>>Yeah. Hello and welcome to the Cuba's International Women's Showcase, featuring International Women's Day. I'm John, host of the Kiwi here in California. Great remote guest. She's amazing founder and C e O of Cuba, and great to see you. Okay, thanks for coming on. Um, good to see you. >>You as well. Always a pleasure. You >>know, International Women's Day is the big celebration. We're doing a lot of interviews with great people making things happen, moving and shaking things. Um, but every day, International Women's Day, As far as I'm concerned, it's happening all around the world. But these are stories of innovation, the stories of changes, the stories of transformation for the better. You've been doing a lot of things. Um and I want to get into that. But let's start with your background. Tell us a bit about who you are and what you've got going on. >>Yeah, my background is a little strange. I used to be a maritime archaeologists. So dumb shit breaks for a little bit. That was amazing. I always just It's only partial just because it's actually a bit of truth to it, that learning how to, you know, handle things at depth really does train you to be a C e o. Because you learn to control your breath and and focus on the things that matter and not be so reactive because it's three activity that will panic that will kill you. Uh, always knowing how to reframe. Return to the basics. Um, there's a really good things to hold on to, even in the world of business. Right? So I at some point, ended up doing doing a lot of things. Largely business development, following my time diving and amazing woman. Um, another woman for International Women's Day named Doctor who was a biotech entrepreneur from Japan, stepping down as her role at the helm of her company. Um, and she wanted to launch a space for a young innovators from around the world who are doing amazing work to tackle this very complex challenges we all know exist, um, and figure out a way to give them time and space to do their best work and pursue their their highest visions for change. We decided that we would focus on for-profit companies largely who were using sustainable, scalable business models to pursue both profit and purpose. Um creating a virtuous cycle between the return of money to a company and putting that into to go even further and faster towards, um, solving a problem. Um, so we now have companies over 200 companies from around the world that we have helped support tackling every single, sustainable development goal. Um, and I'm proud to say, you know, particularly related to the subject that fifty-nine percent of our companies have a woman founder or CO-FOUNDER. Um, and 69% of the founder of color. Um, so we're working with entrepreneurs from every every area of the world. Many approximate to the problem that they are trying to solve, so they intimately understand it. Um, and they're doing amazing things. >>Yeah, you can help the great mission. You have a lot of other things going on your helping women encouraging them to your career in the tech sector. Um, good statistics could be better, right? Is higher and better. So, um, what are you guys doing? What, you specifically to help and encourage women to forge their career and tech? >>Yeah. I mean, look, the good news is I do think that it's getting better. I particularly think that we will see the adventure is improving. Um, it takes a while because the companies that have been funded up until now are still working in the biggest amount in the later stages. So I think that percentage hasn't been shifting. But I have to believe that that's a bit of an illusion, and then a couple of years, we're going to start to sea level out. But you know as well as I do that they're pretty poultry statistics in terms of the amount of venture that women like cos. Capture, Um, and the other ways that women are doubted, um, in terms of their ability and potential. Um, so we we love to work with any underrepresented group of entrepreneurs, and there's ways that we do that whether it's helping them sort of find their power and hold space and be confident. And, um, you know, be able to pitch to any room, talk to any investor, talk to any customer but also working to be directed about some of the systemic challenges, both in terms of talking to existing investors and trying to educate them to see the opportunities that they're missing because there is a an economic imperative to them understanding what they're missing. Um, but there's also some things that we're doing in-house to make sure that we're also helping to close capital gaps for all our entrepreneurs. So we actually now have a suite of three capital mechanisms that are entrepreneurs can access on the back end of our incubator, a microphone fund, which is very quick turnaround, small amounts of capital for entrepreneurs who existing opportunities owns, which is a tax destination. Just this in the U. S. But that's meant to be deployed so that they can access capital towards revenue without credit checks, collateral being put up, a slow moving pace of banks and C. D. S s. It's particularly useful for people who may not raise venture. And it's useful for, uh, you know, people who maybe don't have that friends and family check that they can expect similar. We've got a great angel network who look at the best impact deals from around the world. Um, and it doesn't have to be a housing company, just a great venture that's pursuing impact on profit. Um, and then lastly, we're just about to announce that we have a fund of our own on the back end of our incubator that funds only healthy and companies. Um, it's an early stage fund. Um, but watch this space because our pipeline is just increasing your every year. We used to sort of just 16 companies here. Now, we're serving 60 this year, so, um, yeah, it's really exciting. Um, and so obviously, it's really great that, you know, we're going to be able to help scale the impact that we want to see. Uh, ideally a lot. A lot faster. >>Well, you definitely taking control. I remember when we had a few years ago. I think four years ago, you just thinking about getting going and going now with great tailwind. Um, >>and the diversity >>of sources of capital as well as diversity of firms is increasing. That's helping, uh, that we're seeing, but you're also got the back end fun for the housing companies. But also, you've been involved in we capital for a long time. Can you talk about that? Because that's a specific supporting women entrepreneurs initiative. Um, yeah. What's up with capital share? That >>was That was another venture that I-i embarked on with such coz. Um as well as Sheila Johnson and Jonny Adam, Person who runs Rethink Impact. We capital is a group of about 16 women that I pulled together women investors to invest through rethink impact, which is another fun that is looking for impact businesses but predominantly looking for those businesses that are led by women. So this investment group is women supporting women. Um, through the use of deployment of capital, um, they're doing amazingly well. They've had some really stunning news recently that I'll let you dig up. >>I'll definitely thanks for the lead there. I'm gonna go jump on that story. >>Yeah, >>the Okay, Thanks for that lead on that trend, though in Silicon Valley and certainly in other areas that are hot like New York, Boston and D. C. Where you're at, um, you're seeing now multiple years in almost a decade in of the pioneers of these women, only funds or women only firms and your investment. Um, and it's starting to increase to under all underrepresented minorities and entrepreneurs. Right? So take us through how you see that because it's just getting more popular. Is that going to continue to accelerate in your mind? Are their networks of networks. They cross pollinating. >>Yeah, I think you know, it's It's I'm glad to see it. And, you know, it's been a long time coming. I think you know, I think we all look forward to a future where it's not necessary. Um, and you know, funds. Just invest in everyone Until then, making sure that we have specific pools of capital allocated to ensure that that, you know, those entrepreneurs who have not always been equally represented get to pursue their ideas not just because they deserve to pursue their ideas, but because the world needs their ideas. Right. And as I mentioned, there is a business imperative, right? We've got lots of examples of businesses like banks that you wouldn't have gotten a shot just because the investors just didn't understand the opportunity. Um, and I think that's normal. That's human. It happens to everyone. You are successful as an investor largely because you recognize patterns. And if something is, you know, outside of your life experience, you are not going to identify it. So it's very important that we create different kinds of capital run by different types of people. Um, and, uh, and you know. I know lots of investors have every type that are investing in these funds because they recognize that, you know, perhaps the highest growth potential is gonna come out of these, you know, particular kind of funds, which is really exciting. >>That's super important, because half the world is women, and that's just like the population is inspired by many new ventures. And that's super exciting trend. I wanna ask you about your other areas of doing a lot of work in the queue has been to buy multiple times, um, initially reporting on a region out there, and that's certainly isn't important part of the world. Um, you've got a lot of good news going on there. Can you share what's going on with, uh, the social entrepreneurship going on in Bahrain around the region? >>Yeah, I'm happy to. We we've actually been so privileged to work with a W S for a very long time. Almost since the start of the incubator they've supported are entrepreneurs, all of our entrepreneurs with access to cloud credits and services. Um, and we've sort of double down with a W S in the last couple of years in areas where We both want to create an uplift, um, for small businesses and rapidly growing tax solutions to these these social environmental problems. We see. So there's been an excellent partner to do that. And one of the areas we did in the water was with rain, particularly with women, tech startups, women tech startups in Bahrain. Yeah, we did that last year. We had an amazing group of women over in D. C. Um, and we continue to support them. One of them is actually in the process of raising. I think she just closed her seed round recently. And that's why for, um, al yet, um, and she created playbook, which is an amazing, uh, platform for women to take master classes and network and really sort of level up, as one says, Um, but also, um, the mall of work. Um uh, just really talented women over in Bahrain, um, pushing the envelope and all sorts of directions, and it was wonderful to get the opportunity to work with them. Um, that has now spawned another set of programs serving entrepreneurs in the Middle East in North Africa. They were also working on with us as well as the U S. State Department. Um, so we're going to be working for the next two years with entrepreneurs to help our recovery from covid. Um, in China. Um, and then I'm also proud to say that we're working with a W s in South Africa because there is just an extraordinary energy, you know, in the continent, Um, and some amazing entrepreneurial minds working on, you know, the many problems and opportunities that they're facing and recognizing. Um So we're supporting, you know, companies that are working on finding, um, skilled refugees to be able to help them resettle and use their talents and make money. Um, sadly, are very relevant company now with what's going on in Ukraine. Um, but also, uh, zombie and satellite company, um, companies that are preventing food, food waste by providing, um, solar-powered refrigerators to rural areas in South Africa. Um, so a lot of, um, you know, just incredible talent and ideas that we're seeing globally. Um, and happy to be doubling down on that with the help of a W s. >>That's awesome. Yeah, following the work when we met in D. C. And again, you always had this international view um it's International Women's Day. It's not North America >>Women's Day. It's >>International Women's Day. Can you share your thoughts on how that landscape is changing outside the U. S. For example, and around the world and how the international peace is important and you mentioned pattern matching? Um, you also, when you see patterns, they become trends. What do you see forming that have been that that are locked in on the U. C they're locked in on that are happening that are driving. What are some of those trends that you see on the international side that's evolving? >>Yeah. You know, I think the wonderful opportunity with the Internet and social media is that, you know, both, uh, we can be more transparent about areas for improvement and put a little pressure where maybe things are moving fast enough. We've all seen the power of that, Um, the other, um, you know, things that certainly in countries where women maybe as free to move and operate, they can still acquire skills education they can set up cos they can do so so much. Um, you know, through these amazing technologies that we now have at our disposal growing an amazing rates. Um, they can connect via zoom. Right? I think that while the pandemic definitely set women back and we should acknowledge that, um, uh, the things that the pandemic perhaps helped us to exponentially scale will move women forward. And perhaps that's the target to hang on to, to feel optimistic about where we're headed. >>And also, there's a lot of problems to solve. And I think one of the things we're seeing you mentioned the Ukraine situation. You're seeing the geopolitical landscape changing radically with technology driving a lot of value. So with problems comes opportunities. Um, innovation plays a big role. Can you share some of the successful stories that you were inspired by that you've seen, um, in the past couple of years. And as you look forward, what What some of those innovation stories look like? And what are you inspired by? >>Yeah. I mean, there's so, so many. Um, you know, we just, uh, had a couple of entrepreneurs, and just the last year, Um, you know, after I think everyone sort of took an initial breath with the pandemic, They realize that they either had an opportunity or they had a problem to solve to your point. Um, and they did that well or not. And or some of them, you know, just didn't didn't have any more cards to play and had to really pivot. Um, it was really interesting to see how everyone handled handled that particular moment in time. One company that I think of is everywhere. Um, and she had created a wearable device that you can just put on your ear. It looks like an earring right at the top of your ear. Um, and it was for her for herself because she suffered from pulmonary complications. And, uh, without more discreet wearable, you know, had to wear a huge device and look around and oxygen tank and, you know, just to sort of have a good quality of life. Um, it turns out, obviously, during covid, that is a very useful item, not just for patients suffering from covid and wanting to know what their oxygen levels were doing, but also potentially athletics. So, um, she's really been able to double down as a result of the trends from the pandemic. Um, and I'm really proud of part of her. And that's actually where another great one that we just just came through. Our last 15 is Maya. Um, and she had a brick and mortar store. Um, uh, called Cherry Blossom. Intimate where she helped women have an enjoyable experience finding, uh, and fitting bras post mastectomy to include sort of, you know, the necessary, um, prosthetics and things like that. Um, she even made it so that you could go with your friends who haven't had a mistake, and she could also find some lovely luxury. Um, but the pandemic meant that that experience was sort of off the table. Um, and what they did was she decided to make it a technological one. So now she's she's essentially will be part of it. You can, you know, go to my, um, online. And you can, um, you know, order, uh, measure yourself, work with a specialist, all online, get a few different options, figure out the one that's perfect for you and the rest back. Um, and I don't think without the pandemic, that would not have happened. So she's now able to serve exponentially more. Um, you know, women who deserve to feel like themselves post it to me. >>That's also a model and inspirational. I have to ask you for the young women out there watching. What advice would you share with them as they navigate into a world that's changing and evolving and getting better with other women, mentors and entrepreneurs and or just an ecosystem of community? What advice would you give them as they step into the world and have to engage and experience life? >>Yeah, gosh, part of me always wants to resist that they don't listen to anyone to do you follow your heart, follow your gut, or at least be careful who you listen to because a lot of people will want to give you advice. I would >>say, Uh, that's good advice. Don't take my advice. Well, you've been a great leader. Love the work, you're doing it and I'll say N D. C. But all around the world and again, there's so much change going on with innovation. I mean, just the advances in technology across the board, from with machine learning and AI from linguistics and understanding. And I think we're going to be a bigger community. Your thoughts on as you see community organically becoming a big part of how people are engaging. What's your what's your view As you look out across the landscape, communities becoming a big part of tribes. What's your vision on how the role of communities place? >>You know, we we actually do you think a lot about community and healthy. And we say that are you know, alchemy really is providing space, you know, physical and mental space to think, um, access access to capital access to networks, Um, community, Um, and the community piece is very, very important. Are entrepreneurs leave us like the number one thing that they miss is being among like-minded, um, you know, slightly slightly crazy audacious people. Um, and I often joked that we're building a kind army because it is, you know, it's people who want to do it differently if people want to do it with integrity. Is people who are in it for a very different motivations than just money. Um, and, you know, you start to feel the power of that group together and its entirety and what that might look like as as a community solving global problems. Um, and it really is inspiring. Um, I do think that people are starving for FaceTime and people time, real human time after the pandemic, I think they won't go away. It's a great tool, but we all want a little bit of that, and I will mention just along those lines. And if you don't mind a quick plug for an event that we're having March 16, Um, also in partnership with a W s called Build her relevant to International Women's Day as well. People can, either. If they're in the city, they can come in person. But we also have a virtual program, and we'll be listening to some of the most inspiring. Women leaders and entrepreneurs both in government and also the private sector share their knowledge on the side of the pandemic for for, you know, the next tribal group of women entrepreneurs and leaders. >>That's great. Well, you are on our website for sure. >>Thank you. Thank you. Appreciate it. >>And we love the fact that you're in our community as well. Doing great work. Thanks for spending time with the Cube and on International Women's Day celebration. Thanks for coming on and sharing. >>Thank you, John. >>Okay. The Cube International showcase Women's Day, featuring some great guests all around the world, Not just in the U S. But all over the world. I'm your host. Thanks for watching. Yeah, Yeah, yeah, hm, Yeah.

>>from >>Around the globe, it's the cube with digital coverage of IBM think 2020 >>one brought to you by IBM. Hello everyone and welcome back to the cubes ongoing virtual coverage of IBM think 2021 this is our second virtual think and we're going to talk about what's on the minds of C. T. O. S with a particular point of view from the EMEA region. I'm pleased to welcome rasheed Parmer, who is an IBM fellow and vice president of technology for Armenia that region. Hello rashid, Good to see you. >>Hey David, great to see you. >>So let me start by by asking talk a little bit about the role of the C. T. O. And why is it necessarily important to focus on the C. T. O. Role versus say some of the other technology practitioner roles? >>Yeah. You know, you know, they as you look at all the range of roles of the got in in the I. T. Department, the CTO is uniquely placed in looking forward how technology and how digitization is gonna make a difference in the business but also at the same time is there as the kind of thought leader for how they're going to really you re imagine the use of technology reimagine automation, reimagining, how digitalization helps them go to market different ways. So the CTO is a unique unique position from idea to impact. And in the past we've kind of lost the C. T. A little bit but they're now re emerging as being the thought leader that's owning and driving digitalization going forward in our big plants. >>Yeah I agree. And it really has a deep understanding of that vision and can apply that vision to business success. So you obviously have a technical observation space and you also have some data so maybe you could share with our audience how you inform yourself and your colleagues and IBM on on what C. T. O. S. Are thinking about and what they're worried about. >>Yeah. So what we've done over the last four years now is gone out and interviewed Cdos and we do a very unstructured interviews. It's not it's not a survey in the form of uh you know, filling these uh these 10 questions and tell us yes or no. It really is a structured interviews. We asked things like what's top of mind for you, what are the decisions you're making? What's holding you back? What decisions do you think you shouldn't have made or you wouldn't have liked to make? And it's that range of a real input from the the interview. So last year we interviewed 100 CTO s um this year we're actually doing a lot more. We're working with the IBM Institute Business Value and we're gonna interview a lot more teachers but but the material we're gonna talk about today is is really from those 100 CTO interviews. >>Yeah. And I think that having done a lot of these myself, when you do those, we call them, you know in depth interviews, our I. D. S. You kind of have a structure and you sort of follow that but you learn so much and that it maybe does inform those more structured interviews that you do down the road. You learn so much, but maybe you could summarize some of the concerns in the region. What's on the minds of Ceos? >>Yeah. And you know, the the real decisions are made based around seven points. Right? So the first one is we all know, we're on a journey to the cloud but it's a hybrid multi cloud. How do I think about the range of capabilities and need to be able to unlock the latent potential of existing investments and the cloud based capabilities of God. So, so the hybrid cloud platform is one of the the first and foundational pieces. The second challenge is the C e O s want to modernize their applications and that modernization is a journey of moving towards microservices. That microservices journey has two parts. One is the business facing view and that's what containers is all about, choosing the right container platform at the same time. They also want to use containers as a way of automation and management and reducing the effort in the infrastructure. So, so that's kind of two parts of the whole container journey. So Microsoft, this has really become the business developer view and containers become the operational view At the same time. They want infused new data, they want to climb the ladder, they want to get the new new insights from that data that plugs into those new workflows to get to those workflows. There's a decision around how do I isolate myself from some of the services of using that? And we created a layer in the decisions around what's called cloud services integration. So cloud services integration is kind of the modern day E S B as we might think about it, but it's a way in which you choose which technology, which a P I is. I'm going to use from where and then ultimately, the CTS are trying to build what are the new, the new workflows, intelligent workflows and they're really worried about how do I get the right level of automation that managing that issue between what becomes creepy and valuable, Right? You know, the some workflows that happen, you think, why the hell did that happen? Right. That doesn't make sense. And and and and it really sort of nerves. The consumer, the user where some which are, wow, that's really cool. I really enjoyed that. To try to get the intelligent workflows right is a big concern. And then on the two big perils of that is how do we manage the system, the operational automation right from having the right data observe ability of all the infrastructure, recognizing they've got a spectrum of things from 30 40 50 year old systems to modern day cloud native systems, how to manage how operationally automate that keep that efficient, effective. And then of course protecting from the perpetrators, right? Business, a lot of people out there wanting to begin to the systems and, and, and and draw all kinds of, you know, a data from their system. So security, privacy and making sure that align with the ethics and privacy of the business. So those are those are the kind of range of issues right from the journey to cloud, through to operational automation, through through intelligent workflows, right into manage and protecting the services. >>It's interesting. Thank you for that. I mean I remember and you will as well some of the post Y two K you know, thrust and part part of the modernization back then was during that they had budget to do that. But a lot of times organizations would make the mistake that they would they're going to migrate off of a system that was working just fine. That was there sort of mental model of of modernization. And it turned out to be disastrous in many cases. And so when I talk to Ceos they talk about maybe, you know, I'd look at it is this this abstraction layer we want to protect what we have that works. Yes. Some stuff is going to go into the public cloud, but this hybrid connection that you talk about and then we want control and the way we're gonna get control is we're gonna use microservices to modernize and use modern A. P. I. S. And so very very sort of different thinking. And of course they want to avoid migration at all costs because it's so expensive and risky. I wonder if you could talk about, are there any patterns in terms of where people get started and the kinds of outcomes that they're working towards that they can measure? >>Yeah, we we kind of lumped the learning from the work into three broad patterns, right? Um one pattern is primarily around survival. They recognize that this journey is very complex. The pandemic has created tremendous challenges. The market dynamics means they've got to try and really be thoughtful in in taking cost out and making sure they survive some of these issues. And so the pattern is really around cost reduction. It may start with a hybrid cloud, it may start with intelligent workflows but it's really about taking costs out of the systems. The second pattern is what is referred to as a simplification pattern and this is about saying but we've got we've got so much complexity because of technical debt because of you know systems that we've half migrated and half done things with. So how do I how do I simplify my I. T. Landscape from applications through infrastructure for data and make it more consistent, manageable and and effective. And then the 3rd 1 is their city is saying look we've got a really pick the time when we super scale something, we've got something which we are unique and effective on and I want to take that and really super scale that very quickly and make that consistent and really maximize value of it so that the pattern is really fall into three categories of driving, driving, cost reduction and survival, simplification and modernisation transformation. And then those that have got something which is unique and special and really super scaring up. >>Yeah. Right, right, doubling down on those things. That unique competitive advantage in the, in the studies that you've done over the years. You use this term ADP architectural decision points and some of them are quite compelling. Maybe you could talk about some of those. Were there some anxieties from the cdos that you uncovered? >>Yeah. You know, the, the NDP s talk about the 70 Gps and it starts from the higher ability crowd through to two intelligent workflows and so on. And the NDP s themselves are really distilling the client's words and the clients way of thinking about how they're going to drive those, those technologies, um and also how they're going to use those techniques to make a difference. But if we went through those interviews, what became apparent is, see us do have some anxieties as you refer to, and those anxieties, they couldn't necessarily put words on them and their anxieties. Like, are we thinking enough about the carbon footprint? Are we are we being thoughtful in how we make sure we're reducing carbon footprint or reducing the environmental impact of the infrastructure? You've got, we've got sprawling infrastructure um ripping out rare metals from the earth. Are we being thoughtful in how we reduce the amount of rare metals we have water consumption right through to is the code that we're producing efficient, secure and and fit for for the future. Are we being ethical in capturing the data for its right use? Um Is the ai systems that we're building? Are they explainable? Are they ethical? Are they free from bias or are we kind of amplifying things that we shouldn't be amplifying? So there was a whole bunch of those call anxieties and what we did along with the architectural decision report. A point after decision report was was identify what we call a set of responsibilities. And and we've built a framework about around responsible computing which is which is a basis for how you think through what your responsibilities are as a as a Ceo are as an I. T. Leader. And we're right in the process of building out that that kind of responsible computing framework. >>You know it's interesting a lot of people may may think about they think about the responsible computing and and and the sustainability and they might think that's a 1 80 from Milton Friedman Economics, which is the job of businesses to make profits. But in fact responsible computing, there's a strong business case around it. It actually can help you reduce costs that can help you attract better employees. Because young people are passionate about this. I wonder if you could talk about how how people can get involved with responsible computing and lean in. >>Yeah, so what we're about to publish it is actually manifesto for responsible computing. So I think everybody wants to get that published. I'm hoping to do that in the next two or three months. We're working with a few clients. So there's actually three clients that have chosen through your client cts from the ones that we interviewed were very keen to collaborate with us in laying out that that manifesto and the opportunity really is from anybody listening. If if you if you find this of great value, please do come and reach out to me more than happy to collaborate. We're looking for more insights on this. We've also had some competitions. So in in in a media we've had a competition with business partners, looking for ideas of how we can really showcase examples or exemplars of being responsible computing provider, whether it's at the level of responsible data center, whether it's about responsible code data, use Responsible systems right through the responsible impact. And obviously a lot of our work around things like your tech for good is tied directly to responsible impact. And of course, if you want to see what we have never been doing are responsible responsibility report, which we've been voluntarily publishing for the last 30 years, provides a tremendous set of insights on how we've done that over the years. And and that's a that's a great way for you to see how we've been doing things and see if there are people in your business. >>Yeah. So there's so there's the, the ADP report is available. You can check it out on on linkedin. Um, go to, go to Russia linked in profile, you'll find it. There's a blog post that talks about the next wave of, of digitization, uh, you know, the learnings that you just talked about. So there's a lot of resources for for people to get involved. I'll give you the last word. >>Yeah. And look, this is this is what I call job big and it's not job done that the whole ADP responsible computing is a digitization journey where we want to balance delivering business value and making a difference to the organization, but at the same time being responsible in making sure that we're thoughtful what's needed for the future and we create impact that really matters. And we can feel proud that we've put a foundation for digitization which will which will serve the businesses for many years to come, >>love it, impact investing in your business and in the future. Russia, thanks so much for coming on the cube. Really appreciate it. >>A pleasure. Thank you. >>Okay, keep it right there for more coverage from IBM think 2021 this is Dave Volonte for the Cube. Yeah, yeah.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle in 2000 >>nine. Hal Varian, Google's chief economist, said that statisticians would be the sexiest job in the coming decade. The modern big data movement >>really >>took off later in the following year. After the Second Hadoop World, which was hosted by Claudette Cloudera in New York City. Jeff Ham Abakar famously declared to me and John further in the Cube that the best minds of his generation, we're trying to figure out how to get people to click on ads. And he said that sucks. The industry was abuzz with the realization that data was the new competitive weapon. Hadoop was heralded as the new data management paradigm. Now, what actually transpired Over the next 10 years on Lee, a small handful of companies could really master the complexities of big data and attract the data science talent really necessary to realize massive returns as well. Back then, Cloud was in the early stages of its adoption. When you think about it at the beginning of the last decade and as the years passed, Maurin Mawr data got moved to the cloud and the number of data sources absolutely exploded. Experimentation accelerated, as did the pace of change. Complexity just overwhelmed big data infrastructures and data teams, leading to a continuous stream of incremental technical improvements designed to try and keep pace things like data Lakes, data hubs, new open source projects, new tools which piled on even Mawr complexity. And as we reported, we believe what's needed is a comm pleat bit flip and how we approach data architectures. Our next guest is Jean Marc de Connie, who is the director of emerging technologies That thought works. John Mark is a software engineer, architect, thought leader and adviser to some of the world's most prominent enterprises. She's, in my view, one of the foremost advocates for rethinking and changing the way we create and manage data architectures. Favoring a decentralized over monolithic structure and elevating domain knowledge is a primary criterion. And how we organize so called big data teams and platforms. Chamakh. Welcome to the Cube. It's a pleasure to have you on the program. >>Hi, David. This wonderful to be here. >>Well, okay, so >>you're >>pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms that scale. Why do you feel we need such a radical change? What's your thoughts there? >>Well, I think if you just look back over the last decades you gave us, you know, a summary of what happened since 2000 and 10. But if even if we go before then what we have done over the last few decades is basically repeating and, as you mentioned, incrementally improving how we've managed data based on a certain assumptions around. As you mentioned, centralization data has to be in one place so we can get value from it. But if you look at the parallel movement off our industry in general since the birth of Internet, we are actually moving towards decentralization. If we think today, like if this move data side, if he said the only way Web would work the only way we get access to you know various applications on the Web pages is to centralize it. We would laugh at that idea, but for some reason we don't. We don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, you know, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organization there beyond the bounds of organization. And then look back and say Okay, if that's the trend off our industry in general, Um, given the fabric of computation and data that we put in, you know globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we, you know, put a technology in place, um, to to look at it from a decentralized angle. >>Okay, so let's let's unpack that a little bit. I mean, you've spoken about and written that today's big architecture and you basically just mentioned that it's flawed, So I wanna bring up. I love your diagrams of a simple diagram, guys, if you could bring up ah, figure one. So on the left here we're adjusting data from the operational systems and other enterprise data sets and, of course, external data. We cleanse it, you know, you've gotta do the do the quality thing and then serve them up to the business. So So what's wrong with that picture that we just described and give granted? It's a simplified form. >>Yeah, quite a few things. So, yeah, I would flip the question may be back to you or the audience if we said that. You know, there are so many sources off the data on the Actually, the data comes from systems and from teams that are very diverse in terms off domains. Right? Domain. If if you just think about, I don't know retail, Uh, the the E Commerce versus Order Management versus customer This is a very diverse domains. The data comes from many different diverse domains. And then we expect to put them under the control off a centralized team, a centralized system. And I know that centralization. Probably if you zoom out, it's centralized. If you zoom in it z compartmentalized based on functions that we can talk about that and we assume that the centralized model will be served, you know, getting that data, making sense of it, cleansing and transforming it then to satisfy in need of very diverse set of consumers without really understanding the domains, because the teams responsible for it or not close to the source of the data. So there is a bit of it, um, cognitive gap and domain understanding Gap, um, you know, without really understanding of how the data is going to be used, I've talked to numerous. When we came to this, I came up with the idea. I talked to a lot of data teams globally just to see, you know, what are the pain points? How are they doing it? And one thing that was evident in all of those conversations that they actually didn't know after they built these pipelines and put the data in whether the data warehouse tables or like, they didn't know how the data was being used. But yet the responsible for making the data available for these diverse set of these cases, So s centralized system. A monolithic system often is a bottleneck. So what you find is, a lot of the teams are struggling with satisfying the needs of the consumers, the struggling with really understanding the data. The domain knowledge is lost there is a los off understanding and kind of in that in that transformation. Often, you know, we end up training machine learning models on data that is not really representative off the reality off the business. And then we put them to production and they don't work because the semantic and the same tax off the data gets lost within that translation. So we're struggling with finding people thio, you know, to manage a centralized system because there's still the technology is fairly, in my opinion, fairly low level and exposes the users of those technologies. I said, Let's say warehouse a lot off, you know, complexity. So in summary, I think it's a bottleneck is not gonna, you know, satisfy the pace of change, of pace, of innovation and the pace of, you know, availability of sources. Um, it's disconnected and fragmented, even though the centralizes disconnected and fragmented from where the data comes from and where the data gets used on is managed by, you know, a team off hyper specialized people that you know, they're struggling to understand the actual value of the data, the actual format of the data, so it's not gonna get us where our aspirations and ambitions need to be. >>Yes. So the big data platform is essentially I think you call it, uh, context agnostic. And so is data becomes, you know, more important, our lives. You've got all these new data sources, you know, injected into the system. Experimentation as we said it with the cloud becomes much, much easier. So one of the blockers that you've started, you just mentioned it is you've got these hyper specialized roles the data engineer, the quality engineer, data scientists and and the It's illusory. I mean, it's like an illusion. These guys air, they seemingly they're independent and in scale independently. But I think you've made the point that in fact, they can't that a change in the data source has an effect across the entire data lifecycle entire data pipeline. So maybe you could maybe you could add some color to why that's problematic for some of the organizations that you work with and maybe give some examples. >>Yeah, absolutely so in fact, that initially the hypothesis around that image came from a Siris of requests that we received from our both large scale and progressive clients and progressive in terms of their investment in data architectures. So this is where clients that they were there were larger scale. They had divers and reached out of domains. Some of them were big technology tech companies. Some of them were retail companies, big health care companies. So they had that diversity off the data and the number off. You know, the sources of the domains they had invested for quite a few years in, you know, generations. If they had multi generations of proprietary data warehouses on print that they were moving to cloud, they had moved to the barriers, you know, revisions of the Hadoop clusters and they were moving to the cloud. And they the challenges that they were facing were simply there were not like, if I want to just, like, you know, simplifying in one phrase, they were not getting value from the data that they were collecting. There were continuously struggling Thio shift the culture because there was so much friction between all of these three phases of both consumption of the data and transformation and making it available consumption from sources and then providing it and serving it to the consumer. So that whole process was full of friction. Everybody was unhappy. So its bottom line is that you're collecting all this data. There is delay. There is lack of trust in the data itself because the data is not representative of the reality has gone through a transformation. But people that didn't understand really what the data was got delayed on bond. So there is no trust. It's hard to get to the data. It's hard to create. Ultimately, it's hard to create value from the data, and people are working really hard and under a lot of pressure. But it's still, you know, struggling. So we often you know, our solutions like we are. You know, Technologies will often pointed to technology. So we go. Okay, This this version of you know, some some proprietary data warehouse we're using is not the right thing. We should go to the cloud, and that certainly will solve our problems. Right? Or warehouse wasn't a good one. Let's make a deal Lake version. So instead of you know, extracting and then transforming and loading into the little bits. And that transformation is that, you know, heavy process, because you fundamentally made an assumption using warehouses that if I transform this data into this multi dimensional, perfectly designed schema that then everybody can run whatever choir they want that's gonna solve. You know everybody's problem, but in reality it doesn't because you you are delayed and there is no universal model that serves everybody's need. Everybody that needs the divers data scientists necessarily don't don't like the perfectly modeled data. They're looking for both signals and the noise. So then, you know, we've We've just gone from, uh, et elles to let's say now to Lake, which is okay, let's move the transformation to the to the last mile. Let's just get load the data into, uh into the object stores into semi structured files and get the data. Scientists use it, but they're still struggling because the problems that we mentioned eso then with the solution. What is the solution? Well, next generation data platform, let's put it on the cloud, and we sell clients that actually had gone through, you know, a year or multiple years of migration to the cloud. But with it was great. 18 months I've seen, you know, nine months migrations of the warehouse versus two year migrations of the various data sources to the clubhouse. But ultimately, the result is the same on satisfy frustrated data users, data providers, um, you know, with lack of ability to innovate quickly on relevant data and have have have an experience that they deserve toe have have a delightful experience off discovering and exploring data that they trust. And all of that was still a missed so something something else more fundamentally needed to change than just the technology. >>So then the linchpin to your scenario is this notion of context and you you pointed out you made the other observation that look, we've made our operational systems context aware. But our data platforms are not on bond like CRM system sales guys very comfortable with what's in the CRM system. They own the data. So let's talk about the answer that you and your colleagues are proposing. You're essentially flipping the architecture whereby those domain knowledge workers, the builders, if you will, of data products or data services there now, first class citizens in the data flow and they're injecting by design domain knowledge into the system. So So I wanna put up another one of your charts. Guys, bring up the figure to their, um it talks about, you know, convergence. You showed data distributed domain, dream and architecture. Er this self serve platform design and this notion of product thinking. So maybe you could explain why this approach is is so desirable, in your view, >>sure. The motivation and inspiration for the approach came from studying what has happened over the last few decades in operational systems. We had a very similar problem prior to micro services with monolithic systems, monolithic systems where you know the bottleneck. Um, the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized and we found a nice nation. I'm not saying this is the perfect way of decoupling a monolith, but it's a way that currently where we are in our journey to become data driven, um is a nice place to be, um, which is distribution or decomposition off your system as well as organization. I think when we whenever we talk about systems, we've got to talk about people and teams that's responsible for managing those systems. So the decomposition off the systems and the teams on the data around domains because that's how today we are decoupling our business, right? We're decoupling our businesses around domains, and that's a that's a good thing and that What does that do really for us? What it does? Is it localizes change to the bounded context of fact business. It creates clear boundary and interfaces and contracts between the rest of the universe of the organization on that particular team, so removes the friction that often we have for both managing the change and both serving data or capability. So it's the first principle of data meshes. Let's decouple this world off analytical data the same to mirror the same way we have to couple their systems and teams and business why data is any different. And the moment you do that, So you, the moment you bring the ownership to people who understands the data best, then you get questions that well, how is that any different from silence that's connected databases that we have today and nobody can get to the data? So then the rest of the principles is really to address all of the challenges that comes with this first principle of decomposition around domain Context on the second principle is well, we have to expect a certain level off quality and accountability and responsibility for the teams that provide the data. So let's bring product thinking and treating data as a product to the data that these teams now, um share and let's put accountability around. And we need a new set of incentives and metrics for domain teams to share the data. We need to have a new set off kind of quality metrics that define what it means for the data to be a product. And we can go through that conversation perhaps later eso then the second principle is okay. The teams now that are responsible, the domain teams responsible for the analytical data need to provide that data with a certain level of quality and assurance. Let's call that a product and bring products thinking to that. And then the next question you get asked off by C. E. O s or city or the people who build the infrastructure and, you know, spend the money. They said, Well, it's actually quite complex to manage big data, and now we're We want everybody, every independent team to manage the full stack of, you know, storage and computation and pipelines and, you know, access, control and all of that. And that's well, we have solved that problem in operational world. And that requires really a new level of platform thinking toe provide infrastructure and tooling to the domain teams to now be able to manage and serve their big data. And that I think that requires reimagining the world of our tooling and technology. But for now, let's just assume that we need a new level of abstraction to hide away ton of complexity that unnecessarily people get exposed to and that that's the third principle of creating Selves of infrastructure, um, to allow autonomous teams to build their domains. But then the last pillar, the last you know, fundamental pillar is okay. Once you distributed problem into a smaller problems that you found yourself with another set of problems, which is how I'm gonna connect this data, how I'm gonna you know, that the insights happens and emerges from the interconnection of the data domains right? It does not necessarily locked into one domain. So the concerns around interoperability and standardization and getting value as a result of composition and interconnection of these domains requires a new approach to governance. And we have to think about governance very differently based on a Federated model and based on a computational model. Like once we have this powerful self serve platform, we can computational e automate a lot of governance decisions. Um, that security decisions and policy decisions that applies to you know, this fabric of mesh not just a single domain or not in a centralized. Also, really. As you mentioned that the most important component of the emissions distribution of ownership and distribution of architecture and data the rest of them is to solve all the problems that come with that. >>So very powerful guys. We actually have a picture of what Jamaat just described. Bring up, bring up figure three, if you would tell me it. Essentially, you're advocating for the pushing of the pipeline and all its various functions into the lines of business and abstracting that complexity of the underlying infrastructure, which you kind of show here in this figure, data infrastructure is a platform down below. And you know what I love about this Jama is it to me, it underscores the data is not the new oil because I could put oil in my car I can put in my house, but I can't put the same court in both places. But I think you call it polyglot data, which is really different forms, batch or whatever. But the same data data doesn't follow the laws of scarcity. I can use the same data for many, many uses, and that's what this sort of graphic shows. And then you brought in the really important, you know, sticking problem, which is that you know the governance which is now not a command and control. It's it's Federated governance. So maybe you could add some thoughts on that. >>Sure, absolutely. It's one of those I think I keep referring to data much as a paradigm shift. And it's not just to make it sound ground and, you know, like, kind of ground and exciting or in court. And it's really because I want to point out, we need to question every moment when we make a decision around how we're going to design security or governance or modeling off the data, we need to reflect and go back and say, um, I applying some of my cognitive biases around how I have worked for the last 40 years, I have seen it work. Or do I do I really need to question. And we do need to question the way we have applied governance. I think at the end of the day, the rule of the data governance and objective remains the same. I mean, we all want quality data accessible to a diverse set of users. And these users now have different personas, like David, Personal data, analyst data, scientists, data application, Um, you know, user, very diverse personal. So at the end of the day, we want quality data accessible to them, um, trustworthy in in an easy consumable way. Um, however, how we get there looks very different in as you mentioned that the governance model in the old world has been very commander control, very centralized. Um, you know, they were responsible for quality. They were responsible for certification off the data, you know, applying making sure the data complies. But also such regulations Make sure you know, data gets discovered and made available in the world of the data mesh. Really. The job of the data governance as a function becomes finding that equilibrium between what decisions need to be um, you know, made and enforced globally. And what decisions need to be made locally so that we can have an interoperable measure. If data sets that can move fast and can change fast like it's really about instead of hardest, you know, kind of putting the putting those systems in a straitjacket of being constant and don't change, embrace, change and continuous change of landscape because that's that's just the reality we can't escape. So the role of governance really the governance model called Federated and Computational. And by that I mean, um, every domain needs to have a representative in the governance team. So the role of the data or domain data product owner who really were understand the data that domain really well but also wears that hacks of a product owner. It is an important role that had has to have a representation in the governance. So it's a federation off domains coming together, plus the SMEs and people have, you know, subject matter. Experts who understands the regulations in that environmental understands the data security concerns, but instead off trying to enforce and do this as a central team. They make decisions as what need to be standardized, what need to be enforced. And let's push that into that computational E and in an automated fashion into the into the camp platform itself. For example, instead of trying to do that, you know, be part of the data quality pipeline and inject ourselves as people in that process, let's actually, as a group, define what constitutes quality, like, how do we measure quality? And then let's automate that and let Z codify that into the platform so that every native products will have a C I City pipeline on as part of that pipeline. Those quality metrics gets validated and every day to product needs to publish those SLOC or service level objectives. So you know, whatever we choose as a measure of quality, maybe it's the, you know, the integrity of the data, the delay in the data, the liveliness of it, whatever the are the decisions that you're making, let's codify that. So it's, um, it's really, um, the role of the governance. The objectives of the governance team tried to satisfies the same, but how they do it. It is very, very different. I wrote a new article recently trying to explain the logical architecture that would emerge from applying these principles. And I put a kind of light table to compare and contrast the roll off the You know how we do governance today versus how we will do it differently to just give people a flavor of what does it mean to embrace the centralization? And what does it mean to embrace change and continuous change? Eso hopefully that that that could be helpful. >>Yes, very so many questions I haven't but the point you make it to data quality. Sometimes I feel like quality is the end game. Where is the end game? Should be how fast you could go from idea to monetization with the data service. What happens again? You sort of address this, but what happens to the underlying infrastructure? I mean, spinning a PC to S and S three buckets and my pie torches and tensor flows. And where does that that lives in the business? And who's responsible for that? >>Yeah, that's I'm glad you're asking this question. Maybe because, um, I truly believe we need to re imagine that world. I think there are many pieces that we can use Aziz utilities on foundational pieces, but I but I can see for myself a 5 to 7 year roadmap of building this new tooling. I think, in terms of the ownership, the question around ownership, if that would remains with the platform team, but and perhaps the domain agnostic, technology focused team right that there are providing instead of products themselves. And but the products are the users off those products are data product developers, right? Data domain teams that now have really high expectations in terms of low friction in terms of lead time to create a new data product. Eso We need a new set off tooling, and I think with the language needs to shift from, You know, I need a storage buckets. So I need a storage account. So I need a cluster to run my, you know, spark jobs, too. Here's the declaration of my data products. This is where the data for it will come from. This is the data that I want to serve. These are the policies that I need toe apply in terms of perhaps encryption or access control. Um, go make it happen. Platform, go provision, Everything that I mean so that as a data product developer. All I can focus on is the data itself, representation of semantic and representation of the syntax. And make sure that data meets the quality that I have that I have to assure and it's available. The rest of provisioning of everything that sits underneath will have to get taken care of by the platform. And that's what I mean by requires a re imagination and in fact, Andi, there will be a data platform team, the data platform teams that we set up for our clients. In fact, themselves have a favorite of complexity. Internally, they divide into multiple teams multiple planes, eso there would be a plane, as in a group of capabilities that satisfied that data product developer experience, there would be a set of capabilities that deal with those need a greatly underlying utilities. I call it at this point, utilities, because to me that the level of abstraction of the platform is to go higher than where it is. So what we call platform today are a set of utilities will be continuing to using will be continuing to using object storage, will continue using relation of databases and so on so there will be a plane and a group of people responsible for that. There will be a group of people responsible for capabilities that you know enable the mesh level functionality, for example, be able to correlate and connects. And query data from multiple knows. That's a measure level capability to be able to discover and explore the measure data products as a measure of capability. So it would be set of teams as part of platforms with a strong again platform product thinking embedded and product ownership embedded into that. To satisfy the experience of this now business oriented domain data team teams s way have a lot of work to do. >>I could go on. Unfortunately, we're out of time. But I guess my first I want to tell people there's two pieces that you put out so far. One is, uh, how to move beyond a monolithic data lake to a distributed data mesh. You guys should read that in a data mesh principles and logical architectures kind of part two. I guess my last question in the very limited time we have is our organization is ready for this. >>E think the desire is there I've bean overwhelmed with number off large and medium and small and private and public governments and federal, you know, organizations that reached out to us globally. I mean, it's not This is this is a global movement and I'm humbled by the response of the industry. I think they're the desire is there. The pains are really people acknowledge that something needs to change. Here s so that's the first step. I think that awareness isa spreading organizations. They're more and more becoming aware. In fact, many technology providers are reach out to us asking what you know, what shall we do? Because our clients are asking us, You know, people are already asking We need the data vision. We need the tooling to support. It s oh, that awareness is there In terms of the first step of being ready, However, the ingredients of a successful transformation requires top down and bottom up support. So it requires, you know, support from Chief Data Analytics officers or above the most successful clients that we have with data. Make sure the ones that you know the CEOs have made a statement that, you know, we want to change the experience of every single customer using data and we're going to do, we're going to commit to this. So the investment and support, you know, exists from top to all layers. The engineers are excited that maybe perhaps the traditional data teams are open to change. So there are a lot of ingredients. Substance to transformation is to come together. Um, are we really ready for it? I think I think the pioneers, perhaps the innovators. If you think about that innovation, careful. My doctors, probably pioneers and innovators and leaders. Doctors are making making move towards it. And hopefully, as the technology becomes more available, organizations that are less or in, you know, engineering oriented, they don't have the capability in house today, but they can buy it. They would come next. Maybe those are not the ones who aren't quite ready for it because the technology is not readily available. Requires, you know, internal investment today. >>I think you're right on. I think the leaders are gonna lead in hard, and they're gonna show us the path over the next several years. And I think the the end of this decade is gonna be defined a lot differently than the beginning. Jammeh. Thanks so much for coming in. The Cuban. Participate in the >>program. Pleasure head. >>Alright, Keep it right. Everybody went back right after this short break.

>>on >>the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Okay. Welcome back, everyone. That's the cubes. Live coverage here in Palo Alto, California. I'm John for your host with David Lantana in Boston. Massachusetts. Uh, we got a great panel here. Analysts just gonna break it down. Keynote analysis. Day one, we got Ah, longtime Web services expert analyst Diane Hinchcliffe, principal researcher at N V. P. It constantly research, but he goes way back. Dan, I remember, uh, 2000 and one time frame you and I'm >>reading Last time you and I hang out with Michael Arrington's house back in the TechCrunch days >>back when, you know you were on this was Web services. I mean, that's always, uh, serves on the architectures. They called it back then. This was the beginning. This really was the catalyst of cloud. If you think about virtualization and Web services in that era, that really spawned where we are today so great to >>have you on as an Amazon got their start saying that everyone could get whatever they want to on a P. I now right, >>all right? Well, we've been riding this wave. Certainly it's cotton now more clear for the mainstream America. And I quoted you in my story, uh, on Andy Jassy when I had my one on one with them because I saw your talk with star Bit of the weekend and in the way you kicked it off was the Pandemic four was forced upon everybody, which is true, and that caught my attention was very notable because you talked to a lot of C E. O s. Does jazz sees pitch resonate with them? In your opinion, what's your take on on that on that posture? Because we heard, hey, you know, get busy building or you're dying, right? So get busy building. That's what >>I thought that was a good message. But I mean on and certainly I saw tweets and said, Hey, he's just he's just directly talking to the CEO. But if you ask me, he's still talking to the CTO, right? The technology officer who's got a feels all this technology and bend it into the shape that it will serve the business. You talk to a CEO who wants is trying to get on the cloud their biggest challenges. I know I need armies of people who know all these brand new services. You saw the development velocity of all the things that they announced and things they re emphasized there was There was a lot of things that were bringing back again because they have so many things that they're offering to the public. But the developer skills or not, they're the partner skills are not there. So you talked to CEO, says All right, I buy in and and I have had to transform overnight because of the pandemic, my customers have moved, my workers have moved on, and I have to like, you know, redirect all my I t Overnight and Cloud is the best way to do that. Where's my where's all the skills for the training programs, the department programs that allow me to get access to large amounts of talent? Those are the types of things that the CEO is concerned about is from an operational perspective. We didn't hear anything about, like a sales force type trailhead where we're going to democratize cloud skills to the very far end of your organization. >>Yeah, they're just kind of scratching the service. They didn't mention that, you know, far Gates away to get into server list. I mean, this is ultimately the challenge Dave and Deena like, don't get your thoughts on this because I was talking Teoh a big time CTO and a big time see so and that perspectives were interesting. And here's the Here's the Here's what I want you to react Thio the sea level Say everything is gonna be a service. Otherwise we're gonna be extinct. Okay, that's true. I buy that narrative, Okay, Make it as a service. That's why not use it. And then they go to the C t. And they say, implement, They go Well, it's not that easy. So automation becomes a big thing. And then so there's this debate. Automate, automate, automate. And then everything becomes a service. Is it the cart before the horse? So is automation. It's the cart before the horse, for everything is a service. What do you guys think about that? >>We'll see. I mean, CEO is to Diane's point, are highly risk averse and they like services. And those services generally are highly customized. And I think the tell in the bevy of announcements the buffet have announces that we heard today was in the marketplace what you guys thought of this or if you caught this. But there was a discussion about curated professional services that were tied to software, and there were classic PDM services. But they were very, you know, tight eso sort of off the shelf professional services, and that's kind of how Amazon plays it. And they were designed to be either self serve. It's a Diane's point. Skill sets aren't necessarily there or third parties, not directly from Amazon. So that's a gap that Amazon's got too close. I mean, you talk about all the time without post installations, you know, going on Prem. You know who's gonna support and service those things. You know, that's a that's a white space right now. I think >>e think we're still reading the tea leaves on the announcements. But there was one announcement that was, I thought really important. And that was this VM Ware cloud for a W s. It says, Let's take your VM ware skills, which you've honed and and cultivated and built a talent base inside your organization to run VMS and let's make that work for a W s. So I thought the VM Ware cloud for a W s announcement was key. It was a sleeper. It didn't spend a lot of time on it. But the CEO ears are gonna perk up and say, Wait, I can use native born skills. I already have to go out to the cloud So I didn't think that they did have 11 announcement I thought was compelling in that >>in the spending data shows of VM Ware Cloud on AWS is really gaining momentum by the way, As you see in that open shift So you see in that hybrid zone really picking up. And we heard that from AWS today. John, you and I talked about it at the open I produces in >>Yeah, I want to double down on that point you made because I want to get your thoughts on this a Z analyst because you know, the VM ware is also tell. Sign to what I'm seeing as operating and developing Dev ops as they be called back in the day. But you gotta operate, i t. And if Jassy wants to go after this next tier of spend on premise and edge. He's gotta win the global i t posture game. He's gotta win hybrid. He's got to get there faster to your point. You gotta operate. It's not just develop on it. So you have a development environment. You have operational environment. I think the VM Ware thing that's interesting, cause it's a nice clean hand in glove. VM Ware's got operators who operate I t. And they're using Amazon to develop, but they work together. There's no real conflict like everyone predicted. So is that the tell sign is the operational side. The challenge? The Dev, How does Amazon get that global I t formula down? Is it the VM Ware partnership? >>I think part of it is there, finally learning to say that the leverage that the vast pool of operational data they have on their literally watching millions of organizations run all the different services they should know a lot and I say made that point today, he said, Well, people ask us all the time. You must have all these insights about when things were going right or wrong. Can you just tell us? And so I think the announcement around the Dev ops guru was very significant, also saying you don't necessarily have to again teach all your staff every in and out about how to monitor every aspect of all these new services that are much more powerful for your business. But you don't yet know how to manage, especially at scale. So the Dev Ops guru is gonna basically give a dashboard that says, based on everything that we've known in the past, we could give you insights, operational insights you can act on right away. And so I think that is again a tool that could be put in place on the operational side. Right. So b m where for cloud gives you migration ability, uh, of existing skills and workloads. And then the Dev Ops crew, if it turns out to be everything they say it is, could be a really panacea for unlocking the maturity curve that these operators have to climb >>on. AWS is in the business now of solving a lot of the problems that it sort of helped create. So you look at, for instance, you look at the sage maker Data Wrangler trying to simplify data workloads. The data pipeline in the cloud is very very complex and so they could get paid for helping simplify that. So that's a wonderful, virtuous circle. We've seen it before. >>Yeah. I mean, you have a lot of real time contact lens you've got, um, quick site. I mean, they have to kind of match the features. And And I want to get your guys thoughts on on hybrid because I think, you know, I'm still stuck on this, Okay? They won the as path and their innovations Great. The custom chips I buy that machine learning all awesome. So from the classic cloud I as infrastructure and platform as a service business looking good. Now, if you're thinking global, I t I just don't just not connecting the dots there. See Outpost? What's riel today for Amazon? Can you guys share E? I mean, if you were watching this keynote your head explode because you've got so many announcements. What's actually going on if you're looking at this is the CEO. >>So the challenge you have is the CEO. Is that your you have 10, 20 or 30 or more years of legacy hardware, including mainframes, right. Like so big insurance companies don't use mainframe because their claims systems have been developed in their very risk averse about changing them. Do you have to make all of this work together? Like, you know, we see IBM and Redhead are actually, you know, chasing that mainframe. Which angle, which is gonna die out where Amazon, I think is smart is saying, Look, we understand that container is gonna be the model container orchestration is gonna be how I t goes forward. The CEO is now buy into that. Last year, I was still saying, Are we gonna be able to understand? Understand? Kubernetes is the regular average i t person, which are not, you know, Google or Facebook level engineers Are there gonna be able to do do containers? And so we see the open sourcing of of the AWS is, uh, kubernetes, uh, server on. We see plenty of container options. That's how organizations could build cloud native internally. And when they're ready to go outside because we're gonna move, they're gonna move many times slower than a cloud native company to go outside. Everything is ready there. Um, I like what I'm seeing without posts. I like what I'm seeing with the hybrid options. The VM ware for cloud. They're building a pathway that says you can do real cloud. And I think the big announcement that was that. That s a really, uh, spend time on which is that PCs for everywhere. Um, a saying you're gonna be able to put Amazon services are compute services anywhere. You need it, e think that's a smart message. And that allows people to say I could eventually get toe one model to get my arms around this over time >>day. What does that mean for the numbers? I know you do a lot of research on spend customer data. Um, CEO is clearly no. This is gonna be the world's never go back to the same way it was. They certainly will accelerate cloud toe. What level depends upon where they are in their truth, as Jassy says. But >>what does >>the numbers look at? Because you're looking at the data you got Microsoft, You got Amazon. What's the customer spend look like where they're gonna be spending? >>Well, so a couple things one is that when you strip out the the SAS portion of both Google and Azure, you know, as we know, I asked him pass A W S is the leader, but there's no question that Microsoft is catching up. Says that we were talking about earlier. Uh, it's the law of large numbers Just to give you a sense Amazon this year we'll add. Q four is not done yet, but they'll add 10 billion over last year. And Jesse sort of alluded to that. They do that in 12 months. You know, uh, azure will add close to nine billion this year of incremental revenue. Google much, much smaller. And so So that's, you know, just seeing, uh, as you really catch up there for sure, you know, closing that gap. But still Amazon's got the lead. The other thing I would say is die on you and I were talking about this Is that you know Google is starting. Thio do a little bit better. People love their analytics. They love the built in machine learning things like like big query. And you know, even though they're much, much smaller there, another hedge people don't necessarily want to goto Microsoft unless they're Microsoft Shop. Google gives them that alternative, and that's been a bit of a tailwind for Google. Although I would say again, looking at the numbers. If I look back at where Azure and AWS were at this point where Google is with a few billion dollars in cloud the growth rates, I'd like to see Google growing a little faster. Maybe there's a covert factor there. >>Diane. I want to get your thoughts on this transition. Microsoft Oracle competition Um, Jesse knows he's got a deal with the elite Salesforce's out there. Oracle, Microsoft. Microsoft used to be the innovator. They had the they had the phrase embracing extend back in the day. Now Amazon's embracing and extending, but they gotta go through Oracle and Microsoft if they wanna win the enterprise on premise business and everybody else. Um, eso welcome to the party like Amazon. You What's your take on them versus Microsoft? Calling them out on sequel server licensing practices almost thrown him under the bus big time. >>Well, I think that's you know, we saw the evidence today that they're actually taking aim at Microsoft now. So Babel Fish, which allows you to run Microsoft sequel server workloads directly on Aurora. Uh, that that is what I call the escape pod that gives organizations an easy way That isn't Will parliament to redesign and re architect their applications to say, Just come over to AWS, right? We'll give you a better deal. But I think you've got to see Amazon have, um, or comprehensive sales plan to go into the C. E. O s. Go after the big deals and say, You know, we want to say the whole cloud suite, we have a stack that's unbeatable. You see our velocities, you know, best in class. Arguably against Microsoft is the big challenger, but we'll beat you on on a total cost of ownership. You know, your final bill. At the end of the day, we could we commit to being less than our competitors. Things like that will get the attention. But, you know, uh, Amazon is not known for cutting customized deals. Actually, even frankly, I'm hearing from very CEO is a very large, like Fortune 20 companies. They have very little wiggle room with Microsoft's anybody who's willing to go to the big enterprise and create custom deals. So if you build a sales team that could do that, you have a real shot and saying getting into the CEO's office and saying, You know, we want to move all the I t over and I'm seeing Microsoft getting winds like that. I'm not yet seeing Amazon and they're just gonna have to build a specialized sales team that go up against those guys and migration tools like we saw with Babel fish that says, If you want to come, we can get you over here pretty quick. >>I want to chime in on Oracle to John. I do. I think this is a blind spot somewhat for AWS, Oracle and mainframes. Jesse talks that talks like, Oh yeah, these people, they wanna get off there. And there's no question there are a number of folks that are unhappy, certainly with Oracle's licensing practices. But I talked to a lot of Oracle customers that are running the shops on Oracle database, and it's really good technology. It is world class for mission critical transaction workloads. Transaction workloads tend to be much, much smaller data set sizes, and so and Oracle's got, you know, decades built up, and so their their customers air locked in and and they're actually reasonably happy with the service levels they're getting out of Oracle. So yes, licensing is one thing, but there's more to the story and again, CEO or risk averse. To Diane's point, you're not just gonna chuck away your claim system. It's just a lot of custom code. And it's just the business case isn't there to move? >>Well, I mean, I would argue that Well, first of all, I see where you're coming from. But I would also argue that one of the things that Jesse laid out today that I thought was kind of a nuanced point was during the vertical section. I think it was under the manufacturing. He really laid out the case that I saw for startups and or innovation formula, that horizontal integration around the data. But then being vertically focused with the modern app with same machine learning. So what he was saying, and I don't think he did a good job doing it was you could disrupt horizontally in any industry. That's a that's a disruption formula, but you still could have that scale. That's cloud horizontal scalability, cloud. But the data gives you the ability to do both. I think bringing data together across multiple silos is critical, but having that machine learning in the vertical is the way you could different so horizontally. Scalable vertical specialization for the modern app, I think is a killer formula. And I think >>I think that's a I think it's a really strong point, John, and you're seeing that you're seeing in industries like, for instance, Amazon getting into grocery. And that's a data play. But I do like Thio following your point. The Contact Center solutions. I like the solutions play there and some of the stuff they're doing at the edge with i o T. The equipment optimization, the predictive maintenance, those air specialized solutions. I really like the solutions Focus, which several years ago, Amazon really didn't talk solution. So that's a positive sign, >>Diane, what do you think? The context And I think that was just such low hanging fruit for Amazon. Why not do it? You got the cloud scale. You got the Alexa knowledge, you know, got machine learning >>zone, that natural language processing maturity to allow them to actually monitor that. You know that that contact lens real time allows them a lot of supervisors to intervene them conversations before they go completely south, right? So allowing people to get inside decision windows they couldn't before. I think that's a really important capability. And that's a challenge with analytics in general. Is that generates form or insights than people know how to deal with? And it solutions like contact lens Real time? This is Let's make these insights actionable before it's broken. Let's give you the data to go and fix it before it even finishes breaking. And this is the whole predictive model is very powerful. >>Alright, guys, we got four minutes left. I wanted Segway and finish up with what was said in the keynote. That was a tell sign that gives us some direction of where the dots will connect in the future. There's a lot of stuff that was talked about that was, you know, follow on. That was meat on the bone from previous announcements. Where did Jassy layout? What? I would call the directional shift. Did you see anything particular that you said? Okay, that is solid. I mean, the zones was one I could see. What clearly is an edge piece. Where did you guys see? Um, some really good directional signaling from Jassy in terms of where they really go. Deal with start >>e I felt like Jassy basically said, Hey, we invented cloud. Even use these words we invented cloud and we're gonna define what hybrid looks like We're gonna bring our cloud model to the edge. And the data center just happens to be another edge point. And hey, I thought he laid down the gauntlet. E think it's a very powerful message. >>What do you think Jesse has been saying? That he laid out here, That's >>you laid out a very clear path to the edge that the Amazons marching to the edge. That's the next big frontier in the cloud. It isn't well defined. And that just like they defined cloud in the early days that they don't get out there and be the definitive leader in that space. Then they're gonna be the follower. I think so. We saw announcement after announcement around that you know, from the zones Thio the different options for outpost um, the five g announcement wavelength. All of those things says we're gonna go out to the very tippy edge is what I heard right out to your mobile devices. Right after the most obscure field applications imaginable. We're gonna have an appliance So we're gonna have a service that lets you put Amazon everywhere. And so I think the overarching message was This is a W s everywhere it z gonna go after 100% of I t. Eventually on DSO you can move to that. You know, this one stop shop? Um and you know, we saw him or more discussions about multi cloud, but it was interesting how they stand away from that. And this is what I think One area that they're going to continue to avoid. So it was interesting, >>John, I think I think the edges one by developers. And that's good news for Amazon. And good news for Microsoft. >>We'll see the facilities is gonna be good for me. I think guys, the big take away You guys nailed two of them there, but I think the other one was I think he's trying to speak to this new generation in a very professorial way. Talk about Clay Christensen was a professor at his business school at Harvard. We all know the book. Um, but there was this There was this a posture of speaking to the younger generation like hey, the old guy, the old that was running the mainframe. Wherever the old guys there, you could take over and run this. So it's kind of like more of a leadership preach of preaching like, Hey, it's okay to be cool and innovative, right now is the time to get in cloud. And the people who are blocking you are either holding on to what they built or too afraid to shift. Eso I think a Z we've seen through waves of innovation. You always have those people you know who are gonna stop that innovation. So I was very interesting. You mentioned that would service to the next generation. Um, compute. So he had that kind of posture. Interesting point. Yeah, just very, very preachy. >>E think he's talking to a group of people who also went through the through 2020 and they might be very risk averse and not bold anymore. And so, you know, I think that may have helped address that as well. >>All right, gentlemen, great stuff. Final word in the nutshell. Kena, What do you think about it in general? Will take away. >>Yeah, I I think we saw the continued product development intensity that Amazon is going to use to try and thrash the competition? Uh, the big vision. Um, you know, the real focus on developers first? Um and I think I t and C e O's second, I think before you could say they didn't really think about them too much at all. But now it's a close second. You know, I really liked what I saw, and I think it's It's the right move. I'd like to Seymour on on hybrid cloud migration than that, even when we saw them. >>All right, leave it there. Don. Thanks for coming on from this guest analyst segment. Appreciate you jumping in Cuba. Live. Thank you. >>Thanks. Alright. >>With acute virtual. I'm your host John per day Volonte here covering A W s live covering the keynote in real time State more for more coverage after the break

>>LA Las Vegas. It's the cube hovering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back to the cube. Our day one coverage of AWS reinvent 19 continues. Lisa Martin with Dave Volante. Dave and I have a couple of guests we'd like you to walk up. We've got Anthony Brooks billions, the CEO of HBR back on the cube. You're alumni. We should get you a pin and snowflake alumni. But Chris, your new Chris Dagon, chief revenue officer from snowflake. Chris, welcome to the program. Excited to be here. All right guys. So even though both companies have been on before, Anthony, let's start with you. Give our audience a refresher about HVR, who you guys are at, what you do. >>Sure. So we're in the data integration space, particularly a real time data integration. So we move data to the cloud in the in the most efficient way and we make sure it's secure and it's accurate and you're moving into environments such as snowflake. Um, and that's where we've got some really good customers that we happy to talk about joint custody that we're doing together. But Chris can tell us a little bit about snowflake. >>Sure. And snowflake is a cloud data warehousing company. We are cloud native, we are on AWS or on GCP and we're on Azure. And if you look at the competitive landscape, we compete with our friends at Amazon. We compete with our friends at Microsoft and our friends at Google. So it's super interesting place to be, but it very exciting at the same time and super excited to partner with Anthony and some others who aren't really a friends. That's correct. So I wonder if we could start by just talking about the data warehouse sort of trends that you guys see. When I talk to practitioners in the old days, they used to say to me things like, Oh, infrastructure management, it's such a nightmare. It's like a snake swallowing a basketball every time until it comes out with a new chips. We chase it because we just need more performance and we can't get our jobs done fast enough. And there's only three. There's three guys that we got to go through to get any answers and it was just never really lived up to the promise of 360 degree view of your business and realtime analytics. How has that changed? >>Well, there's that too. I mean obviously the cloud has had a big difference on that illustrious city. Um, what you would find is in, in, in yesterday, customers have these, a retail customer has these big events twice a year. And so to do an analysis on what's being sold and Casper's transactions, they bought this big data warehouse environment for two events a year typically. And so what's happening that's highly cost, highly costly as we know to maintain and then cause the advances in technology and trips and stuff. And then you move into this cloud world which gives you that Lester city of scale up, scale down as you need to. And then particular where we've got Tonies snowflake that is built for that environment and that elicited city. And so you get someone like us that can move this data at today's scale and volume through these techniques we have into an environment that then bleeds into helping them solve the challenge that you talk about of Yesi of >>these big clunky environments. That side, I think you, I think you kind of nailed it. I think like early days. So our founders are from Oracle and they were building Oracle AI nine nine, 10 G. and when I interviewed them I was the first sales rep showing up and day one I'm like, what the heck am I selling? And when I met them I said, tell me what the benefit of snowflake is. And they're like, well at Oracle, and we'd go talk to customers and they'd say, Oracles, you know, I have this problem with Oracle. They'd say, Hey, that's, you know, seven generations ago were Oracle. Do you have an upgraded to the latest code? So one of the things they talked about as being a service, Hey, we want to make it really easy. You never have to upgrade the service. And then to your point around, you have a fixed amount of resources on premise, so you can't all of a sudden if you have a new project, do you want to bring on the first question I asked when I started snowflake to customers was how long does it take you to kick off a net new workload onto your data, onto your Vertica and it take them nine to 12 months because they'd have to go procure the new hardware, install it, and guess what? >>With snowflake, you can make an instantaneous decision and because of our last test city, because the benefits of our partner from Amazon, you can really grow with your demand of your business. >>Many don't have the luxury of nine to 12 months anymore, Chris, because we all know if, if an enterprise legacy business isn't thinking, there's somebody not far behind me who has the elasticity, who has the appetite, who's who understands the opportunity that cloud provides. If you're not thinking that, as auntie Jessie will say, you're going to be on the wrong end of that equation. But for large enterprises, that's hard. The whole change culture is very hard to do. I'd love to get your perspective, Chris, what you're seeing in terms of industries shifting their mindsets to understand the value that they could unlock with this data, but how are big industries legacy industries changing? >>I'd say that, look, we were chasing Amad, we were chasing the cloud providers early days, so five years ago, we're selling to ad tech and online gaming companies today. What's happened in the industry is, and I'll give you a perfect example, is Ben wa and I, one of our founders went out to one of the largest investment banks on wall street five years ago, and they said, and they have more money than God, and they say, Hey, we love what you've built. We love, when are you going to run on premise? And Ben, Ben wa uttered this phrase of, Hey, you will run on the public cloud before we ever run in the private cloud. And guess what? He was a truth teller because five years later, they are one of our largest customers today. And they made the decision to move to the cloud and we're seeing financial services at a blistering face moved to the cloud. >>And that's where, you know, partnering with folks from HR is super important for us because we don't have the ability to just magically have this data appear in the cloud. And that's where we rely quite heavily on on instance. So Anthony, in the financial services world in particular, it used to be a cloud. Never that was an evil word. Automation. No, we have to have full control and in migration, never digital transformation to start to change those things. It's really become an imperative, but it's by in particular is really challenging. So I wonder if we could dig into that a little bit and help us understand how you solve that problem. >>Yes. A customer say they want to adopt some of these technologies. So there's the migration route. They may want to go adopt some of these, these cloud databases, the cloud data warehouses. And so we have some areas where we, you know, we can do that and keep the business up and running at the same time. So the techniques we use are we reading the transactional logs, other databases or something called CDC. And so there'll be an initial transfer of the bulk of the data initiative stantiating or refresh. At that same time we capturing data out of the transaction logs, wildlife systems live and doing a migration to the new environment or into snowflakes world, capturing data where it's happening, where the data is generated and moving that real time securely, accurately into this environment for somewhere like 1-800-FLOWERS where they can do this, make better decisions to say the cost is better at point of sale. >>So have all their business divisions pulling it in. So there's the migration aspects and then there's the, the use case around the realtime reporting as well. So you're essentially refueling the plane. Well while you're in mid air. Um, yeah, that's a good one. So what does the customer see? How disruptive is it? How do you minimize that disruption? Well, the good thing is, well we've all got these experienced teams like Chris said that have been around the block and a lot of us have done this. What we do, what ed days fail for the last 15 years, that companies like golden gate that we sold to Oracle and those things. And so there's a whole consultative approach to them versus just here's some software, good luck with it. So there's that aspect where there's a lot of planning that goes into that and then through that using our technologies that are well suited to this Appleton shows some good success and that's a key focus for us. And in our world, in this subscription by SAS top world, customer success is key. And so we have to build a lot of that into how we make this successful as well. >>I think it's a barrier to entry, like going, going from on premise to the cloud. That's the number one pushback that we get when we go out and say, Hey, we have a cloud native data warehouse. Like how the heck are we going to get the data to the cloud? And that's where, you know, a partnership with HR. Super important. Yeah. >>What are some of the things that you guys encountered? Because we many businesses live in the multi-cloud world most of the time, not by strategy, right? A lot of the CIO say, well we sort of inherited this, or it's M and a or it's developers that have preference. How do you help customers move data appropriately based on the value that the perceived value that it can give in what is really a multi world today? Chris, we'll start with you. >>Yeah, I think so. So as we go into customers, I think the biggest hurdle for them to move to the cloud is security because they think the cloud is not secure. So if we, if you look at our engagement with customers, we go in and we actually have to sell the value snowflake and then they say, well, okay great, go talk to the security team. And then we talked to security team and say, Hey, let me show you how we secure data. And then then they have to get comfortable around how they're going to actually move, get the data from on premise to the cloud. And that's again, when we engage with partners like her. So yeah, >>and then we go through a whole process with a customer. There's a taking some of that data in a, in a POC type environment and proving that after, as before it gets rolled out. And a lot of, you know, references and case studies around it as well. >>Depends on the customer that you have some customers who are bold and it doesn't matter the size. We have a fortune 100 customer who literally had an on premise Teradata system that they moved from on prem, from on premise 30 to choose snowflake in 111 days because they were all in. You have other customers that say, Hey, I'm going to take it easy. I'm going to workload by workload. And it just depends. And the mileage may vary is what can it give us an example of maybe a customer example or in what workloads they moved? Was it reporting? What other kinds? Yeah. >>Oh yeah. We got a couple of, you mean we could talk a little bit about 1-800-FLOWERS. We can talk about someone like Pitney Bowes where they were moving from Oracle to secret server. It's a bunch of SAP data sitting in SAP ECC. So there's some complexity around how you acquire, how you decode that data, which we ever built a unique ability to do where we can decode the cluster and pool tables coupled with our CDC technique and they had some stringent performance loads, um, that a bunch of the vendors couldn't meet the needs between both our companies. And so we were able to solve their challenge for them jointly and move this data at scale in the performance that they needed out with these articles, secret server enrollments into, into snowflake. >>I almost feel like when you have an SAP environment, it's almost stuck in SAP. So to get it out is like, it's scary, right? And this is where it's super awesome for us to do work like this. >>On that front, I wanted to understand your thoughts on transformation. It's a word, it's a theme of reinvent 2019. It's a word that we hear at every event, whether we're talking about digital transformation, workforce, it, et cetera. But one of the things that Andy Jassy said this morning was that got us start. It's this is more than technology, right? This, the next gen cloud is more than technology. It's about getting those senior leaders on board. Chris, your perspective, looking at financial services first, we were really surprised at how quickly they've been able to move. Understanding presumably that if they don't, there's going to be other businesses. But are you seeing that as the chief revenue officer or your conversations starting at that CEO level? >>It kinda has to like in the reason why if you do in bottoms up approach and say, Hey, I've got a great technology and you sell this great technology to, you know, a tech person. The reality is unless the C E O CIO or CTO has an initiative to do digital transformation and move to the cloud, you'll die. You'll die in security, you'll die in legal lawyers love to kill deals. And so those are the two areas that I see D deals, you know, slow down significantly. And that's where, you know, we, it's, it's getting through those processes and finding the champion at the CEO level, CIO level, CTO level. If you're, if you're a modern day CIO and you do not have a a cloud strategy, you're probably going to get replaced >>in 18 months. So you know, you better get on board and you'd better take, you know, taking advantage of what's happening in the industry. >>And I think that coupled with the fact that in today's world, you mean, you said there's a, it gets thrown around as a, as a theme and particularly the last couple of years, I think it's, it's now it is actually a strategy and, and reality because what Josephine is that there's as many it tech savvy people sit in the business side of organizations today that used to sit in legacy it. And I think it's that coupled with the leadership driving it that's, that's demanding it, that demanding to be able to access that certain type of data in a geo to make decisions that affect the business. Right now. >>I wonder if we could talk a little bit more about some of the innovations that are coming up. I mean I've been really hard on data. The data warehouse industry, you can tell I'm jaded. I've been around a long time. I mean I've always said that that Sarbanes Oxley saved the old school BI and data warehousing and because all the reporting requirements, and again that business never lived up to its promises, but it seems like there's this whole new set of workloads emerging in the cloud where you take a data warehouse like a snowflake, you may be bringing in some ML tools, maybe it's Databricks or whatever. You HVR helping you sort of virtualize the data and people are driving new workloads that are, that are bringing insights that they couldn't get before in near real time. What are you seeing in terms of some of those gestalt trends and how are companies taking advantage of these innovations? >>I think one is just the general proliferation of data. There's just more data and like you're saying from many different sources, so they're capturing data from CNC machines in factories, you know like like we do for someone like GE, that type of data is to data financial data that's sitting in a BU taking all of that and going there's just as boss some of data, how can we get a total view of our business and at a board level make better decisions and that's where they got put it in I snowflake in this an elastic environment that allows them to do this consolidated view of that whole organization, but I think it's largely been driven by things that digitize their sensors on everything and there's just a sheer volume of data. I think all of that coming together is what's, what's driven it >>is is data access. We talked about security a little bit, but who has rights to access the data? Is that a challenge? How are you guys solving that or is it, I mean I think it's like anything like once people start to understand how a date where we're an acid compliant date sequel database, so we whatever your security you use on your on premise, you can use the same on snowflake. It's just a misperception that the industry has that being on, on in a data center is more secure than being in the cloud and it's actually wrong. I guess my question is not so much security in the cloud, it's more what you were saying about the disparate data sources that coming in hard and fast now. And how do you keep track of who has access to the data? I mean is it another security tool or is it a partnership within owes? >>Yeah, absolutely man. So there's also, there's in financial data, there's certain geos, data leaves, certain geos, whether it be in the EU or certain companies, particularly this end, there's big banks now California, there's stuff that we can do from a security perspective in the data that we move that's secure, it's encrypted. If we capturing data from multiple different sources, items we have that we have the ability to take it all through one, one proxy in the firewall, which does, it helps him a lot in that aspect. Something unique in our technology. But then there's other tools that they have and largely you sit down with them and it's their sort of governance that they have in the, in the organization to go, how do they tackle that and the rules they set around it, you know? >>Well, last question I have is, so we're seeing, you know, I look at the spending data and my breaking analysis, go on my LinkedIn, you'll see it snowflakes off the charts. It's up there with, with robotic process automation and obviously Redshift. Very strong. Do you see those two? I think you addressed it before, but I'd love to get you on record sort of coexisting and thriving. Really, that's not the enemy, right? It's the, it's the Terra data's and the IBM's and the Oracles. The, >>I think, look, uh, you know, Amazon, our relationship with Amazon is like a, you know, a 20 year marriage, right? Sometimes there's good days, sometimes there's bad days. And I think, uh, you know, every year about this time, you know, we get a bat phone call from someone at Amazon saying, Hey, you know, the Redshift team's coming out with a snowflake killer. And I've heard that literally for six years now. Um, it turns out that there's an opportunity for us to coexist. Turns out there's an opportunity for us to compete. Um, and it's all about how they handle themselves as a business. Amazon has been tremendous in separation of that, of, okay, are going to partner here, we're going to compete here, and we're okay if you guys beat us. And, and so that's how they operate. But yes, it is complex and it's, it's, there are challenges. >>Well, the marketplace guys must love you though because you're selling a lot of computers. >>Well, yeah, yeah. This is three guys. They, when they left, we have a summer thing. You mean NWS have a technological DMS, their data migration service, they work with us. They refer opportunities to us when it's these big enterprises that are use cases, scale complexity, volume of data. That's what we do. We're not necessary into the the smaller mom and pop type shops that just want to adopt it, and I think that's where we all both able to go coexist together. There's more than enough. >>All right. You're right. It's like, it's like, Hey, we have champions in the Esri group, the EEC tuna group, that private link group, you know, across all the Amazon products. So there's a lot of friends of ours. Yeah, the red shift team doesn't like us, but that's okay. I can live in >>healthy coopertition, but it just goes to show that not only do customers and partners have toys, but they're exercising it. Gentlemen, thank you for joining David knee on the key of this afternoon. We appreciate your time. Thank you for having us. Pleasure our pleasure for Dave Volante. I'm Lisa Martin. You're watching the queue from day one of our coverage of AWS reinvent 19 thanks for watching.

>>from our studios in the heart of Silicon Valley. Palo ALTO, California It is a cute conversation. >>Hi, and welcome to the Cube studios for another cube conversation where we go in depth with thought leaders driving innovation across the technology industry. I'm your host, Peter Boris. Digital businesses affecting every enterprise of every size, small and large, and the types of solutions that required the types of outcomes that are being pursued are extremely complex and require an enormous amount of work from some of the best and brightest people on the business side as well as the technology side. And that means not just from a large company. It means from an entire ecosystem of potential sources of genius and insight and good hard work. So the consequence for every enterprises, how do they cobble together that collection of experts and capabilities that are gonna help them transform their business more successfully, Maur completely and more certainly than they would otherwise? And that's we're gonna talk about today. Today we're here with Kelly Ireland, who's the founder and C E o. C. B Technologies. Kelly. Welcome to the >>Cube. Thank you, Peter. Happy to be here, >>so let's start by finding a little bit about CV Technologies to also about what you do. >>Um, I have a IittIe background, so I have been in it for 40 years. In 2001 I decided I had a better idea of how to both support clients as well as my employees. So I opened CB Technologies were value added reseller, um, and then say about five years ago, I decided to do some transforming of the company itself. I saw what was going on in the industry, and I thought this was the time for us to get going. Turned out we were a little early, but we wanted to transform from what you would call it the value added reseller two systems integrator. Because that was the only words what they had for. You know what that end result would be? Now I've heard it's the, um, domain expert integrator, which we like a lot better. And what we've done is gone from this value add, which we've all seen over the last couple of decades, into actually engineering solutions, and mostly with consortiums, which will talk about of the O. T. I t. Convergence and what's going to be needed for that to make our customers successful. >>Well, you just described. In many respects, the vision that businesses have had and how it's changed over years were first. The asset was the hardware. Hence the var. Today, the asset really is the date of the application and how you're going to apply that to change the way your business operates the customer experiences, you provide the profitability that you're able to return back to shareholders. So let's dig into this because that notion of data that notion of digital transformation is especially important in a number of different names, perhaps no more important than in the whole industrial and end of things domain. That intersection of I t know Tia's, you said, Tell us a little bit about what you're experiencing with your customers as they try to think about new ways of applying technology technology rich data to their business challenges. >>We'll use the perfect word you said dig, because this is all about layers. It's all about it was technology and software. Now it's about technology, software and integration. In fact, the conversations were having with our clients. Right now we don't even talk about a no Yim's name. Where before you would. But we haven't our head. What? We know what would be best. What we look at now is the first thing you do is go in and sit down with the client. And not only with the client, the you know, the executives or the C I or the C T. O's et cetera, but the employees themselves. Because what we've seen with I I I o t o t i t Convergence, it's You have to take into account what the worker needs and the people that are addressing it that way. Um, this project that we started with Hewlett Packard Enterprise, they started up what we call the refinery of the future. It could be acts of the future. It doesn't really matter. But it was getting at least up to five use cases with a consortium of partner companies that could go address five different things within the refinery. And the reason that I think it's been so successful is that the owner, the CEO Doug Smith and the VP of ops Linda Salinas, immediately wrap their arms around bringing employees. They're a small company there, maybe 50. They brought half of them to HPD Lab to show them what a smart pump laws for their chemical plant text. More chemical in Galina Park in Texas. Starting from that, it was like they put him on a party bus, took them down, put them in the lab, told them, showed them what a smart pump was and all of a sudden the lights turned on for the workers. These are people that have been, you know, manual valves and turning knobs and, you know, looking at computer screens they'd never seen what a smart, censored pump waas all of it sudden on the drive back to the company, ideas started turning. And then HP took it from there, brought in partners, sat everybody in the room, and we started feathering out. Okay, what's needed. But let's start with what the client needs. What do those different business users within the chemical plant need, and then build use cases from that? So we ended up building five use cases. >>Well, so what? Get another five years cases in a second? But you just described something very interesting, and I think it's something that partners have historically been able to do somewhat uniquely on that is that the customer journey is not taken by just an individual within the business. What really happens is someone has an idea. They find someone, often a partner, that can help them develop that idea. And then they go off and they recruit others within their business and a local partner that has good domain expertise at the time. And energy and customer commitment could be an absolutely essential feature of building the consensus within the organization to really accelerate that customer journey. If I got that right? >>Absolutely, absolutely. And what we saw with Refinery of the Future was getting those partnerships HP East started. It created the project kind of through information out to many of their ecosystem partners trying to gain interest because the thing was is this was kind of our bet was a very educated bet, but it's our bet to say, Yeah, we think this makes sense. So, you know, like I said, I think there's about 14 partners that all joined in both on the I t om side the ot oh am side and then both Deloitte and CB Technologies for the S. I and like expert domain expert integration where you really get into How do you tie OT and I t together? >>All right, so we've got this situation where this is not As you said, It's not just in the refining process, manufacturing businesses. It's in a lot of business. But in this particular one, you guys have actually fashioned what you call the refinery of of the future has got five clear use cases. Just give us an example of what those look like and how you've been RCB technology has been participated in the process of putting those together. >>Um, the 1st 1 was pretty wrapped around Predictive Analytics, and that was led by Deloitte and has a whole host of OT and I t integration on it >>again, not limited to process manufacturing at all >>at all, but and a good group, you know, you have national instruments, Intel flow. Serve. Oh, it's ice off Snyder Electric, PTC riel, where they're such a host >>of the >>consortium and I I think what was most important to start this whole thing was H P E. Came in and said, Here's an MOU. Here's a contract. You all will be contract ID to the overall resorts results. Not just your use case. Not just one or two use cases you're in, but all five because they all can integrate in some sense so >>that all can help. Each of you can help the others think. Problems. Truce. That's the 1st 1 about the 2nd 1 >>The 2nd 1 is video is a sensor that was Intel CB Technologies. I think we have as you're in there as well, doing some of the analytics, some P T. C. And what that was all about was taking video. And, you know, taking a use case from Linda and saying, Where where do you need some sort of video analytics Taking that processing it and what we ended up doing with that one was being able to identify, you know, animals or aggressive animals within the train yard. A downed worker transients that shouldn't be there because we can't decipher between you know, someone that's in text marks p p ease versus somebody that's in street clothes. So taking all that analyzing the information, the pictures, training it to understand when it needs to throw and alert >>lot of data required for that. And that's one of the major major drivers of some of the new storage technologies out there. New fabrics that are out there. How did that play? A role? >>As you can imagine, H p E is the under underlying infrastructure across the entire refinery. The future from compute with the, uh, EJ data center into the Reuben network into nimble storage for storing on site. Um, what we're finding, no matter who we talked to in the industry, it is. Most of them still want to keep it on Prem. In some sense, security. They're still all extremely cautious. So they want to keep it on Prem. So having the nimble storage right in the date, having the edge data center having everything in the middle of this chemical plant was absolutely a necessity. And having all of that set up having my team, which was the C B Tech team that actually did all the integration of setting up the wireless network, because guess what? When you're in a different kind of environment, not inside a building, you're out where there's metal pumps. There's restrictions because ah, flash could cause an explosion so intrinsically safe we had to set up all that and determined how? How could we get the best coverage? Especially? We want that video signal to move quite fast over the WiFi. How do we get all that set up? So it takes the most advantage of, you know, the facility and the capabilities of the Aruban network. >>So that's 12345 quickly were >>three worker safety, which hasn't started yet. We're still waiting for one of the manufacturers to get the certification they need. Um, four we have is connected worker, which is on fire, having a work >>of connected worker on fire and worker >>safety. >>Yeah, they don't sound, but just think of all the data and having the worker have it right at his fingertips. And, oh, by the way, hands free. So they're being ableto to take in all this data and transmit data, whether it's by voice or on screen back >>from a worker central perspective, from one that sustains the context of where the worker is, what stress there under what else? They've got to do it said. >>And and what are they trying to complete and how quickly? And that's where right now we have r A y that's in the 90% which is off the chart. But it's and and what's great about being at Text Mark is we actually can prove this. I can have somebody walk with me, a client that wants to look at it. They can go walk the process with me, and they will immediately see that we reduce the time by 90%. >>So I've given your four. What's the 5th 1? >>Acid intelligence, which is all about three D Point Cloud three D visualization. Actually being able to pull up a smart pump. You know it really? Any pump, you scan the facility you converted into three D and then in the program that we're using, you can actually pull up a pump. You can rotate it 360 degrees. It's got a database behind it that has every single bit of asset information connected videos, cad cams, P and I. D s. For the oil and gas industry. Everything's in their e mails could be attached to it, and then you can also put compliance reports. So there you might need to look a corrosion. One of those tests that they do on a you know, annual or every five year basis. That's point and click. You pull it up and it tells you where it sits, and then it also shows you green, yellow, red. Anything in red is immediate, attest that tension yellow is you need to address it greens. Everything's 100% running. >>So the complexity that we're talking about, the kind of specificity of these solutions, even though they can be generalized. And you know, you talked about analytics all the way out to asset optimization Intel intelligence. There are We can generalize and structure, but there's always going to be, it seems to us there's going to be a degree of specificity that's required, and that means we're not gonna talk about package software that does this kind of stuff. We're talking about sitting down with a customer with a team of experts from a lot of different places and working together and applying that to achieve customer outcome. So I got that right >>absolutely, and what we did with the consortium looking at everything. How they first addressed it was right along that line, and if you look at software development, agile following agile process, it's exactly what we're doing in four I I o T o R O T I t Convergence, because if you don't include all of those people, it's never going to be successful. I heard it a conference the other day that said, POC is goto I ot to die, and it's because a lot of people aren't addressing it the right way. We do something called Innovation Delivery as a service, which is basically a four day, 3 to 4 day boot camp. You get all the right people in, in in the room. You pull in everything from them. You boot out the executive team partway through, and you really get in depth with workers and you have them say what they wouldn't say in front of their bosses that this happened with Doug and Linda and Linda said it was mind blowing. She goes. I didn't realize we had so many problems because she came back in the room and there was a 1,000,000 stickies. And then she said, the more she read it and the more you know, we refined it down, she said it was absolutely delivered, you know, the use case that she would have eventually ended up with, but loved having all the insights from, >>well, work. Too often, tech companies failed to recognize that there's a difference between inventing something and innovation. Inventing is that engineering act of taking what you know about physics or social circumstance Secreting hardware software innovation is a set of social acts that get the customer to adopt it, get a marketplace to adopt it, change their behaviors. And partners historically have been absolutely essential to driving that innovation, to getting customers to actually change the way to do things and embed solutions in their operations. And increasingly, because of that deep knowledge with customers are trying to doing, they're participating. Maurine, the actual invention process, especially on the softer side of you said, >>Yeah, yeah, I think what's really interesting in this, especially with Coyote. When I look back a few years, I look at cloud and you know everything was cloud and everybody ran to it and everybody jumped in with both feet, and then they got burned. And what we're seeing with this whole thing with I o t you would think we're showing these are lies, return on. Investments were showing all this greatness that can come out of it and and they're very slow at sticking their toe in. But what we've found is no one arrives should say the majority of corporations anymore don't want to jump in and say, Let's do it two or five or $10 million project. We see your power point. No, let's let's depart Owen with with what we're doing, it's, you know, a really small amount of money to go in and really direct our attention at exactly what their problem is. It's not off the shelf. It's but it's off the shelf with customization. It's like we've already delivered on connected worker for oil and gas. But now we're are so starting to deliver multiple other industries because they actually walk through text mark. We could do tours, that text mark. That was kind of the trade off. All these partners brought technology and, you know, brought their intelligence and spent. We were now on two years of proving all this out. Well, they said, Fine, open the kimono will let your customers walk through and see it >>makes text mark look like a better suppliers. >>Well, it's enhanced their business greatly. I can tell you they're just starting a new process in another week. And it was all based on people going through, you know, a client that went through and went. Wait >>a minute. I >>really like this. There are also being able to recruit technologists within the use in industry, which you would think text marks 50 employees. It's a small little plant. It's very specialized. It's very small. They pulled one of the top. Uh, sorry. Lost not. I'm trying to think of what the name >>they're. They're a small number of employees, but the process manufacturing typically has huge assets. And any way you look at it, we're talking about major investments, major monies that require deep expertise. And my guess is the text Mark is able to use that to bring an even smarter and better >>people smarter and better. People that are looking at it going they're ahead of the curve, for they're so far ahead of the curve that they want to be on board were that they're bringing in millennials on they're connected. Worker Carlos is there trainload lead. And he dropped an intrinsically safe camera and it broke and he tried to glue it together, tried to super glue it together. And then he ran back to Linda and he said I broke the case and this case is like £10. They call it the Brick. They gotta lug it up. They got to climb up the train car, leg it up, take a picture that they have sealed the valves on all the cars before they leave. Well, he had used the real where had, you know, device. And he went into Linda and he said, I know there's a camera in there. There's camera capabilities. Can I use that until we get another case? And she's like, Yeah, go ahead. Well, he went through, started using that toe like lean over, say, Take photo. We engineered that it could go directly back to the audit file so that everybody knew the minute that picture was taken, it went back into the audio file. This is where we found the process was reduced by 90% of time. But he turned around and trained his entire team. He wasn't asked to, but he thought, this is the greatest thing. He went in trainable. And now, about every two weeks, Carlos walks in to my team that sits a text mark and comes up with another use case for connected worker. It's amazing. It's amazing what you know were developed right out of the customer by using their workers and then, you know, proactively coming to us going. Hey, I got another idea. Let's add this where I think at version 7.0, for connected worker. Because of that feedback because of that live feed back in production. >>Great story, Kelly. So, once again, Callie Ireland is a co founder and CEO of CB Technologies. Thanks for being on the tube. >>Thank you for having me >>on once again. I wanna thank all of you for joining us for another cute conversation. I'm Peter burgers. See you next time.