(upbeat music) >> Welcome to theCUBE coverage of women in tech. International Women's Day 2022. I'm your host, Lisa Martin. Karla Wong joins me next. Country Sales Leader for the Commercial Sector in Peru at AWS. Karla, welcome to theCUBE. >> Thank you so much Lisa and thank you for having me. It's a pleasure to be with you today. >> I'm looking forward to chatting with you. You've been in the tech industry for more than 20 years, you've been a leader in tech and sales and customer service, partners, organizations. Talk to me a little bit about your background. >> I am a system engineer. I have some studies from enterprise direction with a university in Savannah, Columbia and I have a digital transformation certified with MIT in Boston. >> Fantastic, were you always interested in technology or STEM or was it something that you pivoted into somewhere during your career? >> Yes, you know what? Since I was little, I was just fascinated with the technology and all the time I was just trying to figure out how to do things and how to build that things and I remember once I was just, of course many time long ago, I was with this BHS, right? An equipment and I tried to do and tried to understand how this works and just figure out I was with many parts of that equipment and then I didn't realize how to join that parts but it was really funny because all the time I was trying to understand what is behind that kind of equipment, how this works and all the time I was asking and my dad said, I was just feeling so curiosity about that and asking many questions and I have uncles that they are engineers. So I was just all the time asking about that and they said, you know what? You are good in math, maybe you can just decide for an engineering career. They were encouraged me for doing that. So I guess that was my first clue that I'm interested in technology. >> Well, you sounds like you have a natural curiosity that you had great role models in your parents and probably others along your educational route and your career route that kind of encouraged that curiosity and being curious is one of the things that's important to being at AWS. Am I right? >> Yes, it's really important because we promote, you know, our, one of the main leadership principles that you read is learn to be curious and they promote that one, right? They're encouraging you to innovate, to learn more, to try to understand more about our solutions, our customers, how to make the things better and you have the space to propose new things, to do the things better. So they encourage you and they empower you to do that and you feel like your curiosity that you have very natural here's improved and they just promote that you continue to do that. >> That curiosity is so important. I mean, when we think about women in technology and we think about bringing in more thought diversity and DEI, it's important to be curious, to be able to bring different thoughts in so that the organization can be more well rounded, it can learn, you also not only do you lead the sales organization, but you are someone that's very active in volunteering. Tell me a little bit about that and how do you balance leading a sales organization and volunteering at the same time? >> You know, when you talk about this is more like work life balance, right? And when we talk about that you can feel like you need it, right? You need to work on that. It's more like an attitude of it's extremely important to think about mental health for everyone because that of course have impact in your physical health and when you talk about this, it not only matters in terms of attitude, it's action and disciplines as well and you have to keep in mind that. The first thing I believe and all the time I do it give the right value for this balance because it's something that a lot of people want more than anything and I have more than some professional decision thinking about this precisely and I have to thinking of me as a person, my family, how to help the community and you cannot imagine the impact when you decide to go for a volunteering activities how can benefit you and not in only the personal way, in your professional way. Even though you didn't start a volunteering, trying to figure out how this help you in your professional life, you receive a lot of benefits from the volunteering activities and it's amazing how that one's impacting your professional life also. When you are a volunteer, you'll receive new and meaningful experiences. Volunteering can be an excellent getaway to find unique and valuable experiences that you are very difficult to find in a day to day basis, right? And you develop your real life skills, openness to criticism, responsibility, humility, commitment, service, attitude, many things that you can proactively include in your job with your team and you can join with them in teamwork and try to figure out how to engage with them in your activities. This is another way to motivate your team, to build your team, right? Talking with this very valuable experiences and also I find out that that improves your health and mood. >> Sounds very-- >> We talk having-- >> Sorry. >> I'm sorry, no don't worry. >> That's very complimentary, that the volunteer work with leading the sales organization that there's so much value that you're bringing into your sales leadership role from the volunteering that you do. I'm just curious, can you describe some of the volunteer organizations that you work with? I think it's pretty impressive. >> Yes, I started my volunteering 14 years ago I guess but I was in the volunteering activities from the school and my dad was a really strong influence for that because I joined, I remember joining with him and go to do some volunteering activities that he led and I start 14 years I went with Operation and Smile group and then in the last two or three years I start with Project of Love. We are focused on kids with cancer and try to help them to build the last wishes they have because they pass away and at the end of this, this two years ago, I start with local activity that we do for patients with rare diseases and we just try to join two great passion that I have. One is the dance that we have here. The name of our national dance is Marinera Norteña and we are just doing this with a group that they are passion at the same time with this volunteering activities and the dance and we just trying to be the ambassador for and the voice for these patients, try to share with the community, the hard health journey that they have trying to obtain a fair treatment, a fair diagnostic, because they are rare disease and here is very difficult that they investigate about that. So that's why we are just doing this using dance as a way to broadcast our voice and just share happiness and hope and health. >> Happiness and hope. Those are two great things. So as the female leader in the tech industry, what are some of the main challenges that you have found regarding cultural aspects, regarding geographical aspects and LATAM? Talk to me about some of those challenges. >> Let me share with you my personal journey. My challenges started with the moment I decided to start engineering. A career that is traditional considered for men only, although this changes over the time, you will realize that the stereotype remains in many people minds right? It happens not only in Peru I can see it in Latin America. Someone once asked me if I wouldn't like to study something easier for a woman, right? And I just, when I received that question, that helping me to reaffirm that it was taking the right decision and I have the fortune to work with companies that believe in female leadership and the importance of our contribution and empower me to do things differently. Although I must confess that this was not always like this. I experienced the situation when I have to show that I'm so much and more capable and prepared than a man to take a major challenge. So despite the fact in the recent years you have had the great advances in integration of women in the field of science and technology, the gap in equality in equality in this sector still continues and many times the attitude towards women is discriminatory considering that we don't have enough knowledge and we don't have enough strength to overcome challenge without the ability to give the extra mile that is often required, or simply because of a gender issue. And generally speaking, opportunities that they're not equal. Neither in salaries. Several studies have revealed that in the same position since at position level within company, men's salary or benefits are higher than the woman. In addition, sometimes the position for a woman is not necessarily for merit it's just to feel fulfill a gender quota and when it's fulfilled, there's no more opportunities. So it's still a long way to go. We are working in that, we are trying to inspire more women to be part of this world. This is an amazing world and this world needs our leadership, judgment, ambition, as a woman. So that's why we try to inspire and try to be a role model for some young ladies that they are thinking about this career in technology. >> Right, you bring up a great point though about one of the things in terms of hiring for quotas. And as we think about this International Women's Day, this year's theme is Breaking the Bias. Where do you think we are with that? >> I think we have a lot long, long way to go to. Today we don't see that we have more women in some leadership roles in technology. We see more young ladies studying engineering but you know what, when you talk about stereotypes we need to understand, or the bias, the bias is not only what the society it's giving you, it's also your own bias because we need to understand that technology careers is not only for men it's also for a woman. And we need to understand and change the perspective that we see the challenges that we have in our life because sometimes that could be a really stopper in your professional life. And for me, we don't, we really need to understand that it's important. We cannot stop believing in ourself and we can achieve whatever we want. So we never stop pursuing our goals and achieve what you really need to achieve and as I said all the time, get inspired by women with great achievements who have changed this world technology. We have many examples of that for many years. We have Eva Maria Kiesler, the core inventor of Wi-Fi, Radia Joy Perlman, known as the the mother of the internet and Ada Lovelace who became the first female computer programmer. So we have many examples in this story to understand that the limit is on you. So the bias we need to break the first one is the bias that you have of yourself. >> That's a good point. That's a really good point there. I'm curious, what would your recommendation be? You obviously had, you had that natural curiosity that we talked about. You also seems like you had great parents who were very encouraging of all of the different things that you were interested in. What do you recommend for women maybe starting out in the STEM area or in tech in particular? How do they get that courage to just try? >> You know what, the main thing I guess as I mentioned before, is to put aside the stereotypes, right? And get out of your head, the standing out career like science, technology and engineering is only for a man. All the time I have this list for me, that is lesson learned. And my lesson learned is please don't think that you cannot do it. Try it. If you go and the things do not work well, try it again and try it again. So don't feel stopped because you face your first challenge and the challenge it's very difficult, because we have the courage to do that and you know what? It is very and interesting to understand that women has resilience, we have the courage to do anything, we are multi tasking all the time they say women can do many things at the same time and we have this particular way to communicate. We are very inclusive. We make empathy. We're just leading with a cohesion concept of a team. So we need to explore more about our strengths and try to encourage from them. And one of the main things for me is don't feel afraid and transform, you know, when you feel like that, transfer that as your power, you're encouraged to continue. So we need to transform our fears in our, I always said our gasoline to continue and then your motive to be successful. So transform your fears. >> I love that. >> That's my main focus. >> Transform your fear. That's great advice there is. And I will say no, don't be afraid to raise your hand and ask a question 'cause I guarantee you, many people in the room whether it's a physical room these days or it's a virtual video conferencing room, probably have the same question. Be the one to raise your hand and ask. But I love how you're saying transform that fear 'cause it's there. Don't be afraid to fail but also we need to have those female role models, mentors and sponsors that we can see that can have help us kind of in that transformation process, that mentorship is really critical to help guide that along. >> Yes, yes, yes, that's correct and I will, I am, I was really fortunate because I have real role models in my life not only, as I mentioned my dad and also one of the things that I recognize in this company that I work for that empower leadership from women and I identify some role models I want to follow and I ask her in each particular company to be my coach and to be my mentor, because of course you are starting in the technology side and you need more from others that they can share with you her wisdom, right? And try to give you advice, how to work on that. And I always said, and I will always repeat because I sometimes I have the opportunity to mentor young ladies that they are very curious about the technology side and I share with them my experience, my lesson learned so they can build their own story to do this and I share all the time don't compete in a male environment in a gray suit. You have your own personality, you have your own strengths, you're a woman and you have your strength as a woman. Show that, be, you know, the black point in the middle of the white environment because you're different, your leadership is different. You have to understand that, value that and explore more about that so you can inspire others and you can inspire yourself and it's fair to say, please identify your achievements and value them because you deserve that, you fight for them and you have to be celebrate for that. >> Right. >> So that's the main, you know, the main idea when I share with these ladies but it's right, it's fair to be recognized for that. It's your effort, it's your way to do the things differently and it's very appreciated. >> Very appreciated and very inspiring. Thank you so much Karla for sharing your story, how you are balancing work life volunteerism, how it's complimentary. I found this conversation very inspiring so thank you so much for joining me today. >> Thank you. No, thank you so much Lisa. It was really a pleasure for me to be with you today. >> Excellent, likewise. For Karla Wong, I'm Lisa Martin. You're watching theCUBE's coverage of women in tech, International Women's Day 2022. 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>>from around the globe it's the >>cube >>presenting >>Future Cloud one event. A >>world of >>opportunities >>brought to you by Cisco. We're here with Dejoy Pandey a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah I think that's a great question I think what what we're seeing is that pretty much the application is the center of the universe and if you think about it the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this the digitization efforts that all of these companies are going through and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well but hasn't it always been about the application? But it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing? Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency, like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity availability, security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, zero trust used to be a buzzword now, it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah, that's a great question. And I think if you think about it today, that's the way things are. And if you think about this developer, all they want to do is run fast because they want to build those features out and they're going to pick and choose a purpose and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it, but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where there's friction between Netapp, Succop cited hopes and the cloud platform teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think, but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use, connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed, we're right off the back when the fire up that I'd and start developing the application, wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops, netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic. But it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud? Native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say, Ohio escapees, you're touching Cloud API is where the back end might sit, you're touching on primary purpose, maybe it's an oracle database or a mainframe even where transactional data exists, you're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in Salesforce somewhere. So it's cloud API is a song premise branch, it's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saAS providers that the developer has to use. And so this complexity is very very real and this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems. Uh Francisco >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle. I always say it's dangerous out there. And the point is you touched on this? It's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this? And how do you see it evolving? >>Yeah, I mean that that's that's a very important point. I mean I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank. The FBI wherever it sits on tram branch sas cloud, IOS android doesn't matter that FBI is your new security perimeter and the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what? Software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, Things change, Things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this API is security uses reputable. It has compliant, it is compliant to my my organization's needs because it is hosted, let's say from Germany and my organization wants a P is to be used only if they are being hosted out of Germany. So compliance needs and and security needs and reputation. Is it available all the time? Is it secure and being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner? Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in SAN Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability and so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean it's parts of the interview has a great security business. Is growing business. Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so. We do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in random security. I mean the entire portfolio that Cisco brings to the table is I don't run time security. The security checks aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime. Because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you. Pleasure to be here. >>This is Dave Volonte for the cube. Thank you for watching. Mhm. >>Mhm mm.

>>mhm, mm. All right. Mhm. Mhm, mm mm. Mhm. Yeah, mm. Mhm. Yeah, yeah. Mhm, mm. Okay. Mm. Yeah, Yeah. >>Mhm. Mhm. Yeah. Welcome to future cloud made possible by Cisco. My name is Dave Volonte and I'm your host. You know, the cloud is evolving like the universe is expanding at an accelerated pace. No longer is the cloud. Just a remote set of services, you know, somewhere up there. No, the cloud, it's extending to on premises. Data centers are reaching into the cloud through adjacent locations. Clouds are being connected together to each other and eventually they're gonna stretch to the edge and the far edge workloads, location latency, local laws and economics will define the value customers can extract from this new cloud model which unifies the operating experience independent of location. Cloud is moving rapidly from a spare capacity slash infrastructure resource to a platform for application innovation. Now, the challenge is how to make this new cloud simple, secure, agile and programmable. Oh and it has to be cloud agnostic. Now, the real opportunity for customers is to tap into a layer across clouds and data centers that abstracts the underlying complexity of the respective clouds and locations. And it's got to accommodate both mission critical workloads as well as general purpose applications across the spectrum cost, effectively enabling simplicity with minimal labor costs requires infrastructure i. E. Hardware, software, tooling, machine intelligence, AI and partnerships within an ecosystem. It's kind of accommodate a variety of application deployment models like serverless and containers and support for traditional work on VMS. By the way, it also requires a roadmap that will take us well into the next decade because the next 10 years they will not be like the last So why are we here? Well, the cube is covering Cisco's announcements today that connect next generation compute shared memory, intelligent networking and storage resource pools, bringing automation, visibility, application assurance and security to this new decentralized cloud. Now, of course in today's world you wouldn't be considered modern without supporting containers ai and operational tooling that is demanded by forward thinking practitioners. So sit back and enjoy the cubes, special coverage of Cisco's future cloud >>From around the globe. It's the Cube presenting future cloud one event, a world of opportunities brought to you by Cisco. >>We're here with Dejoy Pandey, a VP of emerging tech and incubation at Cisco. V. Joy. Good to see you. Welcome. >>Good to see you as well. Thank you Dave and pleasure to be here. >>So in 2020 we kind of had to redefine the notion of agility when it came to digital business or you know organizations, they had to rethink their concept of agility and business resilience. What are you seeing in terms of how companies are thinking about their operations in this sort of new abnormal context? >>Yeah, I think that's a great question. I think what what we're seeing is that pretty much the application is the center of the universe. And if you think about it, the application is actually driving brand recognition and the brand experience and the brand value. So the example I like to give is think about a banking app uh recovered that did everything that you would expect it to do. But if you wanted to withdraw cash from your bank you would actually have to go to the ATM and punch in some numbers and then look at your screen and go through a process and then finally withdraw cash. Think about what that would have, what what that would do in a post pandemic era where people are trying to go contact less. And so in a situation like this, the digitization efforts that all of these companies are going through and and the modernization of the automation is what is driving brand recognition, brand trust and brand experience. >>Yeah. So I was gonna ask you when I heard you say that, I was gonna say well, but hasn't it always been about the application, but it's different now, isn't it? So I wonder if you talk more about how the application is experience is changing. Yes. As a result of this new digital mandate. But how should organizations think about optimizing those experiences in this new world? >>Absolutely. And I think, yes, it's always been about the application, but it's becoming the center of the universe right now because all interactions with customers and consumers and even businesses are happening through that application. So if the application is unreliable or if the application is not available is untrusted insecure, uh, there's a problem. There's a problem with the brand, with the company and the trust that consumers and customers have with our company. So if you think about an application developer, the weight he or she is carrying on their shoulders is tremendous because you're thinking about rolling features quickly to be competitive. That's the only way to be competitive in this world. You need to think about availability and resiliency. Like you pointed out and experience, you need to think about security and trust. Am I as a customer or consumer willing to put my data in that application? So velocity, availability, Security and trust and all of that depends on the developer. So the experience, the security, the trust, the feature, velocity is what is driving the brand experience now. >>So are those two tensions that say agility and trust, you know, Zero Trust used to be a buzzword now it's a mandate. But are those two vectors counter posed? Can they be merged into one and not affect each other? Does the question makes sense? Right? Security usually handcuffs my speed. But how do you address that? >>Yeah that's a great question. And I think if you think about it today that's the way things are. And if you think about this developer all they want to do is run fast because they want to build those features out and they're going to pick and choose a piece and services that matter to them and build up their app and they want the complexities of the infrastructure and security and trust to be handled by somebody else is not that they don't care about it but they want that abstraction so that is handled by somebody else. And typically within an organization we've seen in the past where this friction between Netapp Sec ops I. T. Tops and and the cloud platform Teams and the developer on one side and these these frictions and these meetings and toil actually take a toll on the developer and that's why companies and apps and developers are not as agile as they would like to be. So I think but it doesn't have to be that way. So I think if there was something that would allow a developer to pick and choose, discover the apis that they would like to use connect those api is in a very simple manner and then be able to scale them out and be able to secure them and in fact not just secure them during the run time when it's deployed. We're right off the back when the fire up that I'd and start developing the application. Wouldn't that be nice? And as you do that, there is a smooth transition between that discovery connectivity and ease of consumption and security with the idea cops. Netapp psych ops teams and see source to ensure that they are not doing something that the organization won't allow them to do in a very seamless manner. >>I want to go back and talk about security but I want to add another complexity before we do that. So for a lot of organizations in the public cloud became a staple of keeping the lights on during the pandemic but it brings new complexities and differences in terms of latency security, which I want to come back to deployment models etcetera. So what are some of the specific networking challenges that you've seen with the cloud native architecture is how are you addressing those? >>Yeah. In fact, if you think about cloud, to me that is a that is a different way of seeing a distributed system. And if you think about a distributed system, what is at the center of the distributed system is the network. So my my favorite comment here is that the network is the wrong time for all distribute systems and modern applications. And that is true because if you think about where things are today, like you said, there's there's cloud assets that a developer might use in the banking example that I gave earlier. I mean if you want to build a contact less app so that you get verified, a customer gets verified on the app. They walk over to the ATM and they were broadcast without touching that ATM. In that kind of an example, you're touching the mobile Rus, let's say U S A P is you're touching cloud API is where the back end might sit. You're touching on primary PS maybe it's an oracle database or a mainframe even where transactional data exists. You're touching branch pipes were the team actually exists and the need for consistency when you withdraw cash and you're carrying all of this and in fact there might be customer data sitting in salesforce somewhere. So it's cloud API is a song premise branch. It's ass is mobile and you need to bring all of these things together and over time you will see more and more of these API is coming from various as providers. So it's not just cloud providers but saas providers that the developer has to use. And so this complexity is very, very real. And this complexity is across the wide open internet. So the application is built across this wide open internet. So the problems of discovery ability, the problems of being able to simply connect these apis and manage the data flow across these apis. The problems of consistency of policy and consumption because all of these areas have their own nuances and what they mean, what the arguments mean and what the A. P. I. Actually means. How do you make it consistent and easy for the developer? That is the networking problem. And that is a problem of building out this network, making traffic engineering easy, making policy easy, making scale out, scale down easy, all of that our networking problems. And so we are solving those problems uh Francisco. >>Yeah the internet is the new private network but it's not so private. So I want to go back to security. I often say that the security model of building a moat, you dig the moat, you get the hardened castle that's just outdated now that the queen is left her castle, I always say it's dangerous out there. And the point is you touched on this, it's it's a huge decentralized system and with distributed apps and data, that notion of perimeter security, it's just no longer valid. So I wonder if you could talk more about how you're thinking about this problem and you definitely address some of that in your earlier comments. But what are you specifically doing to address this and how do you see it evolving? >>Yeah, I mean, that's that's a very important point. I mean, I think if you think about again the wide open internet being the wrong time for all modern applications, what is perimeter security in this uh in this new world? I mean, it's to me it boils down to securing an API because again, going with that running example of this contact lists cash withdrawal feature for a bank, the ap wherever it's it's entre branch SAs cloud, IOS android doesn't matter that FBI is your new security perimeter. And the data object that is trying to access is also the new security perimeter. So if you can secure ap to ap communication and P two data object communication, you should be good. So that is the new frontier. But guess what software is buggy? Everybody's software not saying Cisco software, everybody's Softwares buggy. Uh software is buggy, humans are not reliable and so things mature, things change, things evolve over time. So there needs to be defense in depth. So you need to secure at the API layer had the data object layer, but you also need to secure at every layer below it so that you have good defense and depth if any layer in between is not working out properly. So for us that means ensuring ap to ap communication, not just during long time when the app has been deployed and is running, but during deployment and also during the development life cycle. So as soon as the developer launches an ID, they should be able to figure out that this api is security uses reputable, it has compliant, it is compliant to my to my organization's needs because it is hosted, let's say from Germany and my organization wants appears to be used only if they are being hosted out of Germany so compliance needs and and security needs and reputation. Is it available all the time? Is it secure? And being able to provide that feedback all the time between the security teams and the developer teams in a very seamless real time manner. Yes, again, that's something that we're trying to solve through some of the services that we're trying to produce in san Francisco. >>Yeah, I mean those that layered approach that you're talking about is critical because every layer has, you know, some vulnerability. And so you you've got to protect that with some depth in terms of thinking about security, how should we think about where where Cisco's primary value add is, I mean as parts of the interview has a great security business is growing business, Is it your intention to to to to add value across the entire value chain? I mean obviously you can't do everything so you've got a partner but so has the we think about Cisco's role over the next I'm thinking longer term over the over the next decade. >>Yeah, I mean I think so, we do come in with good strength from the runtime side of the house. So if you think about the security aspects that we haven't played today, uh there's a significant set of assets that we have around user security around around uh with with do and password less. We have significant assets in runtime security. I mean, the entire portfolio that Cisco brings to the table is around one time security, the secure X aspects around posture and policy that will bring to the table. And as you see, Cisco evolve over time, you will see us shifting left. I mean, I know it's an overused term, but that is where security is moving towards. And so that is where api security and data security are moving towards. So learning what we have during runtime because again, runtime is where you learn what's available and that's where you can apply all of the M. L. And I models to figure out what works what doesn't taking those learnings, Taking those catalogs, taking that reputation database and moving it into the deployment and development life cycle and making sure that that's part of that entire they have to deploy to runtime chain is what you will see. Cisco do overtime. >>That's fantastic phenomenal perspective video. Thanks for coming on the cube. Great to have you and look forward to having you again. >>Absolutely. Thank you >>in a moment. We'll talk hybrid cloud applications operations and potential gaps that need to be addressed with costume, Das and VJ Venugopal. You're watching the cube the global leader in high tech coverage. Mhm >>You were cloud. It isn't just a cloud. It's everything flowing through it. It's alive. Yeah, connecting users, applications, data and devices and whether it's cloud, native hybrid or multi cloud, it's more distributed than ever. One company takes you inside, giving you the visibility and the insight you need to take action. >>One company >>has the vision to understand it, all the experience, to securely connect at all on any platform in any environment. So you can work wherever work takes you in a cloud first world between your cloud and being cloud smart, there's a bridge. Cisco the bridge to possible. >>Okay. We're here with costume does, who is the Senior Vice President, General Manager of Cloud and compute at Cisco. And VJ Venugopal, who is the Senior Director for Product Management for cloud compute at Cisco. KTV. J. Good to see you guys welcome. >>Great to see you. Dave to be here. >>Katie, let's talk about cloud you And I last time we're face to face was in Barcelona where we love talking about cloud and I always say to people look, Cisco is not a hyper Scaler, but the big public cloud players, they're like giving you a gift. They spent almost actually over $100 billion last year on Capex. The big four. So you can build on that infrastructure. Cisco is all about hybrid cloud. So help us understand the strategy. There may be how you can leverage that build out and importantly what a customer is telling you they want out of hybrid cloud. >>Yeah, no that's that's that's a perfect question to start with. Dave. So yes. So the hybrid hyper scholars have invested heavily building out their assets. There's a great lot of innovation coming from that space. Um There's also a great innovation set of innovation coming from open source and and that's another source of uh a gift. In fact the I. T. Community. But when I look at my customers they're saying well how do I in the context of my business implement a strategy that takes into consideration everything that I have to manage um in terms of my contemporary work clothes, in terms of my legacy, in terms of everything my developer community wants to do on DEVOPS and really harnessed that innovation that's built in the public cloud, that built an open source that built internally to me, and that naturally leads them down the path of a hybrid cloud strategy. And Siskel's mission is to provide for that imperative, the simplest more power, more powerful platform to deliver hybrid cloud and that platform. Uh It's inter site we've been investing in. Inner side, it's a it's a SAS um service um inner side delivers to them that bridge between their estates of today that were closer today, the need for them to be guardians of enterprise grade resiliency with the agility uh that's needed for the future. The embracing of cloud. Native of new paradigms of deVOPS models, the embracing of innovation coming from public cloud and an open source and bridging those two is what inner side has been doing. That's kind of that's kind of the crux of our strategy. Of course we have the entire portfolio behind it to support any, any version of that, whether that is on prem in the cloud, hybrid, cloud, multi cloud and so forth. >>But but if I understand it correctly from what I heard earlier today, the inter site is really a linchpin of that strategy, is it not? >>It really is and may take a second to totally familiarize those who don't know inner side with what it is. We started building this platform quite a few years back and we we built a ground up to be an immensely scalable SAs, super simple hybrid cloud platform and it's a platform that provides a slew of service is inherently and then on top of that there are suites of services, the sweets of services that are tied to infrastructure, automation. Cisco, as well as Cisco partners. The streets of services that have nothing to do with Cisco um products from a hardware perspective. And it's got to do with more cloud orchestration and cloud native and inner side and its suite of services um continue to kind of increase in pace and velocity of delivery video. Just over the last two quarters we've announced a whole number of things will go a little bit deeper into some of those but they span everything from infrastructure automation to kubernetes and delivering community than service to workload optimization and having visibility into your cloud estate. How much it's costing into your on premise state into your work clothes and how they're performing. It's got integrations with other tooling with both Cisco Abdi uh as well as non Cisco um, assets and then and then it's got a whole slew of capabilities around orchestration because at the end of the day, the job of it is to deliver something that works and works at scale that you can monitor and make sure is resilient and that includes that. That includes a workflow and ability to say, you know, do this and do this and do this. Or it includes other ways of automation, like infrastructure as code and so forth. So it includes self service that so that expand that. But inside the world's simplest hybrid cloud platform, rapidly evolving rapidly delivering new services. And uh we'll talk about some more of those day. >>Great, thank you, Katie VJ. Let's bring you into the discussion. You guys recently made an announcement with the ASCIi corp. I was stoked because even though it seemed like a long time ago, pre covid, I mean in my predictions post, I said, ha, she was a name to watch our data partners. Et are you look at the survey data and they really have become mainstream? You know, particularly we think very important in the whole multi cloud discussion. And as well, they're attractive to customers. They have open source offerings. You can very easily experiment. Smaller organizations can take advantage. But if you want to upgrade to enterprise features like clustering or whatever, you can plug right in. Not a big complicated migration. So a very, very compelling story there. Why is this important? Why is this partnership important to Cisco's customers? Mhm. >>Absolutely. When the spot on every single thing that you said, let me just start by paraphrasing what ambition statement is in the cloud and computer group. Right ambition statement is to enable a cloud operating model for hybrid cloud. And what we mean by that is the ability to have extreme amounts of automation orchestration and observe ability across your hybrid cloud idea operations now. Uh So developers and applications team get a great amount of agility in public clouds and we're on a mission to bring that kind of agility and automation to the private cloud and to the data centers and inter site is a quickie platform and lynchpin to enable that kind of operations. Uh, Cloud like operations in the in the private clouds and the key uh As you rightly said, harsher car is the, you know, they were the inventors of the concept of infrastructure at school and in terra form, they have the world's number one infrastructure as code platform. So it became a natural partnership for Cisco to enter into a technology partnership with harsher card to integrate inter site with hardship cops, terra form to bring the benefits of infrastructure as code to the to hybrid cloud operations. And we've entered into a very tight integration and uh partnership where we allow developers devops teams and infrastructure or administrators to allow the use of infrastructure as code in a SAS delivered manner for both public and private club. So it's a very unique partnership and a unique integration that allows the benefits of cloud managed i E C. To be delivered to hybrid cloud operations. And we've been very happy and proud to be partnering with Russian government shutdown. >>Yeah, Terra form gets very high marks from customers. The a lot of value there. The inner side integration adds to that value. Let's stay on cloud native for a minute. We all talk about cloud native cady was sort of mentioning before you got the the core apps, uh you want to protect those, make sure their enterprise create but they gotta be cool as well for developers. You're connecting to other apps in the cloud or wherever. How are you guys thinking about this? Cloud native trend? What other movies are you making in this regard? >>I mean cloud native is there is one of the paramount I. D. Trends of today and we're seeing massive amounts of adoption of cloud native architecture in all modern applications. Now, Cloud Native has become synonymous with kubernetes these days and communities has emerged as a de facto cloud native platform for modern cloud native app development. Now, what Cisco has done is we have created a brand new SAs delivered kubernetes service that is integrated with inter site, we call it the inter site community service for A. Ks. And this just geared a little over one month ago. Now, what interstate kubernetes service does is it delivers a cloud managed and cloud delivered kubernetes service that can be deployed on any supported target infrastructure. It could be a Cisco infrastructure, it could be a third party infrastructure or it could even be public club. But think of it as kubernetes anywhere delivered as says, managed from inside. It's a very powerful capability that we've just released into inter site to enable the power of communities and clog native to be used to be used anywhere. But today we made a very important aspect because we are today announced the brand new Cisco service mess manager, the Cisco service mesh manager, which is available as an extension to the KS are doing decide basically we see service measures as being the future of networking right in the past we had layer to networking and layer three networking and now with service measures, application networking and layer seven networking is the next frontier of, of networking. But you need to think about networking for the application age very differently how it is managed, how it is deployed. It needs to be ready, developer friendly and developer centric. And so what we've done is we've built out an application networking strategy and built out the service match manager as a very simple way to deliver application networking through the consumers, like like developers and application teams. This is built on an acquisition that Cisco made recently of Banzai Cloud and we've taken the assets of Banzai Cloud and deliver the Cisco service mesh manager as an extension to KS. That brings the promise of future networking and modern networking to application and development gives >>God thank you. BJ. And so Katie, let's let's let's wrap this up. I mean, there was a lot in this announcement today, a lot of themes around openness, heterogeneity and a lot of functionality and value. Give us your final thoughts. >>Absolutely. So, couple of things to close on, first of all, um Inner side is the simplest, most powerful hybrid cloud platform out there. It enables that that cloud operating model that VJ talked about, but enables that across cloud. So it's sad, it's relatively easy to get into it and give it a spin so that I'd highly encouraged anybody who's not familiar with it to try it out and anybody who is familiar with it to look at it again, because they're probably services in there that you didn't notice or didn't know last time you looked at it because we're moving so fast. So that's the first thing. The second thing I close with is um, we've been talking about this bridge that's kind of bridging, bridging uh your your on prem your open source, your cloud estates. And it's so important to to make that mental leap because uh in past generation, we used to talk about integrating technologies together and then with public cloud, we started talking about move to public cloud, but it's really how do we integrate, how do we integrate all of that innovation that's coming from the hyper scale, is everything they're doing to innovate superfast, All of that innovation is coming from open source, all of that innovation that's coming from from companies around the world, including Cisco, How do we integrate that to deliver an outcome? Because at the end of the day, if you're a cloud of Steam, if you're an idea of Steam, your job is to deliver an outcome and our mission is to make it super simple for you to do that. That's the mission we're on and we're hoping that everybody that's excited as we are about how simple we made that. >>Great, thank you a lot in this announcement today, appreciate you guys coming back on and help us unpack you know, some of the details. Thank thanks so much. Great having you. >>Thank you >>Dave in a moment. We're gonna come back and talk about disruptive technologies and futures in the age of hybrid cloud with Vegas Rattana and James leach. You're watching the cube, the global leader in high tech coverage. >>What if your server box >>wasn't a box at >>all? What if it could do anything run anything? >>Be any box you >>need with massive scale precision and intelligence managed and optimized from the cloud integrated with all your clouds, private, public or hybrid. So you can build whatever you need today and tomorrow. The potential of this box is unlimited. Unstoppable unseen ever before. Unbox the future with Cisco UCS X series powered by inter site >>Cisco. >>The bridge to possible. Yeah >>we're here with Vegas Rattana who's the director of product management for Pcs at Cisco. And James Leach is the director of business development for U. C. S. At the Cisco as well. We're gonna talk about computing in the age of hybrid cloud. Welcome gentlemen. Great to see you. >>Thank you. >>Thank you because let's start with you and talk about a little bit about computing architectures. We know that they're evolving. They're supporting new data intensive and other workloads especially as high performance workload requirements. What's this guy's point of view on all this? I mean specifically interested in your thoughts on fabrics. I mean it's kind of your wheelhouse, you've got accelerators. What are the workloads that are driving these evolving technologies and how how is it impacting customers? What are you seeing? >>Sure. First of all, very excited to be here today. You're absolutely right. The pace of innovation and foundational platform ingredients have just been phenomenal in recent years. The fabric that's writers that drives the processing power, the Golden city all have been evolving just an amazing place and the peace will only pick up further. But ultimately it is all about applications and the way applications leverage those innovations. And we do see applications evolving quite rapidly. The new classes of applications are evolving to absorb those innovations and deliver much better business values. Very, very exciting time step. We're talking about the impact on the customers. Well, these innovations have helped them very positively. We do see significant challenges in the data center with the point product based approach of delivering these platforms, innovations to the applications. What has happened is uh, these innovations today are being packaged as point point products to meet the needs of a specific application and as you know, the different applications have no different needs. Some applications need more to abuse, others need more memory, yet others need, you know, more course, something different kinds of fabrics. As a result, if you walk into a data center today, it is very common to see many different point products in the data center. This creates a manageability challenge. Imagine the aspect of managing, you know, several different form factors want you to you purpose built servers. The variety of, you know, a blade form factor, you know, this reminds me of the situation we had before smartphones arrived. You remember the days when you when we used to have a GPS device for navigation system, a cool music device for listening to the music. A phone device for making a call camera for taking the photos right? And we were all excited about it. It's when a smart phones the right that we realized all those cool innovations could be delivered in a much simpler, much convenient and easy to consume through one device. And you know, I could uh, that could completely transform our experience. So we see the customers were benefiting from these innovations to have a way to consume those things in a much more simplistic way than they are able to go to that. >>And I like to look, it's always been about the applications. But to your point, the applications are now moving in a much faster pace. The the customer experience is expectation is way escalated. And when you combine all these, I love your analogy there because because when you combine all these capabilities, it allows us to develop new Applications, new capabilities, new customer experiences. So that's that I always say the next 10 years, they ain't gonna be like the last James Public Cloud obviously is heavily influencing compute design and and and customer operating models. You know, it's funny when the public cloud first hit the market, everyone we were swooning about low cost standard off the shelf servers in storage devices, but it quickly became obvious that customers needed more. So I wonder if you could comment on this. How are the trends that we've seen from the hyper scale, Is how are they filtering into on prem infrastructure and maybe, you know, maybe there's some differences there as well that you could address. >>Absolutely. So I'd say, first of all, quite frankly, you know, public cloud has completely changed the expectations of how our customers want to consume, compute, right? So customers, especially in a public cloud environment, they've gotten used to or, you know, come to accept that they should consume from the application out, right? They want a very application focused view, a services focused view of the world. They don't want to think about infrastructure, right? They want to think about their application, they wanna move outward, Right? So this means that the infrastructure basically has to meet the application where it lives. So what that means for us is that, you know, we're taking a different approach. We're we've decided that we're not going to chase this single pane of glass view of the world, which, frankly, our customers don't want, they don't want a single pane of glass. What they want is a single operating model. They want an operating model that's similar to what they can get at the public with the public cloud, but they wanted across all of their cloud options they wanted across private cloud across hybrid cloud options as well. So what that means is they don't want to just consume infrastructure services. They want all of their cloud services from this operating model. So that means that they may want to consume infrastructure services for automation Orchestration, but they also need kubernetes services. They also need virtualization services, They may need terror form workload optimization. All of these services have to be available, um, from within the operating model, a consistent operating model. Right? So it doesn't matter whether you're talking about private cloud, hybrid cloud anywhere where the application lives. It doesn't matter what matters is that we have a consistent model that we think about it from the application out. And frankly, I'd say this has been the stumbling block for private cloud. Private cloud is hard, right. This is why it hasn't been really solved yet. This is why we had to take a brand new approach. And frankly, it's why we're super excited about X series and inter site as that operating model that fits the hybrid cloud better than anything else we've seen >>is acute. First, first time technology vendor has ever said it's not about a single pane of glass because I've been hearing for decades, we're gonna deliver a single pane of glass is going to be seamless and it never happens. It's like a single version of the truth. It's aspirational and, and it's just not reality. So can we stay in the X series for a minute James? Uh, maybe in this context, but in the launch that we saw today was like a fire hose of announcements. So how does the X series fit into the strategy with inter site and hybrid cloud and this operating model that you're talking about? >>Right. So I think it goes hand in hand, right. Um the two pieces go together very well. So we have uh, you know, this idea of a single operating model that is definitely something that our customers demand, right? It's what we have to have, but at the same time we need to solve the problems of the cost was talking about before we need a single infrastructure to go along with that single operating model. So no longer do we need to have silos within the infrastructure that give us different operating models are different sets of benefits when you want infrastructure that can kind of do all of those configurations, all those applications. And then, you know, the operating model is very important because that's where we abstract the complexity that could come with just throwing all that technology at the infrastructure so that, you know, this is, you know, the way that we think about is the data center is not centered right? It's no longer centered applications live everywhere. Infrastructure lives everywhere. And you know, we need to have that consistent operating model but we need to do things within the infrastructure as well to take full advantage. Right? So we want all the sas benefits um, of a Ci CD model of, you know, the inter site can bring, we want all that that proactive recommendation engine with the power of A I behind it. We want the connected support experience went all of that. They want to do it across the single infrastructure and we think that that's how they tie together, that's why one or the other doesn't really solve the problem. But both together, that's why we're here. That's why we're super excited. >>So Vegas, I make you laugh a little bit when I was an analyst at I D C, I was deep in infrastructure and then when I left I was doing, I was working with application development heads and like you said, uh infrastructure, it was just a, you know, roadblock but but so the target speakers with Cisco announced UCS a decade ago, I totally missed it. I didn't understand it. I thought it was Cisco getting into the traditional server business and it wasn't until I dug in then I realized that your vision was really to transform infrastructure, deployment and management and change them all. I was like, okay, I got that wrong uh but but so let's talk about the the ecosystem and the joint development efforts that are going on there, X series, how does it fit into this, this converged infrastructure business that you've, you've built and grown with partners, you got storage partners like Netapp and Pure, you've got i SV partners in the ecosystem. We see cohesive, he has been a while since we we hung out with all these companies at the Cisco live hopefully next year, but tell us what's happening in that regard. >>Absolutely, I'm looking forward to seeing you in the Cisco live next year. You know, they have absolutely you brought up a very good point. You see this is about the ecosystem that it brings together, it's about making our customers bring up the entire infrastructure from the core foundational hardware all the way to the application level so that they can, you know, go off and running pretty quick. The converse infrastructure has been one of the corners 2.5 hour of the strategy, as you pointed out in the last decade. And and and I'm I'm very glad to share that converse infrastructure continues to be a very popular architecture for several enterprise applications. Seven today, in fact, it is the preferred architecture for mission critical applications where performance resiliency latency are the critical requirements there almost a de facto standards for large scale deployments of virtualized and business critical data bases and so forth with X series with our partnerships with our Stories partners. Those architectures will absolutely continue and will get better. But in addition as a hybrid cloud world, so we are now bringing in the benefits of canvas in infrastructure uh to the world of hybrid cloud will be supporting the hybrid cloud applications now with the CIA infrastructure that we have built together with our strong partnership with the Stories partners to deliver the same benefits to the new ways applications as well. >>Yeah, that's what customers want. They want that cloud operating model. Right, go ahead please. >>I was going to say, you know, the CIA model will continue to thrive. It will transition uh it will expand the use cases now for the new use cases that were beginning to, you know, say they've absolutely >>great thank you for that. And James uh have said earlier today, we heard this huge announcement, um a lot of lot of parts to it and we heard Katie talk about this initiative is it's really computing built for the next decade. I mean I like that because it shows some vision and you've got a road map that you've thought through the coming changes in workloads and infrastructure management and and some of the technology that you can take advantage of beyond just uh, you know, one or two product cycles. So, but I want to understand what you've done here specifically that you feel differentiates you from other competitive architectures in the industry. >>Sure. You know that's a great question. Number one. Number two, um I'm frankly a little bit concerned at times for for customers in general for our customers customers in general because if you look at what's in the market, right, these rinse and repeat systems that were effectively just rehashes of the same old design, right? That we've seen since before 2000 and nine when we brought you C. S to market these are what we're seeing over and over and over again. That's that's not really going to work anymore frankly. And I think that people are getting lulled into a false sense of security by seeing those things continually put in the market. We rethought this from the ground up because frankly future proofing starts now, right? If you're not doing it right today, future proofing isn't even on your radar because you're not even you're not even today proved. So we re thought the entire chassis, the entire architecture from the ground up. Okay. If you look at other vendors, if you look at other solutions in the market, what you'll see is things like management inside the chassis. That's a great example, daisy chaining them together >>like who >>needs that? Who wants that? Like that kind of complexity is first of all, it's ridiculous. Um, second of all, um, if you want to manage across clouds, you have to do it from the cloud, right. It's just common sense. You have to move management where it can have the scale and the scope that it needs to impact your entire domain, your world, which is much larger now than it was before. We're talking about true hybrid cloud here. Right. So we had to solve certain problems that existed in the traditional architecture. You know, I can't tell you how many times I heard you talk about the mid plane is a great example. You know, the mid plane and a chastity is a limiting factor. It limits us on how much we can connect or how much bandwidth we have available to the chassis. It limits us on air flow and other things. So how do you solve that problem? Simple. Just get rid of it. Like we just we took it out, right. It's not no longer a problem. We designed an architecture that doesn't need it. It doesn't rely on it. No forklift upgrades. So, as we start moving down the path of needing liquid cooling or maybe we need to take advantage of some new, high performance, low latency fabrics. We can do that with almost. No problem at all. Right, So, we don't have any forklift upgrades. Park your forklift on the side. You won't need it anymore because you can upgrade gradually. You can move along as technologies come into existence that maybe don't even exist. They they may not even be on our radar today to take advantage of. But I like to think of these technologies, they're really important to our customers. These are, you know, we can call them disruptive technologies. The reality is that we don't want to disrupt our customers with these technologies. We want to give them these technologies so they can go out and be disruptive themselves. Right? And this is the way that we've designed this from the ground up to be easy to consume and to take advantage of what we know about today and what's coming in the future that we may not even know about. So we think this is a way to give our customers that ultimate capability flexibility and and future proofing. >>I like I like that phrase True hybrid cloud. It's one that we've used for years and but to me this is all about that horizontal infrastructure that can support that vision of what true hybrid cloud is. You can support the mission critical applications. You can you can develop on the system and you can support a variety of workload. You're not locked into one narrow stovepipe and that does have legs, Vegas and James. Thanks so much for coming on the program. Great to see you. >>Yeah. Thank you. Thank you. >>When we return shortly thomas Shiva who leads Cisco's data center group will be here and thomas has some thoughts about the transformation of networking I. T. Teams. You don't wanna miss what he has to say. You're watching the cube. The global leader in high tech company. Okay, >>mm. Mhm, mm. Okay. Mhm. Yeah. Mhm. Yeah. >>Mhm. Yes. Yeah. Okay. We're here with thomas Shiva who is the Vice president of Product Management, A K A VP of all things data center, networking STN cloud. You name it in that category. Welcome thomas. Good to see you again. >>Hey Sam. Yes. Thanks for having me on. >>Yeah, it's our pleasure. Okay, let's get right into observe ability. When you think about observe ability, visibility, infrastructure monitoring problem resolution across the network. How does cloud change things? In other words, what are the challenges that networking teams are currently facing as they're moving to the cloud and trying to implement hybrid cloud? >>Yeah. Yeah, visibility as always is very, very important. And it's quite frankly, it's not just it's not just the networking team is actually the application team to write. And as you pointed out, the underlying impetus to what's going on here is the data center is where the data is. And I think we set us a couple years back and really what happens the applications are going to be deployed uh in different locations, right. Whether it's in a public cloud, whether it's on prayer, uh, and they are built differently right there, built as microservices, they might actually be distributed as well at the same application. And so what that really means is you need as an operator as well as actually a user better visibility. Where are my pieces and you need to be able to correlate between where the app is and what the underlying network is that is in place in these different locations. So you have actually a good knowledge while the app is running so fantastic or sometimes not. So I think that's that's really the problem statement. What what we're trying to go afterwards, observe ability. >>Okay, and let's double click on that. So a lot of customers tell me that you gotta stare at log files until your eyes bleed and you gotta bring in guys with lab coats who have phds to figure all this stuff out. So, so you just described, it's getting more complex, but at the same time you have to simplify things. So how how are you doing that, >>correct? So what we basically have done is we have this fantastic product that that is called 1000 Ice. And so what this does is basically as the name, which I think is a fantastic fantastic name. You have these sensors everywhere. Um, and you can have a good correlation on uh links between if I run from a site to aside from a site to a cloud, from a cloud to cloud and you basically can measure what is the performance of these links. And so what we're, what we're doing here is we're actually extending the footprint of these thousands agent. Right? Instead of just having uh inversion machine clouds, we are now embedding them with the Cisco network devices. Right? We announced this with the catalyst 9000 and we're extending this now to our 8000 catalyst product line for the for the SD were in products as well as to the data center products the next line. Um and so what you see is is, you know, half a saying, you have 1000 eyes, you get a million insights and you get a billion dollar of improvements uh for how your applications run. And this is really uh, the power of tying together the footprint of where the network is with the visibility, what is going on. So you actually know the application behavior that is attached to this network. >>I see. So okay. So as the cloud evolves and expands it connects your actually enabling 1000 eyes to go further, not just confined within a single data center location, but out to the network across clouds, et cetera, >>correct. Wherever the network is, you're going to have 1000 I sensor and you can't bring this together and you can quite frankly pick if you want to say, hey, I have my application in public cloud provider, a uh, domain one and I have another one domain to, I can't do monitor that link. I can also monitor have a user that has a campus location or branch location. I kind of put an agent there and then I can monitor the connectivity from that branch location all the way to the let's say corporations that data centre, our headquarter or to the cloud. And I can have these probes and just we have visibility and saying, hey, if there's a performance, I know where the issue is and then I obviously can use all the other foods that we have to address those. >>All right, let's talk about the cloud operating model. Everybody tells us it's really the change in the model that drives big numbers in terms of R. O. I. And I want you to maybe address how you're bringing automation and devops to this world of of hybrid and specifically how is Cisco enabling I. T. Organizations to move to a cloud operating model? Is that cloud definition expands? >>Yeah, no that's that's another interesting topic beyond the observe ability. So really, really what we're seeing and this is going on for uh I want to say a couple of years now, it's really this transition from operating infrastructure as a networking team more like a service like what you would expect from a cloud provider. Right? It's really around the network team offering services like a cloud provided us. And that's really what the meaning is of cloud operating model. Right? But this is infrastructure running your own data center where that's linking that infrastructure was whatever runs on the public club is operating and like a cloud service. And so we are on this journey for why? So one of the examples uh then we have removing some of the control software assets, the customers that they can deploy on prayer uh to uh an instance that they can deploy in a cloud provider and just busy, insane. She ate things there and then just run it that way. Right. And so the latest example for this is what we have our identity service engine that is now limited availability available on AWS and will become available in mid this year, both in Italy as unusual as a service. You can just go to market place, you can load it there and now you create, you can start running your policy control in a cloud, managing your access infrastructure in your data center, in your campus wherever you want to do it. And so that's just one example of how we see our customers network operations team taking advantage of a cloud operating model and basically employing their, their tools where they need them and when they need them. >>So what's the scope of, I hope I'm saying it right. Ice, right. I see. I think it's called ice. What's the scope of that like for instance, turn in effect my or even, you know, address simplify my security approach. >>Absolutely. That's now coming to what is the beauty of the product itself? Yes. What you can do is really is that there's a lot of people talking about else. How do I get to zero trust approach to networking? How do I get to a much more dynamic, flexible segmentation in my infrastructure. Again, whether this is only campus X as well as a data center and Ice help today, you can use this as a point to define your policies and then any connect from there. Right. In this particular case we would instant Ice in the cloud as a software load. You now can connect and say, hey, I want to manage and program my network infrastructure and my data center on my campus, going to the respective control over this DNA Center for campus or whether it is the A. C. I. Policy controller. And so yes, what you get as an effect out of this is a very elegant way to automatically manage in one place. What is my policy and then drive the right segmentation in your network infrastructure? >>zero. Trust that, you know, it was pre pandemic. It was kind of a buzzword. Now it's become a mandate. I wonder if we could talk about right. I mean I wonder if you talk about cloud native apps, you got all these developers that are working inside organizations. They're maintaining legacy apps. They're connecting their data to systems in the cloud there, sharing that data. I need these developers, they're rapidly advancing their skill sets. How is Cisco enabling its infrastructure to support this world of cloud? Native making infrastructure more responsive and agile for application developers? >>Yeah. So, you know, we're going to the top of his visibility, we talked about the operating model, how how our network operators actually want to use tools going forward. Now, the next step to this is it's not just the operator. How do they actually, where do they want to put these tools, how they, how they interact with these tools as well as quite frankly as how, let's say, a devops team on application team or Oclock team also wants to take advantage of the program ability of the underlying network. And this is where we're moving into this whole cloud native discussion, right? Which is really two angles, that is the cloud native way, how applications are being built. And then there is the cloud native way, how you interact with infrastructure. Right? And so what we have done is we're a putting in place the on ramps between clouds and then on top of it we're exposing for all these tools, a P I S that can be used in leverage by standard uh cloud tools or uh cloud native tools. Right. And one example or two examples we always have and again, we're on this journey for a while is both answerable uh script capabilities that exist from red hat as well as uh Ashitaka from capabilities that you can orchestrate across infrastructure to drive infrastructure, automation and what what really stands behind it is what either the networking operations team wants to do or even the ap team. They want to be able to describe the application as a code and then drive automatically or programmatically in situation of infrastructure needed for that application. And so what you see us doing is providing all these capability as an interface for all our network tools. Right. Whether it's this ice that I just mentioned, whether this is our D. C. And controllers in the data center, uh whether these are the controllers in the in the campus for all of those, we have cloud native interfaces. So operator or uh devops team can actually interact directly with that infrastructure the way they would do today with everything that lives in the cloud, with everything how they brought the application. >>This is key. You can't even have the conversation of op cloud operating model that includes and comprises on prem without programmable infrastructure. So that's that's very important. Last question, thomas our customers actually using this, they made the announcement today. There are there are there any examples of customers out there doing this? >>We do have a lot of customers out there that are moving down the past and using the D. D. Cisco high performance infrastructure, but also on the compute side as well as on an exercise one of the customers. Uh and this is like an interesting case. It's Rakuten uh record and is a large tackle provider, a mobile five G. Operator uh in Japan and expanding and is in different countries. Uh and so people something oh, cloud, you must be talking about the public cloud provider, the big the big three or four. But if you look at it, there's a lot of the tackle service providers are actually cloud providers as well and expanding very rapidly. And so we're actually very proud to work together with with Rakuten and help them building a high performance uh, data and infrastructure based on hard gig and actually phone a gig uh to drive their deployment to. It's a five G mobile cloud infrastructure, which is which is uh where the whole the whole world where traffic is going. And so it's really exciting to see this development and see the power of automation visibility uh together with the high performance infrastructure becoming reality and delivering actually services, >>you have some great points you're making there. Yes, you have the big four clouds, your enormous, but then you have a lot of actually quite large clouds. Telcos that are either approximate to those clouds or they're in places where those hyper scholars may not have a presence and building out their own infrastructure. So so that's a great case study uh thomas, hey, great having you on. Thanks so much for spending some time with us. >>Yeah, same here. I appreciate it. Thanks a lot. >>I'd like to thank Cisco and our guests today V Joy, Katie VJ, viscous James and thomas for all your insights into this evolving world of hybrid cloud, as we said at the top of the next decade will be defined by an entirely new set of rules. And it's quite possible things will evolve more quickly because the cloud is maturing and has paved the way for a new operating model where everything is delivered as a service, automation has become a mandate because we just can't keep throwing it labor at the problem anymore. And with a I so much more as possible in terms of driving operational efficiencies, simplicity and support of the workloads that are driving the digital transformation that we talk about all the time. This is Dave Volonte and I hope you've enjoyed today's program. Stay Safe, be well and we'll see you next time.

>>from around the globe. It's the >>cube >>With digital coverage of IBM think 2021 brought to you by IBM. Welcome back everyone to the cube coverage of IBM Think 2021. I'm john for a host of the cube got a great guest here scott heaven or vice president of marketing at IBM for data and AI cube. Alumni has been around the wave around data, had many conversations over the years scott. Welcome back to the Cuban, I wish we were in person but we're remote for the virtual conference for think 2021. Thanks for coming on >>john great to be here. And yeah, I guess we have adapted to the world of being on the screen. >>Well, great, great to have you in. One of the things about virtualization of media is that we get more content this year. There's so many more signature stories around um, IBM think and one of the things that's really fun for us is the data conversations in a I as as the transformation and innovation equations are coming together at scale. You're seeing an accelerated piece here. My first question for you is this digital shift that's going on? The preferences are shifting to virtual now digital in the wake of Covid, what do companies need to adapt from your perspective as you see this playing out? What's your perspective? >>It's interesting to use that term. So we've been calling it the great digital shift. And uh yeah, there's an there was an interesting survey, a pretty big survey of global C suite that Mackenzie did. And they pointed out that 79% of those leaders felt that Covid highlighted the immaturity of their digital capability. And while they thought they were on the right path and they were building strong digital capabilities, the whole world of the pandemic remote work, how you engage with customers call centers going, you know, off the hooks in terms of people calling, it just goes on and on and on. And And they also pointed out that 90, I think it was 96 of them are going to speed their digital reinvention. And you mentioned data, if you think about it, it's data that a few fuels digital capabilities. Right? What good is digital if it's not data? Right? It's all data. So it's the fuel that makes it all work. And when you think about the ability to leverage all your dad, you got to democratize it, it's siloed all over the place, it's growing at six times rate over the next three years. It's really all over the place, every touch point across the digital ecosystem. Um and the only way to deal with the data in to unlock its value, particularly in predictive ways is to Ai Right? And so what we're seeing is a huge amount of investment in multi cloud, really bringing together this notion of hybrid and then applying AI as the intelligence to create a more predictable and resilient business right through a digital model, right? Yeah, it's really the investment is really going through the roof. You >>know, I think AI has been, it's been demystified over the years, been a lot of people saw the machine learning and now you got NLP and data control planes that are making it more addressable. But the real thing that comes up here, I think this year is this role between business and consumer and AI has that kind of dynamic. And I want to ask you because I was just having a conversation with one of your partner, IBM partner Samsung, KC Joy runs E V P E V P for the B to B B to G Group at Samsung. It's a huge I. O. T. Thing. And AI is a big part of that consumer and we talked about the consumer electronics business issues, how is A I different for business versus the consumer is obviously an industrial iot edge and you've got automation piece. What's the difference? I mean, someone asked you that between business and consumer AI. >>Yeah, actually, I think that's one of the areas that we really differentiate ourselves and we're putting the bulk of investments, this notion of AI for business, Right? And you know, a lot of people think of A I sometimes they think of Siri and Alexa and things that go on in your car and all that. Obviously that's a big part of applying machine learning and all that, but when we talk about AI for business, we're thinking about four core attributes. Uh One is that it needs to understand the unique language of your business and industry, right? And that's not just natural language but it's the ability to debate, it's the ability to read documents, interpret documents. Um It's the ability to really understand the context because you and I can ask the same question five or six different ways and it needs to understand the business to be able to interpret that and help answer the question unlike like Siri or Alexa where you really got to have the right semantics and you know, it won't understand the nuances as well, so understand the language of businesses. 12 is that we believe ai is the engine for automation. Um So Ai is really about automating workflows and experiences because anything that you want to automate and make more productive you have to have some predictive capabilities to it to understand what to do and you have to learn about you know, what's trying to be accomplished which is always unique and personalized. So that's the second one is about automation. The third is it is about driving trust and outcomes right in the business outcomes, which means, you know, if you were to, if some a model say scott go jump off a bridge, you know, I probably wouldn't want to do that unless it really explained to me, prove instantly that I should do that and they will but explain ability and trust is such a critical part of aI for business and then finally it needs to run everywhere. It has to integrate everything. And we believe unlike a lot of the competitors where you have to bring the data to a I we're saying leave the data where it lives and bring ai to the data so it runs anywhere from the data center to the edge. The same model, the same capabilities in a distributed environment. Um So those four kind of attributes come together to what we call A I for business. Um And that's what's gonna allow call centers and supply chains and business planning and risk and regulatory, you know, mitigation. I mean those kind of things to really come to life in a predictive way without those attributes, it's much harder to do a lot more coding and you're not gonna as much accuracy. >>Yeah, I mean what you're just walking through there is interesting and if you think about consumer, okay yeah, Alexa, go get me, you know, what's the weather like in Palo alto or whatever, you know, those kinds of all back in pretty complicated but it's not as complicated as moving data to the edge and moving computer around. And the complexity of dealing with data has always been an open discussion but now with ai such at the center point of the value pressure and becoming table stakes. I mean we're hearing companies say if you don't have an Ai innovation strategy you're going to be you know irrelevant or even delisted from the stock market. That's some radical views. But um talk about this complexity and how it's being tamed for customers because if you don't have the data exposed, you're only as good as the data that you have. And this has been a conversation we've had on the cube many times before with you and some of your peers here at IBM you can't get the data. What good is it? The insights are only as good as what you can program. So this means that date is gonna be accessible and it's also complexity to move it around. So can you unpack that equation? >>Yeah, it's the whole notion of garbage in garbage out and ai you know ai its lifeblood is data and we have equipped that we always say that there's no Ai without an I. A. An information architecture And we are well over 30,000 engagements um among our clients around A I you know we have the AI ladder which is a prescriptive approach. We've learned a ton over the years and and we said before, you know the great digital shift, well the great inhibitor is the complexity of all this data and the average large enterprise has over 1000 repositories and sources of data as things go out into the edge that's just multiply. Um there's more and more movement to put applications, you know software as a service applications on the cloud and most businesses have multiple clouds so you're further fragmenting all the data and if you look at what the gardener has said and many others, these big data projects in the past are very slow and costly and they've had limited impact. This idea of moving data replicating data. It's just not going to work as the explosion of data increases in terms of touch points in terms of types and in terms of pure velocity and also at the same time the value of data, it's lifespan is rapidly decreasing. A customer record that was created yesterday may not be as valuable a year from now or even in three months from now because things change so much. Right. >>Alright. Alright. So I gotta ask you the question then because this is kind of from a customer. What's in it for me? At the end of the day I got data problem. You take it you got my attention. Um I gotta move date. I got to edge Hybrid cloud has been defined as a bona fide. A done deal is hybrid multi clouds around the corner. But that's just a subsystem of the operating system that's business now. So Hybrid cloud is the operating model data. Supercritical. What does IBM offer? What can you offer me as a customer and why is it good you guys got some announcements with cloud pack for data specifically here? Think what's the solution? How do I solve this? What's IBM offering? >>Yeah. So I think it starts with the fact that we have a fully unified data and AI platform meaning that they're not separate thoughts. They're all unified together as one on life cycle. And it runs anywhere on any cloud data center. To the answer starts with that notion and it helps you collect, organize and analyze data and infuse ai um throughout the business. Now, when it comes to the data complexity three core principles that were put into the next version of call Pat for data, one is automation is inevitable. It's the only way to deal with all this complexity. Uh leave the data where it is, where it lives, where it thrives and bring ai to the data. And so what we are putting into the next generation of compact for data is an intelligent data fabric, right? That is fueled by A. I. And that is going to abstract a lot of the complexity out of all this. Let you keep the data where it's at and be able to discover that data intelligently, be able to catalogue it, be able to understand it right? And more importantly, to do unified queries and updates across all these distributed sources of data and bring the records together without having to take weeks and months to build new data pipelines and across that entire ecosystem, be able to enforce universal privacy and usage policies which is absolutely critical. Forrester estimates that 50 of data is not used because they're afraid that it's gonna break policy. Oh >>yeah, I mean that's a huge trust issue. I mean I I was talking to a practitioner and he's like you know, we don't even want to do some of these transactions that are interesting experiments and and cloud opportunities because of the compliance risk, they're afraid to get sued. Yeah, >>that's right. And each one of those data stores just think about the ecosystem we're talking about here of sources and consumers, data consumers, ai consumers and of course all the sources that are silent all over the place. A lot of these repositories and a lot of these different cloud violence have different policies in terms of usage and in privacy. Right? So how do you bring all that together? What we're delivering the next version of compact? Her dad is a universal privacy plane if you will, which called auto privacy and it will basically abstract all the complexity of the different policies allow you to create them and enforce it universally. And you couldn't imagine the productivity of being to deliver that versus having a hand deal with this in a manual way. Yeah, that's an example with the data fabric. You know, what's interesting >>is you're getting at these. I mean I'm hearing the conversation about the solution, it's okay. I'm not in mind going okay, what's the benefits? I hear, I hear uh speed, um I hear, you know, ease of use, compliance trust, but what you're really getting at is agility and there's a, there's a upside for agility that's moving fast and getting taking advantage of new opportunities or automating something away. But you mentioned trust peace because you know, that's where I see people afraid like, okay, if I move too fast, will I trip on over or some governance issue? Like that's a huge thing. This is a big problem. >>It's a massive problem. I mean, I think there's four, Four areas from a business perspective, right? One is think about digital experiences and we know that six and 10 customers that defect from a brand because of some bad experience usually don't return. And it's estimated that is costing the industry, you know, close to $500 billion responsive experiences, which is You have to bring the data together to be able to do that, right? The second is the regulatory and reputational risk. Um that's another 180 billion or so. Which in many cases eight of revenue just to mitigate all that risk of using data. Not only regulatory but reputational. This thing about lost productivity, how many, how many hours every week is a worker doing mundane tasks, low value work because it's not automated. Um That's like another 100 or so billion dollars of costs for enterprises um can go on with interact with planning and forecasting. Um Supply chains being inefficient. All this is being fueled by the data, right? So the more you can bring all this data together, unify it, create new views that are aggregate and nature and uncover hidden insights that you couldn't do before. Um That's the magic sauce here. Right. >>Well my last question for you on the on this product before we wrap up is there's a huge trend towards ecosystem network effect integration. Right there more more integration. People are partnering. I mean you have solutions where that rely on different people in the supply chain or value chain of a of a solution whether you're a concession at a ballpark or an enterprise you're connecting with other a piece. This is cloud, right? How does your cloud pack for data handle that integration and that trust? Because this is really the deployment scenario. Your thoughts? >>Yeah. I mean I think the core of top after data is it's going to greatly enhance productivity. It's going to lower costs of these, you know, complex data states. It's going to lower risk of all this and it's going to help you uncover hidden insights that you couldn't see before. Not only because of A I, but because when you unify the data to get more out of it, we then go on to really point out that it's a truly open platform with an open ecosystem. So we are partnering with all the cloud partners. Right. We have a vast network of software providers that can extend and intimacy customized the platform. We have Integrator partners and it's all based on open source communities. So it is fully extensible and customizable to unique needs of every customer on any cloud yuan or across the city college. All >>right, scott. That's great stuff. Thanks for coming on the cube. Great to see you scott, Wapner. Vice President Marketing at IBM for data. And they are the hottest area. Great. Great cube alumni. Great insight. Thanks scott for coming on. Thank you. Okay, I'm jennifer with the cube You're watching ibn think 2021 coverage. Thanks for watching. Yeah. >>Mm

>>from around the >>globe. It's >>the cube >>with digital >>coverage of IBM >>Think 2021 >>brought to you by IBM. Welcome back everyone to the cube coverage of IBM Think 2021. I'm john for a host of the cube. Got a great guest here scott, senior Vice president of marketing at IBM for data and ai cube alumni has been around the wave around data, had many conversations over the years. Scott welcome back to the Cuban, I wish we were in person but we're remote for the virtual conference for think 2021. Thanks for coming on >>john great to be here. And yeah, I guess we have adapted to the world of being on the screen. >>Well, great, great to have you in. One of the things about virtualization of media is that we get more content this year. There's so many more signature stories around um, IBM think and one of the things that's really fun for us is the data conversations in A I as as the transformation and innovation equations are coming together at scale, you're seeing an accelerated piece here. My first question for you is, you know, this digital shift that's going on, the preferences are shifting to virtual now digital in the wake of Covid, what do companies need to adapt from your perspective as you see this playing out? What's your perspective? >>It's interesting to use that term. So we've been calling it the great digital shift. And uh yeah, there's an there was an interesting survey, a pretty big survey of global C suite that Mackenzie did. And they pointed out that 79% of those leaders felt that Covid highlighted the immaturity of their digital capability. And while they thought they were on the right path and they were building strong digital capabilities, the whole world of the pandemic remote work, how you engage with customers call centers going off the hooks in terms of people calling, it just goes on and on and on. And And they also pointed out that 90, I think it was, 96 of them are going to speed their digital reinvention. And you mentioned data, if you think about it, it's data that a few fuels digital capabilities. Right? What good is digital if it's not data, right, It's all data. So it's the fuel that makes it all work. And when you think about the ability to leverage all your dad, you got to democratize it, It's siloed all over the place, it's growing at six times rate over the next three years. It's really all over the place, every touch point across the digital ecosystem. Um, and the only way to deal with the data in to unlock its value, particularly in predictive ways is to AI. Right. And so what we're seeing is a huge amount of investment in multi cloud, really bringing together this notion of hybrid and then applying AI as the intelligence to create a more predictable and resilient business right through a digital model, right? Yeah, it's really the investment is really going through the roof. >>You know, I think AI has been, it's been demystified over the years, been a lot of people saw the machine learning and now you got NLP and data control planes that are making it more addressable. But the real thing that comes up here, I think this year is this role between business and consumer and AI has that kind of dynamic. And I want to ask you because I was just having a conversation with one of your partner, IBM partner Samsung, KC Joy runs E V P E V P for the B to B B to G Group at Samsung. It's a huge I. O. T. Thing. And AI is a big part of that consumer and we talked about the consumer electronics business issues, how is A I different for business versus the consumer is obviously got industrial iot edge and you got automation piece, what's the difference? And someone asked you that between business and consumer Ai. >>Yeah, actually I think that's one of the areas that we really differentiate ourselves and we're putting the bulk of investments this notion of AI for business, right? And you know, a lot of people think of A I sometimes they think of Siri and Alexa and things that go on in your car and all that. Obviously that's a big part of applying machine learning and all that, but when we talk about AI for business, we're thinking about four core attributes. Uh one is that it needs to understand the unique language of your business and industry, right? And that's not just natural language but it's the ability to debate, it's the ability to read documents, interpret documents. Um It's the ability to really understand the context because you and I can ask the same question in five or six different ways and it needs to understand the business to be able to interpret that and help answer the question unlike like Siri or Alexa, where you really got to have the right semantics and you know, it won't understand the nuances as well, so understand the language of businesses. 12 is that we believe ai is the engine for automation. Um So Ai is really about automating workflows and experiences because anything that you want to automate and make more productive, you have to have some predictive capabilities to it to understand what to do and you have to learn about you know, what's trying to be accomplished which is always unique and personalized. So that's the second one is about automation. The third is it is about driving trust and outcomes right? In the business outcomes, which means, you know, if you were to if some a model say scott go jump off a bridge, you know I probably wouldn't want to do that unless it really explained to me convincingly that I should do that well but explain ability and trust is such a critical part of aI for business and then finally it needs to run everywhere. It has to integrate everything. And we believe unlike a lot of the competitors where you have to bring the data to a I we're saying leave the data where it lives and bring ai to the data. So it runs anywhere from the data center to the edge, The same model, the same capabilities in a distributed environment. Um So those four kind of attributes come together to what we call a I for business. Um And that's what's gonna allow call centers and supply chains and business planning and risk and regulatory, you know, mitigation, I mean those kind of things to really come to life in a predictive way without those attributes, it's much harder to do a lot more coding and you're not gonna as much accuracy. >>Yeah, I mean what you're just walking through there is interesting and if you think about consumer, okay, yeah, Alexa, go get me, you know, what's the weather like in Palo alto or whatever, you know, those kinds of all back in pretty complicated but it's not as complicated as moving data to the edge and moving compute around. And the complexity of dealing with data has always been an open discussion. But now with ai such at the center point of the value pressure and becoming table stakes. I mean we're hearing companies say if you don't have an Ai innovation strategy, you're going to be you know, irrelevant or even delisted from the stock market. That's some radical views. But um talk about this complexity and how it's being tamed for customers because if you don't have the data exposed, you're only as good as the data that you have and this has been a conversation we've had on the cube many times before with you and some of your other peers here at IBM you can't get the data. What good is it? The insights are only as good as what you can program. So this means that date is gonna be accessible and it's also complexity to move it around. So can you unpack that equation? >>Yeah, it's the whole notion of garbage in garbage out and ai you know ai its lifeblood is data and we have equipped that we always say that there's no Ai without an I. A. An information architecture And we are well over 30,000 engagements um among our clients around A I you know we have the AI ladder which is a prescriptive approach. We've learned a ton over the years and and we said before, you know the great digital shift, well the great inhibitor is the complexity of all this data and the average large enterprise has over 1000 repositories and sources of data as things go out into the edge that's just multiply. Um there's more and more movement to put applications, you know software as a service applications on the cloud and most businesses have multiple clouds so you're further fragmenting all the data and if you look at what the gardener has said and many others, these big data projects in the past are very slow, costly and they've had limited impact. This idea of moving data replicating data. It's just not going to work as the explosion of data increases in terms of touch points in terms of types and in terms of pure velocity and also at the same time the value of data, it's lifespan is rapidly decreasing. A customer record that was created yesterday may not be as valuable a year from now or even in three months from now because things change so much. Right. >>Alright. So I gotta ask you the question then because this is kind of from a customer. What's in it for me? At the end of the day I got data problem. You take it you got my attention. Um I gotta move date. I got the edge. Hybrid cloud has been defined as a bona fide is done deals Hybrid multi clouds around the corner. But that's just a subsystem of the operating system that's business now. So Hybrid cloud is the operating model. Data. Supercritical. What does IBM offer? What can you offer me as a customer and why is it good? You guys got some announcements with cloud pack for data specifically here? Think what's the solution? How do I solve this? What's IBM offering? >>Yeah. So I think it starts with the fact that we have a fully unified data and AI platform meaning that they're not separate thoughts. They're all unified together as one on life cycle. And it runs anywhere on any cloud data center. To the answer starts with that notion. It helps you collect, organize and analyze data and infuse ai um throughout the business. Now, when it comes to the data complexity three core principles that were put into the next version of call Pat for data, one is automation is inevitable. It's the only way to deal with all this complexity. Uh leave the data where it is, where it lives, where it thrives and bring ai to the data. And so what we are putting into the next generation of compact for data is an intelligent data fabric, right? That is fueled by A. I. And that is going to abstract a lot of the complexity out of all this. Let me keep the data where it's at and be able to discover that data intelligently be able to catalogue it, be able to understand it right? And more importantly, to do unified queries and updates across all these distributed sources of data and bring the records together without having to take weeks and months to build new data pipelines and across that entire ecosystem, be able to enforce universal privacy and usage policies which is absolutely critical. Forrester estimates that 50 of data is not used because they're afraid that it's gonna break policy. Oh >>yeah. I mean that's a huge trust issue. I mean I I was talking to a practitioner and he's like, you know, we don't even want to do some of these transactions that are interesting experiments and and cloud opportunities because of the compliance risk, they're afraid to get sued. Yeah, >>that's right. And each one of those data stores, so if you think about the ecosystem we're talking about here of sources and consumers, data consumers, ai consumers and of course all the sources that are silent all over the place. A lot of these repositories and a lot of these different cloud violence have different policies in terms of usage and pump in privacy. Right? So how do you bring all that together? What we're delivering? The next version of compact for dad is a universal privacy plane if you will, which called auto privacy and it will basically abstract all the complexity of the different policies allow you to create them and enforce it universally. And you couldn't imagine the productivity of being to deliver that versus having a hand deal with this in a manual way. That's an example of what the data fabric, >>you know, what's interesting is you're getting at this? I'm hearing the conversation about the solution. It's okay. I'm not a mind going okay, what's the benefits? I hear I hear uh speed, um, I hear, you know, ease of use, compliance trust. But what you're really getting at is agility and there's a, there's a upside for agility that's moving fast and getting taking advantage of new opportunities or automating something away. But you mentioned the trust piece because that's where I see people afraid like, okay, if I move too fast, will I trip on over or some governance issue? Like that's a huge thing. This is a big problem. >>It's a massive problem. I mean, I mean, I think there's four, Four areas from a business perspective, right? One is think about digital experiences and we know that six and 10 customers that defect from a brand because of some bad experience usually don't return. And it's estimated that is costing the industry, you know close to $500 billion responsive experiences, which is, You have to bring the data together to do that, right? The second is the regulatory and reputational risk. Um that's another 180 billion or so. Which in many cases eight of revenue just to mitigate all that risk of using data. Not only regulatory reputational. This thing about lost productivity, how many, how many hours every week is a worker doing mundane tasks, low value work because it's not automated. Um that's like another 100 or so billion dollars of costs for enterprises. Um go on with interact with planning and forecasting. Um supply chains being inefficient. All this is being fueled by the data, right? So the more you can bring all this data together, unify it create new views that are aggregate and nature and uncover hidden insights that you couldn't do before. Um That's the magic sauce here. Right. >>Well, my last question for you on the on this product before we wrap up is there's a huge trend towards ecosystem network effect integration right there more more integration and people are partnering. I mean you have solutions where that rely on different people in the supply chain or value chain of a of a solution whether you're a concession at a ballpark or an enterprise you're connecting with other a piece, this is cloud, right? How does your cloud pack for data handle that integration and that trust? Because this is really the deployment scenario. Your thoughts? >>Yeah. I mean I think the core of top after data is it's going to greatly enhance productivity. It's going to lower costs of these, you know, complex data states. It's going to lower risk of all this and it's going to help you uncover hidden insights that you couldn't see before. Not only because of A I but because when you unify the data to get more out of it, we then go on to really point out that it's a truly open platform with an open ecosystem. So we are partnering with all the cloud partners. Right? We have a vast network of software providers that can extend and intimacy customized the platform. We have integrator partners and it's all based on open source communities. So it is fully extensible and customizable to the unique needs of every customer on any Juwan or across the city college. All >>right scott. That's great stuff. Thanks for coming on the cube. Great to see you scott, Wapner. Vice president Marketing at IBM for data and they are the hottest area. Great. Great cube alumni. Great insight. Thanks scott for coming on. Thank you. Okay, I'm jennifer with the cube You're watching ibn think 2021 coverage. Thanks for watching. Mhm >>mm. >>Yeah.

>>Yeah, it's the queue covering the virtual vertical Big Data Conference 2020 Brought to You by vertical. >>Welcome back, everybody. My name is Dave Vellante, and you're watching the Cube's coverage of the verdict of Virtual Big Data conference. The Cube has been at every BTC, and it's our pleasure in these difficult times to be covering BBC as a virtual event. This digital program really excited to have Joy King joining us. Joy is the vice president of product and go to market strategy in particular. And if that weren't enough, he also runs marketing and education curve for him. So, Joe, you're a multi tool players. You've got the technical side and the marketing gene, So welcome to the Cube. You're always a great guest. Love to have you on. >>Thank you so much, David. The pleasure, it really is. >>So I want to get in. You know, we'll have some time. We've been talking about the conference and the virtual event, but I really want to dig in to the product stuff. It's a big day for you guys. You announced 10.0. But before we get into the announcements, step back a little bit you know, you guys are riding the waves. I've said to ah, number of our guests that that brick has always been good. It riding the wave not only the initial MPP, but you you embraced, embraced HD fs. You embrace data science and analytics and in the cloud. So one of the trends that you see the big waves that you're writing >>Well, you're absolutely right, Dave. I mean, what what I think is most interesting and important is because verdict is, at its core a true engineering culture founded by, well, a pretty famous guy, right, Dr Stone Breaker, who embedded that very technical vertical engineering culture. It means that we don't pretend to know everything that's coming, but we are committed to embracing the tech. An ology trends, the innovations, things like that. We don't pretend to know it all. We just do it all. So right now, I think I see three big imminent trends that we are addressing. And matters had we have been for a while, but that are particularly relevant right now. The first is a combination of, I guess, a disappointment in what Hadoop was able to deliver. I always feel a little guilty because she's a very reasonably capable elephant. She was designed to be HD fs highly distributed file store, but she cant be an entire zoo, so there's a lot of disappointment in the market, but a lot of data. In HD FM, you combine that with some of the well, not some the explosion of cloud object storage. You're talking about even more data, but even more data silos. So data growth and and data silos is Trend one. Then what I would say Trend, too, is the cloud Reality Cloud brings so many events. There are so many opportunities that public cloud computing delivers. But I think we've learned enough now to know that there's also some reality. The cloud providers themselves. Dave. Don't talk about it well, because not, is it more agile? Can you do things without having to manage your own data center? Of course you can. That the reality is it's a little more pricey than we expected. There are some security and privacy concerns. There's some workloads that can go to the cloud, so hybrid and also multi cloud deployments are the next trend that are mandatory. And then maybe the one that is the most exciting in terms of changing the world we could use. A little change right now is operationalize in machine learning. There's so much potential in the technology, but it's somehow has been stuck for the most part in science projects and data science lab, and the time is now to operationalize it. Those are the three big trends that vertical is focusing on right now. >>That's great. I wonder if I could ask you a couple questions about that. I mean, I like you have a soft spot in my heart for the and the thing about the Hadoop that that was, I think, profound was it got people thinking about, you know, bringing compute to the data and leaving data in place, and it really got people thinking about data driven cultures. It didn't solve all the problems, but it collected a lot of data that we can now take your third trend and apply machine intelligence on top of that data. And then the cloud is really the ability to scale, and it gives you that agility and that it's not really that cloud experience. It's not not just the cloud itself, it's bringing the cloud experience to wherever the data lives. And I think that's what I'm hearing from you. Those are the three big super powers of innovation today. >>That's exactly right. So, you know, I have to say I think we all know that Data Analytics machine learning none of that delivers real value unless the volume of data is there to be able to truly predict and influence the future. So the last 7 to 10 years has been correctly about collecting the data, getting the data into a common location, and H DFS was well designed for that. But we live in a capitalist world, and some companies stepped in and tried to make HD Fs and the broader Hadoop ecosystem be the single solution to big data. It's not true. So now that the key is, how do we take advantage of all of that data? And now that's exactly what verdict is focusing on. So as you know, we began our journey with vertical back in the day in 2007 with our first release, and we saw the growth of the dupe. So we announced many years ago verdict a sequel on that. The idea to be able to deploy vertical on Hadoop nodes and query the data in Hadoop. We wanted to help. Now with Verdict A 10. We are also introducing vertical in eon mode, and we can talk more about that. But Verdict and Ian Mode for HDs, This is a way to apply it and see sequel database management platform to H DFS infrastructure and data in each DFS file storage. And that is a great way to leverage the investment that so many companies have made in HD Fs. And I think it's fair to the elephant to treat >>her well. Okay, let's get into the hard news and auto. Um, she's got, but you got a mature stack, but one of the highlights of append auto. And then we can drill into some of the technologies >>Absolutely so in well in 2018 vertical announced vertical in Deon mode is the separation of compute from storage. Now this is a great example of vertical embracing innovation. Vertical was designed for on premises, data centers and bare metal servers, tightly coupled storage de l three eighties from Hewlett Packard Enterprises, Dell, etcetera. But we saw that cloud computing was changing fundamentally data center architectures, and it made sense to separate compute from storage. So you add compute when you need compute. You add storage when you need storage. That's exactly what the cloud's introduced, but it was only available on the club. So first thing we did was architect vertical and EON mode, which is not a new product. Eight. This is really important. It's a deployment option. And in 2018 our customers had the opportunity to deploy their vertical licenses in EON mode on AWS in September of 2019. We then broke an important record. We brought cloud architecture down to earth and we announced vertical in eon mode so vertical with communal or shared storage, leveraging pure storage flash blade that gave us all the advantages of separating compute from storage. All of the workload, isolation, the scale up scale down the ability to manage clusters. And we did that with on Premise Data Center. And now, with vertical 10 we are announcing verdict in eon mode on HD fs and vertically on mode on Google Cloud. So what we've got here, in summary, is vertical Andy on mode, multi cloud and multiple on premise data that storage, and that gives us the opportunity to help our customers both with the hybrid and multi cloud strategies they have and unifying their data silos. But America 10 goes farther. >>Well, let me stop you there, because I just wanna I want to mention So we talked to Joe Gonzalez and past Mutual, who essentially, he was brought in. And one of this task was the lead into eon mode. Why? Because I'm asking. You still had three separate data silos and they wanted to bring those together. They're investing heavily in technology. Joe is an expert, though that really put data at their core and beyond Mode was a key part of that because they're using S three and s o. So that was Ah, very important step for those guys carry on. What else do we need to know about? >>So one of the reasons, for example, that Mass Mutual is so excited about John Mode is because of the operational advantages. You think about exactly what Joe told you about multiple clusters serving must multiple use cases and maybe multiple divisions. And look, let's be clear. Marketing doesn't always get along with finance and finance doesn't necessarily get along with up, and I t is often caught the middle. Erica and Dion mode allows workload, isolation, meaning allocating the compute resource is that different use cases need without allowing them to interfere with other use cases and allowing everybody to access the data. So it's a great way to bring the corporate world together but still protect them from each other. And that's one of the things that Mass Mutual is going to benefit from, as well, so many of >>our other customers I also want to mention. So when I saw you, ah, last last year at the Pure Storage Accelerate conference just today we are the only company that separates you from storage that that runs on Prem and in the cloud. And I was like I had to think about it. I've researched. I still can't find anybody anybody else who doesn't know. I want to mention you beat actually a number of the cloud players with that capability. So good job and I think is a differentiator, assuming that you're giving me that cloud experience and the licensing and the pricing capability. So I want to talk about that a little >>bit. Well, you're absolutely right. So let's be clear. There is no question that the public cloud public clouds introduced the separation of compute storage and these advantages that they do not have the ability or the interest to replicate that on premise for vertical. We were born to be software only. We make no money on underlying infrastructure. We don't charge as a package for the hardware underneath, so we are totally motivated to be independent of that and also to continuously optimize the software to be as efficient as possible. And we do the exact same thing to your question about life. Cloud providers charge for note indignance. That's how they charge for their underlying infrastructure. Well, in some cases, if you're being, if you're talking about a use case where you have a whole lot of data, but you don't necessarily have a lot of compute for that workload, it may make sense to pay her note. Then it's unlimited data. But what if you have a huge compute need on a relatively small data set that's not so good? Vertical offers per node and four terabyte for our customers, depending on their use case, we also offer perpetual licenses for customers who want capital. But we also offer subscription for companies that they Nope, I have to have opt in. And while this can certainly cause some complexity for our field organization, we know that it's all about choice, that everybody in today's world wants it personalized just for me. And that's exactly what we're doing with our pricing in life. >>So just to clarify, you're saying I can pay by the drink if I want to. You're not going to force me necessarily into a term or Aiken choose to have, you know, more predictable pricing. Is that, Is that correct? >>Well, so it's partially correct. The first verdict, a subscription licensing is a fixed amount for the period of the subscription. We do that so many of our customers cannot, and I'm one of them, by the way, cannot tell finance what the budgets forecast is going to be for the quarter after I spent you say what it's gonna be before, So our subscription facing is a fixed amount for a period of time. However, we do respect the fact that some companies do want usage based pricing. So on AWS, you can use verdict up by the hour and you pay by the hour. We are about to launch the very same thing on Google Cloud. So for us, it's about what do you need? And we make it happen natively directly with us or through AWS and Google Cloud. >>So I want to send so the the fixed isn't some floor. And then if you want a surge above that, you can allow usage pricing. If you're on the cloud, correct. >>Well, you actually license your cluster vertical by the hour on AWS and you run your cluster there. Or you can buy a license from vertical or a fixed capacity or a fixed number of nodes and deploy it on the cloud. And then, if you want to add more nodes or add more capacity, you can. It's not usage based for the license that you bring to the cloud. But if you purchase through the cloud provider, it is usage. >>Yeah, okay. And you guys are in the marketplace. Is that right? So, again, if I want up X, I can do that. I can choose to do that. >>That's awesome. Next usage through the AWS marketplace or yeah, directly from vertical >>because every small business who then goes to a salesforce management system knows this. Okay, great. I can pay by the month. Well, yeah, Well, not really. Here's our three year term in it, right? And it's very frustrating. >>Well, and even in the public cloud you can pay for by the hour by the minute or whatever, but it becomes pretty obvious that you're better off if you have reserved instance types or committed amounts in that by vertical offers subscription. That says, Hey, you want to have 100 terabytes for the next year? Here's what it will cost you. We do interval billing. You want to do monthly orderly bi annual will do that. But we won't charge you for usage that you didn't even know you were using until after you get the bill. And frankly, that's something my finance team does not like. >>Yeah, I think you know, I know this is kind of a wonky discussion, but so many people gloss over the licensing and the pricing, and I think my take away here is Optionality. You know, pricing your way of That's great. Thank you for that clarification. Okay, so you got Google Cloud? I want to talk about storage. Optionality. If I found him up, I got history. I got I'm presuming Google now of you you're pure >>is an s three compatible storage yet So your story >>Google object store >>like Google object store Amazon s three object store HD fs pure storage flash blade, which is an object store on prim. And we are continuing on this theft because ultimately we know that our customers need the option of having next generation data center architecture, which is sort of shared or communal storage. So all the data is in one place. Workloads can be managed independently on that data, and that's exactly what we're doing. But what we already have in two public clouds and to on premise deployment options today. And as you said, I did challenge you back when we saw each other at the conference. Today, vertical is the only analytic data warehouse platform that offers that option on premise and in multiple public clouds. >>Okay, let's talk about the ah, go back through the innovation cocktail. I'll call it So it's It's the data applying machine intelligence to that data. And we've talked about scaling at Cloud and some of the other advantages of Let's Talk About the Machine Intelligence, the machine learning piece of it. What's your story there? Give us any updates on your embracing of tooling and and the like. >>Well, quite a few years ago, we began building some in database native in database machine learning algorithms into vertical, and the reason we did that was we knew that the architecture of MPP Columbia execution would dramatically improve performance. We also knew that a lot of people speak sequel, but at the time, not so many people spoke R or even Python. And so what if we could give act us to machine learning in the database via sequel and deliver that kind of performance? So that's the journey we started out. And then we realized that actually, machine learning is a lot more as everybody knows and just algorithms. So we then built in the full end to end machine learning functions from data preparation to model training, model scoring and evaluation all the way through to fold the point and all of this again sequel accessible. You speak sequel. You speak to the data and the other advantage of this approach was we realized that accuracy was compromised if you down sample. If you moved a portion of the data from a database to a specialty machine learning platform, you you were challenged by accuracy and also what the industry is calling replica ability. And that means if a model makes a decision like, let's say, credit scoring and that decision isn't anyway challenged, well, you have to be able to replicate it to prove that you made the decision correctly. And there was a bit of, ah, you know, blow up in the media not too long ago about a credit scoring decision that appeared to be gender bias. But unfortunately, because the model could not be replicated, there was no way to this Prove that, and that was not a good thing. So all of this is built in a vertical, and with vertical 10. We've taken the next step, just like with with Hadoop. We know that innovation happens within vertical, but also outside of vertical. We saw that data scientists really love their preferred language. Like python, they love their tools and platforms like tensor flow with vertical 10. We now integrate even more with python, which we have for a while, but we also integrate with tensorflow integration and PM ML. What does that mean? It means that if you build and train a model external to vertical, using the machine learning platform that you like, you can import that model into a vertical and run it on the full end to end process. But run it on all the data. No more accuracy challenges MPP Kilometer execution. So it's blazing fast. And if somebody wants to know why a model made a decision, you can replicate that model, and you can explain why those are very powerful. And it's also another cultural unification. Dave. It unifies the business analyst community who speak sequel with the data scientist community who love their tools like Tensorflow and Python. >>Well, I think joy. That's important because so much of machine intelligence and ai there's a black box problem. You can't replicate the model. Then you do run into a potential gender bias. In the example that you're talking about there in their many you know, let's say an individual is very wealthy. He goes for a mortgage and his wife goes for some credit she gets rejected. He gets accepted this to say it's the same household, but the bias in the model that may be gender bias that could be race bias. And so being able to replicate that in and open up and make the the machine intelligence transparent is very, very important, >>It really is. And that replica ability as well as accuracy. It's critical because if you're down sampling and you're running models on different sets of data, things can get confusing. And yet you don't really have a choice. Because if you're talking about petabytes of data and you need to export that data to a machine learning platform and then try to put it back and get the next at the next day, you're looking at way too much time doing it in the database or training the model and then importing it into the database for production. That's what vertical allows, and our customers are. So it right they reopens. Of course, you know, they are the ones that are sort of the Trailblazers they've always been, and ah, this is the next step. In blazing the ML >>thrill joint customers want analytics. They want functional analytics full function. Analytics. What are they pushing you for now? What are you delivering? What's your thought on that? >>Well, I would say the number one thing that our customers are demanding right now is deployment. Flexibility. What? What the what the CEO or the CFO mandated six months ago? Now shout Whatever that thou shalt is is different. And they would, I tell them is it is impossible. No, what you're going to be commanded to do or what options you might have in the future. The key is not having to choose, and they are very, very committed to that. We have a large telco customer who is multi cloud as their commit. Why multi cloud? Well, because they see innovation available in different public clouds. They want to take advantage of all of them. They also, admittedly, the that there's the risk of lock it right. Like any vendor, they don't want that either, so they want multi cloud. We have other customers who say we have some workloads that make sense for the cloud and some that we absolutely cannot in the cloud. But we want a unified analytics strategy, so they are adamant in focusing on deployment flexibility. That's what I'd say is 1st 2nd I would say that the interest in operationalize in machine learning but not necessarily forcing the analytics team to hammer the data science team about which tools or the best tools. That's the probably number two. And then I'd say Number three. And it's because when you look at companies like Uber or the Trade Desk or A T and T or Cerner performance at scale, when they say milliseconds, they think that flow. When they say petabytes, they're like, Yeah, that was yesterday. So performance at scale good enough for vertical is never good enough. And it's why we're constantly building at the core the next generation execution engine, database designer, optimization engine, all that stuff >>I wanna also ask you. When I first started following vertical, we covered the cube covering the BBC. One of things I noticed was in talking to customers and people in the community is that you have a community edition, uh, free addition, and it's not neutered ais that have you maintain that that ethos, you know, through the transitions into into micro focus. And can you talk about that a little bit >>absolutely vertical community edition is vertical. It's all of the verdict of functionality geospatial time series, pattern matching, machine learning, all of the verdict, vertical neon mode, vertical and enterprise mode. All vertical is the community edition. The only limitation is one terabyte of data and three notes, and it's free now. If you want commercial support, where you can file a support ticket and and things like that, you do have to buy the life. But it's free, and we people say, Well, free for how long? Like our field? I've asked that and I say forever and what he said, What do you mean forever? Because we want people to use vertical for use cases that are small. They want to learn that they want to try, and we see no reason to limit that. And what we look for is when they're ready to grow when they need the next set of data that goes beyond a terabyte or they need more compute than three notes, then we're here for them, and it also brings up an important thing that I should remind you or tell you about Davis. You haven't heard it, and that's about the Vertical Academy Academy that vertical dot com well, what is that? That is, well, self paced on demand as well as vertical essential certification. Training and certification means you have seven days with your hands on a vertical cluster hosted in the cloud to go through all the certification. And guess what? All of that is free. Why why would you give it for free? Because for us empowering the market, giving the market the expert East, the learning they need to take advantage of vertical, just like with Community Edition is fundamental to our mission because we see the advantage that vertical can bring. And we want to make it possible for every company all around the world that take advantage >>of it. I love that ethos of vertical. I mean, obviously great product. But it's not just the product. It's the business practices and really progressive progressive pricing and embracing of all these trends and not running away from the waves but really leaning in joy. Thanks so much. Great interview really appreciate it. And, ah, I wished we could have been faced face in Boston, but I think it's prudent thing to do, >>I promise you, Dave we will, because the verdict of BTC and 2021 is already booked. So I will see you there. >>Haas enjoyed King. Thanks so much for coming on the Cube. And thank you for watching. Remember, the Cube is running this program in conjunction with the virtual vertical BDC goto vertical dot com slash BBC 2020 for all the coverage and keep it right there. This is Dave Vellante with the Cube. We'll be right back. >>Yeah, >>yeah, yeah.

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

>> Announcer: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hi, everybody, welcome back to theCUBE's coverage of the Virtual Vertica BDC, Big Data Conference. It was, of course, going to be in Boston, but now we're covering it online. It's really our pleasure to invite back Joy King, she's the vice president of product and go-to-market strategy at Vertica. She also manages marketing and education programs. Joy, great to see you. >> It's great to be back, as always, Dave, thank you. >> Let's talk about BDC, Virtual BDC. We took a break. theCUBE has been at every Big Data Conference. I love that show, great customers, awesome buzz, great outside speakers. I actually had the pleasure of being up on stage with some database experts, of which I'm not, but I'm a (laughs) inch deep and a mile wide. >> I remember that! (laughs) >> And it was a lot of fun going head to head with some of the folks, and just really a great vibe over that conference. But, so, now, you had to make the decision, because of the coronavirus, to go digital. You didn't delay, and I love the fact that you guys leaned right in, you've got all this content. So talk about what we can expect at BDC. >> Well, you know, Dave, the BDC is really special, and I have to give Colin Mahoney, our GM, the credit for the idea. Sometimes his ideas are really good, and the execution can be, well, challenging. But when we started the BDC, he had an idea. He said, "You know, we have such a passionate "community, we need to get them together. "We need, like, a user group." Well, that user group, for the first BDC, was the first and only event I have ever been responsible for where, yes, it's true, we exceeded the fire code of the venue, and we had more people that registered than we were allowed to accept. That's never happened before. It's because the passion was so real. We made a commitment. We said the only people that could speak at the BDC were engineers who architected and write the code, and customers who've used the code. We were determined to keep the technical credibility, the value of best practices, the sharing among the community. Marketing was responsible for appropriate amounts of coffee and alcohol at the appropriate times, (Dave laughs) but today, that is still why the BDC is so special. Now, I have to tell you, we have been somewhat limited in our ability to confirm coffee, alcohol, et cetera in the Virtual BDC, but we are still true to our mission. The people that will be speaking during the sessions that we have, and for all of the recordings that we will do in addition after we complete the live BDC, are engineers and architects who design and write the code, hands on the keyboard, and customers who use Vertica to power their businesses every day. That's the rule. Some people don't like it, but that's how we play. >> Well, and to your point, and we've interviewed a number of your customers, and I can second that. The database engineers are proud to put Vertica in their title. >> Yes. >> They embrace it, they love to train people and get adoption going, so that's awesome. Let's talk about some of the logistics of the BDC, the Virtual BDC. Tuesday, March 31st, and then the next day, April 1st, you've got keynotes, you've got breakouts, and of course, we've got theCUBE. After the keynotes, we'll be doing CUBE coverage for two days, wall-to-wall coverage of Virtual BDC. And to your point, and I think this is a nuance that I think people are going to learn with digital, is there's a post-event that really is going to continue that engagement with your community. >> That's right. As much as everybody knows there's nothing that replaces face-to-face interaction, there are advantages to the virtual world. First of all, people are getting pretty creative, I've got to say, and second, it gives global reach to people who would have loved to come to the BDC but couldn't. They couldn't travel, there were restrictions, they were busy with other things. So, yes, all day Tuesday and all day Wednesday. After the keynote on Tuesday will be two parallel tracks, and this is East Coast time, from U.S. East Coast time, on Tuesday afternoon, and then two parallel tracks all day Wednesday. And then on Thursday, in addition to all of those webinars, all of those sessions being available on demand, we are also, right now, recording additional sessions because we just didn't have enough slots, but we had more speakers, both customers and engineers, that wanted to, and all of that will be available on the BDC website on Thursday and beyond. And we're going to continue with two webinar series that we're very proud of. One is called "Under the Hood," which is technical webinars, and the other is called "Data Disruptors," and those are the customers that love to tell their stories. And that, in parallel with ongoing CUBE interviews, will keep the energy all the way up until late March of 2021, when we have already confirmed the next live BDC. >> Awesome, so go to vertica.com/bdc2020, register, you got to register, to see the keynotes. It's lightweight registration, it's not a hundred fields, we want you to come in. And then, of course, theCUBE.net is going to be covering, theCUBE interviews, and SiliconANGLE.com will have editorial. Joy, looking forward to it. Thanks so much for giving us the update, and we'll see you online. >> It will be a pleasure, see ya, bye. >> And we'll see you. Thank you, everybody, and go, like I said, go register, again, it's vertica.com/bdc2020. This is Dave Vellante from theCUBE, and we'll see you at the Virtual Vertica Big Data Conference. (upbeat music)

>> From Boston, Massachusets, it's The Cube. Covering Actifio 2019: Data Driven, Brought to you by Actifio. >> Welcome back to Boston, everybody. We're here at the Intercontinental Hotel at Actifio's Data Driven conference, day one. You're watching The Cube. The leader in on-the-ground tech coverage. My name is is Dave Valante, Stu Minamin is here, so is John Ferrer, my friend Frank Gens is here, he's the Senior Vice President and Chief Analyst at IDC and Head Dot Connector. Frank, welcome to The Cube. >> Well thank you Dave. >> First time. >> First time. >> Newbie. >> Yep. >> You're going to crush it, I know. >> Be gentle. >> You know, you're awesome, I've watched you over the many years, of course, you know, you seem to get competitive, and it's like who gets the best rating? Frank always had the best ratings at the Directions conference. He's blushing but I could- >> I don't know if that's true but I'll accept it. >> I could never beat him, no matter how hard I tried. But you are a phenomenal speaker, you gave a great conversation this morning. I'm sure you drew a lot from your Directions talk, but every year you lay down this, you know, sort of, mini manifesto. You describe it as, you connect the dots, IDC, thousands of analysts. And it's your job to say okay, what does this all mean? Not in the micro, let's up-level a little bit. So, what's happening? You talked today, You know you gave your version of the wave slides. So, where are we in the waves? We are exiting the experimentation phase, and coming in to a new phase that multiplied innovation. I saw AI on there, block-chain, some other technologies. Where are we today? >> Yeah, well I think having mental models of the6 industry or any complex system is pretty important. I mean I've made a career dumbing-down a complex industry into something simple enough that I can understand, so we've done it again now with what we call the third platform. So, ten years ago seeing the whole raft of new technologies at the time were coming in that would become the foundation for the next thirty years of tech, so, that's an old story now. Cloud, mobile, social, big data, obviously IOT technologies coming in, block-chain, and so forth. So we call this general era the third platform, but we noticed a few years ago, well, we're at the threshold of kind of a major scale-up of innovation in this third platform that's very different from the last ten or twelve years, which we called the experimentation stage. Where people were using this stuff, using the cloud, using mobile, big data, to create cool things, but they were doing it in kind of a isolated way. Kind of the traditional, well I'm going to invent something and I may have a few friends help me, whereas, the promise of the cloud has been , well, if you have a lot of developers out on the cloud, that form a community, an ecosystem, think of GitHub, you know, any of the big code repositories, or the ability to have shared service as often Amazon, Cloud, or IBM, or Google, or Microsoft, the promise is there to actually bring to life what Bill Joy said, you know, in the nineties. Which was no matter how smart you are, most of the smart people in the world work for someone else. So the questions always been, well, how do I tap into all those other smart people who don't work for me? So we can feel that where we are in the industry right now is the business model of multiplied innovation or if you prefer, a network of collaborative innovation, being able to build something interesting quickly, using a lot of innovation from other people, and then adding your special sauce. But that's going to take the scale of innovation just up a couple of orders of magnitude. And the pace, of course, that goes with that, is people are innovating much more rapid clip now. So really, the full promise of a cloud-native innovation model, so we kind of feel like we're right here, which means there's lots of big changes around the technologies, around kind of the world of developers and apps, AI is changing, and of course, the industry structure itself. You know the power positions, you know, a lot of vendors have spent a lot of energy trying to protect the power positions of the last thirty years. >> Yeah so we're getting into some of that. So, but you know, everybody talks about digital transformation, and they kind of roll their eyes, like it's a big buzzword, but it's real. It's dataware at a data-driven conference. And data, you know, being at the heart of businesses means that you're seeing businesses transition industries, or traverse industries, you know, Amazon getting into groceries, Apple getting into content, Amazon as well, etcetera, etcetera, etcetera, so, my question is, what's a tech company? I mean, you know, Bennyhoff says that, you know, every company's a sass company, and you're certainly seeing that, and it's got to be great for your business. >> Yeah, yeah absolutely >> Quantifying all those markets, but I mean, the market that you quantify is just it's every company now. Banks, insurance companies, grocers, you know? Everybody is a tech company. >> I think, yeah, that's a hundred percent right. It is that this is the biggest revolution in the economy, you know, for many many decades. Or you might say centuries even. Is yeah, whoever put it, was it Mark Andreson or whoever used to talk about software leading the world, we're in the middle of that. Only, software now is being delivered in the form of digital or cloud services so, you know, every company is a tech company. And of course it really raises the question, well what are tech companies? You know, they need to kind of think back about where does our value add? But it is great. It's when we look at the world of clouds, one of the first things we observed in 2007, 2008 was, well, clouds wasn't just about S3 storage clouds, or salesforce.com's softwares and service. It's a model that can be applied to any industry, any company, any offering. And of course we've seen all these startups whether it's Uber or Netflix or whoever it is, basically digital innovation in every single industry, transforming that industry. So, to me that's the exciting part is if that model of transforming industries through the use of software, through digital technology. In that kind of experimentation stage it was mainly a startup story. All those unicorns. To me the multiplied innovation chapter, it's about- (audio cuts out) finally, you know, the cities, the Procter & Gambles, the Walmarts, the John Deere's, they're finally saying hey, this cloud platform and digital innovation, if we can do that in our industry. >> Yeah, so intrapreneurship is actually, you know, starting to- >> Yeah. >> So you and I have seen a lot of psychos, we watched the you know, the mainframe wave get crushed by the micro-processor based revolution, IDC at the time spent a lot of time looking at that. >> Vacuum tubes. >> Water coolant is back. So but the industry has marched to the cadence of Moore's Law forever. Even Thomas Friedman when he talks about, you know, his stuff and he throws in Moore's Law. But no longer Moore's Law the sort of engine of innovation. There's other factors. So what's the innovation cocktail looking forward over the next ten years? You've talked about cloud, you know, we've talked about AI, what's that, you know, sandwich, the innovation sandwich look like? >> Yeah so to me I think it is the harnessing of all this flood of technologies, again, that are mainly coming off the cloud, and that parade is not stopping. Quantum, you know, lots of other technologies are coming down the pipe. But to me, you know, it is the mixture of number one the cloud, public cloud stacks being able to travel anywhere in the world. So take the cloud on the road. So it's even, I would say, not even just scale, I think of, that's almost like a mount of compute power. Which could happen inside multiple hyperscale data centers. I'm also thinking about scale in terms of the horizontal. >> Bringing that model anywhere. >> Take me out to the edge. >> Wherever your data lives. >> Take me to a Carnival cruise ship, you know, take me to, you know, an apple-powered autonomous car, or take me to a hospital or a retail store. So the public cloud stacks where all the innovation is basically happening in the industry. Jail-breaking that out so it can come, you know it's through Amazon, AWS Outpost, or Ajerstack, or Google Anthos, this movement of the cloud guys, to say we'll take public cloud innovation wherever you need it. That to me is a big part of the cocktail because that's you know, basically the public clouds have been the epicenter of most tech innovation the last three or four years, so, that's very important. I think, you know just quickly, the other piece of the puzzle is the revolution that's happening in the modularity of apps. So the micro services revolution. So, the building of new apps and the refactoring of old apps using containers, using servos technologies, you know, API lifecycle management technologies, and of course, agile development methods. Kind of getting to this kind of iterative sped up deployment model, where people might've deployed new code four times a year, they're now deploying it four times a minute. >> Yeah right. >> So to me that's- and kind of aligned with that is what I was mentioning before, that if you can apply that, kind of, rapid scale, massive volume innovation model and bring others into the party, so now you're part of a cloud-connected community of innovators. And again, that could be around a Github, or could be around a Google or Amazon, or it could be around, you know, Walmart. In a retail world. Or an Amazon in retail. Or it could be around a Proctor & Gamble, or around a Disney, digital entertainment, you know, where they're creating ecosystems of innovators, and so to me, bringing people, you know, so it's not just these technologies that enable rapid, high-volume modular innovation, but it's saying okay now plugging lots of people's brains together is just going to, I think that, here's the- >> And all the data that throws off obviously. >> Throws a ton of data, but, to me the number we use it kind of is the punchline for, well where does multiplied innovation lead? A distributed cloud, this revolution in distributing modular massive scale development, that we think the next five years, we'll see as many new apps developed and deploye6d as we saw developed and deployed in the last forty years. So five years, the next five years, versus the last forty years, and so to me that's, that is the revolution. Because, you know, when that happens that means we're going to start seeing that long tail of used cases that people could never get to, you know, all the highly verticalized used cases are going to be filled, you know we're going to finally a lot of white space has been white for decades, is going to start getting a lot of cool colors and a lot of solutions delivered to them. >> Let's talk about some of the macro stuff, I don't know the exact numbers, but it's probably three trillion, maybe it's four trillion now, big market. You talked today about the market's going two x GDP. >> Yeah. >> For the tech market, that is. Why is it that the tech market is able to grow at a rate faster than GDP? And is there a relationship between GDP and tech growth? >> Yeah, well, I think, we are still, while, you know, we've been in tech, talk about those apps developed the last forty years, we've both been there, so- >> And that includes the iPhone apps, too, so that's actually a pretty impressive number when you think about the last ten years being included in that number. >> Absolutely, but if you think about it, we are still kind of teenagers when you think about that Andreson idea of software eating the world. You know, we're just kind of on the early appetizer, you know, the sorbet is coming to clear our palates before we go to the next course. But we're not even close to the main course. And so I think when you look at the kind of, the percentage of companies and industry process that is digital, that has been highly digitized. We're still early days, so to me, I think that's why. That the kind of the steady state of how much of an industry is kind of process and data flow is based on software. I'll just make up a number, you know, we may be a third of the way to whatever the steady state is. We've got two-thirds of the way to go. So to me, that supports growth of IT investment rising at double the rate of overall. Because it's sucking in and absorbing and transforming big pieces of the existing economy, >> So given the size of the market, given that all companies are tech companies. What are your thoughts on the narrative right now? You're hearing a lot of pressure from, you know, public policy to break up big tech. And we saw, you know you and I were there when Microsoft, and I would argue, they were, you know, breaking the law. Okay, the Department of Justice did the right thing, and they put handcuffs on them. >> Yeah. >> But they never really, you know, went after the whole breakup scenario, and you hear a lot of that, a lot of the vitriol. Do you think that makes sense? To break up big tech and what would the result be? >> You don't think I'm going to step on those land mines, do you? >> Okay well I've got an opinion. >> Alright I'll give you mine then. Alright, since- >> I mean, I'll lay it out there, I just think if you break up big tech the little techs are going to get bigger. It's going to be like AT&T all over again. The other thing I would add is if you want to go after China for, you know, IP theft, okay fine, but why would you attack the AI leaders? Now, if they're breaking the law, that should not be allowed. I'm not for you know, monopolistic, you know, illegal behavior. What are your thoughts? >> Alright, you've convinced me to answer this question. >> We're having a conversation- >> Nothing like a little competitive juice going. You're totally wrong. >> Lay it out for me. >> No, I think, but this has been a recurring pattern, as you were saying, it even goes back further to you know, AT&T and people wanting to connect other people to the chiraphone, and it goes IBM mainframes, opening up to peripherals. Right, it goes back to it. Exactly. It goes back to the wheel. But it's yeah, to me it's a valid question to ask. And I think, you know, part of the story I was telling, that multiplied innovation story, and Bill Joy, Joy's Law is really about platform. Right? And so when you get aggregated portfolio of technical capabilities that allow innovation to happen. Right, so the great thing is, you know, you typically see concentration, consolidation around those platforms. But of course they give life to a lot of competition and growth on top of them. So that to me is the, that's the conundrum, because if you attack the platform, you may send us back into this kind of disaggregated, less creative- so that's the art, is to take the scalpel and figure out well, where are the appropriate boundaries for, you know, putting those walls, where if you're in this part of the industry, you can't be in this. So, to me I think one, at least reasonable way to think about it is, so for example, if you are a major cloud platform player, right, you're providing all of the AI services, the cloud services, the compute services, the block-chain services, that a lot of the sass world is using. That, somebody could argue, well, if you get too strong in the sass world, you then could be in a position to give yourself favorable position from the platform. Because everyone in the sass world is depending on the platform. So somebody might say you can't be in. You know, if you're in the sass position you'll have to separate that from the platform business. But I think to me, so that's a logical way to do it, but I think you also have to ask, well, are people actually abusing? Right, so I- >> I think it's a really good question. >> I don't think it's fair to just say well, theoretically it could be abused. If the abuse is not happening, I don't think you, it's appropriate to prophylactically, it's like go after a crime before it's committed. So I think, the other thing that is happening is, often these monopolies or power positions have been about economic power, pricing power, I think there's another dynamic happening because consumer date, people's data, the Facebook phenomenon, the Twitter and the rest, there's a lot of stuff that's not necessarily about pricing, but that's about kind of social norms and privacy that I think are at work and that we haven't really seen as big a factor, I mean obviously we've had privacy regulation is Europe with GDPR and the rest, obviously in check, but part of that's because of the social platforms, so that's another vector that is coming in. >> Well, you would like to see the government actually say okay, this is the framework, or this is what we think the law should be. I mean, part of it is okay, Facebook they have incentive to appropriate our data and they get, okay, and maybe they're not taking enough responsibility for. But I to date have not seen the evidence as we did with, you know, Microsoft wiping out, you know, Lotus, and Novel, and Word Perfect through bundling and what it did to Netscape with bundling the browser and the price practices that- I don't see that, today, maybe I'm just missing it, but- >> Yeah I think that's going to be all around, you know, online advertising, and all that, to me that's kind of the market- >> Yeah, so Google, some of the Google stuff, that's probably legit, and that's fine, they should stop that. >> But to me the bigger issue is more around privacy.6 You know, it's a social norm, it's societal, it's not an economic factor I think around Facebook and the social platforms, and I think, I don't know what the right answer is, but I think certainly government it's legitimate for those questions to be asked. >> Well maybe GDPR becomes that framework, so, they're trying to give us the hook but, I'm having too much fun. So we're going to- I don't know how closely you follow Facebook, I mean they're obviously big tech, so Facebook has this whole crypto-play, seems like they're using it for driving an ecosystem and making money. As opposed to dealing with the privacy issue. I'd like to see more on the latter than the former, perhaps, but, any thoughts on Facebook and what's going on there with their crypto-play? >> Yeah I don't study them all that much so, I am fascinated when Mark Zuckerberg was saying well now our key business now is about privacy, which I find interesting. It doesn't feel that way necessarily, as a consumer and an observer, but- >> Well you're on Facebook, I'm on Facebook, >> Yeah yeah. >> Okay so how about big IPOs, we're in the tenth year now of this huge, you know, tail-wind for tech. Obviously you have guys like Uber, Lyft going IPO,6 losing tons of money. Stocks actually haven't done that well which is kind of interesting. You saw Zoom, you know, go public, doing very well. Slack is about to go public. So there's really a rush to IPO. Your thoughts on that? Is this sustainable? Or are we kind of coming to the end here? >> Yeah so, I think in part, you know, predicting the stock market waves is a very tough thing to do, but I think one kind of secular trend is going to be relevant for these tech IPOs is what I was mentioning earlier, is that we've now had a ten, twelve year run of basically startups coming in and reinventing industries while the incumbents in the industries are basically sitting on their hands, or sleeping. So to me the next ten years, those startups are going to, not that, I mean we've seen that large companies waking up doesn't necessarily always lead to success but it feels to me like it's going to be a more competitive environment for all those startups Because the incumbents, not all of them, and maybe not even most of them, but some decent portion of them are going to wind up becoming digital giants in their own industry. So to me I think that's a different world the next ten years than the last ten. I do think one important thing, and I think around acquisitions MNA, and we saw it just the last few weeks with Google Looker and we saw Tab Low with Salesforce, is if that, the mega-cloud world of Microsoft, Ajer, and Amazon, Google. That world is clearly consolidating. There's room for three or four global players and that game is almost over. But there's another power position on top of that, which is around where did all the app, business app guys, all the suite guys, SAP, Oracle, Salesforce, Adobe, Microsoft, you name it. Where did they go? And so we see, we think- >> Service Now, now kind of getting big. >> Absolutely, so we're entering a intensive period, and I think again, the Tab Low and Looker is just an example where those companies are all stepping on the gas to become better platforms. So apps as platforms, or app portfolio as platforms, so, much more of a data play, analytics play, buying other pieces of the app portfolio, that they may not have. And basically scaling up to become the business process platforms and ecosystems there. So I think we are just at the beginning of that, so look for a lot of sass companies. >> And I wonder if Amazon could become a platform for developers to actually disrupt those traditional sass guys. It's not obvious to me how those guys get disrupted, and I'm thinking, everybody says oh is Amazon going to get into the app space? Maybe some day if they happen to do a cam expans6ion, But it seems to me that they become a platform fo6r new apps you know, your apps explosion.6 At the edge, obviously, you know, local. >> Well there's no question. I think those appcentric apps is what I'd call that competition up there and versus kind of a mega cloud. There's no question the mega cloud guys. They've already started launching like call center, contact center software, they're creeping up into that world of business apps so I don't think they're going to stop and so I think that that is a reasonable place to look is will they just start trying to create and effect suites and platforms around sass of their own. >> Startups, ecosystems like you were saying. Alright, I got to give you some rapid fire questions here, so, when do you think, or do you think, no, I'm going to say when you think, that owning and driving your own car will become the exception, rather than the norm? Buy into the autonomous vehicles hype? Or- >> I think, to me, that's a ten-year type of horizon. >> Okay, ten plus, alright. When will machines be able to make better diagnosis than than doctors? >> Well, you could argue that in some fields we're almost there, or we're there. So it's all about the scope of issue, right? So if it's reading a radiology, you know, film or image, to look for something right there, we're almost there. But for complex cancers or whatever that's going to take- >> One more dot connecting question. >> Yeah yeah. >> So do you think large retail stores will essentially disappear? >> Oh boy that's a- they certainly won't disappear, but I think they can so witness Apple and Amazon even trying to come in, so it feels that the mix is certainly shifting, right? So it feels to me that the model of retail presence, I think that will still be important. Touch, feel, look, socialize. But it feels like the days of, you know, ten thousand or five thousand store chains, it feels like that's declining in a big way. >> How about big banks? You think they'll lose control of the payment systems? >> I think they're already starting to, yeah, so, I would say that is, and they're trying to get in to compete, so I think that is on its way, no question. I think that horse is out of the barn. >> So cloud, AI, new apps, new innovation cocktails, software eating the world, everybody is a tech company. Frank Gens, great to have you. >> Dave, always great to see you. >> Alright, keep it right there buddy. You're watching The Cube, from Actifio: Data Driven nineteen. We'll be right back right after this short break. (bouncy electronic music)

>> Live from Las Vegas it's theCUBE, covering Dell Technologies World 2019 brought to you by Dell Technologies and its ecosystem partners. >> Okay welcome back everyone we are here live in Las Vegas with Dell Technology World 2019 and I'm John Furrier and my co-host Dave Vellante breaking down all the action, three days of wall-to-wall coverage. We go all day, all night here at Dell's great event. We're here with the CMO of Dell Technology Allison Dew, great to see you, thanks for coming on. >> My pleasure, it's nice to be here. >> Good to see you again, Allison. >> It's fun. >> What a show, action-packed as always. We got two sets, we call it the theCUBE content cannons. We're just firing off content, a lot of conversations, a lot of boxes being checked, but also growth, lookin' at the numbers. The business performance of Dell is strong. Leadership across all categories, large-scale, and an integrated approach with the products and the relationship with VMware paying off in big-time. Azure News, Microsoft integrating in, so a lot of great product leadership, business results, things are booming at Dell Technologies. >> They really are and you know, when you think about the journey for us in particular over the last three years since starting the EMC combination, and all of the things that are written about integrations, technology integrations of this scale and scope, and you look at what the teams together have successfully done, the business performance, the share growth across categories, and as of today, the true end-to-end solutions that we're announcing in partnership with VMware and Secureworks. And we tend to be a pretty humble culture, but I will say, I think it's a pretty impressive result, when you look at most integrations are focused on don't break anything, and not only did we not break anything, we've kept the trust of our customers, we've continued to grow the customer base, and now we're really focused on, how across the Dell Technologies family, primarily with VMware and Secureworks and Pivotal do we bring to life the solutions that solve our customers' biggest IT problems. Pretty amazing spot to be in. >> You know one of the luxuries of doing theCUBE for 10 years is that we've had conversations over 10 years and I remember many years ago when Michael was about to go private, we saw him in Austin, was a small Dell world back then, we had two conferences, and he was standing there alone. We approached him, Dave and I, and we had a long conversation with him, he was very approachable, and then when he talked about, when he did the private and then the acquisition at these points, everyone was pooh-poohing it at saying, it's a declining market, things are going, why would you want to do this? Obviously the scale benefits are showing, but the macroeconomic conditions of the marketplace, you couldn't be happier for. Public cloud drove a lot of application deployment, you have SAS businesses started, you have on-premise booming, refresh and infrastructure, a complete growth. >> Right. >> Yeah, there's actual growth there. >> Right. >> So the bet paid off. You as a marketer have to market this now, so what's your strategy because you have digital transformation as the kind of standard positioning posture, but as you have to market Dell Technology on the portfolio of capabilities, which is large, I can only imagine it's challenging. >> So let me actually back up, and to one of the points that you talked about, and then I'll answer your actual question. So I can't remember off the top of my head, but we very jokingly talk about, in the era since the PC was declared dead, we have sold billions of PCs right and it would be funnier if I could remember the number, but you know we used to joke around with Jeff Clark, ala Monty Python, I'm not dead yet. >> Yeah. >> And so you get this hype about what's happening in the industry, and the truth is it's actually a very different picture than some of that hype, and one of the reasons I think that's important is because obviously we've continued to take share on the PC business, we've continued to grow there, but we also believe that the hype sometimes applies to these other technology cycles as well. So if you go back a couple of years ago, it was everything was going to the public cloud. If you don't go to the public cloud you are a dinosaur. You don't know what you're doing. You're going to go out of business. The traditional infrastructure companies are going to go out of the business, and to be honest, that is also just nonsense, right. And so if you think about what's evolving, is we believe very firmly that we're going to see the continued growth of a hybrid cloud, multi-cloud world and it's not one thing or the other. And in fact, when you look at all of the research around the economics of doing one or the other, it all becomes workload-dependent. So for some workloads you should go to the public cloud. For some workloads, you should have it on-prem and that conversation may not be as interesting a headline, but it's the truth. >> It's reality actually. >> It's the truth. >> Well it's also reality, the workloads are dictating what the architecture should be or the solutions. That's what you're saying is a reality. >> Exactly, and so that's why we're so excited about the announcements that we had this morning with VMware, with Microsoft. We're really talking about a multi-cloud, hybrid cloud world, and across all of the solutions that we announced this morning. The key, continuity and what we're really focused on, sounds so hackneyed, is how do we make it simpler for our customers? How do you make it simpler to manage and deploy PCs? How do you make it simpler to manage and deploy your cloud environment, that's it. >> So let's talk about the show a little bit, let's see 15,000 attendees, 122 countries represented, 4,000 channel partners, 250 industry analysts and media folks, so pretty big numbers. You could see it in the hallways. It's not quiet. You're kind of doing a lot of this. >> It's actually sort of hard to pay attention to you guys with all the noise in the background. You must be used to it. I'm like a goldfish, like what's happening? >> Now the interesting thing to me is, and we were talking about you know, it's the transitions, consolidations, oh it's traditional infrastructure companies are dead, et cetera, et cetera. I'd observe that over the years the testament of today's leaders is they respond, they don't just sit back and say oh Unix is snake-oil. Do you remember that famous quote? Look at what Microsoft has done, but my point is Michael's keynote today, it wasn't about a bunch of products, it was about big visions, solving a lot of the world's problems, and really conveying that Dell is in a position to help these companies as a partner. I presume you had some input to that keynote, I just wonder. >> I hope so. (laughs) >> What the thinking was there? >> So there's a lot of conversation and it's, you don't have to go that far in the media to read everything about technology as a force of evil in the world. One of the things that you notice, Michael's keynote this morning and I'll come back to what we're doing about it again later this week, is we are putting a very firm stake in the ground that we believe that technology is overall a force for positive change in the world and we're having a conversation about that on Wednesday that I'll talk a little bit more about in a second. And there's a subtlety there, that I think sometimes again, may not be the most interesting headline but is true, which is technology in aggregate drives great progress in the world, however we as leaders, we as humans, also have a responsibility to drive the responsible use of technology and so you see some of the conversations that we're having later this week in the Guru sessions, for example, where Joy Bilal-Meany is talking about responsible use of AI and some of the inherent biases in AI. Those are the tough issues that leaders need to be tackling now. >> Yeah well and one of the other you know, you're right a trade press loves to pick up on it and pick at it but one of the things to talk about, of course, is jobs, automation affecting jobs, I know Erik Brynjolfsson is one of your speakers, he's been on theCUBE before, and the discussion we had was machines have always replaced humans. For the first time ever,now they're replacing humans in cognitive functions. So the the answer is not protect the past from the future it's educate people, find new ways to be creative. I mean, technology has always been-- >> That's right. >> Part of human good and human advancement. There's always a two-sided coin, but it's got to be managed. >> That's right, one of the conversations that I think gets lost is when we talk about, I am a Battlestar Galactica fan, the second one not the one from the 70s, so you know I always say jokingly-- >> Darn. >> Yeah, yeah. >> We're a little older. >> Did you watch the one from the 2,000s? >> Yes, of course. >> 2,000s are so good. You know the conversation about are the Cylons coming to get us? And is AI really the thing that's destroying what's happening for human populations? The reality is AI has been evolving for many years, so it's not actually new. What is new is the combination of AI and data and the compute power to make that real and I do think it requires a different conversation with societies, with employers about how do you continue to reeducate your employee base? What does that mean? And that is really meaty stuff that we need to be leaning into. On aside, you've got me thinking of this whole Battlestar Galactica. My mind's thinking Star Trek, Star Wars. I heard a rumor that you guys had so many unhappy employees because Game of Thrones was on yesterday. >> Yeah. >> That you actually rented a big screen? >> Yeah, we did. >> A lot of Game of Thrones fans? Are you in that mix? >> So yeah. >> No spoiler alerts. >> No, I won't say anything about what happened. But I'll tell you, so we have all of our employees who work at the show, have to get here on Saturday or Sunday at the very latest. And even me personally, we came to Las Vegas and I thought, well I can watch it in my hotel room and then my hotel room didn't have HBO and I thought I don't really want to watch it on my little HBO Go app that's about this big because we're all waiting for what's going to happen in episode three, and I won't tell you if you haven't seen it. >> It's a lot of battling. >> So exactly, so my team and I had this conversation about could we have a joint viewing of Game of Thrones and it's really my team who did all of the work, but it was super-fun and we had a party with a bunch of team, had a few beers and it was fun. >> That's a great culture. >> I just wanted to get that out there. I think, cool culture. Allison, you mentioned something about the press and stories for good and how people looking for headlines. You know we're not advertising, so we're not trying to chase the clickbait, it's about getting the story right and sometimes the boring story doesn't get the headlines. Or the page views, advertising. So we're in a world now where a lot of other people in the media, they're censoring posts, there was an incident on Forbes where I wrote a negative post about a company and they took it down, that was Oracle. A lot of journalists looking for stories just to put tech in a bad spot. >> Right. >> And there's a lot of tech for good, but a lot of people can't point to one thing saying that's an example for tech for good and there's some few out there missing children, exploited children, trafficking, all kinds of things, talk about that dynamic because this is changing how you market, how people consume. You have the role of open communities. >> Yep. >> Social networking. A lot of dynamics going on. How do you view all this? >> So first of all, I think so much of the conversation about tech for good or tech for bad actually indexes only on social media and media broadly, and perhaps that's because it's the media who are writing about that. And so there's sort of this loop that we get in and I do think there are real issues that we need to think about in terms of social media. You guys likely saw Kara Swisher had a an op-ed in the New York Times after the Sri Lankan bombings where she, long-term technology advocate, actually said after the Sri Lankan bombings when the government shut down all social media communications, I thought that was a good thing and so that probably actually did help with the immediate situation on the ground and yet is a very scary precedent, right? I'd like to to take the conversation and say what about media? Right, so there's a lot of work that we need to do in order to maintain media fairness and then there's a whole other conversation about technology that we're not talking about. Everything that we're doing in terms of medicine and indexing the human genome, and addressing deafness and Michael talked about that even this morning, there are these really big technology problems that were really leaning into, and yet we're either talking about Amazon drone delivery or what Facebook is doing. We need to talk about those, but let's talk about where technology is really struggling to address real problems. >> I just read an essay yesterday from Dana Boyd who wrote a great fascinating piece around extremism in social media. Media's being hijacked by these extreme groups and they're mixing up causation and correlation and conflating many things to just tell a story to support an initiatives, no curation. >> Right. >> And with social media everything's open so that just flies out there. And so that's a big problem. >> And then takes off, you know. >> So how do you deal with that as a CMO 'cause you're spending advertising dollars. You're trying to deploy capital. You now have a new open source kind of mindset around communities customers are shopping themselves now. >> Right, so this is going to sound possibly a little bit overly simplistic but what I am responsible for in my job is the reputation and brand of this company right. I think about other things in terms of how we think about media and everything but I want to make sure that we are spending our media dollars in a responsible way and yet also recognize that people can disagree with us and that's okay and be comfortable with, we can be both a media advertiser on a publication who might write a review where they don't like one of our products and I'm never going to be in the business of saying take down our media dollars because that sets a terrible precedent and frankly there are people who would say take down our media dollars so that's one thing that we're really focused on. And then the other is, we consistently year-over-year are recognized as one of the world's most ethical companies and I will tell you from the leadership with Michael across the board I believe that that is true. And we actually think about business in an ethical way and we behave in an ethical way and that's why frankly you're not reading those headlines about us which are a lot more problematic. >> It's a cultural thing you guys have. Michael's always been a direct-to-consumer. That's been a direct mail, back in the glory days, now-- >> We still do that actually. >> Cloud, SAS, he texts me all the time. Hey John, what's going on? So he's he's open. >> Yeah. >> He's also now with Cloud and SAS, it's a direct to consumer business. >> I love your positive attitude. You have a session tomorrow, Optimism and Happiness in the Digital Age, looking forward to that. I have a personal question. So you started out your career, I think, in East Asia studies, right? >> That's right, good memory. >> You speak multiple languages. >> Yeah. >> I think three languages? >> If you count English, three. >> Yes okay so you're trilingual. >> Trilingual, yeah. >> If you speak two, you're what? >> Bilingual. >> Speak one, you're what? >> Monolingual, American. (all laughing) American, I was like, I know this joke. >> I wonder how that affected sort of your career? >> Absolutely. >> In terms of getting into this business. >> I would first say that I was an incredibly naive undergraduate. I wanted to be an editor of a paper and I loved foreign languages. So I studied Japanese and French and that led me to going to Japan as a very naive 22 year old and I started working in this small Japanese ad agency. I was the only non-Japanese person in that company and of course I learned some functional things in terms of the art of advertising but what I actually learned was how to survive in an environment that was so different to mine. Even if you speak Japanese, it is a language of unsaid things and you have to constantly be figuring out what's actually happening here and so ironically that decision that I made at 18, very naively, to study Japanese is one of the things that sets the course of my life because I've always been, my entire career, in international jobs and I think if I ever had to come back to just being in an American job, I wouldn't know what to do with myself, I'd be so bored. And it's also one of the reasons when we talk about technology and education and AI and what are robots going to do, This is my personal opinion, somewhat controversial opinion which is of course we need to support STEM, of course I want to see more women in STEM. At the same time, I want to see us focus our children on critical thinking skills. How do you write well? How do you have an argument? How do you convince somebody? And that's because until I went to business school I was a liberal arts major born and bred and so that's not the pat answer that you expect from somebody in my job which is it's all about STEM. It's about STEM and more. >> Emotional quotient's a big thing we're seeing a lot. The whole self. That's a big part of the kids growing up being aware. >> Yeah. >> Socially emotional. Allison, thanks coming on theCUBE and sharing. >> My pleasure. >> Great insights here in theCUBE. We're here with the CMO, Allison Dew, with Dell Technologies. I'm John Furrier, Dave Vellante. Stay with us for more day one coverage after this short break. >> Awesome. (upbeat electronic music)

>> From Palo Alto, California, it's theCUBE. Covering VMware, Women Transforming Technology 2019. Brought to you by VMware. >> Hi, Lisa Martin, on the ground with theCUBE, at Vmware in Palo Alto, California at the fourth annual Women Transforming Technology event, WT-squared. Love this event. So excited to welcome back to theCUBE Betsy Sutter, VMware's Chief People Officer. Betsy, this event is incredible, year after year. >> Yeah. >> How do you do it? >> I don't do it. A team of people do it. But I love it and I love it that you're here. You're as passionate about this as I am. Our fourth! And this one is bigger and better than ever. I love it. And, you know, it's really all about just connecting women so we can continue to innovate and shape the future. So, super fun! >> It is super fun. One of the things that I love is that as soon as you walk onto the campus in the morning, ahead of the event, even walking up to registration, you can feel positivity, sharing, collaboration, experiences being shared. This community movement-- you literally can feel it. And then we walked in, your opening keynote this morning. >> Yeah, wasn't she amazing? Joy Buolamwini >> Wow. Amazing. What she was sharing. Breakthrough data of all the biases that are being built into just facial recognition software alone. >> Yeah. >> Her passion for highlighting the bias and then identifying it and then mitigating it, that passion was not only coming from her, but the entire audience. In person, I can imagine the livestream, just got it. >> Yeah. You know, she is amazing. I mean, she's an innovator. I mean, she's a brainiac. She's funny, she's artsy. But she's an innovator. But what's interesting about her is she's an inclusive innovator. Right? It's all about inclusion and I love her approach to this. I just spent an hour with her in a Fireside Chat where a number of us got to have a conversation with her and she's about as interesting as anybody I've ever met in terms of where she's taking this research so that she can create, just a better world. >> And she's doing that. One of the things that was, the word inclusivity kind of popped up, and intersectionality, a number of times, where she was showing data, AI data, from Microsoft, IBM, Face++, and just showing the massive differences in those data sets alone, so the whole inclusivity theme was very paralleled, in my opinion, but she's actually getting these companies to start evaluating their data sets to change that so that Oprah Winfrey, for example, face recognition doesn't come up as a male. >> That's right. Yeah, she has done some interesting, interesting work, and she's not approaching it as if it's a race issue in particular, right. She's taking a completely different, very positive approach, to highlighting a real problem. I mean, we knew that inclusion is a challenge in technology, but inclusion in artificial intelligence is by far worse, and I love it that she's unpacking that. >> I also love that, as a marketer, I loved how she formed the Algorithmic Justice League. >> Right. >> I couldn't think of a better name, myself. But that she's seeing three tenets of that. One is highlight the bias. >> That's right. >> And I thought, that's awareness. There needs to be more awareness of that because my mind was blown seeing these models today, and then she brings in Amazon and shows them, look at your data sets. >> Right. >> And so there needs to be more awareness, consistent awareness, it's kind of classic marketing of, there are a lot of challenges, but AI is so pervasive, I can imagine a lot of baby boomers probably have iPhones with facial recognition and don't understand, wow, even that, unlocking my phone, is a problem. How deep does this go across emerging technologies that are being developed today? >> That's right. And then she just talks about, in such broad terms, I mean she has a global mind around the social impact that this is having, whether it's in artwork, whether it's in self-driving car technologies, whatever it is. I mean, it's huge. And she's able to kind of look out and think about it in that light. And given the work that we're doing at VMware around inclusion and diversity, it's kind of a fresh new angle to really unpacking the layers of complexity that face these issues. >> Yeah, you're right. That was a thing that also caught my attention was there were so many layers of bias. >> Yeah, yeah. >> We can think of, you know, the numbers of women, or lack thereof, in technology. One of the things that Joy said, kind of along the parallels of layers was, the under-represented majority, as she says, it's women and people of color. >> That's right. >> It's layer upon layer upon layer. >> It is. >> Wow. Just cracking the surface. >> She's just scratching things, but the way she's doing her approach, I think, just brings a whole new light to this. I'm very grateful that she was able to speak to all of us, right. It's really about bringing women together to have these kinds of conversations so we can start to think about how we want to innovate and shape the future. She also touches on just this aspect of communities, which I love. And, you know, I've long said that people join communities, not companies, per se, and one of the things that we've done at VMware is tried to think about how do you create an inclusive culture, if you will, that embraces all sorts of communities. And Joy just started talking about a whole new dimension to how we think about that, which was fun. >> So you have been at the helm of people at VMware for a long time. >> I have. >> Lots of transformation. >> Yeah. >> I'm curious to get your, if you look back at the last four years now of WT-squared, how have you learned from even just speakers like Joy and helped to transform not just WT-squared but VMware, its diversity and inclusion efforts in and of themself? >> Yeah, you know, one of the things that I love about VMware and I love about WT-squared is that it's really a consortium or a collective of companies coming together, so this is not a VMware branded event, or a VMware event just by itself. It's just a collective. And then we try and broaden that circle so we can have more and more conversation. And I think that's what I'm most pleased with, I mean, we work hard at making sure that this collective is involved from the get-go in terms of, what do we want to talk about, so we can have the real and relevant conversations about inclusion and diversity, especially as women in tech, which, in some regards, is getting better, but in many, it's just not, and so how do you double down on that in an authentic way and really get business results. >> Exactly. It's all about getting business results. >> It is. >> One of the things that surprises me, in some cases, is when you see, whether it's from McKenzie or whatnot, different studies that show how much more profitable businesses are with women at the executive levels, and it just, that seems like a no-brainer, yet there's so many, the lack of women in technology, but also the attrition rates. >> Yeah. >> Really staggering, if you look at it, compared to any other industries. >> That's right. And, you know, we have a longstanding relationship with Stanford. >> Yes. >> The Clayman Institute. VMware helped found the VMware Stanford Women's Leadership Innovation Lab, which I'm exceedingly proud of. But, yeah, research shows this over and over. But one of the things that I love about my work is bridging that into how corporations operate and how people just work at work, and so that keeps me intellectually engaged, I'll say that, for sure. But, yeah, that is the big challenge. >> I'm also, what I love, just observing the attendees at the event, is you see all age levels. >> Yeah, I love that, too. >> And you have the tracks, the Emerging Leaders track for those who are younger, earlier in their career, The Executive track, the Technical track, and you've got a track about of sharing best practices, which I also love, or just hearing stories of, "How did you face this obstacle, maybe it wasn't, that didn't cause you to turn, or to leave the industry?" I think those are so important to help share. "Oh my God, I'm going through the same thing," for example. But might just help the next, or not just the next generation, but even those of us who might be middle-career from not leaving and going, "Okay, maybe it's the situation, I need to get into a different department, a different company, but I love technology and I'm going to stay no matter what." >> Yeah. Keeping those conversations elevated is one aspect of this, but then to your point, the cross-pollination of all these different kinds of women and what they've experienced in tech, the panel today was amazing, right. We had Ray, we had Lisa, and we had Susan. All different perspectives, different generations, but talking about sort of their challenges as they've navigated this, and where they all want to see it go. So I do think there's a bit of a common vision for where we want this to go, which is wonderful, but bringing all these different perspectives is the differential. And that's what we do here. We try and replicate that. And what will happen all through the day as I go to those different tracks, I'll hear from these different women and the questions are always just a blast to hear, right, because I learn so much from what's top-of-mind, what's keeping people up at night as they venture into tech and continue into tech. >> Anything in particular that surprises you? >> You know, one young woman asked me about my concern around communication and interaction because of how technology's affected how people do that-- rarely face-to-face like you and I are right now. And there're so many other visual and sensory cues that go into having a conversation with another human being, so we had a great conversation about what's good about it from a technology standpoint, and what's bad about it, and I think that's actually what Joy was talking about in her talk today, as well. But I was pleased that a very young person asked me that question. I know people of my generation, we talk about it, but it was fun to hear, kind of inspiring to hear a younger person say, "Is this all good?" >> Well and you're right, it probably was a nice, pleasant, refreshing surprise because we think of younger generations as, kind of, you say, cloud-native or born of the cloud, born on the phone, who are so used to communicating through different social media platforms. To hear that generation saying, you know, or even bringing it to our attention, like, "Shouldn't we be actually talking in person or by using technology like video conferencing and zoom things for engaging?" Think of how many people wouldn't fall asleep in meetings if video conferencing was required? >> That's right. That's exactly right. And another woman, a little further along in her career, what was weighing on her was how she stayed being a responsible and ethical person when she doesn't really know all the ingredients of what she's helping to create. And that's just a mindset that I haven't heard before. I thought that was wonderful. >> That is. Because we often talk about responsibility and accountability with respect to data science or AI, for example. It's interesting to hear an individual contributor talking about, "Where do I fall in that accountability/responsibility spectrum?" Is not a common question. >> No, and you know, we think we're creating a world of more transparency but, really, when you're coding you're not really sure what might happen with that code. And I thought Susan Fowler did a lovely job talking about that today on the panel, as well. That there's a huge responsibility in terms of what you're doing. So connecting those dots, understanding all the ingredients, I think corporations like VMware, and VMware does this in large part today, it gets harder, it's more complex, but we're going to have to answer those questions about what kind of pie or cake are we really baking with this, right? >> Exactly. Exactly. Could you have, if you looked back to when you first joined VMware, envisioned all of the transformation and the strength in community and numbers that you're helping to achieve with women transforming technology? >> I really couldn't. I mean, the industry is amazing, you know, I was at the right place at the right time and got to ride this tech wave. It's been great. No, I couldn't have imagined it, and now things are moving at an unprecedented place, things are much more complex. I have to call my adult children to get input onto this, that, and the other. >> (laughs) >> But no, it is a dream come true. It's been an absolute honor and privilege for me to be a part of this. I love it. >> When you talk with VMware partners or customers, are they looking to-- Betsy, how have you been able to build this groundswell and maintain it? >> Yeah, you know, my focus is primarily on the culture and the environment of the company, and I'm a really good listener. So that's the key. >> It is key. You just listen and pay attention to what people are saying, what matters to them, what's bothering them, and you continue to hold on to, sort of, those, you know, those North Stars of what you're trying to build and I always knew that I wanted to build the sustainable cultures, something that would last the test of time. So we're at 21 years. I've done 19 of them, so it's been great. You know, but you want to make sure you keep that rebar in the ground as you continue to build up. This community is solid. They're doin' it. Yeah, it's great. >> And it must be receptive. We talked about companies or leaders or businesses being receptive to change. I think I talked about that with Caroline and Shannon, who were part of that panel, and said, you know, oftentimes, we're talking with leaders, again, business units, companies, who aren't receptive to that change. Cultural change is really difficult, but it's essential. I was talking with Michael Dell a few months ago at Boomi World and said, "How have you managed as Dell has grown so massively to change the culture in a way that, you know, enables that growth?" It's a really hard thing to do. But for companies to do digital transformation and IT transformation, the culture, the people have to be receptive. I think, to one of your strengths, they have to be willing to listen. >> Yeah. And you never really arrive, right. So you constantly are in beta mode in the world, and so if you never assume that you've arrived, then you can pause, or that you just constantly want to beta things, then you have an edge, and I think Michael Dell's clearly got vision around that, right. I know Pat Gelsinger does, too. And so I like just partnering with those great minds, those great business and strategic minds, and then just building on the people component or the cultural component. But I, too, I'm constantly trying to produce new products and pay attention to what the customer wants. >> When you see things in the news like some of the harassment issues, say, for example, that Uber has experienced, I imagine you're watching the news or reading it and you're thinking, if I could just say three things to those people. When you see things like that, what are the top three things you would recommend that, not in reaction, though, but how can that culture change to deliver the customer experience, ultimately, that they need to, but what are some of the things that you think, these are easy fixes? >> Yeah, I think in watching a lot of my companies in the industry and how they've responded, for me, my advice would be, you should elevate that conversation. That conversation's not going to go away. And so you need to elevate it, give it a lot of sunlight and oxygen, really understand it, don't try and move away from it, don't push it down. And that's something we do at VMware, we're constantly elevating the conversation. One of the things I love about this culture, it's made me a lot better at what I do, is I can always answer the question, "Why are we doing that?" And so that's, why are we doing that? And if I can't answer why, we have a problem. And a why just sort of symbolizes intellectual curiosity, right, so that's what we're trying to keep alive and that's what I tell my other colleagues in the industry is just keep that conversation going: there's no quick fix to this, people are complex, don't pretend you really know. So elevate it and let's get to really know each other a lot better. >> And there's so much good that can come from any sort of blight or negativity, there really is, but you're right. Especially in this day and age, with everything being on camera, you can't hide. >> And, you know, it's okay to admit that you made a mistake. >> I agree. >> It's really okay. And so there's something about that that we've got to get back. >> I think it's one of the most admirable things of any human trait or corporation is just admitting, ah, this was the wrong turn, >> Right. >> I said the wrong thing. >> You know what, we made a mistake. We've course-corrected. >> I'm human. >> Yes. >> Exactly. >> Exactly. >> So we talked about Joy opening things off today and Ashley Judd-- >> I know, I can't wait. >> I bet you can't wait. She is the closing keynote. What are the things that inspire you about Ashley's work? >> I just think that she's wicked-smart. And I think she's using her platform in a really powerful way. And for her to want to come here and speak to us just reflects her passion, and the juxtaposition of Joy with Ashley is fabulous, right. Really gives you a lot to think about, so I can't wait to see Ashley. >> And just even juxtaposing those two, like you said, you can just see massive diversity there, in thought, in background, and experience, in life experiences, but both coming from different perspectives and different angles that can be so inspirational >> Yeah. To all of us in the audience. >> Yeah, and positive. You know, they're taking this positive approach to this movement and, yeah, very different women, but both really, really smart, very passionate. Resilient, clearly. And persistent. They're going to keep movin' it forward. >> Persistence is the key. So, great event so far. It's not even over, but what are your dreams for next year's event? >> Oh, we just have to keep going. I'd love to see more companies join the consortium. We've learned a couple things about, we just are going to start the conversation earlier about what we want the event to be. We love hosting people on the campus, obviously, and luckily we have terrific weather today, but I would just like to see companies come together and have the conversation, and that was really the impetus for this, is that we wanted to make sure we got a lot of diverse perspectives that were dealing with these real issues, and let's talk about what women in technology at all levels, as you pointed out, what's top-of-mind for them? And what do they need to have the conversation about? Let's bring 'em together, let's let 'em connect and start to innovate and create the future. >> Well I'm already looking forward to next year, Betsy. >> Yeah, me too. >> It's been such a pleasure to talk to you again. >> Thank you, Lisa. >> Thank you so much for spending time with me on theCUBE today. >> Thank you. >> Appreciate your time. >> Super fun. >> Good. You're watching theCUBE. I'm Lisa Martin on the ground at Women Transforming Technology, the fourth annual. Thanks for watching. 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>> from Palo Alto, California It's the Cube covering the em where women transforming technology twenty nineteen Brought to You by V. M. >> Where >> Hi, Lisa Martin on the ground of'Em were in Palo Alto, California, at the fourth Annual Women Transforming Technology Event, or W T. Squared one of my absolute favorite events to cover. And I'm pleased to welcome from one of the sponsors, Jennifer Cohen, the vice president of operations at Toyota Research Institute. Welcome to the Cube. >> Thank you, is that I'm really excited to be here to >> This is such a great event. It's It's morning time. You and I both have a lot of energy coming from even before you walk into the keynote here. Collaboration. The positive spirit, the energy, all of these women talking about and menas well past experiences. It's you walk in, and the energy of Deputy squared is palpable. This is your fourth year. So you being here now at all four >> have, and that's why I keep coming back because the energy here is so good because every year I walk away with tips I can use at work and in my personal life, championing diversity >> and diversity inclusion one of the tracks here, as well as trucks like helping emerging leadership the younger generation, which is key because the attrition rates in technology are so, so high. Tell me a little bit about Tech Toyota Research Institute, Terra What you guys doing? And what made it important for tea Right to sponsor W T Square this year. So Toyota Research >> Institute is a subsidiary of China. We're working on a really exciting things like autonomous driving robotics to help elders, agent place and material sciences. So it's really exciting next level stuff. And it's thrilling to kind of coming to work every day on things that we've been hearing about in the world. And now they're real world things, not just the Jetsons, you know? Yes. >> And so you were here as I mentioned the last three years. But last year, uh, when you were here, you were saying a minute ago. You leave this event every year with really useful kind of we'LL put it into tech terms act personal insights, absolutely clueless about your conversations at Tier I that where they said yes, this is an important event for us to >> sponsor, absolutely so that when I When I came back last year, I had brought a couple of folks from T. Ry to attend the event because I've been attending since the beginning. And as I said, every year I find something that I can bring back to the teams, if not multiple things. Andi weaken our chief diversity officer, Our senior chief of staff is also our diversity inclusion Head. She was very passionate about also supportive event. We're involved with Grace Hopper. We have a women's employee resource group. We're really putting our efforts our time here. They were glad to sponsor. And what was so exciting to walk into that room full of energy today and to see t rise logo up there? It was amazing. >> And I'm sure that for that you mentioned that there's about twelve of your your folks that are here that probably feel it's great that you're not just it's not just a logo. Now, this isn't just branding. This is actual. We're here, You're here. It's a focused, concerted effort. That tiara has an in fact when you join Tiara on the last couple of years, one of the things that inspired you was there's a Chena female leadership here, which is not >> common. No, it's definitely not definite, not common in my career. So one of the reasons I started at here I was because of my manager. Who's her name is Kelly K. She's our EVP and CFO, and she's an amazing leader and so on having the opportunity to go to another company. I wanted to go to one that makes a difference. Like tea, right? Look working to improve the quality of human life. And I wanted to work for somebody that I really respect. It could learn from on. It's been pretty rare in my career tohave women, female leaders to report to. So it's been amazing. And that, I think shows in the role that I have the role, that our chief of staff has Kelly's role and the fact that we're here today. It all flows through. >> So talking. Let's talk about more about flow as VP of operations tell me, like, for example, last year's W T squared what were some of the learnings that you brought back and used in your team, whether it's your management style or even hiring the next generation, >> so a few things that I've learned and not all of them are from last year. I'LL be honest. I'm not. All of them are ones I've just up like at you write. But some of them are things about management. Patty Vargas was here a couple years ago, talking about winds and challenges and really highlighting wins and every team meeting that something that it took back. And it well, it's not necessarily diversity. It's been transformational for me as a leader and really helpful to my team's. Then something. Other things I learned were about on, especially in a few years ago, about saying tohr, I'm not accepting any candidates until you have a diverse candidate pool. That's made a really big difference. And it's hard to say it's hard to stick with because it is hard to find women in technology. However, sticking with that has really helped in my career, hiring folks to have a more diverse team, >> so sticking with it, you've been in a technology for a long time. Tell me a little bit about your career path where you stem from the time you were a kid knowing I love computer science, or was it more zigzag ee >> Ah, little's exactly I was actually history, major say, But I always love technology. Back when we had trs eighties, I love technology. And so I actually started doing that to put myself through school, and I loved it so much. It's what I've stopped what's happened in technology for twenty five years, starting as health desk and systems administrator and moving my way up in my career over time, and every so often they still let me touch something technology and a firewall or some of my best. I keep a little bit of that skill set, but it is quarter who I am, and it's quarter Why I made it. Twenty five years sets >> a milestone. Congratulations, by >> the way, twenty five years in any industry that techno technology industry. I was reading some reports the other day upwards of forty five percent contrition, which is higher than any other industry. What have been some of the secrets to your Obviously I'm imagining persistence, but twenty five years is a long time to stick with anything, but you clearly have a passion for this, but I'm sure it hasn't been easy. Give us a little bit of an understanding and maybe some of those more challenging times you encountered. And how did you just kind of with that internal rules also know I'm I like technology. This is what I wanted. >> So, you know, it's always tough being the only woman in a room that's happened the bulk of my career, although thankfully, not a tear I but it has happened across and actually was the only woman at one company, and I thought it was gonna be a great opportunity. And I love the technology that we were doing. And I was excited Teo to infrastructure in operations and support it. And it was really a bad experience. And it wasn't imagine purposeful, but it was not great. And I was there a very short period time when I realized it wasn't gonna work and I had to take a real hard look. Don't want to keep doing this for a living. I do. I don't want to give up technology. So the right thing was to give up that company, right? And the right thing was t make sure that I stayed and what I loved, but not in the wrong spot. So I think being stubborn and persistent. Not being willing to give up the stuff that I love because the environment wasn't right was a huge part of why I have made it this far. And my daughter is a computer science major, and so I really want for her not to have to go through those things apart. The reason I come here today, what I'm excited about W T two is I want to make sure she has a far easier time of it than I had growing up. >> So was your daughter always >> an interested Or did she? Is she kind of following in Mom's footsteps? She >> wasn't the beginning. Actually, she don't want anything to do with it. And my mom's a c P A. And I don't want to do anything to find >> a way. >> So maybe a cool and her uncle, but never the parent, >> exactly. But as she took coding classes, she actually did Girls who code the seven week immersion camp she found like me that she loves it. So I think she'd like to not compare it to Mom. She doesn't want to hear Mom wars, but she absolutely has that same passion. She she loves to code and see the output and see the changes it can make in her life and potentially others. >> So she'd underground. Currently she is. You should give you anything back on the diversity in her. Yes, is she >> does. And I wish I could give you something inspiring. But unfortunately, she it's for four girls to forty guys. >> Okay, so maybe she has that. Maybe it's a DNA thing where she has that some people might say Stubbornness bad. However, I think you're a great example of how that can be, you know, sort of flipped that coin and look at it is persistence. What keeps her saying, I don't care that I'm for forty? >> I'm not sure. I think e think it's similarly the same thing that it's she's passing around and also she's had everybody's in lovely to her. She's had no mistreatment, so she's definitely loving it, but does notice that she's one of, you know, four out of forty. So but would you >> would you advise? And I, I know not like to say the next generation like your daughter's generation, but it's It's the generation of US women who are in technology now with the attrition rates. If they're in a situation, how would you advise him to recognize the experience that you shared with us? That this is situational? This is an industry wide. I'm not going to make a generalization. What would your advice be to them in terms of making that decision to not not leave? >> So I would say, actually, a mentor of mine told me when I was years ago at a company says, Do you like the work or do you do not like the work? Do you like the people do not like the people. If you don't like the people, you need to go somewhere else. But if you like the war, if you don't like the work here in the wrong industry and I like the work and I always have So I would say if you'd like the work, find the right opportunity and see what change you, Khun, doing the company that you're at. If you're at a company and things aren't right, have you to talk to a man in your manager HR there's ways tto see if you could fix it and if you can't, it's okay. Go somewhere else and do what you love. >> I love that it is. Okay, So one of the things that I'd loved digging on as well as you had gone to Terry's a HR and said, I'm not going to be looking at any candidates until you actually did >> a previous companies. But that is my stance since then, >> you know, >> it's without a diverse school, >> okay? And so what is diverse mean to you? What do you say to them? I know you can find us. >> Yes, Well, I diverse. I don't I don't want to dictate it. I just don't wanna have to, you know, the team's all be the same person. I think Joy is talking up the keynote right now about how important it is that we be careful of bias and that we look at those things and that we are having the people who build the technology be well rounded because this technology that's built here in the Valley goes all over the world has to serve everyone, not just the folks who build it. So I think it's having that same mindset going into it, goingto hiring >> one of and that's so important. And there's also debated. Is it a pipeline problem? I just read Emily changed Look proto Pia and where she kind of documents where that pipeline problem was created? Yes, many, many, many decades ago. And a lot of people would say it's a pipeline problem. But the majorities, the underrepresented, which isn't just women and people of absolutely well who say it's not a piper and problem this. And even if we look at a I, there's so many exciting possibilities. All the autonomous vehicle weren't that tear eyes doing, for example, that will impact everybody and jurors facial recognition? You know, there's probably people in the baby boomer, a generation that have iPhones with facial recognition. But the things that joy wish areas about the bias Easter thes malls being trained on, really, it gives me goose bumps. Didn't mind blowing more. People need to understand. We need better data and more diverse data, not just that to train the models to recognize more agree, but there needs to be lots of different, uh, data sets. So this inclusiveness and I think of diversity, inclusion. One of the things that I thought of when Joy was talking about inclusivity is its inclusivity of different data sets and different technologies, so that ultimately going forward, we can start reducing these biases and this technology that is all for good. >> And I think one of things that we've done is, you know, for our company, we actually had on all hands doing unconscious bias training like we are absolutely committed to making sure that we're thinking about those things on the idea if it's pipeline or if it's or or if it's not, I think it's a combination because the fact is, my daughter is in a class with four girls in forty men, and that's not necessarily, you know, there's no judgment there, but that's the reality. So there's pipeline. But I also think we can demand is hiring managers to have a diverse pool come to us? University isn't just I speak to women because that's what you know. That's my story. But there's not. There's, You know, we had those other kinds of diversity inclusion, you know, we have our G d l G B T. Q plus energy starts a lot of letters to get out at once. We have our women than allies. Yogi Employee resource Scripts were supporting that. It's here, I But I think, you know, we see people out there in the world all trying toe push forward on this. I think if we come out of these conferences and take those actions, that's how overtime it's going to get better. So that's my personal thought. >> I love that last question. What are you looking forward to? Taking away from Debbie U T squared for inclusive innovators as the >> well being of a company doing innovation? I'm really curious to see what's presented today, and I know that we've heard studies that talk about women, run companies and with women on board that profitability and innovation go up. So I think that the more inclusive we are, the better. All of our technology that comes out of the Valley is going to be so I'm looking forward to the whatever thought leadership is here today. That's different from each year that there's something different here that I learned it's not the same thing was Pipelines four years ago, right? Like the last year. It was a lot about women's leadership, so I'm really excited to see what comes out today. >> Well, Jennifer, I thank you so much for sharing some of your time on the kid with me today. And I think a lot of people are going to be able to learn a lot from us. Well, we appreciate your time. Thank you. My pleasure. Lisa Martin on the ground with the Cube. Thanks. For what?

>> from Palo Alto, California It's the Cube covering the EM Where women transforming technology twenty nineteen. Brought to you by V. M. Where. >> Hi Lisa Martin with the Cube on the ground at the end. Where. Palo Alto, California For the fourth Annual Women Transforming Technology Even W squared. Excited to welcome back to the Cube. Kathy Chou, VP of R and D. Operations and central services at work. Cappy. It's a pleasure to have you back. It's one of you will be back. So you and I saw each other this morning. Big hug. This is one of my favorite events to be at, and I'm proud to be here with the cute because this this authentic community of women is unlike anything that I've really seen or felt in a long time. Fourth annual. I know it's grown over the last year. What do you What are some of your thoughts, even just walking in the doors this morning? Well, it's funny. It is the fourth annual and I I've been toe all four. The very first time I came, I was not a B M or employee, and I fell in love with the company. The campus because it was the very first time. And every single time I come to one of these events, I either meet someone or multiple people better fantastics or learn multiple things that will help me do what I need to do and I will tell you, and I'm not just saying cause you're here. But last year when I met you, I just felt like there was an instant spark. And like you say at these conferences, don't you feel it's safe? You can. You could be authentic. You could be who you want to be. You could be vulnerable, right? And as we can learn with each other, we can share what we need to work on. You move on and we can also Peter chests a little bit right for stuff that we've done well that sharing is so critical. Eye all the women that I've spoken to today we look at even our own career. Trajectories are looking at a lot of the statistics of the loan numbers that women technology where where is the attrition happening? What's happening in and grade school in middle school when girls, you know between seven and twelve years old, way have to help each other build up cos it's just and I think there's no better >> way than sharing stories and cheer point that means being vulnerable. I think vulnerability is one of the best price you can exhibit, period. But it used truly conceit and feel the impact Hearing. >> As you've said, you've seen that over the last four years that this is really an authentic community in every >> sense of the word. Absolutely. And, you know, you mentioned quite a few things that I'd like to talk about. So first, is these >> young. Let's start first with diversity. Okay, I know a lot of people do talk aboutthe. They think of gender diversity or ethnic diversity. Diversity of the capital. >> Dia's much broader, right? It's okay. Diversity of experience, education, you know, geography, seniority, right. There's all different types of diversity. But if we do hope, focus in a little bit on young girls. Right? Because you think about that. I was just in the I wish conference in Cork, Ireland. Stop back. Yeah. And what was amazing about that was so this is all of Court County. They had all of the what they called secondary school girls every single one of them for two days at this conference. But they got to listen to speakers from all over the world to give them that confidence to stay in, because statistics are when they're in primary school or middle school. Right? Girls say I want to be a computer scientist. I wantto do this techie thing. I'm gonna do Sam with them when they go to high school there, given all these messages like, you can't do it and you don't look like a computer scientist, right? And then all of a sudden it gets It becomes because in her head and it really does affect our confidence. And then, sad to say, years and years ago, when I graduated from college, there was only nine percent of the women were mechanical engineers. Sad to say today, that number is not challenged much. Do something just conferences like these that give us the courage to be better mentors and sponsors of those that will come after us. >> I agree. I think that it's and in some cases it seems like it's so simple where we make I don't think we're making this so hard, but I think that having the opportunity of a community to just have okay like minded people in terms of experiences that they shared well, how did you get through this barrier of, for example, you know, really kind of dissecting to your point diversity with a capital B. There's so many layers to that. What does that mean? How do we achieve it? I mean, if you look at a lot of the statistics companies that have you say females, uh, on the executive staff are like twenty seven percent more profitable. Yes, the amount of oven of reinvesting of income that women do back into the community. Their family's one of the things, Joy said this morning in her keynote joyful Fulham. We need him saying that, >> right? So is it looking at women and people of color as the underrepresented majority that that was absolutely spot on? I absolutely >> thought it was spot on this well, and you know, if you think about it, think about these experiences. You know again about diversity. There's a new dawn. It's a new phrase. But intersectionality is the word, which means, you know Okay, you're a woman. I'm a woman. I'm an Asian woman, But I'm also a woman that lived on the East Coast. I went to these sorts of schools. I had these types of experiences. So what it means is everyone bring something to the table. So if you really think about diversity now, we'LL hear this talk about inclusion. That's kind of the big word. And I've I've actually witnessed this myself on my own team because if you look at my direct staff on paper, when you look at them, they look very diverse. But actually diversity. That's like the tip of the iceberg. What you see is only the little piece when you bring down, get to those deeper layers. You realize, >> really how diverse team Miss Wright of spiritual >> diversity, experiential all of that and by including and created a inclusive environment were able to get the most out of diversity. And I think that's how you do it, because I thought about this. When you single out groups, you're not being inclusive, right? That's a good point. So I think the goal is to get what we can call the model. What we think is the majority, which is the minority to embrace the underrepresented majority and >> your perspective? How do you think V m? Where is doing on that? I was talking with Betsy said earlier, and some other folks and learned that the eggs I don't know how far down this goes, but at least execs are actually their bonuses are related to our tied to diversity and inclusion. That's a huge kind of bold statement that a company like the Mars making, not just to the tech industry, but every industry. Where do you think the emperor is on this journey of really identifying diversity and inclusion and actually starting to realise the positive impact? >> Yes. So first of all, I think you said something earlier. This is a It's an epidemic situation. OK, in that I do tell me, almost in every industry, there isthe right entertainment manufacturing, high tech, legal, professional, whatever way, there's an issue with diversity, and you're absolutely right. The peace and above our bonuses air tied to diversity, inclusion the awareness of the, um, where is second of them. The interesting thing is, there's no silver bullet. If it were that easy, we would've solved it. So what? It iss. It's one of those things where I say it takes a village and it's little things like talk about inclusion earlier, right? Hey, when you have a meeting, make sure everyone's voices voices are heard. Doesn't matter who it is. I don't care if it's a woman and under represent minority or white male. It doesn't matter. You shouldn't it? It shouldn't right. Everyone should be heard. And I was just giving a breakout talk about when you increase. Inclusion will drive more innovation. And that's my job as a leader of six hundred folks in an RD organization is to create that culture that allows people to have confidence, to take risks, to be vulnerable, authentic and to innovate right and to do new things. And if I can create that culture of inclusion, it will drive those business results. >> I couldn't agree more Tell me about like since we spoke last year. I love that driving inclusion to drive innovation. What are some of the things that you've actually seen as outcomes? Maybe just for your team as well as your own expertise as a manager? >> Yes. So I've been with him where for two and a half years, and when I first came Basically my team was a compilation of three separate teams, so each of them traditional silo new themselves in their own style but did not understand the power of the team across. So at that time, no one team was greater than one hundred people. Okay, let's say now imagine a mighty force of six hundred strong marching in the same direction, trying to do things together. One of the things that we're trying to do is start to build platforms across our organization. And what are the commonalities? That that's the difference is what commonalities across our teams so that we can drive that innovation much more effectively and efficiently. And so those are some of the things that we're doing have another fun story to tell me. Everything that I do to try to create an inclusive environment, just have opportunities for team members to meet each other. It's a simple assed. Hey, I don't know. Lisa. Lisa, what do you do? Oh, my gosh. I have a project that might need your help. I don't know how many times when we were working in the silos would enter calling someone outside our team to get the expert advice when it was on her own. And so we had one event when we had two people that sat next to each other. They didn't know each other at all. One needed some machine learning expertise. The other one was in machine learning enthusiast Fast. They came together. They have now built a patent pending piece of micro service called instead ML. That's so, uh, that's what happens when people when you're included >> and you think, Why is it so difficult? In some cases, technology is sort of sort of fuels that right because we get so used to being I could do everything from here >> on the phone from an airplane from the hotel from home, from or ever so we get more >> used to being less communicative. Absolutely right, Tio. Let's actually let's let's go back to the olden days where there were, You know, there was no device and phoniness and actually have a conversation because to your point, suddenly are uncovering. Oh my gosh. All of these skill sets are here. What if we did nothing for years? >> You're speaking my language. Eso You're absolutely right. But there's this. They used to be this rule that's a new one you wanted to communicate to someone. You have to tell them something seven times, >> right, because they're busy doing other times on the age of social media, they say. Now it's eleven times. Oh, great. And how I got exactly. So how often have you seen people who are sitting like this and they're >> communicating with each other? Be attacks and they're sitting right here. Why, it's >> important to go back old school. By the way, I think I'm old school. >> Whenever I want to pick up the phone, talk to my kids. It's on the phone. I don't care if they're, uh, ready for me to talk >> to her, and I just called them. It's because when you're innovating, it's not just the mind, it's the heart. >> And when you catch those human relationships, right is what makes the innovation stick. It makes you want to do more. It makes you want to achieve greater heights. Then you would have cause you're invested. You see, when it's an academic exercise, it's like check the box. But when you're invested in your hearts and you I feel like I can't let Lisa down, believe me, you're going to get more in depth and more advanced innovation. >> So with that and kind of the empathy approach in love to get your perspectives on a I, we talk about it all the time at every event that we go to on the Cube globally. And there's different schools of thought. Aye, aye is fantastic. It's phenomenal. It's it's becoming new standard, even a baby boomers known to some degree what it is. Yes, then there's the It's taking jobs away yet, But he's going to create new jobs. Yes, and there's the whole ethics behind this morning. Joy really kind of showed us a lot of the models and facial recognition at big companies that are better being built with bias. But one of the things I think that I hear resoundingly at events is it's going to be a combination of humans and machines. Yes, because machines can learn a lot. But it's that heart that you just mentioned in that empathy that comes from the human. So do you see those two as essential forces coming together is a. I continues to grow and take over the world. >> It's essential. Like you say. Technology is very How do we sit? Neutral. Okay, If you put it in front of a bad actor, it becomes bad. If you put it in front of a good actor, it becomes good. Okay, so technology is neutral, right? So now the goal is how do >> we ensure that we Khun tamp down the bad actors, people who want to use it for bad? And >> by the way, I am a fundamental believer that there are some jobs that should be automated. >> I mean, come on, some of the And by the way, things >> in the health industry. When you have big data and you've got a lot of things, you have to process a lot of information so we could be more accurate on things. Um, there other examples of if it's not in check, it can go right, right. Where will Over reliance on machines. Unfortunately, the seven. Thirty seven max eight is an example of it being too smart, right, and that >> you needed the human to actually adjust. So now I think also kind of combining a lot of the topics that we talked about. We need to train our children to understand that this technology is here to stay and with each and every one of them, how can they take that wonderful technology and use it for good? And I think that's the whole that's peace around inclusion. That's the peace around, building confidence in these young people and being examples. And so we need more people like joy out there so that she can. She has now raised this flag up saying, Hey, did you realize this >> happen? We need more young people. By the way, she's very young person. I'm >> totally impressed with what she's been able to do in here great for years, very, very inspiring. But if we all did a >> little bit of what joy did, we could change the world. >> Absolutely. The accountability factor and the social responsibility is so important. I was impressed with her on many levels, but one of them was the impact that she's already making with with Microsoft, IBM, uh, and actually starting to impact facial recognition a. I based on the research that she's done and show them Hey, you've got some problems here. So she's She's kind of at that intersection of your point neutral technology, good actors, bad actors. Maybe it's not good or bad. It's just Well, this is the data that we have. And it's training the models to do this. Oh, the but the accountability in the responsibility that it appears that a Microsoft and IBM face plus plus and even Amazon that she said, Hey, guys, look at how far off your models are. It sounds like these companies are actually starting to take some accountability. Civility for >> that? Yes, well, I think she proved it in our talk because last year, right, the numbers were in the eighty eighty percent tiles, and now they're up to ninety five. So you know, she's saying, by kind >> of being that lightning rod on this issue, one person could make this amount of change. Imagine if all was just a fraction of what she did, right? I mean, I think, and again, I feel very because I'm older and I have my own children just inspiring this generation, too. We could build up more joys in this world. >> So you have four boys. Yes. How are you inspiring them to finally become good humans, but also to look at the technology, the opportunities that it creates to be inclusive why it's important that some of the lessons that even parted on your boys >> Yes, first of all, I've one thing that's really >> important to me is I want them to accept whoever their partner will be for whatever they want to do. So if their partner wants to stay home and then you support them, if they want to work and go, do you support them? But just be supportive, be that partner, whatever that is, that's really important. >> The other thing is, I think just >> my husband and I are excellent examples of how that isthe, because he's an orthodontist and I've got a busy high tech job. I'm traveling a lot. My husband does more than his fair share of the household duties, and we split things pretty evenly. So I hope they've seen witness. It's not just talk, it's action and that this can actually work. And fortunately, I'm >> boys are a little older now because if you begin in the beginning, I thought, Oh, working. I don't >> know how these boys are going to turn out right, but three of them are college age and older, and they really turned into some fantastic children. The youngest is on his path as well as a junior in high school. And, you know, and I also see the type of friends that they make and how they treat women and other people that are different from them, and it just makes me very proud. >> Think the world needs more? Kathy Chow's I really dio Are you going off to see Ashley Judd? Her? What? Some of the things that you're looking >> forward to hearing her talking. Well, it's funny. I just came from a VP session. She is I again. You see someone right on the screen and you see him as an actor and you heard about Time's up and her speech and that sort of thing. But way had, but how were we just answered? Questions. She is so thoughtful, so connected, so well spoken communicates in a way that really touches you. She's another one of those lightning rides. I think w t, too, didn't excellent job of getting English speakers this year. Uh, and it's very different from joy. It's much more from a from her view, in her mind went in arts, and Joyce was much more from a technical aspect. But messages are the same, right? It's to be inclusive, understanding, embrace diversity and be authentic. You >> inclusive animators. Kathy is so great to have you back on the Cube. And Charlie, I know we could keep chatting, but we thank you so much of your time. We can't wait for next year. Wait. Excellent. Thank you for the Cuban Lisa Martin. You're >> watching the show from women Transforming Technology, fourth annual somewhere. Thanks for watching.

>> From Palo Alto, California, it's theCUBE. Covering VMware Women Transforming Technology 2019. Brought to you by VMware. >> Hi, Lisa Martin on the ground with theCUBE at the fourth annual Women Transforming Technology event VMware, WT squared, one of my favorite events and I'm joined by two PhDs, both from, I'm going to say this one time, the Stanford VMware Women's Leadership Innovation Lab, we've got Shannon Gilmartin, senior research scholar. Hi, Shannon. >> Hi, great to be here. >> And we've got, great to have you, we've got Caroline Simard, managing director of the lab. Ladies, thank you so much for joining. >> Thank you, it's a pleasure to be here. >> So this event, we were talking about before we started, that you, walk into the keynote, opening keynote which in and of itself was electric but the energy that comes into the room with, VMware was telling me a little while ago, about 1500 live attendees. >> Incredible. >> Not even including those that were watching the livestream. The energy comes into the room and then, of course, this morning with Joy, I'm going to try to say her name, Buolamwini. The poet of code, the MIT researcher who started really, sharing with us the significant biases in AI. The energy, if it could even be down that more, I can't even imagine it, so. I can imagine the panel that you guys were on this morning was quite charged. The panel title was, I found interesting, Inclusive Innovators Designing For Change. So Caroline, talk to us about designing for change. You look through a design lens, what does that mean? >> Yeah, so I think what, to frame the morning, and then Shannon was the moderator, so I want, she picked the topic of design. But I think what Joy really showed is the power that is possible to realize when women and women of color and people from different dimensions of identity are included in creating technology and how much better technology will be for society, right? If all voices are included, and I would also say that some of her comments also make it clear that it is fundamentally irresponsible not to have diversity at the table in designing the technology of tomorrow. The consequences on different kinds of people and different populations are significant. And so this is why Shannon really picked this idea of, as engineers and designers and creators of this technology, how do you keep in mind the responsibility that you have? >> So yeah, talk to us more about the design and why that is so critical. >> And the way we positioned it for our panelists, it was titled Inclusive Innovators Designing For Change, and we were going to explore how meaningful change towards greater diversity and equity is realized in engineering cultures. And in the very technology that's being created. More specifically though, how do individuals and communities of people design for change in their technical environments? Even when this environment may not be initially very receptive to new ways of interacting. To new ways of thinking, to new ways of achieving. And so the whole panel was premised on this idea of people are designers of change in their environments. How does that happen? How do people interface with barriers to those design processes? And what is advice for the younger generation as they look ahead to their pathways as designers for change? >> Yeah, 'cause change in any context of life is hard. >> Yep. >> Yes. >> Right, it's an uphill battle. But designing for that change, I'm curious what some of the commentary was from the panelists about, when you're encountering, whether it's a company or a leadership group within a company that, to your point, isn't receptive, what were some of the comments or stories of how that was changed over time to become receptive and understand, the massive potential that that change can have? I mean we look at numbers like, companies with women on the leadership communities are far more profitable, so what were some of those, from, I don't get it, to, oh my gosh, why aren't we doing sooner? >> And we have this amazing range of perspectives represented on the panel, so we had a VMware CTO, chief technology officer Ray O'Farrell. And he was really talking about from a leader perspective, a key idea here when there are barriers and blocks and inertia, is to open things up and really start listening. And this is a skill and a talent and a group practice that is so little done, so infrequently done. So poorly done, sometimes. But really key in the face of those barriers is to actually say, instead of shutting down, open up and start listening to what's happening. Another one of our panelists, Susan Fowler who is the Time Magazine Person of the Year as one of the silence breakers in 2017, she was really talking about how, expect the steps, you're going to need to go through a lot of steps to make your voice heard. And ultimately, for Susan, she made the decision to go public with what she had encountered and was facing and grappling with and struggling, as were many of her colleagues. But she was really talking about the step by step process that's involved in a large organization, when you're hitting blocks, you just got to keep on fighting that good fight, and you also need to be doing your very best work at the same time, it's a high pressure situation. >> Yeah, absolutely. >> So. >> Absolutely, we also heard from Lisa Gelobter who is the CEO of tEQuitable, an organization that's creating a safe place for change agents to share their stories when they're encountering these blocks and this kind of unfair treatment. And she talked about, also, the need to do your best work but also the critical importance of community in being more resilient as you're trying drive change in your environment, right? And this is the kind of community that is being built today with this event, right? It's really paying attention especially for her, as a black woman engineer, being the only one constantly at the table fighting for change has been something that she has realized she needs to pay a lot of attention to so that she can be much more resilient as a leader for longterm change. Another topic that I think, in terms of generating change, that really came through both in the panel and during this morning's keynote, and that we pay a lot of attention to at the lab, is to really highlight bias. Is to really diagnose what is really happening in organizations? Or in AI, as we heard from Joy this morning. So a lot of people genuinely aspire to treat others fairly, right? But they don't realize that their workplaces are so far from being a meritocracy, that there's these structural inequalities that are really embedded in all of the ways that people are working. And so when you're able to show people exactly how it shows up in their company, right? The promotion rates for women of color for example, being lower than for other people, the exact points of data that they need to see, that they're not treating people the same way and creating the same kind of pathways for impact for different kinds of people, then that has a lot of power to drive change because a lot of people, then, will be very motivated to say, okay, I see this is happening in my org every day. Now I can design a different approach, right? How do I redesign the way I'm working today? In my units. >> And take action. >> And take action. >> 'Cause you actually have the data, it's such a dichotomy at times, that we have, we're surrounded by data especially in Silicon Valley. But one of the things that shocked me, what Joy showed this morning is, when she put on blast, IBM, Microsoft, and what was it, Face++, about looking at all of the built in biases to facial recognition. But, one of the things that really also, I thought, was interesting, was that, she went and showed this to these companies, who responded, and those numbers are actually improving. And then when she said, hey Amazon, so, the fact that even that one person is able to show, look at some of the massive problems that you're training these models to have, they need to be able to see that. So the highlight, I think, the highlight the bias, and the communicate, communicate, communicate and listen, are three critical elements to any place being successful. >> Exactly. >> Exactly. One additional part of both Joy's presentation and Lisa's comments too, really spoke to action needing to take an intersectional approach. So Joy's data breaks it down by race and gender and all of a sudden, you see completely different trends. Lisa spoke to that as well in her comments. Key to this designing for change process is really wearing the hat of someone who is looking through the world with an intersectional lens. And understanding how different axes operate together uniquely for different groups. And that's when you see these biases being highlighted really in full force, in full relief. So both of these points and these presentations really brought that up. >> Yeah and the intersectionality that Joy talked about was even evident and you could parallel it to, why it was important to look at all these different sources of facial recognition data, how disparate some of them were. >> Right, right. >> I know. >> Without that lens you couldn't see all of that variation even across the different providers. >> Exactly. >> Yeah, and she talked, too, about how everything is classified in a binary way, right? In terms of gender identity, and then where data doesn't even see people who are Non-Binary. >> Exactly. >> So it's like, >> That's still a huge omission >> again, exactly. That we have a lot more work to do to have data that truly captures all the dimensions we're interested in. >> It does, it does. Long way to go, but the fact that it's being highlighted and opportunities like, not just what VMware does but the lab as well. So let's talk a little bit about the lab. It kind of got its start in 2013 when then Stanford president Doctor John Hennessy, provided some funding. I had the opportunity to interview him last week, lovely man. Last year VMware did a big endowment of about 15 million. What's going on, Caroline, we'll start with you, what's going on at the lab? What are you guys studying now? What are some of the breakthroughs that have been uncovered in the last 12 months? >> Yeah, so a big part of our lab's work and since we began this work, has been to really bridge the gap between research and practice, right? And so a lot of why there's little progress being made is because you have a lot of research happening in the academy, in the ivory tower, if you will. And then you have a lot of innovative practices being tested but without necessarily the research foundation and the research frameworks to truly evaluate it. And so, our work has been to really bridge those two things together. And explore those boundaries so we can have more innovative research but also more evidence based practices come in, right? And since the VMware endowment we've been able to, really grow in our aspirations in the kind of data, in the kind of research questions that we can really ask. One of them is this focus on the more intersectional, longterm study of really documenting the experience of women of color. And really understanding the nature of their career pathways across racial dimensions, right? And really highlighting a lot more of, qualitative deep insight, generate their stories, right? And really centering their experience. The other one is, investing in large scale datasets that capture gender, race, age, and other identity dimensions and look at their longterm career trajectories. This is actually work that Shannon is leading. So we have an exciting dataset where we have people through five years and we see what happens to them, who gets promoted? Who doesn't? Who gets top talent designation, who gets a salary increase? Who, and then we're excitingly, looking at social network data, so who's meeting with who? And then what kind of connections do you need to be able to advance in your career? And are there some systematic inequalities there, right? And a big part of our work then is to design these interventions where we work with companies to test what we call a small wins approach. It always starts with diagnosis, here's what's going on in your very specific workplace and your culture. And then we co-design with leaders and managers. It doesn't work for us or HR or anybody to say, go do this, or you should do this. It's really about really engaging managers who want to do better in coming up with the design fix, if you will, that they can come up with. Informed by our research, so it's a co-design process. And then we roll it out and we test the outcomes pre and post, so. We're doing a lot more work now to disseminate what we're learning through these interventions so that other organizations can implement this very similar approach. >> First I love that it's called an intervention. 'Cause I think that's incredibly appropriate. (Shannon and Caroline laughing) Second, are you seeing an uptick in the last year of companies, obviously VMware and Dell being two great companies that are very focused on, not just women in technology, but I loved how Joy said today, it's women and people of color are the underrepresented majority. Are you seeing an uptick in companies willing to, accept the intervention and collaborate with you to really design from within for that change? >> Yes absolutely. And I would say that in this industry people are comfortable with piloting things and doing a little R and D experiment, right? So it's also a culturally appropriate way of thinking, okay, what if we try this, and see what happens? And so I see a lot of energy from organizations and based on what you were talking about, it's also, I think companies are aware that it's, the overlapping dimensions of identity increasingly aware, are within their own walls, but then, in their consumer base, right? So how is their product affecting different kinds of people? Are their customers experiencing bias from the very platforms that they build? And so I think that's also a very powerful, entryway into this intersectional conversation because, the product is, so foundational to the business of the company. >> It is, and especially event after event that we cover on theCUBE, customer experience in any industry, is critical because as consumers of whatever it is, we have so much choice. Shannon last question for you. One of the things that always interests me is the attrition rate being so high in technology. I'm curious what you guys are finding in the lab with, mentioning following women on maybe their first five years. Are you seeing any glaringly obvious, challenges that are driving that attrition? Is it, it's got to be more than the motherhood penalty. >> Right, right. We're looking at a range of, what we call pathway outcomes really for young people just starting out in their very first, second jobs, where they are several years later, we're looking at odds of promotion, odds of leaving the company, odds of moving and making a lateral move into some other kind of line of business, maybe taking them out of, let's say, a technical role and moving them into a non technical role. Each and every one of those critical moments is worthy of deeper study for us. And what we're doing, really, is taking this intersectional lens and understanding how do those different moments vary for different groups of women? It's not enough just to say, all women have some x percentage of an attrition rate. We're trying to understand how attrition really varies by sub-groups of women. And how that varies over time with what interactions that precede it and then follow. One of the themes that we've really been looking at in, for instance, attrition stories, is the assignment. Which projects, what kinds of assignments are people getting in their first few years on the job? How are some of those make or break? With what net consequence for women, men, from different racial ethnic backgrounds, different ages, different countries? And understanding, really, the role of those assignments in someone's longer term career pathway, just how important they are. And what kinds of interventions we can hand design to really elevate access to the best assignments for everyone, basically. >> Gosh, you guys, this is so fascinating and so inspiring what you're doing at the lab I wish we had more time, but you'll have to come back next year! >> Exactly. >> Absolutely we will thank you so much for having us. >> Thank you so much, Lisa. >> Thank you. >> Thank you. >> Thank you so much. For theCUBE I'm Lisa Martin, on the ground at WT squared, thanks for watching. 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Jeff Rick here at the cube we're at the LA Convention Center at e3 is our first time coming to this convention is sixty eight thousand people and every single hall and outside inside hotels it's pretty crazy great to see you thank you so much for having me [Music] years ago it was really much more about a a trade show so that you know the big people who are gonna buy the disc could actually come to eat right right check out our games and place their disorders and now it's really much more of a consumer phenomenon right let's have a competition let a brand's find outdo each other but more of let's make this more about the games than the booth babes and those things it's funny everything changed in dubbings chains right people are always super excited there's always gamers that want to see the newest stuff that hasn't changed at all but just the sheer technology differences so we're doing this series as part of the Western Digital data makes possible and data is such a big part of what you guys do you can really start to understand who your players are and so if you're gonna do an upsell offer you know you can understand like oh this person has actually already purchased this type of material so I'm gonna give them this type of upsell versus this type of upsell or you know I see all my players are really struggling on level three and no one's making it through what's wrong with level three they're spending too much time in an area not knowing what they're doing will go OK right we need to change that we need to signpost back to serenity we need to turn around say how can we make it clearer to the players they know what they do but also keep the reward so that they feel like they've achieved it they feel like they've figured it out right we've placed people in front of the game in very early stages to receive him alcohol ideas of working and then based on that we then look at video footage interviews and all that stuff some kind of that feedback see into the design loop process previously years ago to get some of these insights you would have had to be one of the largest game company from them and now with you know the democratization of these different game engines and then the democratization of this type of like to lean and online services that are available it really creates an amazing opportunity for all developers everywhere we see these tremendous boots that are here fabulous graphics VR coming down the pike CPU and graphical chips are all over the place so basically power an internet and 5 G's coming mobility is gonna be way way faster the horsepower that you need to run this kind of game is actually pretty staggering we can compute a lot of stuff on the GPU the CPUs tons and tons of the objects get physics constraints and things that are costly for computation cycles and then there's like memory issues you know we have streaming that we have to kind of get better at these worlds are very large and so to store the things that you're gonna see and do takes a lot of actual you know harddrive space and the speed at which we can load and unload things is that critical factor in terms of you know unlocking the freedom of your experience right we really have a PC development technology that is easy to port the Xbox and PlayStation so we have a private cloud in Europe and a private cloud and we run this on your own inference we're on our totally on our own infrastructure and it has its advantages because we're completely in control but I think now just don't need to make the big investment in hardware upfront you can solve all the problems in a cloud solution right now and then deploy either privately or publicly it's much more flexible now than it was we know from our creator standpoint the biggest thing that they complain about is hey I want to grow right like I've been streaming for X amount of years I'm creating content how do I grow at twitch we have like the broadest means of ways to monetize but also the lowest barrier of entry to take advantage of them and our subscribers by the way they know that they're supporting you and proud to do so Joy's supporting the kind of courage do they know if they didn't support you you might not be streaming they love being playing a role in keeping their favorite creators around the content that you see here today much more diverse and much broader you know we still have a long way to go as an industry but it's very different than my first 17 years ago used to be gamers played games because of the technology and now they play games because of the games right because no one cares about the technology right because you could do almost anything on any device now and now so it's really important to us as game developers to hide the technology from players and just give them a great expression and every year you know new stuff rolls out slightly newer Xbox slightly newer PlayStation better pcs so we just stay up-to-date with the drivers and make sure that we support whatever crazy hardware is coming out right and it all works great you're watching the cube from e3 I like convention center thanks for watching [Music]

>> Announcer: From the Corinium Chief Analytics Officer Conference, Spring, San Francisco, its theCUBE. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Corinium Chief Analytics Officer event in San Francisco, Spring, 2018. About 100 people, predominantly practitioners, which is a pretty unique event. Not a lot of vendors, a couple of them around, but really a lot of people that are out in the wild doing this work. We're really excited to have a return guest. We last saw him at Spark Summit East 2017. Can you believe I keep all these shows straight? I do not. Alfred Essa, he is the VP, Analytics and R&D at McGraw-Hill Education. Alfred, great to see you again. >> Great being here, thank you. >> Absolutely, so last time we were talking it was Spark Summit, it was all about data in motion and data on the fly, and real-time analytics. You talked a lot about trying to apply these types of new-edge technologies and cutting-edge things to actually education. What a concept, to use artificial intelligence, a machine learning for people learning. Give us a quick update on that journey, how's it been progressing? >> Yeah, the journey progresses. We recently have a new CEO come on board, started two weeks ago. Nana Banerjee, very interesting background. PhD in mathematics and his area of expertise is Data Analytics. It just confirms the direction of McGraw-Hill Education that our future is deeply embedded in data and analytics. >> Right. It's funny, there's a often quoted kind of fact that if somebody came from a time machine from, let's just pick 1849, here in San Francisco, everything would look different except for Market Street and the schools. The way we get around is different. >> Right. >> The things we do to earn a living are different. The way we get around is different, but the schools are just slow to change. Education, ironically, has been slow to adopt new technology. You guys are trying to really change that paradigm and bring the best and latest in cutting edge to help people learn better. Why do you think it's taken education so long and must just see nothing but opportunity ahead for you. >> Yeah, I think the... It was sort of a paradox in the 70s and 80s when it came to IT. I think we have something similar going on. Economists noticed that we were investing lots and lots of money, billions of dollars, in information technology, but there were no productivity gains. So this was somewhat of a paradox. When, and why are we not seeing productivity gains based on those investments? It turned out that the productivity gains did appear and trail, and it was because just investment in technology in itself is not sufficient. You have to also have business process transformation. >> Jeff Frick: Right. >> So I think what we're seeing is, we are at that cusp where people recognize that technology can make a difference, but it's not technology alone. Faculty have to teach differently, students have to understand what they need to do. It's a similar business transformation in education that I think we're starting to see now occur. >> Yeah it's great, 'cause I think the old way is clearly not the way for the way forward. That's, I think, pretty clear. Let's dig into some of these topics, 'cause you're a super smart guy. One thing's talk about is this algorithmic transparency. A lot of stuff in the news going on, of course we have all the stuff with self-driving cars where there's these black box machine learning algorithms, and artificial intelligence, or augmented intelligence, bunch of stuff goes in and out pops either a chihuahua or a blueberry muffin. Sometimes it's hard to tell the difference. Really, it's important to open up the black box. To open up so you can at least explain to some level of, what was the method that took these inputs and derived this outpout. People don't necessarily want to open up the black box, so kind of what is the state that you're seeing? >> Yeah, so I think this is an area where not only is it necessary that we have algorithmic transparency, but I think those companies and organizations that are transparent, I think that will become a competitive advantage. That's how we view algorithms. Specifically, I think in the world of machine learning and artificial intelligence, there's skepticism, and that skepticism is justified. What are these machines? They're making decisions, making judgments. Just because it's a machine, doesn't mean it can't be biased. We know it can be. >> Right, right. >> I think there are techniques. For example, in the case of machine learning, what the machines learns, it learns the algorithm, and those rules are embedded in parameters. I sort of think of it as gears in the black box, or in the box. >> Jeff Frick: Right. >> What we should be able to do is allow our customers, academic researchers, users, to understand at whatever level they need to understand and want to understand >> Right. >> What the gears do and how they work. >> Jeff Frick: Right. >> Fundamental, I think for us, is we believe that the smarter our customers are and the smarter our users are, and one of the ways in which they can become smarter is understanding how these algorithms work. >> Jeff Frick: Right. >> We think that that will allow us to gain a greater market share. So what we see is that our customers are becoming smarter. They're asking more questions and I think this is just the beginning. >> Jeff Frick: Right. >> We definitely see this as an area that we want to distinguish ourselves. >> So how do you draw lines, right? Because there's a lot of big science underneath those algorithms. To different degrees, some of it might be relatively easy to explain as a simple formula, other stuff maybe is going into some crazy, statistical process that most layman, or business, or stakeholders may or may not understand. Is there a way you slice it? Is there kind of wars of magnitude in how much you expose, and the way you expose within that box? >> Yeah, I think there is a tension. The tension traditionally, I think organizations think of algorithms like they think of everything else, as intellectual property. We want to lock down our intellectual property, we don't want to expose that to our competitors. I think... I think that's... We do need to have intellectual property, however, I think many organizations get locked into a mental model, which I don't think is just the right one. I think we can, and we want our customers to understand how our algorithm works. We also collaborate quite a bit with academic researchers. We want validation from the academic research community that yeah, the stuff that you're building is in fact based on learning science. That it has warrant. That when you make claims that it works, yes, we can validate that. Now, where I think... Based on the research that we do, things that we publish, our collaboration with researchers, we are exposing and letting the world know how we do things. At the same time, it's very, very difficult to build an engineer, an architect, scalable solutions that implement those algorithms for millions of users. That's not trivial. >> Right, right, right. >> Even if we give away quite a bit of our secret sauce, it's not easy to implement that. >> Jeff Frick: Right. >> At the same time, I believe and we believe, that it's good to be chased by our competition. We're just going to go faster. Being more open also creates excitement and an ecosystem around our products and solutions, and it just makes us go faster. >> Right, which gives to another transition point, which would you talk about kind of the old mental model of closed IP systems, and we're seeing that just get crushed with open source. Not only open source movements around specific applications, and like, we saw you at Spark Summit, which is an open source project. Even within what you would think for sure has got to be core IP, like Facebook opening up their hardware spec for their data centers, again. I think what's interesting, 'cause you said the mental model. I love that because the ethos of open source, by rule, is that all the smartest people are not inside your four walls. >> Exactly. >> There's more of them outside the four walls regardless of how big your four walls are, so it's more of a significant mental shift to embrace, adopt, and engage that community from a much bigger accumulative brain power than trying to just trying to hire the smartest, and keep it all inside. How is that impacting your world, how's that impacting education, how can you bring that power to bear within your products? >> Yeah, I think... You were in effect quoting, I think it was Bill Joy saying, one of the founders of Sun Microsystems, they're always, you have smart people in your organization, there are always more smarter people outside your organization, right? How can we entice, lure, and collaborate with the best and the brightest? One of the ways we're doing that is around analytics, and data, and learning science. We've put together a advisory board of learning science researchers. These are the best and brightest learning science researcher, data scientists, learning scientists, they're on our advisory board and they help and set, give us guidance on our research portfolio. That research portfolio is, it's not blue sky research, we're on Google and Facebook, but it's very much applied research. We try to take the no-knowns in learning science and we go through a very quick iterative, innovative pipeline where we do research, move a subset of those to product validation, and then another subset of that to product development. This is under the guidance, and advice, and collaboration with the academic research community. >> Right, right. You guys are at an interesting spot, because people learn one way, and you've mentioned a couple times this interview, using good learning science is the way that people learn. Machines learn a completely different way because of the way they're built and what they do well, and what they don't do so well. Again, I joked before about the chihuahua and the blueberry muffin, which is still one of my favorite pictures, if you haven't seen it, go find it on the internet. You'll laugh and smile I promise. You guys are really trying to bring together the latter to really help the former. Where do those things intersect, where do they clash, how do you meld those two methodologies together? >> Yeah, it's a very interesting question. I think where they do overlap quite a bit is... in many ways machines learn the way we learn. What do I mean by that? Machine learning and deep learning, the way machines learn is... By making errors. There's something, a technical concept in machine learning called a loss function, or a cost function. It's basically the difference between your predicted output and ground truth, and then there's some sort of optimizer that says "Okay, you didn't quite get it right. "Try again." Make this adjustment. >> Get a little closer. >> That's how machines learn, they're making lots and lots of errors, and there's something behind the scenes called the optimizer, which is giving the machine feedback. That's how humans learn. It's by making errors and getting lots and lots of feedback. That's one of the things that's been absent in traditional schooling. You have a lecture mode, and then a test. >> Jeff Frick: Right. >> So what we're trying to do is incorporate what's called formative assessment, this is just feedback. Make errors, practice. You're not going to learn something, especially something that's complicated, the first time. You need to practice, practice, practice. Need lots and lots of feedback. That's very much how we learn and how machines learn. Now, the differences are, technologically and state of knowledge, machines can now do many things really well but there's still some things and many things, that humans are really good at. What we're trying to do is not have machines replace humans, but have augmented intelligence. Unify things that machines can do really well, bring that to bear in the case of learning, also insights that we provide. Instructors, advisors. I think this is the great promise now of combining the best of machine intelligence and human intelligence. >> Right, which is great. We had Gary Kasparov on and it comes up time and time again. The machine is not better than a person, but a machine and a person together are better than a person or a machine to really add that context. >> Yeah, and that dynamics of, how do you set up the context so that both are working in tandem in the combination. >> Right, right. Alright Alfred, I think we'll leave it there 'cause I think there's not a better lesson that we could extract from our time together. I thank you for taking a few minutes out of your day, and great to catch up again. >> Thank you very much. >> Alright, he's Alfred, I'm Jeff. You're watching theCUBE from the Corinium Chief Analytics Officer event in downtown San Francisco. Thanks for watching. (energetic music)