Ah, observation. We can see that date 1 99% of the time is less than date, too. 1% of the time. It's not probably indicative of a data quality issue, but going a step further, we can also build a business rule that says Day one is less than date to. And so then when it pops up again, we can quickly identify and re mediate that problem. So these are the kinds of things that we could do with with iota going even a step further. You could take your your favorite data science solution production ISAT and incorporated into our next version a zey what we call a worker process to do your own bespoke analytics. >>We spoke analytics. Excellent, Lester. Thank you. So a J talk us through some examples of where you're putting this to use. And also what is some of the feedback from >>some customers? But I think it helped do this Bring it to life a little bit. Lisa is just to talk through a case study way. Pull something together. I know it's available for download, but in ah, well known telecommunications media company, they had a lot of the issues that lasted. You spoke about lots of teams of Amanda's, um, super bright data practitioners, um, on baby looking to to get more productivity out of their day on, deliver a good result for their own customers for cell phone subscribers, Um, on broadband users. So you know that some of the examples that we can see here is how we went about auto generating a lot of that understanding off that data within hours. So Amanda had her data catalog populated automatically. A business class three built up on it. Really? Then start to see. Okay, where do I want Thio? Apply some policies to the data to to set in place some controls where they want to adapt, how different lines of business, maybe tax versus customer operations have different access or permissions to that data on What we've been able to do there is, is to build up that picture to see how does data move across the entire organization across the state. Andi on monitor that overtime for improvement, so have taken it from being a reactive. Let's do something Thio. Fix something. Thio, Now more proactive. We can see what's happening with our data. Who's using it? Who's accessing it, how it's being used, how it's being combined. Um, on from there. Taking a proactive approach is a real smart use of of the talents in in that telco organization Onda folks that worked there with data. >>Okay, Jason, dig into that a little bit deeper. And one of the things I was thinking when you were talking through some of those outcomes that you're helping customers achieve is our ally. How do customers measure are? Why? What are they seeing with iota host >>solution? Yeah, right now that the big ticket item is time to value on. And I think in data, a lot of the upfront investment cause quite expensive. They have been today with a lot of the larger vendors and technologies. So what a CEO and economic bio really needs to be certain of is how quickly can I get that are away. I think we've got something we can show. Just pull up a before and after, and it really comes down to hours, days and weeks. Um, where we've been able Thio have that impact on in this playbook that we pulled together before and after picture really shows. You know, those savings that committed a bit through providing data into some actionable form within hours and days to to drive agility, but at the same time being out and forced the controls to protect the use of that data who has access to it. So these are the number one thing I'd have to say. It's time on. We can see that on the the graphic that we've just pulled up here. >>We talk about achieving adaptive data governance. Lester, you guys talk about automation. You talk about machine learning. How are you seeing those technologies being a facilitator of organizations adopting adaptive data governance? Well, >>Azaz, we see Mitt Emmanuel day. The days of manual effort are so I think you know this >>is a >>multi step process. But the very first step is understanding what you have in normalizing that across your data estate. So you couple this with the ontology, that air unique to your business. There is no algorithms, and you basically go across and you identify and tag tag that data that allows for the next steps toe happen. So now I can write business rules not in terms of columns named columns, but I could write him in terms of the tags being able to automate. That is a huge time saver and the fact that we can suggest that as a rule, rather than waiting for a person to come along and say, Oh, wow. Okay, I need this rule. I need this will thes air steps that increased that are, I should say, decrease that time to value that A. J talked about and then, lastly, a couple of machine learning because even with even with great automation and being able to profile all of your data and getting a good understanding, that brings you to a certain point. But there's still ambiguities in the data. So, for example, I might have to columns date one and date to. I may have even observed the date. One should be less than day two, but I don't really know what date one and date to our other than a date. So this is where it comes in, and I might ask the user said, >>Can >>you help me identify what date? One and date You are in this in this table. Turns out they're a start date and an end date for alone That gets remembered, cycled into the machine learning. So if I start to see this pattern of date one day to elsewhere, I'm going to say, Is it start dating and date? And these Bringing all these things together with this all this automation is really what's key to enabling this This'll data governance. Yeah, >>great. Thanks. Lester and a j wanna wrap things up with something that you mentioned in the beginning about what you guys were doing with Oracle. Take us out by telling us what you're doing there. How are you guys working together? >>Yeah, I think those of us who worked in i t for many years we've We've learned Thio trust articles technology that they're shifting now to ah, hybrid on Prohm Cloud Generation to platform, which is exciting. Andi on their existing customers and new customers moving to article on a journey. So? So Oracle came to us and said, you know, we can see how quickly you're able to help us change mindsets Ondas mindsets are locked in a way of thinking around operating models of I t. That there may be no agile and what siloed on day wanting to break free of that and adopt a more agile A p I at driven approach. A lot of the work that we're doing with our recall no is around, uh, accelerating what customers conduce with understanding their data and to build digital APS by identifying the the underlying data that has value. Onda at the time were able to do that in in in hours, days and weeks. Rather many months. Is opening up the eyes to Chief Data Officers CEO to say, Well, maybe we can do this whole digital transformation this year. Maybe we can bring that forward and and transform who we are as a company on that's driving innovation, which we're excited about it. I know Oracle, a keen Thio to drive through and >>helping businesses transformed digitally is so incredibly important in this time as we look Thio things changing in 2021 a. J. Lester thank you so much for joining me on this segment explaining adaptive data governance, how organizations can use it benefit from it and achieve our Oi. Thanks so much, guys. >>Thank you. Thanks again, Lisa. >>In a moment, we'll look a adaptive data governance in banking. This is the Cube, your global leader in high tech coverage. >>Innovation, impact influence. Welcome to the Cube. Disruptors. Developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on the Cube, your global leader in high tech digital coverage. >>Our next segment here is an interesting panel you're gonna hear from three gentlemen about adaptive data. Governments want to talk a lot about that. Please welcome Yusuf Khan, the global director of data services for Iot Tahoe. We also have Santiago Castor, the chief data officer at the First Bank of Nigeria, and good John Vander Wal, Oracle's senior manager of digital transformation and industries. Gentlemen, it's great to have you joining us in this in this panel. Great >>to be >>tried for me. >>Alright, Santiago, we're going to start with you. Can you talk to the audience a little bit about the first Bank of Nigeria and its scale? This is beyond Nigeria. Talk to us about that. >>Yes, eso First Bank of Nigeria was created 125 years ago. One of the oldest ignored the old in Africa because of the history he grew everywhere in the region on beyond the region. I am calling based in London, where it's kind of the headquarters and it really promotes trade, finance, institutional banking, corporate banking, private banking around the world in particular, in relationship to Africa. We are also in Asia in in the Middle East. >>So, Sanjay, go talk to me about what adaptive data governance means to you. And how does it help the first Bank of Nigeria to be able to innovate faster with the data that you have? >>Yes, I like that concept off adaptive data governor, because it's kind of Ah, I would say an approach that can really happen today with the new technologies before it was much more difficult to implement. So just to give you a little bit of context, I I used to work in consulting for 16, 17 years before joining the president of Nigeria, and I saw many organizations trying to apply different type of approaches in the governance on by the beginning early days was really kind of a year. A Chicago A. A top down approach where data governance was seeing as implement a set of rules, policies and procedures. But really, from the top down on is important. It's important to have the battle off your sea level of your of your director. Whatever I saw, just the way it fails, you really need to have a complimentary approach. You can say bottom are actually as a CEO are really trying to decentralize the governor's. Really, Instead of imposing a framework that some people in the business don't understand or don't care about it, it really needs to come from them. So what I'm trying to say is that data basically support business objectives on what you need to do is every business area needs information on the detector decisions toe actually be able to be more efficient or create value etcetera. Now, depending on the business questions they have to solve, they will need certain data set. So they need actually to be ableto have data quality for their own. For us now, when they understand that they become the stores naturally on their own data sets. And that is where my bottom line is meeting my top down. You can guide them from the top, but they need themselves to be also empower and be actually, in a way flexible to adapt the different questions that they have in orderto be able to respond to the business needs. Now I cannot impose at the finish for everyone. I need them to adapt and to bring their answers toe their own business questions. That is adaptive data governor and all That is possible because we have. And I was saying at the very beginning just to finalize the point, we have new technologies that allow you to do this method data classifications, uh, in a very sophisticated way that you can actually create analitico of your metadata. You can understand your different data sources in order to be able to create those classifications like nationalities, a way of classifying your customers, your products, etcetera. >>So one of the things that you just said Santa kind of struck me to enable the users to be adaptive. They probably don't want to be logging in support ticket. So how do you support that sort of self service to meet the demand of the users so that they can be adaptive. >>More and more business users wants autonomy, and they want to basically be ableto grab the data and answer their own question. Now when you have, that is great, because then you have demand of businesses asking for data. They're asking for the insight. Eso How do you actually support that? I would say there is a changing culture that is happening more and more. I would say even the current pandemic has helped a lot into that because you have had, in a way, off course, technology is one of the biggest winners without technology. We couldn't have been working remotely without these technologies where people can actually looking from their homes and still have a market data marketplaces where they self serve their their information. But even beyond that data is a big winner. Data because the pandemic has shown us that crisis happened, that we cannot predict everything and that we are actually facing a new kind of situation out of our comfort zone, where we need to explore that we need to adapt and we need to be flexible. How do we do that with data. Every single company either saw the revenue going down or the revenue going very up For those companies that are very digital already. Now it changed the reality, so they needed to adapt. But for that they needed information. In order to think on innovate, try toe, create responses So that type of, uh, self service off data Haider for data in order to be able to understand what's happening when the prospect is changing is something that is becoming more, uh, the topic today because off the condemning because of the new abilities, the technologies that allow that and then you then are allowed to basically help your data. Citizens that call them in the organization people that no other business and can actually start playing and an answer their own questions. Eso so these technologies that gives more accessibility to the data that is some cataloging so they can understand where to go or what to find lineage and relationships. All this is is basically the new type of platforms and tools that allow you to create what are called a data marketplace. I think these new tools are really strong because they are now allowing for people that are not technology or I t people to be able to play with data because it comes in the digital world There. Used to a given example without your who You have a very interesting search functionality. Where if you want to find your data you want to sell, Sir, you go there in that search and you actually go on book for your data. Everybody knows how to search in Google, everybody's searching Internet. So this is part of the data culture, the digital culture. They know how to use those schools. Now, similarly, that data marketplace is, uh, in you can, for example, see which data sources they're mostly used >>and enabling that speed that we're all demanding today during these unprecedented times. Goodwin, I wanted to go to you as we talk about in the spirit of evolution, technology is changing. Talk to us a little bit about Oracle Digital. What are you guys doing there? >>Yeah, Thank you. Um, well, Oracle Digital is a business unit that Oracle EMEA on. We focus on emerging countries as well as low and enterprises in the mid market, in more developed countries and four years ago. This started with the idea to engage digital with our customers. Fear Central helps across EMEA. That means engaging with video, having conference calls, having a wall, a green wall where we stand in front and engage with our customers. No one at that time could have foreseen how this is the situation today, and this helps us to engage with our customers in the way we were already doing and then about my team. The focus of my team is to have early stage conversations with our with our customers on digital transformation and innovation. And we also have a team off industry experts who engaged with our customers and share expertise across EMEA, and we inspire our customers. The outcome of these conversations for Oracle is a deep understanding of our customer needs, which is very important so we can help the customer and for the customer means that we will help them with our technology and our resource is to achieve their goals. >>It's all about outcomes, right? Good Ron. So in terms of automation, what are some of the things Oracle's doing there to help your clients leverage automation to improve agility? So that they can innovate faster, which in these interesting times it's demanded. >>Yeah, thank you. Well, traditionally, Oracle is known for their databases, which have bean innovated year over year. So here's the first lunch on the latest innovation is the autonomous database and autonomous data warehouse. For our customers, this means a reduction in operational costs by 90% with a multi medal converts, database and machine learning based automation for full life cycle management. Our databases self driving. This means we automate database provisioning, tuning and scaling. The database is self securing. This means ultimate data protection and security, and it's self repairing the automates failure, detection fail over and repair. And then the question is for our customers, What does it mean? It means they can focus on their on their business instead off maintaining their infrastructure and their operations. >>That's absolutely critical use if I want to go over to you now. Some of the things that we've talked about, just the massive progression and technology, the evolution of that. But we know that whether we're talking about beta management or digital transformation, a one size fits all approach doesn't work to address the challenges that the business has, um that the i t folks have, as you're looking through the industry with what Santiago told us about first Bank of Nigeria. What are some of the changes that you're seeing that I owe Tahoe seeing throughout the industry? >>Uh, well, Lisa, I think the first way I'd characterize it is to say, the traditional kind of top down approach to data where you have almost a data Policeman who tells you what you can and can't do, just doesn't work anymore. It's too slow. It's too resource intensive. Uh, data management data, governments, digital transformation itself. It has to be collaborative on. There has to be in a personalization to data users. Um, in the environment we find ourselves in. Now, it has to be about enabling self service as well. Um, a one size fits all model when it comes to those things around. Data doesn't work. As Santiago was saying, it needs to be adapted toe how the data is used. Andi, who is using it on in order to do this cos enterprises organizations really need to know their data. They need to understand what data they hold, where it is on what the sensitivity of it is they can then any more agile way apply appropriate controls on access so that people themselves are and groups within businesses are our job and could innovate. Otherwise, everything grinds to a halt, and you risk falling behind your competitors. >>Yeah, that one size fits all term just doesn't apply when you're talking about adaptive and agility. So we heard from Santiago about some of the impact that they're making with First Bank of Nigeria. Used to talk to us about some of the business outcomes that you're seeing other customers make leveraging automation that they could not do >>before it's it's automatically being able to classify terabytes, terabytes of data or even petabytes of data across different sources to find duplicates, which you can then re mediate on. Deletes now, with the capabilities that iota offers on the Oracle offers, you can do things not just where the five times or 10 times improvement, but it actually enables you to do projects for Stop that otherwise would fail or you would just not be able to dio I mean, uh, classifying multi terrible and multi petabytes states across different sources, formats very large volumes of data in many scenarios. You just can't do that manually. I mean, we've worked with government departments on the issues there is expect are the result of fragmented data. There's a lot of different sources. There's lot of different formats and without these newer technologies to address it with automation on machine learning, the project isn't durable. But now it is on that that could lead to a revolution in some of these businesses organizations >>to enable that revolution that there's got to be the right cultural mindset. And one of the when Santiago was talking about folks really kind of adapted that. The thing I always call that getting comfortably uncomfortable. But that's hard for organizations to. The technology is here to enable that. But well, you're talking with customers use. How do you help them build the trust in the confidence that the new technologies and a new approaches can deliver what they need? How do you help drive the kind of a tech in the culture? >>It's really good question is because it can be quite scary. I think the first thing we'd start with is to say, Look, the technology is here with businesses like I Tahoe. Unlike Oracle, it's already arrived. What you need to be comfortable doing is experimenting being agile around it, Andi trying new ways of doing things. Uh, if you don't wanna get less behind that Santiago on the team that fbn are a great example off embracing it, testing it on a small scale on, then scaling up a Toyota, we offer what we call a data health check, which can actually be done very quickly in a matter of a few weeks. So we'll work with a customer. Picky use case, install the application, uh, analyzed data. Drive out Cem Cem quick winds. So we worked in the last few weeks of a large entity energy supplier, and in about 20 days, we were able to give them an accurate understanding of their critical data. Elements apply. Helping apply data protection policies. Minimize copies of the data on work out what data they needed to delete to reduce their infrastructure. Spend eso. It's about experimenting on that small scale, being agile on, then scaling up in a kind of very modern way. >>Great advice. Uh, Santiago, I'd like to go back to Is we kind of look at again that that topic of culture and the need to get that mindset there to facilitate these rapid changes, I want to understand kind of last question for you about how you're doing that from a digital transformation perspective. We know everything is accelerating in 2020. So how are you building resilience into your data architecture and also driving that cultural change that can help everyone in this shift to remote working and a lot of the the digital challenges and changes that we're all going through? >>The new technologies allowed us to discover the dating anyway. Toe flawed and see very quickly Information toe. Have new models off over in the data on giving autonomy to our different data units. Now, from that autonomy, they can then compose an innovator own ways. So for me now, we're talking about resilience because in a way, autonomy and flexibility in a organization in a data structure with platform gives you resilience. The organizations and the business units that I have experienced in the pandemic are working well. Are those that actually because they're not physically present during more in the office, you need to give them their autonomy and let them actually engaged on their own side that do their own job and trust them in a way on as you give them, that they start innovating and they start having a really interesting ideas. So autonomy and flexibility. I think this is a key component off the new infrastructure. But even the new reality that on then it show us that, yes, we used to be very kind off structure, policies, procedures as very important. But now we learn flexibility and adaptability of the same side. Now, when you have that a key, other components of resiliency speed, because people want, you know, to access the data and access it fast and on the site fast, especially changes are changing so quickly nowadays that you need to be ableto do you know, interact. Reiterate with your information to answer your questions. Pretty, um, so technology that allows you toe be flexible iterating on in a very fast job way continue will allow you toe actually be resilient in that way, because you are flexible, you adapt your job and you continue answering questions as they come without having everything, setting a structure that is too hard. We also are a partner off Oracle and Oracle. Embodies is great. They have embedded within the transactional system many algorithms that are allowing us to calculate as the transactions happened. What happened there is that when our customers engaged with algorithms and again without your powers, well, the machine learning that is there for for speeding the automation of how you find your data allows you to create a new alliance with the machine. The machine is their toe, actually, in a way to your best friend to actually have more volume of data calculated faster. In a way, it's cover more variety. I mean, we couldn't hope without being connected to this algorithm on >>that engagement is absolutely critical. Santiago. Thank you for sharing that. I do wanna rap really quickly. Good On one last question for you, Santiago talked about Oracle. You've talked about a little bit. As we look at digital resilience, talk to us a little bit in the last minute about the evolution of Oracle. What you guys were doing there to help your customers get the resilience that they have toe have to be not just survive but thrive. >>Yeah. Oracle has a cloud offering for infrastructure, database, platform service and a complete solutions offered a South on Daz. As Santiago also mentioned, We are using AI across our entire portfolio and by this will help our customers to focus on their business innovation and capitalize on data by enabling new business models. Um, and Oracle has a global conference with our cloud regions. It's massively investing and innovating and expanding their clouds. And by offering clouds as public cloud in our data centers and also as private cloud with clouded customer, we can meet every sovereignty and security requirements. And in this way we help people to see data in new ways. We discover insights and unlock endless possibilities. And and maybe 11 of my takeaways is if I If I speak with customers, I always tell them you better start collecting your data. Now we enable this partners like Iota help us as well. If you collect your data now, you are ready for tomorrow. You can never collect your data backwards, So that is my take away for today. >>You can't collect your data backwards. Excellently, John. Gentlemen, thank you for sharing all of your insights. Very informative conversation in a moment, we'll address the question. Do you know your data? >>Are you interested in test driving the iota Ho platform kick Start the benefits of data automation for your business through the Iota Ho Data Health check program. Ah, flexible, scalable sandbox environment on the cloud of your choice with set up service and support provided by Iota ho. Look time with a data engineer to learn more and see Io Tahoe in action from around the globe. It's the Cube presenting adaptive data governance brought to you by Iota Ho. >>In this next segment, we're gonna be talking to you about getting to know your data. And specifically you're gonna hear from two folks at Io Tahoe. We've got enterprise account execs to be to Davis here, as well as Enterprise Data engineer Patrick Simon. They're gonna be sharing insights and tips and tricks for how you could get to know your data and quickly on. We also want to encourage you to engage with the media and Patrick, use the chat feature to the right, send comments, questions or feedback so you can participate. All right, Patrick Savita, take it away. Alright. >>Thankfully saw great to be here as Lisa mentioned guys, I'm the enterprise account executive here in Ohio. Tahoe you Pat? >>Yeah. Hey, everyone so great to be here. I said my name is Patrick Samit. I'm the enterprise data engineer here in Ohio Tahoe. And we're so excited to be here and talk about this topic as one thing we're really trying to perpetuate is that data is everyone's business. >>So, guys, what patent I got? I've actually had multiple discussions with clients from different organizations with different roles. So we spoke with both your technical and your non technical audience. So while they were interested in different aspects of our platform, we found that what they had in common was they wanted to make data easy to understand and usable. So that comes back. The pats point off to being everybody's business because no matter your role, we're all dependent on data. So what Pan I wanted to do today was wanted to walk you guys through some of those client questions, slash pain points that we're hearing from different industries and different rules and demo how our platform here, like Tahoe, is used for automating Dozier related tasks. So with that said are you ready for the first one, Pat? >>Yeah, Let's do it. >>Great. So I'm gonna put my technical hat on for this one. So I'm a data practitioner. I just started my job. ABC Bank. I have, like, over 100 different data sources. So I have data kept in Data Lakes, legacy data, sources, even the cloud. So my issue is I don't know what those data sources hold. I don't know what data sensitive, and I don't even understand how that data is connected. So how can I saw who help? >>Yeah, I think that's a very common experience many are facing and definitely something I've encountered in my past. Typically, the first step is to catalog the data and then start mapping the relationships between your various data stores. Now, more often than not, this has tackled through numerous meetings and a combination of excel and something similar to video which are too great tools in their own part. But they're very difficult to maintain. Just due to the rate that we are creating data in the modern world. It starts to beg for an idea that can scale with your business needs. And this is where a platform like Io Tahoe becomes so appealing, you can see here visualization of the data relationships created by the I. O. Tahoe service. Now, what is fantastic about this is it's not only laid out in a very human and digestible format in the same action of creating this view, the data catalog was constructed. >>Um so is the data catalog automatically populated? Correct. Okay, so So what I'm using Iota hope at what I'm getting is this complete, unified automated platform without the added cost? Of course. >>Exactly. And that's at the heart of Iota Ho. A great feature with that data catalog is that Iota Ho will also profile your data as it creates the catalog, assigning some meaning to those pesky column underscore ones and custom variable underscore tents. They're always such a joy to deal with. Now, by leveraging this interface, we can start to answer the first part of your question and understand where the core relationships within our data exists. Uh, personally, I'm a big fan of this view, as it really just helps the i b naturally John to these focal points that coincide with these key columns following that train of thought, Let's examine the customer I D column that seems to be at the center of a lot of these relationships. We can see that it's a fairly important column as it's maintaining the relationship between at least three other tables. >>Now you >>notice all the connectors are in this blue color. This means that their system defined relationships. But I hope Tahoe goes that extra mile and actually creates thes orange colored connectors as well. These air ones that are machine learning algorithms have predicted to be relationships on. You can leverage to try and make new and powerful relationships within your data. >>Eso So this is really cool, and I can see how this could be leverage quickly now. What if I added new data sources or your multiple data sources and need toe identify what data sensitive can iota who detect that? >>Yeah, definitely. Within the hotel platform. There, already over 300 pre defined policies such as hip for C, C, P. A and the like one can choose which of these policies to run against their data along for flexibility and efficiency and running the policies that affect organization. >>Okay, so so 300 is an exceptional number. I'll give you that. But what about internal policies that apply to my organization? Is there any ability for me to write custom policies? >>Yeah, that's no issue. And it's something that clients leverage fairly often to utilize this function when simply has to write a rejects that our team has helped many deploy. After that, the custom policy is stored for future use to profile sensitive data. One then selects the data sources they're interested in and select the policies that meet your particular needs. The interface will automatically take your data according to the policies of detects, after which you can review the discoveries confirming or rejecting the tagging. All of these insights are easily exported through the interface. Someone can work these into the action items within your project management systems, and I think this lends to the collaboration as a team can work through the discovery simultaneously, and as each item is confirmed or rejected, they can see it ni instantaneously. All this translates to a confidence that with iota hope, you can be sure you're in compliance. >>So I'm glad you mentioned compliance because that's extremely important to my organization. So what you're saying when I use the eye a Tahoe automated platform, we'd be 90% more compliant that before were other than if you were going to be using a human. >>Yeah, definitely the collaboration and documentation that the Iot Tahoe interface lends itself to really help you build that confidence that your compliance is sound. >>So we're planning a migration. Andi, I have a set of reports I need to migrate. But what I need to know is, uh well, what what data sources? Those report those reports are dependent on. And what's feeding those tables? >>Yeah, it's a fantastic questions to be toe identifying critical data elements, and the interdependencies within the various databases could be a time consuming but vital process and the migration initiative. Luckily, Iota Ho does have an answer, and again, it's presented in a very visual format. >>Eso So what I'm looking at here is my entire day landscape. >>Yes, exactly. >>Let's say I add another data source. I can still see that unified 3 60 view. >>Yeah, One future that is particularly helpful is the ability to add data sources after the data lineage. Discovery has finished alone for the flexibility and scope necessary for any data migration project. If you only need need to select a few databases or your entirety, this service will provide the answers. You're looking for things. Visual representation of the connectivity makes the identification of critical data elements a simple matter. The connections air driven by both system defined flows as well as those predicted by our algorithms, the confidence of which, uh, can actually be customized to make sure that they're meeting the needs of the initiative that you have in place. This also provides tabular output in case you needed for your own internal documentation or for your action items, which we can see right here. Uh, in this interface, you can actually also confirm or deny the pair rejection the pair directions, allowing to make sure that the data is as accurate as possible. Does that help with your data lineage needs? >>Definitely. So So, Pat, My next big question here is So now I know a little bit about my data. How do I know I can trust >>it? So >>what I'm interested in knowing, really is is it in a fit state for me to use it? Is it accurate? Does it conform to the right format? >>Yeah, that's a great question. And I think that is a pain point felt across the board, be it by data practitioners or data consumers alike. Another service that I owe Tahoe provides is the ability to write custom data quality rules and understand how well the data pertains to these rules. This dashboard gives a unified view of the strength of these rules, and your dad is overall quality. >>Okay, so Pat s o on on the accuracy scores there. So if my marketing team needs to run, a campaign can read dependent those accuracy scores to know what what tables have quality data to use for our marketing campaign. >>Yeah, this view would allow you to understand your overall accuracy as well as dive into the minutia to see which data elements are of the highest quality. So for that marketing campaign, if you need everything in a strong form, you'll be able to see very quickly with these high level numbers. But if you're only dependent on a few columns to get that information out the door, you can find that within this view, eso >>you >>no longer have to rely on reports about reports, but instead just come to this one platform to help drive conversations between stakeholders and data practitioners. >>So I get now the value of IATA who brings by automatically capturing all those technical metadata from sources. But how do we match that with the business glossary? >>Yeah, within the same data quality service that we just reviewed, one can actually add business rules detailing the definitions and the business domains that these fall into. What's more is that the data quality rules were just looking at can then be tied into these definitions. Allowing insight into the strength of these business rules is this service that empowers stakeholders across the business to be involved with the data life cycle and take ownership over the rules that fall within their domain. >>Okay, >>so those custom rules can I apply that across data sources? >>Yeah, you could bring in as many data sources as you need, so long as you could tie them to that unified definition. >>Okay, great. Thanks so much bad. And we just want to quickly say to everyone working in data, we understand your pain, so please feel free to reach out to us. we are Website the chapel. Oh, Arlington. And let's get a conversation started on how iota Who can help you guys automate all those manual task to help save you time and money. Thank you. Thank >>you. Your Honor, >>if I could ask you one quick question, how do you advise customers? You just walk in this great example this banking example that you instantly to talk through. How do you advise customers get started? >>Yeah, I think the number one thing that customers could do to get started with our platform is to just run the tag discovery and build up that data catalog. It lends itself very quickly to the other needs you might have, such as thes quality rules. A swell is identifying those kind of tricky columns that might exist in your data. Those custom variable underscore tens I mentioned before >>last questions to be to anything to add to what Pat just described as a starting place. >>I'm no, I think actually passed something that pretty well, I mean, just just by automating all those manual task. I mean, it definitely can save your company a lot of time and money, so we we encourage you just reach out to us. Let's get that conversation >>started. Excellent. So, Pete and Pat, thank you so much. We hope you have learned a lot from these folks about how to get to know your data. Make sure that it's quality, something you can maximize the value of it. Thanks >>for watching. Thanks again, Lisa, for that very insightful and useful deep dive into the world of adaptive data governance with Iota Ho Oracle First Bank of Nigeria This is Dave a lot You won't wanna mess Iota, whose fifth episode in the data automation Siri's in that we'll talk to experts from Red Hat and Happiest Minds about their best practices for managing data across hybrid cloud Inter Cloud multi Cloud I T environment So market calendar for Wednesday, January 27th That's Episode five. You're watching the Cube Global Leader digital event technique

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to you by Dell Technologies. Welcome back to the cubes. Continuing coverage of Dell Technology World del Tech, World 2020. Jeff Clark is here. He is the chief operating officer and vice chairman of Dell Technologies. Jeff, awesome to see you. Thanks for coming on. >>Thanks for having me today. Appreciate it. >>Yeah, you're very welcome. When my first question is, when do you have time to be vice chairman? Well, >>you know, in today's world, it's pretty hectic. We're all working around the clock. If there's anything about the new norm, there are no boundaries. And unless you establish some boundaries so I've been able to find a rhythm that works for me personally, but also allows me to look after the company and, uh, kind of keep things moving and making progress of Dell. So pretty exciting times. It's certainly been a challenge finding new ways to break through new ways to get things done. But our team has done a great job rising to the occasion. >>Well, you know, a Z. You know, I didn't know you that well prior to you taking over the whole enchilada and do it going back into the enterprise. I mean, I knew you were obviously, but you have been able to see you know, how you operate in the decision making on how you rally the troops. Your several years now into the new Dell, you had to do a lot of tactical things, you know, including product portfolio rationalizations. But I wanted to start with the macro picture in a particular Can you share some of the acceleration points and the levers that you're really pulling in the operation? >>Well, clearly, if you look back at the company's strategy and I'll start there and then kind of build on from that platform if you think about the first tenet of our strategy is to win in the consolidation in our court marketplaces. So the core commercial PC market, the course server market in the course storage market, and clearly what we've been able to do and certainly been at this now for Gosh, I think it's three years now that we've been turning over the portfolio and modernizing the portfolio on the I s g side and to the point you referenced earlier. We've now modernized that portfolio. It is now under all the power brand and now represents new, fresh modern architecture er modern products that allows us to be competitive going forward across the entire eyes. T portfolio. We've had continued success on the commercial PC side. Then if you think about the next tenant of our strategy, which is to really build deeply integrated solutions across the Dell Technologies portfolio, we've made a lot of progress in the last handful of years, particularly integrating this new competitiveness of our I S G portfolio with the M R. And we're now beginning to see the fruits of that labor PC side will quickly. You've seen that with unified workspace work workspace one are leading services and are leading PC products to be able to bring a different change experience for end users on the PC side on the side. This all started with getting again this competitive portfolio. It started with Dell Technology Cloud a little over a year ago. It now is in joint collaboration around the edge. You've heard from my comments during the keynote around five g going forward. So as we think about this new modern world playing out. We now have the infrastructure competitive. We have a great asset and capability with VM, are now have figured out how to tightly integrate those and innovate on top of those platforms. And we think that's sort of the success for the future as we move forward. >>So it sounds like I mean, covitz change so many things, but it doesn't sound like it's materially changed your thinking on these leverage points or your strategy is gonna pre cove in Post Cove. It you kind of sort of approaching the same playbook, if you will. >>Well, a covert in many levels. While it's had a huge impact on many lives around the world, which we shouldn't, that should not be lost on any of us and the impact that it's had across many businesses and many parts of the world. If you step back and what I try to mention the keynote, what cove it has done is really accelerate digital transformation. I've heard many characterizations, but the way I tend to look at it is if you think of what's happened around us and the forcing of working remote learning remote the world as we look at it going forward, data driven. It's accelerated 10 years of what I thought would take us to get done into the first half of this decade. In many cases the first three years, Uh, this nomenclature that I've talk about is the future is now, and what it's really done is actually reinforced. The points that we thought were going toe happen brought them sooner and has made us believe mawr double down, if you will, that the path we're on is the right path, and we see our customers migrating that way rapidly. In fact, what's interesting? If you look at customers who embrace digital transformation earlier, we call them digital leaders. They're actually breaking away from the pack, sort of speak from their peer set and driving differentiated performance in their sector. We think that's a great, obviously proof point of digital transformation. But what all companies will have to go through to compete >>Well, it's interesting we saw early on in the US locked down worldwide, locked down you have you have such a broad portfolio that yeah, maybe some parts of the portfolio or, you know, directly negatively affected. Certainly. For instance, your you know your airline customers or your hospitality customers, etcetera. But the work from home was was a tailwind for you guys. So the fact that you have that broad portfolio somewhat, you know, one part of the business that cushioned you, maybe the other part of the business, You felt that. But on balance, you're able to get through that, and part of that was your supply chain. And some of your competitors struggled, you know, for instance, with laptop supplies. But you guys really have done a good job, sort of navigating through that, almost like you've been through it before. But nobody's been through this before. >>No, you know, David, thanks for recognizing it. One of the benefits of the Indian portfolio we have, which no one else has. The Indian portfolio that we do. We're able to weather the storm of different impacts to whether it's sectors, whether it's different parts of the business. And we've been able to do that on our our supply chain has performed well. It's been unbelievably resilient. We think it's appointed differentiation over us against anyone else in the marketplace. You couple that with our global service footprint, the two of them working together we designated those capabilities is essential. Very early in the pandemic, we protected our team members and we were able to serve our customers and a pretty non disruptive way. Now, behind the scenes are teams were doing all sorts of things to bring, uh, that continuity supply and those expectations we sent to our customers to the forefront. But I couldn't be more pleased at how we responded, and it set us up to where things were going to go. When we think about the future and migrating tomb or integrated solutions, I suspect we may talk about as a service and the capabilities needed with that services in the supply chain play a key role. >>I guess so much to talk to you about. What? I wanna come back to digital transformation For a minute. I was talking to the C i o the other day and I asked him what was the digital transformation mean to you? He said, David, I got a 15 year old s a P system. Digital transformation means to me I My business has changed in the last 15 years, but my s a P system Hasn't I gotta bring it up to speed. I have to modernize. So there's a spectrum. On the other hand, if if you're not digital today and you're, say, a restaurant, you can't do business. So what does that spectrum look like of digital transformation to you and your customers? >>Well, I think your examples were very good. I mean, our industries as a long reputation of overhyping, different constructs. The fact is, the world is rapidly digitizing. It's undeniable. If you look at the cost of a sensor and how those sensors air now being placed in everything, all of the data that's being collected as a result, That's certainly the forefront of what's happening. And every business has to deal with that. You mean you can't We talked about hospitality. You got hotel rooms that have sensors in them for lights, for water, for a temperature. You think about what's happening in the finance sector in the amount of data that's being created on the edge of that has to be processed on the edge. You think about smart factory smart hospitals in the amount of technology that's going in to bring those new areas to the forefront. So in my mind. Digital transformation is catching up with where the world's going. We know the world is going from an analog world to a digital world, and as that acceleration, mhm goes faster and faster and faster, which I absolutely we absolutely believe this happening. Companies have to change the business. They have to change their models. They have to figure out how to take all of this data and turn data into information to drive better business outcomes. We tend to get into this digital transformation and everyone to talk about this piece of gear, this piece of gear, this piece of gear. I actually don't spend any time on that. It's where customers are going. What are they doing to really instrument, if you will, the digital world they're going to participate in and have to figure out how to overcome the obstacles and barriers with that to compete in their particular sectors. That's where we come in. We help them help them with certainly the gear part of it, but more importantly, the solution orientation to bring better business outcomes to them, to help them get to where they want to go. Does that help? >>Yes, and it does, and it sort of leads me to the hybrid cloud multi cloud. To me, it's edges all part of that and it's critical for your customers. Digital transformations. I mean, what I mean by that is creating a trusted operating environment across whatever platform you're on, whether you're on Prem when you're in a public cloud, whether you're at the edge, so multi cloud is part of that. You know, I used to think a lot of this stuff was aspirational. It seems to becoming more and more really. Where do you see your customers in that maturity cycle? >>Well, I love the way you described it. What we see is the notion of Cloud is much broader than perhaps we would have talked about earlier on when I got this job was the public cloud. No, there's Public Cloud. There's private clouds, and clearly the edge is going to be a cloud operating a model. In fact, we see the world of five G edge and cloud, those three circles intersecting toe high degree. So we're gonna bring a cloud operating model to the edge. We're gonna bring new advanced connectivity data driven connective ity to this edge where all of this instrumentation and all of this data is going to be created that will have toe have real time analytics done, uh, at the edge we think, is this opportunity to really step back and go well. Those cloud things can't be separate. They have to be a set of systems. In fact, it has to become an integrated system. And we think that integrated system has to be able to move data, be able to consistently manage, consistently orchestrate and consistently Dr Operations across those three cloud environments, I think we have gone. Probably the best characterization is early innings. We're certainly not in the first inning. We're not in the ninth inning, but we're certainly into the ballgame here of helping customers orchestrate a multi cloud hybrid cloud environment. If you think about what we've done with VM wars enablement or interaction with the public domains, the work that we've done from our private area, we have accomplished a lot in a short period of time, I'd also tell you there's a fair amount of work in front of us as this spends very quickly and the edge of balls we have to connect those worlds and not leave the edge out on an island by itself. We have to bring it together. We're bringing into the public and private cloud domains that we have today, >>and I definitely wanna hit on as a service. But since we're on this topic, I wanna I wanna talk about five G and Telco a little bit. Let me just spiel for a bit and then you can respond. So I mean, this seems to be a lot of confusion around five G. There's very high expectations. There's there's a there's a lot of talk, but if it's hard toe sort of identify the true impact, that's that's tangible today, anyway. And then you got the telecom telco transformation going on. We've been We've been hearing this for a long, long time. Meanwhile, you got the over over the top providers. They're living off the infrastructure. The telcos price per bit is declining, but the usage is exploding. And so what do you make of all this? You know, the telcos air reinventing themselves. Five g is a part of that consumers Airway waiting for that. There's a lot of, you know, mixed marketing messages going on. What's your take on this and what's tells role? >>Well, look, I I tend to try to break it down into things. At least I can understand. If I look at five G is the next generation Cellular, which I believe it's far more than that. I mean, I think it's the next data fabric for the data era. I think it's going to be this intersection, as I mentioned moments ago of five g Cloud and Edge, all coming together. But I think about it from the infrastructure side that you describe. What we have is the first opportunity to bring a cloud environment to the telco space that hasn't happened before. And I think a cloud environment needs to be implemented because I think there are cost pressures in that sector, and this is going to be a way to become more competitive and to bring out new technologies and services much faster. So now if you bring a cloud operating model to this which I believe five g enables, there is now the opportunity to bring, I think, um, or standard based infrastructure rather than the proprietary ones. In the past, we now can bring a industry standard set of architectures was softer to find layers in the stack. And for the first time in the telcos space, you have the ran going through significant transformation. And on my mind, Iran is one of the significant control points in the telco or five g stack, and that is going to be more open. And then we have to think of five. G is just more than a cellular network. I mean, we're gonna have private private five G. So to the degree that it displaces why, if I will be interesting to see and unfold. But there's a huge opportunity now. Is those sensors that I talked about in the digitization of hospitals and factories and cities, all interconnected by a bunch of private five G networks, all working in an interactive combined system way. I think it just lends itself to a solutions orientation, a standardization orientation, a cloud model, and that's sort of what we do. So I get excited. All of what I just said or alluded to is not solved to your point. You've been hearing this discussion for some time, but the opportunity is large for us. It's one of the single biggest largest opportune, single biggest opportunity that we see for Delon View more and we're going to pursue it together. And we think we can take our at scale technologies that we brought to the Enterprise Data Center and bring those to the telco providers in the private five g build out. >>It's amazing, Jeff, when you think about the when you and I started in this business and how far we've come, it's It's just just mind boggling, isn't it? It >>really is. We've been at this a while and things have changed. But again, it's been on this consistent technology curve, this consistent standardization curve, and it's now applying to new sectors >>I want to end with as a service. You mentioned that before and and so you've got actually really growing business in subscriptions? Uh, you got a lot of options for customers, which is good, but sometimes it's confusing. What's the strategy around as a service? What can we expect there? >>Well, one of the things that we've done and you're right, we've made a lot of progress. We launched L Technology on demand last year. We have 2000 plus customers of $1.3 billion revenue run rate, it's growing at 30% so we're pleased. But at the same time, all the data suggest customers we're gonna want to deploy even at a greater rate. So I think I made reference during our keynote. Today, about 75% of the world's data is gonna be created outside of the data center, 75% off the edge. Build out is going to be done as a service, as is half of the infrastructure. So we think we need to take this to the proverbial next level. We announced Project Apex, Project Apex for us to take all of the properties that we have across the company, all of the different activities and to unify them a single effort for as a service model for the Dell company going forward for our entire portfolio. We think the timing is right. We think we have to be able to, if you will project APEC should be translated as the easy button for our customers. It's a way to make things simpler. It's a way to give them the choice they need to drive consistency in the operating model, and that's the path Ron, we're pretty excited about this unification, if you will. Galvanizing across the entire organization with Project Apex. >>Awesome. Listen, I know you're super busy. Appreciate all the time you've given us your You're a fun executive toe. Hang around with a mission, man. I wish we were together, but hopefully, hopefully sometime soon we can We could see each other face to face. >>I would like that very much. I missed the interactions themselves. I appreciate the time today. Thank you, Dave. >>All right, We'll see you, Jeff. Thanks again. All right. Thank you for watching everybody. Keep it right there. We're back with our next guest. It del Technology World 2020. You're watching the Cube.

>> Narrator: From around the globe, it's The Cube, with digital coverage of Dell technologies world digital experience brought to you by Dell technologies. >> Welcome back to The Cube's continuing coverage of Dell technology world. Dell tech world 2020, Jeff Clark is here. He's the chief operating officer and vice chairman of Dell technologies. Jeff, awesome to see you. Thanks for coming on. >> Thanks for having me today, I appreciate it. >> Yeah, you're very welcome. Well, my first question is when do you have time to be vice chairman? >> Well, you know, in today's world, it's pretty hectic. We're all working around the clock. If there's anything about the new norm, there are no boundaries unless you establish some boundaries. So I've been able to find a rhythm that works for me personally but also allows me to look after the company and kind of keep things moving and making progress at Dell. So pretty exciting times, it's certainly been a challenge, finding new ways to break through, new ways to get things done, but our team has done a great job rising to the occasion. >> Well, you know as you know, I didn't know you that well prior to you taking over the whole enchilada and going back into the enterprise. I mean, I knew who you were obviously but you know, been able to see how you operate and the decision making and how you rally the troops. You're several years now, into the new deal. You had to do a lot of tactical things you know, including product portfolio rationalizations but I wanted to start with the macro picture. And in particular, can you share some of the acceleration points and the leavers that you're really pulling in the operation? >> Well, clearly if you look back at the company strategy and I'll start there and then kind of build on from that platform, if you think about the first tenant of our strategy is to win in the consolidation in our core marketplaces. So the core commercial PC market, the core server market and the core storage market, and clearly what we've been able to do, and certainly been at this now for, gosh, I think it's three years now that we've been turning over the portfolio and modernizing the portfolio on the ISG side. And to the point you referenced earlier we've now modernized that portfolio. It is now under all of the power brand it now represents new fresh, modern architecture, modern products that allows us to be competitive going forward across the entire ISG portfolio. We've had continued success on the commercial PC side. Then if you think about the next tenant of our strategy which is to really build deeply integrated solutions across the Dell technologies portfolio we've made a lot of progress in the last handful of years particularly integrating this new competitiveness of our ISG portfolio with VMware. And we're now beginning to see the fruits of that labor PC side real quickly. You've seen that with unified workspace, workspace one are leading services and are leading PC products to be able to bring a differentiated experience for end users on the PC side. On the ISG side, this all started with getting again, this competitive portfolio, it started with Dell technology cloud a little over a year ago, it now is in joint collaboration around the Edge. You've heard from my comments during the keynote around 5G going forward. So as we think about this new modern world playing out, we now have the infrastructure competitive. We have a great asset and capability with VMware or it now have figured out how to tightly integrate those and innovate on top of those platforms. And we think that's sort of the success for the future as we move forward. >> So it sounds like, I mean, COVID changed so many things, but it doesn't sound like it's materially changed your thinking on these leverage points or your strategy is going to pre COVID, post COVID. You kind of sort of approaching the same playbook if you will. >> Well, COVID many levels, well, it's had a huge impact on many lives around the world which that should not be lost on any of us and the impact that it's had across many businesses and in many parts of the world if you step back and what I try to mention the keynote, what COVID has done is really accelerate digital transformation. I've heard many characterizations but the way I tend to look at it is if you think of what's happened around us and the forcing of working remote, learning remote, the world, as we look at it, going forward, data driven, it's accelerated 10 years of what I thought would take us to get done into the first half of this decade in many cases, the first three years. This nomenclature that I talk about is the future is now. And what it's really done is actually reinforced the points that we thought were going to happen, brought them sooner, and has made us believe more doubled down if you will, that the path we were on is the right path. And we see our customers migrating that way rapidly. In fact, what's interesting, if you look at customers who embraced digital transformation earlier, we call them digital leaders. They are actually breaking away from the pack, so to speak from their peer set and driving differentiated performance in their sector, we think that's a great obviously proof point of digital transformation, but what all companies will have to go through to compete. >> Well, it's interesting. We saw early on in the US lockdown, worldwide lockdown, you have such a broad portfolio that yeah maybe some parts of the portfolio were, you know, directly negatively affected, certainly for instance, you know, your airline customers or your hospitality customers, et cetera. But the work from home was a tailwind for you guys. So the fact that you have that broad portfolio, somewhat, you know, one part of the business that cushioned you maybe the other part of the business, you felt it but on balance, you're able to get through that. And part of that was your supply chain. And some of your competitors struggled you know, for instance, with laptop supplies but you guys really have done a good job sort of navigating through that. Almost like you'd been through it before, but nobody's been through this before. >> No, you know, Dave, thanks for recognizing that one of the benefits of the end to end portfolio we have which no one else has the Indian portfolio that we do, we're able to weather the storm of different impacts to whether it's sectors, whether it's different parts of the business and we've been able to do that. And our supply chain has performed well. It's been unbelievably resilient. We think it's a pointed differentiation over us against anyone else in the marketplace. You couple that with our global service footprint, the two of them working together, we designated those capabilities as essential, very early in the pandemic, we protected our team members and we were able to serve our customers in a pretty non-disruptive way. Now behind the scenes, our teams were doing all sorts of things to bring that continuity of supply and those expectations we set to our customers to the forefront but I couldn't be more pleased at how we responded and it set us up to where things are going to go. When we think about the future and migrating to more integrated solutions, I suspect we may talk about as a service and the capabilities needed but that services in the supply chain play a key role. >> Yeah, I got so much to talk to you about, but I want to come back to digital transformation for a minute. I was talking to the CIO the other day and I asked them what was digital transformation mean to you? He said, "Dave, I got a 15 year old SAP system, Digital transformation means to me, my business has changed in the last 15 years but my SAP system hasn't, I got to bring it up to speed. I have to modernize." So there's a spectrum, on the other hand, if you're not digital today and you're say a restaurant, you can't do business. So what does that spectrum look like of digital transformation to you and your customers? >> Well, I think your examples were very good. I mean, our industries, has a long reputation of over hyping different constructs, the fact is the world is rapidly digitizing. It's undeniable. If you look at the cost of a sensor and how those sensors are now being placed in everything, in all of the data that's being collected as a result, that's certainly the forefront of what's happening and every business has to deal with it. You can't, I mean, we talked about hospitality, you got hotel rooms that have sensors in them, for lights, for water, for temperature. You think about what's happening in the finance sector and the amount of data that's being created on the edge that has to be processed on the edge. You think about smart factory, smart hospitals, and the amount of technology that's going in to bring those new areas to the forefront. So in my mind, digital transformation is catching up with where the world's going. We know the world is going from an analog world to a digital world. And as that acceleration goes faster and faster and faster which I absolutely, we absolutely believe is happening, companies have to change the business, they have to change their models, they have to figure out, how to take all of this data and turn data into information to drive better business outcomes. We tend to get into this digital transformation and every wants to talk about this piece of gear, or this piece of gear or this piece of gear. I actually don't spend any time on that. It's where customers are going, what are they doing to really instrument if you will, the digital world they're going to participate in and have to figure out how to overcome the obstacles and barriers with that to compete in their particular sectors. That's where we come in, we help them, help them with certainly the gear part of it, but more importantly the solution orientation to bring better business outcomes to them, to help them get to where they want to go. Does that help? >> Yes and it does. And it sort of leads me to the hybrid cloud, multi-cloud, to me, it's the edge is all part of that. And it's critical for your customers, digital transformation. What I mean by that is creating a trusted operating environment across whatever platform you're on, whether you're on prem, whether you're in a public cloud, whether you're at the edge. So multicloud is part of that. You know, I used to think a lot of this stuff was aspirational. It seems to becoming more and more real. Where do you see your customers in that maturity cycle? >> Well, I love the way you described it. What we see is the notion of cloud is much broader than perhaps we would have talked about early on, when I got this job was the public cloud. Now there's public cloud, there's private clouds and clearly The Edge is going to be a cloud operating model. In fact, we see the world of 5G, edge and cloud, those three circles intersecting to a high degree. So we're going to bring a cloud operating model to The Edge. We're going to bring new advanced connectivity, data-driven connectivity, to this edge where all of this instrumentation and all of this data is going to be created. That we'll have to have real time analytics done at the edge. We think is this opportunity to really step back and go, well, those cloud things can't be separate. They have to be a set of systems. In fact, it has to be done in an integrated system. And we think that integrated system has to be able to move data, be able to consistently manage, consistently orchestrated and consistently drive operations across those three cloud environments. I think we have gone probably the best characterization is early innings. We're certainly not in the first ending. We're not in the ninth inning but we're certainly into the ballgame here of helping customers orchestrate a multicloud hybrid cloud environment. If you think about what we've done with VMware's enablement or interaction with the public domain, the work that we've done from our private area, we have accomplished a lot in a short period of time. I'd also tell you there's a fair amount of work in front of us, as this spins very quickly and the edge of evolves, we have to connect those worlds and not leave the edge out on an island by itself. We have to bring it together or bringing into the public and private cloud domains that we have today. >> And I definitely want to hit on, as a service, but since we're on this topic, I want to, talk about 5G and telco a little bit. Let me just spiel for a bit, and then you can respond. So, I mean, there seems to be a lot of confusion around 5G, there's very high expectations. There's a lot of talk, but if it's hard to sort of identify the true impact that's tangible today anyway and then you got the telco transformation going on, and we've been hearing this for a long, long time. Meanwhile, you've got over the top providers they're living off the infrastructure of the telcos, price per bid is declining, but the usage is exploding. And so what do you make of all this? You know, that the telcos are reinventing themselves. 5G is a part of that. Consumers are waiting for that. There's a lot of, you know, mixed marketing messages going on. What's your take on this and what's Dell's role? >> Well, look, I tend to try to break it down into things at least I can understand. If I look at 5G as the next generation cellular which I believe it's far more than that. I mean, I think it's the next data fabric for the data era. I think it's going to be this intersection as I mentioned moments ago of 5G cloud and edge all coming together. But you think about it from the infrastructure side that you described. What we have is the first opportunity to bring a cloud environment to the telco space that hasn't happened before. And I think a cloud environment needs to be implemented because I think there are cost pressures in that sector. And this is going to be a way to become more competitive and to bring out new technologies and services much faster. So now if you bring a cloud operating model to this, which I believe 5G enables, there's now the opportunity to bring I think, a more standard based infrastructure rather than proprietary ones of the past. We now can bring a industry standard set of architectures with software defined layers in the stack. And for the first time in the telco space you have the RAN going through significant transformation. And on my mind the RAN is one of the significant control points in the telco or 5G stack. And that is going to be more opened. And then we have to think of 5G is just more than a cellular network. I mean, we're going to have private 5G. So to the degree that it displaces wifi will be interesting to see an unfold but there's a huge opportunity. Now, as those sensors that I talked about in the digitization of hospitals, in factories, in cities, all interconnected by a bunch of private 5G networks all working in an interactive and combined system way, I think it just lends itself to a solutions orientation, a standardizations orientation, a cloud model, and that's sort of what we do. So I get excited all in what I just said or alluded to is not solved to your point. You've been hearing this discussion for some time, but the opportunity is large for us. It's one of the single biggest opportunity that we see for Dell and VMware, and we're going to pursue it together. And we think we can take our at scale technologies that we brought to the enterprise data center and bring those to the telco providers and the private 5G build out. >> Yeah, it's amazing Jeff, when you think about the, when you and I started in this business and how far we've come, but it's just it's mind boggling, isn't it? (laughing) >> It really is. We've been at this a while and things have changed but again, it's been on this consistent technology curve, this consistent standardization curve and it's now applying to new sectors. >> I want to end with, as a service. You mentioned that before. And so you've got actually a really growing business in subscriptions. You got a lot of options for customers which is good, but sometimes it's confusing. What's the strategy around as a service? What can we expect there? >> Well, one of the things that we've done and you're right we've made a lot of progress. We launched Dell technology on demand last year, we have 2000 plus customers at $1.3 billion revenue run rate. It's growing at 30%. So we're pleased but at the same time, all the data suggests customers are going to want to deploy even at a greater rate. So I think I made reference during our keynote today about 75% of the world's data is going to be created outside of the data center, 75% of the edge build out is going to be done as a service as this half of the infrastructure. So we think we need to take this to the proverbial next level. We announced project APEC, project APEC for us to take all of the properties that we have across the company, all of the different activities and to unified them, a single effort for as a service model for the Dell company going forward, for our entire portfolio, we think the timing's right. We think we have to be able to if you will, project APEC should be translated as the easy button for our customers. It's a way to make things simpler. It's a way to give them the choice they need to drive consistency in the operating model. And that's the path we're on. We're pretty excited about this unification, if you will galvanizing across the entire organization with project APEC. >> Awesome, listen, I know you're super busy. I appreciate all the time you've given us, you're a fun executive to hang around with a mission man. I wish we were together, but hopefully sometime soon we can see each other face to face. >> I would like that very much. I miss the interactions themselves. I appreciate the time of day. Thank you Dave. >> All right we'll see you Jeff, thanks again. All right, Thank you for watching everybody. Keep it right there, will be back with our next guest at Dell technology world 2020. You're watching The Cube. (lighthearted music)

>> Announcer: Live from Orlando, Florida it's theCUBE! Covering Microsoft Ignite, brought to you by Cohesity. >> Hello, and happy taco Tuesday CUBE viewers! You are watching theCUBE's live coverage of Microsoft's Ignite here in Orlando, Florida. I'm your host Rebecca Knight, along with Stu Miniman. We're joined by Scott Hanselman, he is the partner program manager at Microsoft. Thank you so much for coming on theCUBE! >> Absolutely, my pleasure! >> Rebecca: And happy taco Tuesday to you! Will code for tacos. >> Will code for tacos. >> I'm digging it, I'm digging it >> I'm a very inexpensive coder. >> So you are the partner program manager, but you're really the people's programmer at Microsoft. Satya Nadella up on the main stage yesterday, talking about programming for everyone, empowering ordinary citizen developers, and you yourself were on the main stage this morning, "App Development for All", why is this such a priority for Microsoft at this point in time? >> Well there's the priority for Microsoft, and then I'll also speak selfishly as a priority for me, because when we talk about inclusion, what does that really mean? Well it is the opposite of exclusion. So when we mean inclusion, we need to mean everyone, we need to include everyone. So what can we do to make technology, to make programming possible, to make everyone enabled, whether that be something like drag and drop, and PowerApps, and the Power platform, all the way down to doing things like we did in the keynote this morning with C# on a tiny micro-controller, and the entire spectrum in between, whether it be citizen programmers in Excel using Power BI to go and do machine learning, or the silly things that we did in the keynote with rock, paper scissors that we might be able to talk about. All of that means including everyone and if the site isn't accessible, if Visual Studio as a tool isn't accessible, if you're training your AI in a non-ethical way, you are consciously excluding people. So back to what Satya thinks is why can't everyone do this? SatyaSacha thinks is why can't everyone do this? Why are we as programmers having any gate keeping, or you know, "You can't do that you're not a programmer, "you know, I'm a programmer, you can't have that." >> So what does the future look like, >> Rebecca: So what does the future look like, if everyone knows how to do it? I mean, do some imagining, visioning right now about if everyone does know how to do this, or at least can learn the building blocks for it, what does technology look like? >> Well hopefully it will be ethical, and it'll be democratized so that everyone can do it. I think that the things that are interesting, or innovative today will become commoditized tomorrow, like, something as simple as a webcam detecting your face, and putting a square around it and then you move around, and the square, we were like, "Oh my God, that was amazing!" And now it's just a library that you can download. What is amazing and interesting today, like AR and VR, where it's like, "Oh wow, I've never seen augmented reality work like that!" My eight-year-old will be able to do it in five years, and they'll be older than eight. >> So Scott, one of the big takeaways I had from the app dev keynote that you did this morning was in the past it was trying to get everybody on the same page, let's move them to our stack, let's move them to our cloud, let's move them on this programming language, and you really talked about how the example of Chipotle is different parts of the organization will write in a different language, and there needs to be, it's almost, you know, that service bus that you have between all of these environments, because we've spent, a lot of us, I know in my career I've spent decades trying to help break down those silos, and get everybody to work together, but we're never going to have everybody doing the same jobs, so we need to meet them where they are, they need to allow them to use the tools, the languages, the platforms that they want, but they need to all be able to work together, and this is not the Microsoft that I grew up with that is now an enabler of that environment. The word we keep coming back to is trust at the keynote. I know there's some awesome, cool new stuff about .net which is a piece of it, but it's all of the things together. >> Right, you know I was teaching a class at Mesa Community College down in San Diego a couple of days ago and they were trying, they were all people who wanted jobs, just community college people, I went to community college and it's like, I just want to know how to get a job, what is the thing that I can do? What language should I learn? And that's a tough question. They wonder, do I learn Java, do I learn C#? And someone had a really funny analogy, and I'll share it with you. They said, well you know English is the language, right? Why don't the other languages just give up? They said, you know, Finland, they're not going to win, right? Their language didn't win, so they should just give up, and they should all speak English, and I said, What an awful thing! They like their language! I'm not going to go to people who do Haskell, or Rust, or Scala, or F#, and say, you should give up! You're not going to win because C won, or Java won, or C# won. So instead, why don't we focus on standards where we can inter-operate, where we can accept that the reality is a hybrid cloud things like Azure Arc that allows us to connect multiple clouds, multi-vendor clouds together. That is all encompassing the concept of inclusion, including everyone means including every language, and as many standards as you can. So it might sound a little bit like a Tower of Babel, but we do have standards and the standards are HTTP, REST, JSON, JavaScript. It may not be the web we deserve, but it's the web that we have, so we'll use those building block technologies, and then let people do their own thing. >> So speaking of the keynote this morning, one of the cool things you were doing was talking about the rock, paper, scissors game, and how it's expanding. Tell our viewers a little bit more about the new elements to rock, paper, scissors. >> So folks named Sam Kass, a gentleman named Sam Kass many, many years ago on the internet, when the internet was much simpler web pages, created a game called Rock, Paper, Scissors, Lizard, Spock, and a lot of people will know that from a popular TV show on CBS, and they'll give credit to that show, in fact it was Sam Kass and Karen Bryla who created that, and we sent them a note and said, "Hey can I write a game about this?" And we basically built a Rock, Paper, Scissors, Lizard, Spock game in the cloud containerized at scale with multiple languages, and then we also put it on a tiny device, and what's fun about the game from a complexity perspective is that rock, paper, scissors is easy. There's only three rules, right? Paper covers rock, which makes no sense, but when you have five, it's hard! Spock shoots the Rock with his phaser, and then the lizard poisons Spock, and the paper disproves, and it gets really hard and complicated, but it's also super fun and nerdy. So we went and created a containerized app where we had all different bots, we had node, Python, Java, C#, and PHP, and then you can say, I'm going to pick Spock and .net, or node and paper, and have them fight, and then we added in some AI, and some machine learning, and some custom vision such that if you sign in with Twitter in this game, it will learn your patterns, and try to defeat you using your patterns and then, clicking on your choices and fun, snd then, clicking on your choices and fun, because we all want to go, "Rock, Paper, Scissors shoot!" So we made a custom vision model that would go, and detect your hand or whatever that is saying, this is Spock and then it would select it and play the game. So it was just great fun, and it was a lot more fun than a lot of the corporate demos that you see these days. >> All right Scott, you're doing a lot of different things at the show here. We said there's just a barrage of different announcements that were made. Love if you could share some of the things that might have flown under the radar. You know, Arc, everyone's talking about, but some cool things or things that you're geeking out on that you'd want to share with others? >> Two of the things that I'm most excited, one is an announcement that's specific to Ignite, and one's a community thing, the announcement is that .net Core 3.1 is coming. .net Core 3 has been a long time coming as we have began to mature, and create a cross platform open source .net runtime, but .net Core 3.1 LTS Long Term Support means that that's a version of .net core that you can put on a system for three years and be supported. Because a lot of people are saying, "All this open source is moving so fast! "I just upgraded to this, "and I don't want to upgrade to that". LTS releases are going to happen every November in the odd numbered years. So that means 2019, 2021, 2023, there's going to be a version of .net you can count on for three years, and then if you want to follow that train, the safe train, you can do that. In the even numbered years we're going to come out with a version of .net that will push the envelope, maybe introduce a new version of C#, it'll do something interesting and new, then we tighten the screws and then the following year that becomes a long term support version of .net. >> A question for you on that. One of the challenges I hear from customers is, when you talk about hybrid cloud, they're starting to get pulled apart a little bit, because in the public cloud, if I'm running Azure, I'm always on the latest version, but in my data center, often as you said, I want longer term support, I'm not ready to be able to take that CICD push all of the time, so it feels like I live, maybe call it bimodal if you want, but I'm being pulled with the am I always on the latest, getting the latest security, and it's all tested by them? Or am I on my own there? How do you help customers with that, when Microsoft's developing things, how do you live in both of those worlds or pull them together? >> Well, we're really just working on this idea of side-by-side, whether it be different versions of Visual Studio that are side-by-side, the stable one that your company is paying for, and then the preview version that you can go have side-by-side, or whether you could have .net Core 3, 3.1, or the next version, a preview version, and a safe version side-by-side. We want to enable people to experiment without fear of us messing up their machine, which is really, really important. >> One of the other things you were talking about is a cool community announcement. Can you tell us a little bit more about that? >> So this is a really cool product from a very, very small company out of Oregon, from a company called Wilderness Labs, and Wilderness Labs makes a micro-controller, not a micro-processor, not a raspberry pie, it doesn't run Linux, what it runs is .net, so we're actually playing Rock, Paper, Scissors, Lizard, Spock on this device. We've wired it all up, this is a screen from our friends at Adafruit, and I can write .net, so somehow if someone is working at, I don't know, the IT department at Little Debbie Snack Cakes, and they're making WinForms applications, they're suddenly now an IOT developer, 'cause they can go and write C# code, and control a device like this. And when you have a micro-controller, this will run for weeks on a battery, not hours. You go and 3D print a case, make this really tiny, it could become a sensor, it could become an IOT device, or one of thousands of devices that could check crops, check humidity, moisture wetness, whatever you want, and we're going to enable all kinds of things. This is just a commodity device here, this screen, it's not special. The actual device, this is the development version, size of my finger, it could be even smaller if we wanted to make it that way, and these are our friends at Wilderness Labs. and they had a successful Kickstarter, and I just wanted to give them a shout out, and I just wanted to give them a shoutout, I don't have any relationship with them, I just think they're great. >> Very cool, very cool. So you are a busy guy, and as Stu said, you're in a lot of different things within Microsoft, and yet you still have time to teach at community college. I'm interested in your perspective of why you do that? Why do you think it's so important to democratize learning about how to do this stuff? >> I am very fortunate and I think that we people, who have achieved some amount of success in our space, need to recognize that luck played a factor in that. That privilege played a factor in that. But, why can't we be the luck for somebody else, the luck can be as simple as a warm introduction. I believe very strongly in what I call the transitive value of friendship, so if we're friends, and you're friends, then the hypotenuse can be friends as well. A warm intro, a LinkedIn, a note that like, "Hey, I met this person, you should talk to them!" Non-transactional networking is really important. So I can go to a community college, and talk to a person that maybe wanted to quit, and give a speech and give them, I don't know, a week, three months, six months, more whatever, chutzpah, moxie, something that will keep them to finish their degree and then succeed, then I'm going to put good karma out into the world. >> Paying it forward. >> Exactly. >> So Scott, you mentioned that when people ask for advice, it's not about what language they do, is to, you know, is to,q you know, we talk in general about intellectual curiosity of course is good, being part of a community is a great way to participate, and Microsoft has a phenomenal one, any other tips you'd give for our listeners out there today? >> The fundamentals will never go out of style, and rather than thinking about learning how to code, why not think about learning how to think, and learning about systems thinking. One of my friends, Kishau Rogers, talked about systems thinking, I've hade her on my podcast a number of times, and we were giving a presentation at Black Girls Code, and I was talking to a fifteen-year-old young woman, and we were giving a presentation. It was clear that her mom wanted her to be there, and she's like, "Why are we here?" And I said, "All right, let's talk about programming "everybody, we're talking about programming. "My toaster is broken and the toast is not working. "What do you think is wrong?" Big, long, awkward pause and someone says, "Well is the power on?" I was like, "Well, I plugged a light in, "and nothing came on" and they were like, "Well is the fuse blown?" and then one little girl said "Well did the neighbors have power?", And I said, "You're debugging, we are debugging right?" This is the thing, you're a systems thinker, I don't know what's going on with the computer when my dad calls, I'm just figuring it out like, "Oh, I'm so happy, you work for Microsoft, "you're able to figure it out." >> Rebecca: He has his own IT guy now in you! >> Yeah, I don't know, I unplug the router, right? But that ability to think about things in the context of a larger system. I want toast, power is out in the neighborhood, drawing that line, that makes you a programmer, the language is secondary. >> Finally, the YouTube videos. Tell our viewers a little bit about those. you can go to D-O-T.net, so dot.net, the word dot, you can go to d-o-t.net, so dot.net, the word dot, slash videos and we went, and we made a 100 YouTube videos on everything from C# 101, .net, all the way up to database access, and putting things in the cloud. A very gentle, "Mr. Rodgers' Neighborhood" on-ramp. A lot of things, if you've ever seen that cartoon that says, "Want to draw an owl? "Well draw two circles, "and then draw the rest of the fricking owl." A lot of tutorials feel like that, and we don't want to do that, you know. We've got to have an on-ramp before we get on the freeway. So we've made those at dot.net/videos. >> Excellent, well that's a great plug! Thank you so much for coming on the show, Scott. >> Absolutely my pleasure! >> I'm Rebecca Knight, for Stu Miniman., stay tuned for more of theCUBE's live coverage of Microsoft Ignite. (upbeat music)

(electronic music) >> Announcer: Live from Orlando Florida, it's the Cube, covering Grace Hopper Celebration of Women in Computing, brought to you by SiliconANGLE Media. >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlando, Florida. I'm your host, Rebecca Knight. We're joined by LaFawn Davis, she is the global head of culture and inclusion at Twilio. Thanks so much for joining us. >> Thank you for having me. >> So let's start by telling our viewers what you do at Twilio. What does the global head of culture and inclusion do? >> That's a great question, it's kind of a newer title, so the culture piece is around our environment, our workspace, how employees feel, and it also incorporates employee experience, so we want to make sure that all the great talent we get in, we actually keep and develop and grow, and then there's the inclusion piece, the D&I piece, and that's the piece that people typically understand, so that is attracting, recruiting, retaining and developing top talent, it's making sure that we're looking at all of the diverse workforce that we want to have in the company, that we're serving our employees in the right way, and so it's nice that it's going to have both sides of that so it's not just purely about recruiting, it's not purely about numbers. It really is about how employees feel and it's whether or not they feel included, but also belong. >> So how do you do that? I mean, that's what every company wants, is to make employees feel happy about coming to work every morning. How do you do it? >> You have to ask. So it's really important that we have values that we can stand upon, every day. So we have what we call Nine Things, and they really are values, things like draw the owl, which is like you have to start somewhere. >> Rebecca: Draw the owl? >> Draw the owl. It's from an old internet meme that's around the way you draw an owl is you start with two circles, and then you draw the rest of the owl. You have to start somewhere. We have another one that's be humble. No shenanigans, that one you hear a lot, like if you're in a meeting and people are kind of ... thinking of doing things a different way? >> There are a few tech companies that maybe could have benefited from those shenanigans, but yeah. >> We'll call each other out, I mean, you'll hear it around the office. >> Rebecca: Do they, though? >> Oh no, absolutely. They absolutely will, they'll say, "That sounds a little shenanigan-y." or, you know, "We're not supposed to be doing "shenanigans here, so let's really "figure out how to do the right thing." And I think when you have values that are that specific, you can stand on them, you can count on them, and you can call each other out. >> Shenanigan-y? I love it, okay. >> (laughs) So it's like, let's be honest, and let's do what's right. >> But at the same time, I mean, it is, I understand how that can become the sort of safe word, and it's almost funny to say, "Hey, what are you doing here?" But how do you make those employees feel empowered enough to be able to call someone out, particularly if that person is a manager or a white guy that just has more bluster. >> Yeah, it starts from the top down. But even before I got to Twilio, I've only been at Twilio for six months but I did in the space for well over a decade, and what Twilio has is a top down and a bottoms up, so they were doing diversity inclusion and had employee resource groups before I got there. Three years before I got there, and the CEO is fantastic, and it really starts from that, messaging, you can tell the CEO he's being shenanigan-y. He expects you to, so we're hiring in people that espouse our values, we're looking for that, we're making sure that people come in with that understanding of, we don't want shenanigans here, we want you to be humble here, we want you to draw the owl, we want you to really acquire knowledge and thirst after it. Those are the things we look for, and so if you keep hiring people like that that already lend to your values, you're going to have, continue to have that culture. And it's not really about, oh I don't want to say this in front of, like, a C-Suite executive or in front of a leader, it's expected of you that you live those values no matter who you are. >> So as you've said, you've been in this space for a while, you worked for PayPal, Google, Yahoo. What have been the biggest changes you've seen over the course of your career? >> Yeah, so it's really a journey, right? I think the diversity journey especially ten years ago started with diversity, numbers, demographics, and it was really just gender globally and ethnicity U.S., and that's it and that's what people talked about, and those were the efforts that people made. It was really about recruiting, and now it's gone into more of the inclusion space and making sure people feel like they have a voice that can be heard, or they have a seat at the table, but honestly right now where we're at is the belonging space, right? Inclusion is really about making sure other people feel included and that you're hearing other perspectives. Belonging is a personal feeling. I feel like I belong here, and I'll tell you a funny story. When I first started Twilio, probably about two weeks in, I sit on the people team, which is next to the legal team, and the legal team's having this discussion and I'm like, wait a minute, oh my gosh, are you all conspiracy theorists? And they're like yeah! And I go, oh! Oh, you're my people! (Rebecca laughs) 'Cause I'm the one with the whiteboard and the red string and the tinfoil hat, and I immediately felt a sense of, you're my people, I feel like I'm supposed to be here. Everyone wants that feeling, and so the belonging space is really where companies are starting to focus, it's not just about having a seat at the table. Do you want to be here, do teams work well together? Are we working on something that's important to you? Do we have a vision that's inspiring to you? And that's more around belonging. I think the next step in this journey is equality, and we are a long way from that. >> And what do you make of that? I mean, you have been in this space for a while now, at some of the biggest, most respected tech names in the industry, and some of their names have been dragged through the mud around these issues, so I mean, are you discouraged, are you hopeful, what's your feeling now? >> I'm hopeful. I don't think I would still be doing it this long if I wasn't hopeful, and yes, I get tired. (laughs) >> Yeah, that we're still talking about it. >> Definitely get fatigued, but I'm very passionate about it, and that's how I ended up in this career. I started off in operations when I was at Google, and I was one of the founding members of the Black Googler Network, which is an employee's resource group, and I just got really passionate about being strategic. It wasn't just about building a sense of community. It was, no, let's figure out how to attract, recruit, retain and develop talent. Let's figure out like what the company needs and how we can plug in, and not just ... I mean, it lit a fire in me, and so I took lots of different roles within the D&I space and every time I think I'm going to step out, I get sucked back in. (they laugh) And so I think there's so much work to do. I think people inherently want to do the right thing. There's some bad apples that have been dragged through the mud lately, absolutely, but I think for the most part, people are coming from a good place. They may not know what to do, I think we have to change the conversation, because if we continue to do the same things over and over again, and they're not working, that should say something, right? >> So these, in terms of your past companies, Yahoo, Google, PayPal, they are much bigger than Twilio, Twilio is ... >> Less than a thousand employees. >> Less than a thousand people. How would you describe the biggest differences in terms of trying to affect change? >> Yeah, so I think the nice thing is, this is the first company where I don't fee like I have to talk about the business case for diversity. >> Rebecca: They already get it. >> They already get it, it's already got. My CEO will tell the story that when he started this company, he's like, I'm trying to build a company, and people were like, diversity, diversity, he's like, I'm trying to build a company. And then he really thought about it, and said, "Well, when is the right time to think about diversity? Is it when I have a thousand white male engineers?" Right, at that point you're fixing a problem as opposed to just starting with it and hiring people around that, and so it's the first company where I feel like that was already there, which is wonderful because now I can focus on the things that make the greatest impact, instead of starting from scratch, and so a smaller company, especially with more of a startup mentality, they just went public last year, I think it's almost easier in a way to make more progress because of that. >> And just in terms of what your CEO said about having to fix the problem, how do you think Twilio's products, how can you, how would a customer be able to tell that this was made by a diverse group of people, and it wasn't just a bunch of white guys in a room wearing hoodies, developing the Twilio suite? >> Platform. >> Rebecca: Yeah. >> The whole goal of the Twilio platform is to power up communication, right? That's the entire goal, and so I think as we're out and about, I mean we have this really cool role and it made this all tour, I just don't know it, and they're called developer evangelists, which I would love to be if I actually coded a little bit more, and they actually are the kind of, the middle of coding and evangelizing kind of what Twilio does, but a little bit of sales too, and so they're actually touching the community. We have community developers, we have, so it's not just people sitting at a desk in a room talking about what's best for people. It's we get out into the community, we understand what developers need, and we're constantly trying to figure out how do we create more doers, that's what we call people who create things. How do we create more doers? We have twilio.org, which is our foundation working with nonprofits, and there are social justice apps built on the platform. There are life-saving apps built on the platform. And we're funding these organizations so they can continue to build more and more on our platforms and change people's lives, and so I think that, and those examples, actually help people understand it's not just 400 white guys sitting in a room creating something for them. We're actually getting out and understanding what people need. >> And the research around diversity shows that diverse teams, it may take them a little slower to get the work done but the work is better, because it has taken in multiple perspectives, it has there's been more sort of fighting, and I don't mean to say fighting in the pejorative sense, but just getting to the ... >> LaFawn: Debating. >> The right answer, yeah, debate, exactly. (LaFawn laughs) To get to the right answer. I mean, would you say that's the experience? And I know you're not on the technical side, but what are you hearing from your ... >> I challenge that. >> Rebecca: Okay, all right. >> Every employee is encouraged to build something on the Twilio platform when they start, no matter what role they're in, and I am not in a technical role, but I know a little bit of coding now. But yes, absolutely, healthy debate is absolutely encouraged. How else are you going to build something for other people? It's really easy to just say, "I think we need to do this feature," right, but if that's not what people need, or you're not getting other perspectives, then you're building an inferior product. And so absolutely, you have to have that healthy debate, it's encouraged, and I see it (laughs) but it's not in a disrespectful way. So I have, being a part of the tech industry for a long time, I have seen some conversations that weren't so great, and people not treating each other well, thinking that that's how you have-- >> A little shenanigan-y. >> That's very shenanigan-y, right? Or calling each other names because they think that's how you get your point across. And I just don't feel that way at Twilio. It's much more respectful. I'm not saying that they don't get into it because I think you have to in order to really innovate. >> Well, LaFawn, thank you so much for joining us. It's been really a lot of fun talking to you. >> Thank you so much, you too. >> We will have more from Grace Hopper just after this. (electronic music)

>> Male Voiceover: Live from Stanford University, it's The Cube covering the Women in Data Science Conference 2017. >> Hi, welcome back to The Cube, I'm Lisa Martin and we are live at Stanford University at the second annual Women in Data Science Technical Conference. It's a one day event here, incredibly inspiring morning we've had. We're joined by Janet George, who is the chief data scientist at Western Digital. Janet, welcome to the show. >> Thank you very much. >> You're a speaker at-- >> Very happy to be here. >> We're very happy to have you. You're a speaker at this event and we want to talk about what you're going to be talking about. Industrialized data science. What is that? >> Industrialized data science is mostly about how data science is applied in the industry. It's less about more research work, but it's more about practical application of industry use cases in which we actually apply machine learning and artificial intelligence. >> What are some of the use cases at Western Digital for that application? >> One of the use case that we use is, we are in the business of creating new technology nodes and for creating new technology nodes we actually create a lot of data. And with that data, we actually look at, can we understand pattern recognition at very large scale? We're talking millions of wafers. Can we understand memory holes? The shape, the type, the curvature, circularity, radius, can we detect these patterns at scale? And then how can we detect if the memory hole is warped or deformed and how can we have machine learning do that for us? We also look at things like correlations during the manufacturing process. Strong correlations, weak correlations, and we try to figure out interactions between different correlations. >> Fantastic. So if we look at big data, it's probably applicable across every industry. How has it helped to transform Western Digital, that's been an institution here in Silicon Valley for a while? >> We in Western Digital we move mountains of data. That's just part of our job, right? And so we are the leaders in storage technology, people store data in Western Digital products, and so data's inherently very familiar to us. We actually deal with data on a regular basis. And now we've started confronting our data with data science. And we started confronting our data with machine learning because we are very aware that artificial intelligence, machine learning can bring a different value to that data. We can look at the insides, we can develop intelligence about how we build our storage products. What we do with our storage. Failure analysis is a huge area for us. So we're really tapping into our data to figure out how can we make artificial intelligence and machine learning ingrained in the way we do work. >> So from a cultural perspective, you've really done a lot to evolve the culture of Western Digital to apply the learnings, to improve the values that you deliver to all of your customers. >> Yes, believe it or not, we've become a data-driven company. That's amazing, because we've invested in our own data, and we've said "Hey, if we are going to store the world's data, we need to lead, from a data perspective" and so we've sort of embraced machine learning and artificial intelligence. We've embraced new algorithms, technologies that's out there we can tap into to look at our data. >> So from a machine learning, human perspective, in storage manufacturing, is there still a dependence on human insight where storage manufacturing devices are concerned, or are you seeing the machine learning really, in this case, take more of a lead? >> No, I think humans play a huge role, right? Because these are domain experts. We're talking about Ph.D.'s in material science and device physics areas so what I see is the augmentation between machine learning and humans, and the domain experts. Domain experts will not be able to scale. When the scale of wafer production becomes very large. So let's talk about 3 million wafers. How is a machine going to physically look at all the failure patterns on those wafers? We're not going to be able to scale just having domain expertise. But taking our core domain expertise and using that as training data to build intelligence models that can inform the domain expert and be smart and come up with all the ideas, that's where we want to be. >> Excellent. So you talked a little bit about the manufacturing process. Who are some of the other constituents that you collaborate with as chief data scientist at Western Digital that are demanding access to data, marketing, etcetera, what are some of those key collaborators for your group? >> Many of our marketing department, as well as our customer service department, we also have collaborations going on with universities, but one of the things we found out was when a drive fails, and it goes to our customer, it's much better for us to figure out the failure. So we've started modeling out all the customer returns that we've received, and look at that and see "How can we predict the life cycle of our storage?" And get to those return possibilities or potential issues before it lands in the hands of customers. >> That's excellent. >> So that's one area we've been focusing quite a bit on, to look at the whole life cycle of failures. >> You also talked about collaborating with universities. Share a little bit about that in terms of, is there a program for internships for example? How are you helping to shape the next generation of computer scientists? >> We are very strongly embedded in universities. We usually have a very good internship program. Six to eight weeks, to 12 weeks in the summer, the interns come in. Ours is a little different where we treat our interns as real value add. They come in, and they're given a hypothesis, or problem domain that they need to go after. And within six to eight weeks, and they have access to tremendous amounts of data, so they get to play with all this industry data that they would never get to play with. They can quickly bring their academic background, or their academic learning to that data. We also take really hard research-ended problems or further out problems and we collaborate with universities on that, especially Stanford University, we've been doing great collaborations with them. I'm super encouraged with Feliz's work on computer vision, and we've been looking into things around deep neural networks. This is an area of great passion for me. I think the cognitive computing space is just started to open up and we have a lot to learn from neural networks and how they work and where the value can be added. >> Looking at, just want to explore the internship topic for a second. And we're at the second annual Women in Data Science Conference. There's a lot of young minds here, not just here in person, but in many cities across the globe. What are you seeing with some of the interns that come in? Are they confident enough to say "I'm getting access to real world data I wouldn't have access to in school", are they confident to play around with that, test out a hypothesis and fail? Or do they fear, "I need to get this right right away, this is my career at stake?" >> It's an interesting dichotomy because they have a really short time frame. That's an issue because of the time frame, and they have to quickly discover. Failing fast and learning fast is part of data science and I really think that we have to get to that point where we're really comfortable with failure, and the learning we get from the failure. Remember the light bulb was invented with 99% negative knowledge, so we have to get to that negative knowledge and treat that as learning. So we encourage a culture, we encourage a style of different learning cycles so we say, "What did we learn in the first learning cycle?" "What discoveries, what hypothesis did we figure out in the first learning cycle, which will then prepare our second learning cycle?" And we don't see it as a one-stop, rather more iterative form of work. Also with the internships, I think sometimes it's really essential to have critical thinking. And so the interns get that environment to learn critical thinking in the industry space. >> Tell us about, from a skills perspective, these are, you can share with us, presumably young people studying computer science, maybe engineering topics, what are some of the traditional data science skills that you think are still absolutely there? Maybe it's a hybrid of a hacker and someone who's got, great statistician background. What about the creative side and the ability to communicate? What's your ideal data scientist today? What are the embodiments of those? >> So this is a fantastic question, because I've been thinking about this a lot. I think the ideal data scientist is at the intersection of three circles. The first circle is really somebody who's very comfortable with data, mathematics, statistics, machine learning, that sort of thing. The second circle is in the intersection of implementation, engineering, computer science, electrical engineering, those backgrounds where they've had discipline. They understand that they can take complex math or complex algorithms and then actually implement them to get business value out of them. And the third circle is around business acumen, program management, critical thinking, really going deeper, asking the questions, explaining the results, very complex charts. The ability to visualize that data and understand the trends in that data. So it's the intersection of these very diverse disciplines, and somebody who has deep critical thinking and never gives up. (laughs) >> That's a great one, that never gives up. But looking at it, in that way, have you seen this, we're really here at a revolution, right? Have you seen that data science traditionalist role evolve into these three, the intersection of these three elements? >> Yeah, traditionally, if you did a lot of computer science, or you did a lot of math, you'd be considered a great data scientist. But if you don't have that business acumen, how do you look at the critical problems? How do you communicate what you found? How do you communicate that what you found actually matters in the scheme of things? Sometimes people talk about anomalies, and I always say "is the anomaly structured enough that I need to care about?" Is it systematic? Why should I care about this anomaly? Why is it different from an alert? If you have modeled all the behaviors, and you understand that this is a different anomaly than I've normally seen, and you must care about it. So you need to have business acumen to ask the right business questions and understand why that matters. >> So your background in computer science, your bachelor's Ph.D.? >> Bachelor's and master's in computer science, mathematics, and statistics, so I've got a combination of all of those and then my business experience comes from being in the field. >> Lisa: I was going to ask you that, how did you get that business acumen? Sounds like it was by in-field training, basically on-the-job? >> It was in the industry, it was on-the-job, I put myself in positions where I've had great opportunities and tackled great business problems that I had to go out and solve, very unique set of business problems that I had to dig deep into figuring out what the solutions were, and so then gained the experience from that. >> So going back to Western Digital, how you're leveraging data science to really evolve the company. You talked about the cultural evolution there, which we both were mentioning off-camera, is quite a feat because it's very challenging. Data from many angles, security, usage, is a board level, boardroom conversation. I'd love to understand, and you also talked about collaboration, so talk to us a little bit about how, and some of the ways, tangible ways, that data science and your team have helped evolve Western Digital. Improving products, improving services, improving revenue. >> I think of it as when an algorithm or a machine learning model is smart, it cannot be a threat. There's a difference between being smart and being a threat. It's smart when it actually provides value. It's a threat when it takes away or does something you would be wanting to do, and here I see that initially there's a lot of fear in the industry, and I think the fear is related to "oh, here's a new technology," and we've seen technologies come in and disrupt in a major way. And machine learning will make a lot of disruptions in the industry for sure. But I think that will cause a shift, or a change. Look at our phone industry, and how much the phone industry has gone through. We never complain that the smart phone is smarter than us. (laughs) We love the fact that the smartphone can show us maps and it can send us in the right, of course, it sends us in the wrong direction sometimes, most of the time it's pretty good. We've grown to rely on our cell phones. We've grown to rely on the smartness. I look at when technology becomes your partner, when technology becomes your ally, and when it actually becomes useful to you, there is a shift in culture. We start by saying "how do we earn the value of the humans?" How can machine learning, how can the algorithms we built, actually show you the difference? How can it come up with things you didn't see? How can it discover new things for you that will create a wow factor for you? And when it does create a wow factor for you, you will want more of it, so it's more, to me, it's most an intent-based progress, in terms of a culture change. You can't push any new technology on people. People will be reluctant to adapt. The only way you can, that people adopt to new technologies is when they the value of the technology instantly and then they become believers. It's a very grassroots-level change, if you will. >> For the foreseeable future, that from a fear perspective and maybe job security, that at least in the storage and manufacturing industry, people aren't going to be replaced by machines. You think it's going to maybe live together for a very long, long time? >> I totally agree. I think that it's going to augment the humans for a long, long time. I think that we will get over our fear, we worry that the humans, I think humans are incredibly powerful. We give way too little credit to ourselves. I think we have huge creative capacity. Machines do have processing capacity, they have very large scale processing capacity, and humans and machines can augment each other. I do believe that the time when we had computers and we relied on our computers for data processing. We're going to rely on computers for machine learning. We're going to get smarter, so we don't have to do all the automation and the daily grind of stuff. If you can predict, and that prediction can help you, and you can feed that prediction model some learning mechanism by reinforced learning or reading or ranking. Look at spam industry. We just taught the Spam-a-Guccis to become so good at catching spam, and we don't worry about the fact that they do the cleansing of that level of data for us and so we'll get to that stage first, and then we'll get better and better and better. I think humans have a natural tendency to step up, they always do. We've always, through many generations, we have always stepped up higher than where we were before, so this is going to make us step up further. We're going to demand more, we're going to invent more, we're going to create more. But it's not going to be, I don't see it as a real threat. The places where I see it as a threat is when the data has bias, or the data is manipulated, which exists even without machine learning. >> I love though, that the analogy that you're making is as technology is evolving, it's kind of a natural catalyst >> Janet: It is a natural catalyst. >> For us humans to evolve and learn and progress and that's a great cycle that you're-- >> Yeah, imagine how we did farming ten years ago, twenty years ago. Imagine how we drive our cars today than we did many years ago. Imagine the role of maps in our lives. Imagine the role of autonomous cars. This is a natural progression of the human race, that's how I see it, and you can see the younger, young people now are so natural for them, technology is so natural for them. They can tweet, and swipe, and that's the natural progression of the human race. I don't think we can stop that, I think we have to embrace that it's a gift. >> That's a great message, embracing it. It is a gift. Well, we wish you the best of luck this year at Western Digital, and thank you for inspiring us and probably many that are here and those that are watching the livestream. Janet George, thanks so much for being on The Cube. >> Thank you. >> Thank you for watching The Cube. We are again live from the second annual Women in Data Science conference at Stanford, I'm Lisa Martin, don't go away. We'll be right back. (upbeat electronic music)

>> Narrator: Live from San Jose, California in the heart of silicon valley, it's theCUBE! Covering QuickBooks Connect 2016. Sponsored by Intuit QuickBooks. Now here are your hosts Jeff Frick and John Walls. >> Welcome back to San Jose, California. We continue here on theCUBE our coverage of QuickBooks Connect 2016. Of course theCube is the flagship broadcast here on SiliconANGLE TV where we extract the signal from the noise and I tell you what, with our next guest, we have a lot of signal to bring you. Scott Cook, the founder and the chairman of the executive committee at Intuit. Scott, thank you for being with us. We really appreciate the time and have been looking forward to this for quite some time once we knew you were going to be on theCube. It's good to have you. >> Good to be here. >> Let's talk about just first off, look at where you are now, right? 30-some odd years. It's been quite a ride I would assume for you. >> Yeah, it started, you know Tom and I got together and then there were two of us and then we eventually had seven of us in a basement. Well they called it the garden level. But the only part of the garden you could see would be the roots and the gophers. (laughter) And then we hit bad times and the things ... We just couldn't get money. We couldn't get sales so we shrunk down to four people. Couldn't pay salaries. It was pretty ugly. And from that, to look at 5,000 people here today. 8,000 employees in the company. When I started the biggest PC software company was 160 employees, and they were huge! Oh these giants! (laughter) >> How do I manage all this? >> Yeah, yeah. >> Well a quote that we've heard a couple of times today. We heard on the keynote stage. About the corporate philosophy of we fall in love with your problems, not our solutions. And is that the driving force you think? I mean, why you've made it through 33 years? >> I think yeah. Yeah, I actually think that's pretty important not just to the success of Intuit and QuickBooks and Mint and TurboTax, but to business in general. My theory is what great entrepreneurs do is they find the intersection of two circles. So think of a Venn diagram and the intersection. One circle is what are people's biggest, most important unsolved problems? Not the problems that are already solved by someone else. Find the ones that aren't solved yet. And then look for the ones that we can solve. Cause you can't solve everything. But look where we can apply the best technologies in the world. What's in that intersection? And focus there. >> And in some of the research to get ready for this. You've talked about really focusing on the important stuff. You gave a great example in that Khan Academy talk about there's really only 1 1/2 things that you should really be focusing on to really move the ship forward. And that was a very great insight. >> Yeah, you know all of of us have the desire to do too many things. You get groups. You've got 10 people in a room, they each have their ideas and it's tempting to shoot at too many targets. And those 10 targets are not of equal importance. You got to go through and kind of rigorously and be disciplined and say what's the 1 1/2 most important? And stay relentlessly focused on that. >> And then how is your role changed? As time has passed and you're no longer the CEO. Now you're chairman head of the executive board. How have you kind of learned to still keep your hands on it but in kind of a little bit more of a distant role? >> Well, first of all, thank goodness for leaders like Brad Smith, Sasan Goodarzi who heads up our small business group, that's really the host of this show. Thank goodness for great leaders like that. So my role's changed a ton. I work really on two areas now which is strategy and coaching our entrepreneurs. So strategy over to Brad and our other leaders. I'm trying to help our leaders see the future and make the big strategic calls. What's really most important? How do we know? And then work with our entrepreneurs. We're a collection of entrepreneurs basically. We've got a couple hundred entrepreneurial projects going on inside the company at any one time. And each one of those is like a little startup. I mean, they've got a customer in mind. They've got a problem they're trying to solve to improve people's lives so fundamentally. And there are challenges. So helping grow our entrepreneurs and then grow the culture around them to allow great entrepreneurs to invent things to change the world and do that from within Intuit with a huge reach to be able to get the inventions out in the hands of millions. And change the lives of tens of millions of people. >> So, over the course of the run of the company, they haven't all been home runs. >> Scott: Oh yeah. >> Right. So how have you learned from those swings and misses? And applied them to the small businesses that you're serving? Who are swinging and missing on a regular basis and you're trying to narrow that margin, right? Trying to make them more successful. >> Scott: Yeah. >> So what did you learn you think maybe through your attempts about that culture of trying basically. >> I think maybe the most important thing really dovetails with what you just said. Early on, when the company was, before we even had our first product out, we'd build a version of it and then we would bring in test audiences of it and have them test it to see if they could figure it out without us saying anything. And they couldn't. So then we'd redesign it and then we'd test again. And then we'd redesign it and test again. Over time kind of lost some of that dedication to running experiments. And it became whose opinion? And you'd build, and it was the loudest opinion in the room. Or the boss' opinion. And that produced a number of failures. Things that just didn't work. Customers didn't buy it. Or they bought it and it didn't it didn't produce the desired effect when they bought it. So the thing I've learned about life and companies is to set up a culture where you make decisions based on fast cheap experiments. That very thing you were talking about. If you got an idea, figure out, okay, what's a leap of faith assumption, let's go try it. And don't debate it. Try it. And then we learned from trying. Oh, a bunch of those don't work. And then we learned from the things. Why didn't it work? And that teaches us something we didn't know before. That maybe the fulcrum, the pivot, to a new idea. And some of those do work or most of it worked. But other pieces didn't. And we learned by doing. Not by debating in a conference room. So to set up your company so that people throughout the company can take their idea and run the experiment. That produces great entrepreneurs and great learning. A continuous stream of learning. I guess the learning begins when you first get real people trying your idea for real. >> Let me follow up. Cause the other thing you talk about is that often comes from the youngest and the newest employees. Which is completely antithesis to a kind of hierarchical structure. Where these are the people that you should be listening and giving them the opportunity within this comfortable framework to do these experiments. >> Absolutely. Sometimes the very freshest ideas come from the people farthest from the boss. Newest in the company. Closest to the customer. But typically in a hierarchy, whose got the least clout? Whose ideas are the least listened to? It'd be the new person, the young person. >> Jeff: Right. >> And so part of the genius of running a company of decision by experiment is that everyone's ideas can be run as an experiment. The boss' idea. The CEO's idea. And the person that's new. We should be testing each of those. Except in a crisis where you got to make snap decisions. And hopefully those aren't very often. You should run the company so that each good idea can be tested, regardless of where it comes from. And then the great thing is, then you get the best ideas from all your folks and they learn from doing. If their idea doesn't work, now they learn from that. Ooh, okay. I thought it was going to do X, it did Y. Why? What didn't I know? That's where learning comes from. Learning doesn't tend to come from the successes, learning comes from the things that didn't work. >> So, I think we've all seen good executives. How they operate. They hire good people, right? That's ... You have a vision and then you hire people who surround that and amplify that vision. So when you're looking for people or when you've been looking for people to work with you. What's that common thread? Or what are the traits that you've looked for the most to think that's a good fit? Or this is the person that I want on my team. In order to carry on this vision to where it's expanded to where it is today. >> Let me break that into two buckets. There are a set of things which are unique to particular career paths. So certain things from engineers might be different than certain things from a salesperson or a marketer or a finance person. So let's set that aside. Let's cover the commonalities. I think there's a few things. When you think about the people you've most loved working with or for. There are people who are great creative problem solvers. Instead of seeing a problem or barrier and giving up or being unglued by it. Can figure out okay, how're we going to solve that problem? And then there's people who are there to serve. Where it's not all about them. I've got a thing that I tell our folks that others won't care how much you know until they first know how much you care. So if one of our speakers today said it. If your first job is to serve yourself you're not going to go very far. Because who wants to work with someone who's self serving? Who wants to buy from a company that's only looking after its own front P&L? Job one is you got to serve who you're serving. The customer or the person of the company who you serve. So we look for people who are really motivated by the outside to try to do right by the customer. I think you look for people who are achievement oriented. Who get stuff done. Who make things happen. Do you want to work with somebody who always needs to be dragged along? No. You want to work with somebody who's pulling you along. Who's getting a lot done. So you go, wow, that person gets a lot done. So I think those are pretty core. Solve the creative problems. Have the passion and energy to serve, do what's right for the customer. And then get a lot done. >> And then you've talked about the curse of success. And avoiding the curse of success. And you guys have done that, obviously. So what are the kind of the lessons to say fresh? This started as a checkbook register and now the future of payments and mobile and the options are just tremendous. Bitcoin, who knows where that's going. So, as the future keeps evolving, how do you stay fresh? How do you keep the team fresh? How do you not rest on your laurels even though you have 5,000 fans walking around San Jose convention center today? >> This is a real challenge for companies. Because success turns organizations. It makes them dumb and slow. It's tempting, the thing I would avoid is it's tempting to look at your achievements. To look through the rear view mirror. And look at boy, how much we've achieved. But that only makes you self satisfied. In fact, with an organization you need to do the opposite. Look to where we want to be. Look to where we should be. And we're here. And then say, well shoot we are not very far. So for example, and I define these in customer terms. For example, we started our first product helped somebody manage a checkbook and pay bills. If you look at it really, the problem of paying bills has gotten worse. It used to be all bills came in the mail. So you had a little physical reminder. Some come in the mail, some you get by e-mail with invoices from some people. Some you go online and find a website. You pay some at a bank website. Maybe you go to the biller, you pay some. You write checks for some. It's much harder now. We have not actually got to the point. When our nirvana is you never worry about a bill. And you're never late. And you're never overdraft. The overdraft rate in the country is around 30% of households have a late payment during the year from which they get fees. And the overdraft rates, the overdraft charges can be $30, $35. We have not solved that yet. We got to look and say with all that we've done, that's what we should have done. So we've got a team working on that right now. Because we got re-focused on it. So we'll be coming out in December with stuff in there. Look at tax. Tax many people would say is one of our best businesses. And it is. Look at all we've achieved. But, look at the reality. People are still spending a lot of time on tax. Who wants to be spending time typing stuff into tax software? Does anybody? (laughter) No. There's not an accountant, there's not a consumer. We haven't solved that yet guys. There are still a hundred million people in the country typing stuff in to systems to do taxes every February, March and April. That's where we want to be. Is ultimately there is no typing in. All that information you have that goes in your tax return goes in automatically. And if you're an accountant, it all goes in for your clients automatically. So that you can focus on the high level stuff and not the drudgery. So, viewed from the lens of really what life should be. What's our aspiration? Our ideal? Keep people focused on that. And it sure has helped motivate us. I mean, we should be finding a lot of money for small businesses. And we're launching, announcing today ways that we help small businesses find more money. We should be eliminating the drudgery of running a small business. Nobody wants to do the book work. Instead, they want to do what they love to do in business. It could be working with clients. It could be the craft of doing the business. It could be selling new business. Every business person has something they love to do. And it's not doing the books. And that yet, people still have to do it. We want to have it on your phone so you don't have to do the books. It's done automatically. And you got a question, boop boop, there's the answer. >> So you mentioned the phone. Is that the next big growth opportunity? Mobile this is top priority with so many different sectors right now. >> Yeah, yeah. It's the growth today. In fact, every new feature and new benefit that Sasan Goodarzi showed today in his keynote address. Every one of 'em, he showed it on a mobile phone. Every one. It's the fastest growing. TurboTax the great consumer business. It's the fastest growing platform by far. So yeah, if you can take stuff off a desktop and put it so automatically that you can just get on your phone, say, okay, yep, do it. >> Right, right. >> Yeah, so that's where we're aiming a lot of our innovation. And these are amazing platforms. A simple example, the fastest growing form of employment in the United States and in fact, in the world is self employed. Where you think of an Uber driver or someone like that. People who work as consultants, contractors, they work for themselves. They've got to keep track of all their business expenses. Or they lose that money on their tax returns. Money out of their pocket. They got to keep track of every individual business expense which of course, they co-mingle with their personal checking, personal credit card. And they got to keep track of every mile they drive for business. And keep it separate with contemporaneous records that the IRS requires with the starting odometer reading, the ending odometer reading, and the destination and what it was for. Well you can imagine that's such a pain in the butt. So many independent business people, freelancers fail. Or they do some but not others. And that's money right out of their pocket. Thousands of dollars they don't get. They should get that they deserve. So we've devised and a team really creative work, QuickBooks Self Employed. It sits on your phone in your pocket. It reads what's coming from your bank and your credit cards and anytime you're stopped at a stop light or you've got two minutes before a meeting starts. You can go through and say oh, that was a business expense, business, business. That was personal, personal. It's that fast. And then you get complete records for your taxes. Oh then mileage. There's lots of software out there that'll track your mileage but it does by pinging the GPS. GPS takes battery. You ping the GPS all day long, what happens? Zhoom. >> Goodbye phone. >> Bye bye phone. So it's worthless. Our guys we launched that. Quickly found out that people stopped using it because it drained their battery just like everyone else. So, three clever engineers. Together with a couple others came up with a really clever idea which we've patented now. And it tracks your location without pinging your GPS all day long. So it doesn't drain your battery. So now you had complete records. It can detect when you're driving and where you started, where you finished. How many miles. Keeps perfect record, just as the IRS requires. And then you just have to tell it which are business, which are personal. And then it learns. Which one are business trips. So that over time, it knows when you're driving on business and you don't have to do anything. You get complete tax records. We've got businesses using it who get on average $7,000 of tax deductions. $7,000 of tax deductions. Because of the way it tracks. >> And you're taking advantage of the platform. You're taking advantage of the accelerometer. >> Yes. >> More importantly I think. The thing about mobile that most people don't maybe consciously think of is the way we interact with it as you said is little bits of time here, there, and everywhere. >> Scott: Yes. >> It's not the sit down thing. But I think what I think is most exciting about this show is it's a lot of talk about technology. But at the end of the day, it's really more about business. And small business. And small medium size business. And getting business done. >> Scott: Yes. >> And letting people do those dreams like the gal that was on the keynote. >> Scott: Yes. >> Letting her build her company and her franchise. And not have to worry about am I getting all the right deductions. >> That's right. I think the technology is the enabler. But it's all to enable what? What are we trying to deliver? And you saw it, in the kind of lead of slides. We're trying to fuel the success of small business. This is all about success. The technology's an enabler but that's not the center, the star of the show. The star of the show are small businesses and how they succeed. And how the suite of things that hundreds of developers and hundreds of software entrepreneurs who all build for the QuickBooks ecosystem. The new methods, and new ways to drive small business success. And at the end of the day, we don't measure ourselves with software. We measure ourselves with how much more money did we make small businesses? How much time did we save them so they could do what they love? How did we help them grow their business? Running a small business is a, and I know from starting Intuit, it absorbs who you are. You identify with that business. It is your representation to the world. To your spouse, to your in-laws. And if that business is successful, it's something about you that's irreplaceably positive. If that business is struggling, it strikes to the core. I mean, you feel bad. You look bad. So helping businesses succeed. And move them from mediocrity to success is such a home run for the psychology of this growing part of our economy. For each individual, it's your report card on yourself. And we can help make those report cards much better. That's our mission. That's how we're going to change the world so, so dramatically. People can't imagine going back. >> I'd say that you've already changed it dramatically. And it is exciting to hear about the next steps but this whole blend of strategy and execution and culture you're being commended for. It's just a great example of all those factors coming together and make great things happen for a lot of people around the globe so congratulations for that and thank you for being with us Scott. We appreciate the time here on theCube. >> Jeff, John thank you very much. This was a pleasure. >> Jeff: Thank you. >> You bet. Back with more from San Jose in just a bit. You're watching theCube here on SiliconANGLE TV. (techno music)