(gentle upbeat music) >> Hello, everyone, welcome to theCUBE's coverage of International Women's Day. I'm John Furrier host here in Palo Alto, California. theCUBE's second year covering International Women's Day. It's been a great celebration of all the smart leaders in the world who are making a difference from all kinds of backgrounds, from technology to business and everything in between. Today we've got a great guest, Dominique Bastos, who's the senior Vice President of Cloud at Persistent Systems, formerly with AWS. That's where we first met at re:Invent. Dominique, great to have you on the program here for International Women's Day. Thanks for coming on. >> Thank you John, for having me back on theCUBE. This is an honor, especially given the theme. >> Well, I'm excited to have you on, I consider you one of those typecast personas where you've kind of done a lot of things. You're powerful, you've got great business acumen you're technical, and we're in a world where, you know the world's coming completely digital and 50% of the world is women, 51%, some say. So you got mostly male dominated industry and you have a dual engineering background and that's super impressive as well. Again, technical world, male dominated you're in there in the mix. What inspires you to get these engineering degrees? >> I think even it was more so shifted towards males. When I had the inspiration to go to engineering school I was accused as a young girl of being a tomboy and fiddling around with all my brother's toys versus focusing on my dolls and other kind of stereotypical toys that you would give a girl. I really had a curiosity for building, a curiosity for just breaking things apart and putting them back together. I was very lucky in that my I guess you call it primary school, maybe middle school, had a program for, it was like electronics, that was the class electronics. So building circuit boards and things like that. And I really enjoyed that aspect of building. I think it was more actually going into engineering school. Picking that as a discipline was a little bit, my mom's reaction to when I announced that I wanted to do engineering which was, "No, that's for boys." >> Really. >> And that really, you know, I think she, it came from a good place in trying to protect me from what she has experienced herself in terms of how women are received in those spaces. So I kind of shrugged it off and thought "Okay, well I'm definitely now going to do this." >> (laughs) If I was told not to, you're going to do it. >> I was told not to, that's all I needed to hear. And also, I think my passion was to design cars and I figured if I enroll in an industrial engineering program I could focus on ergonomic design and ultimately, you know have a career doing something that I'm passionate about. So yeah, so my inspiration was kind of a little bit of don't do this, a lot of curiosity. I'm also a very analytical person. I've been, and I don't know what the science is around left right brain to be honest, but been told that I'm a very much a logical person versus a feeler. So I don't know if that's good or bad. >> Straight shooter. What were your engineering degrees if you don't mind sharing? >> So I did industrial engineering and so I did a dual degree, industrial engineering and robotics. At the time it was like a manufacturing robotics program. It was very, very cool because we got to, I mean now looking back, the evolution of robotics is just insane. But you, you know, programmed a robotic arm to pick things up. I actually crashed the Civil Engineering School's Concrete Canoe Building Competition where you literally have to design a concrete canoe and do all the load testing and the strength testing of the materials and basically then, you know you go against other universities to race the canoe in a body of water. We did that at, in Alabama and in Georgia. So I was lucky to experience that two times. It was a lot of fun. >> But you knew, so you knew, deep down, you were technical you had a nerd vibe you were geeking out on math, tech, robotics. What happened next? I mean, what were some of the challenges you faced? How did you progress forward? Did you have any blockers and roadblocks in front of you and how did you handle those? >> Yeah, I mean I had, I had a very eye-opening experience with, in my freshman year of engineering school. I kind of went in gung-ho with zero hesitation, all the confidence in the world, 'cause I was always a very big nerd academically, I hate admitting this but myself and somebody else got most intellectual, voted by the students in high school. It's like, you don't want to be voted most intellectual when you're in high school. >> Now it's a big deal. (laughs) >> Yeah, you want to be voted like popular or anything like that? No, I was a nerd, but in engineering school, it's a, it was very humbling. That whole confidence that I had. I experienced prof, ooh, I don't want to name the school. Everybody can google it though, but, so anyway so I had experience with some professors that actually looked at me and said, "You're in the wrong program. This is difficult." I, and I think I've shared this before in other forums where, you know, my thermodynamic teacher basically told me "Cheerleading's down the hall," and it it was a very shocking thing to hear because it really made me wonder like, what am I up against here? Is this what it's going to be like going forward? And I decided not to pay attention to that. I think at the moment when you hear something like that you just, you absorb it and you also don't know how to react. And I decided immediately to just walk right past him and sit down front center in the class. In my head I was cursing him, of course, 'cause I mean, let's be real. And I was like, I'm going to show this bleep bleep. And proceeded to basically set the curve class crushed it and was back to be the teacher's assistant. So I think that was one. >> But you became his teacher assistant after, or another one? >> Yeah, I gave him a mini speech. I said, do not do this. You, you could, you could have broken me and if you would've done this to somebody who wasn't as steadfast in her goals or whatever, I was really focused like I'm doing this, I would've backed out potentially and said, you know this isn't something I want to experience on the daily. So I think that was actually a good experience because it gave me an opportunity to understand what I was up against but also double down in how I was going to deal with it. >> Nice to slay the misogynistic teachers who typecast people. Now you had a very technical career but also you had a great career at AWS on the business side you've handled 'em all of the big accounts, I won't say the names, but like we're talking about monster accounts, sales and now basically it's not really selling, you're managing a big account, it's like a big business. It's a business development thing. Technical to business transition, how do you handle that? Was that something you were natural for? Obviously you, you stared down the naysayers out of the gate in college and then in business, did that continue and how did you drive through that? >> So I think even when I was coming out of university I knew that I wanted to have a balance between the engineering program and business. A lot of my colleagues went on to do their PEs so continue to get their masters basically in engineering or their PhDs in engineering. I didn't really have an interest for that. I did international business and finance as my MBA because I wanted to explore the ability of taking what I had learned in engineering school and applying it to building businesses. I mean, at the time I didn't have it in my head that I would want to do startups but I definitely knew that I wanted to get a feel for what are they learning in business school that I missed out in engineering school. So I think that helped me when I transitioned, well when I applied, I was asked to come apply at AWS and I kind of went, no I'm going to, the DNA is going to be rejected. >> You thought, you thought you'd be rejected from AWS. >> I thought I'd be, yeah, because I have very much a startup founder kind of disruptive personality. And to me, when I first saw AWS at the stage early 2016 I saw it as a corporation. Even though from a techie standpoint, I was like, these people are insane. This is amazing what they're building. But I didn't know what the cultural vibe would feel like. I had been with GE at the beginning of my career for almost three years. So I kind of equated AWS Amazon to GE given the size because in between, I had done startups. So when I went to AWS I think initially, and I do have to kind of shout out, you know Todd Weatherby basically was the worldwide leader for ProServe and it was being built, he built it and I went into ProServe to help from that standpoint. >> John: ProServe, Professional services >> Professional services, right. To help these big enterprise customers. And specifically my first customer was an amazing experience in taking, basically the company revolves around strategic selling, right? It's not like you take a salesperson with a conventional schooling that salespeople would have and plug them into AWS in 2016. It was very much a consultative strategic approach. And for me, having a technical background and loving to solve problems for customers, working with the team, I would say, it was a dream team that I joined. And also the ability to come to the table with a technical background, knowing how to interact with senior executives to help them envision where they want to go, and then to bring a team along with you to make that happen. I mean, that was like magical for me. I loved that experience. >> So you like the culture, I mean, Andy Jassy, I've interviewed many times, always talked about builders and been a builder mentality. You mentioned that earlier at the top of this interview you've always building things, curious and you mentioned potentially your confidence might have been shaken. So you, you had the confidence. So being a builder, you know, being curious and having confidence seems to be what your superpower is. A lot of people talk about the confidence angle. How important is that and how important is that for encouraging more women to get into tech? Because I still hear that all the time. Not that they don't have confidence, but there's so many signals that potentially could shake confidence in industry >> Yeah, that's actually a really good point that you're making. A lot of signals that women get could shake their confidence and that needs to be, I mean, it's easy to say that it should be innate. I mean that's kind of like textbook, "Oh it has to come from within." Of course it does. But also, you know, we need to understand that in a population where 50% of the population is women but only 7% of the positions in tech, and I don't know the most current number in tech leadership, is women, and probably a smaller percentage in the C-suite. When you're looking at a woman who's wanting to go up the trajectory in a tech company and then there's a subconscious understanding that there's a limit to how far you'll go, your confidence, you know, in even subconsciously gets shaken a little bit because despite your best efforts, you're already seeing the cap. I would say that we need to coach girls to speak confidently to navigate conflict versus running away from it, to own your own success and be secure in what you bring to the table. And then I think a very important thing is to celebrate each other and the wins that we see for women in tech, in the industry. >> That's awesome. What's, the, in your opinion, the, you look at that, the challenges for this next generation women, and women in general, what are some of the challenges for them and that they need to overcome today? I mean, obviously the world's changed for the better. Still not there. I mean the numbers one in four women, Rachel Thornton came on, former CMO of AWS, she's at MessageBird now. They had a study where only one in four women go to the executive board level. And so there's still, still numbers are bad and then the numbers still got to get up, up big time. That's, and the industry's working on that, but it's changed. But today, what are some of the challenges for this current generation and the next generation of women and how can we and the industry meet, we being us, women in the industry, be strong role models for them? >> Well, I think the challenge is one of how many women are there in the pipeline and what are we doing to retain them and how are we offering up the opportunities to fill. As you know, as Rachel said and I haven't had an opportunity to see her, in how are we giving them this opportunity to take up those seats in the C-suite right, in these leadership roles. And I think this is a little bit exacerbated with the pandemic in that, you know when everything shut down when people were going back to deal with family and work at the same time, for better or for worse the brunt of it fell on probably, you know the maternal type caregiver within the family unit. You know, I've been, I raised my daughter alone and for me, even without the pandemic it was a struggle constantly to balance the risk that I was willing to take to show up for those positions versus investing even more of that time raising a child, right? Nevermind the unconscious bias or cultural kind of expectations that you get from the male counterparts where there's zero understanding of what a mom might go through at home to then show up to a meeting, you know fully fresh and ready to kind of spit out some wisdom. It's like, you know, your kid just freaking lost their whatever and you know, they, so you have to sort a bunch of things out. I think the challenge that women are still facing and will we have to keep working at it is making sure that there's a good pipeline. A good amount of young ladies of people taking interest in tech. And then as they're, you know, going through the funnel at stages in their career, we're providing the mentoring we're, there's representation, right? To what they're aspiring to. We're celebrating their interest in the field, right? And, and I think also we're doing things to retain them, because again, the pandemic affected everybody. I think women specifically and I don't know the statistics but I was reading something about this were the ones to tend to kind of pull it back and say well now I need to be home with, you know you name how many kids and pets and the aging parents, people that got sick to take on that position. In addition to the career aspirations that they might have. We need to make it easier basically. >> I think that's a great call out and I appreciate you bringing that up about family and being a single mom. And by the way, you're savage warrior to doing that. It's amazing. You got to, I know you have a daughter in computer science at Stanford, I want to get to that in a second. But that empathy and I mentioned Rachel Thornton, who's the CMO MessageBird and former CMO of AWS. Her thing right now to your point is mentoring and sponsorship is very key. And her company and the video that's on the site here people should look at that and reference that. They talk a lot about that empathy of people's situation whether it's a single mom, family life, men and women but mainly women because they're the ones who people aren't having a lot of empathy for in that situation, as you called it out. This is huge. And I think remote work has opened up this whole aperture of everyone has to have a view into how people are coming to the table at work. So, you know, props are bringing that up, and I recommend everyone look at check out Rachel Thornton. So how do you balance that, that home life and talk about your daughter's journey because sounds like she's nerding out at Stanford 'cause you know Stanford's called Nerd Nation, that's their motto, so you must be proud. >> I am so proud, I'm so proud. And I will say, I have to admit, because I did encounter so many obstacles and so many hurdles in my journey, it's almost like I forgot that I should set that aside and not worry about my daughter. My hope for her was for her to kind of be artistic and a painter or go into something more lighthearted and fun because I just wanted to think, I guess my mom had the same idea, right? She, always been very driven. She, I want to say that I got very lucky that she picked me to be her mom. Biologically I'm her mom, but I told her she was like a little star that fell from the sky and I, and ended up with me. I think for me, balancing being a single mom and a career where I'm leading and mentoring and making big decisions that affect people's lives as well. You have to take the best of everything you get from each of those roles. And I think that the best way is play to your strengths, right? So having been kind of a nerd and very organized person and all about, you know, systems for effectiveness, I mean, industrial engineering, parenting for me was, I'm going to make it sound super annoying and horrible, but (laughs) >> It's funny, you know, Dave Vellante and I when we started SiliconANGLE and theCUBE years ago, one of the things we were all like sports lovers. So we liked sports and we are like we looked at the people in tech as tech athletes and except there's no men and women teams, it's one team. It's all one thing. So, you know, I consider you a tech athlete you're hard charging strong and professional and smart and beautiful and brilliant, all those good things. >> Thank you. >> Now this game is changing and okay, and you've done startups, and you've done corporate jobs, now you're in a new role. What's the current tech landscape from a, you know I won't say athletic per standpoint but as people who are smart. You have all kinds of different skill sets. You have the startup warriors, you have the folks who like to be in the middle of the corporate world grow up through corporate, climb the corporate ladder. You have investors, you have, you know, creatives. What have you enjoyed most and where do you see all the action? >> I mean, I think what I've enjoyed the most has been being able to bring all of the things that I feel I'm strong at and bring it together to apply that to whatever the problem is at hand, right? So kind of like, you know if you look at a renaissance man who can kind of pop in anywhere and, oh, he's good at, you know sports and he's good at reading and, or she's good at this or, take all of those strengths and somehow bring them together to deal with the issue at hand, versus breaking up your mindset into this is textbook what I learned and this is how business should be done and I'm going to draw these hard lines between personal life and work life, or between how you do selling and how you do engineering. So I think my, the thing that I loved, really loved about AWS was a lot of leaders saw something in me that I potentially didn't see, which was, yeah you might be great at running that big account but we need help over here doing go to market for a new product launch and boom, there you go. Now I'm in a different org helping solve that problem and getting something launched. And I think if you don't box yourself in to I'm only good at this, or, you know put a label on yourself as being the rockstar in that. It leaves room for opportunities to present themselves but also it leaves room within your own mind to see yourself as somebody capable of doing anything. Right, I don't know if I answered the question accurately. >> No, that's good, no, that's awesome. I love the sharing, Yeah, great, great share there. Question is, what do you see, what do you currently during now you're building a business of Persistent for the cloud, obviously AWS and Persistent's a leader global system integrator around the world, thousands and thousands of customers from what we know and been reporting on theCUBE, what's next for you? Where do you see yourself going? Obviously you're going to knock this out of the park. Where do you see yourself as you kind of look at the continuing journey of your mission, personal, professional what's on your mind? Where do you see yourself going next? >> Well, I think, you know, again, going back to not boxing yourself in. This role is an amazing one where I have an opportunity to take all the pieces of my career in tech and apply them to building a business within a business. And that involves all the goodness of coaching and mentoring and strategizing. And I'm loving it. I'm loving the opportunity to work with such great leaders. Persistent itself is very, very good at providing opportunities, very diverse opportunities. We just had a huge Semicolon; Hackathon. Some of the winners were females. The turnout was amazing in the CTO's office. We have very strong women leading the charge for innovation. I think to answer your question about the future and where I may see myself going next, I think now that my job, well they say the job is never done. But now that Chloe's kind of settled into Stanford and kind of doing her own thing, I have always had a passion to continue leading in a way that brings me to, into the fold a lot more. So maybe, you know, maybe in a VC firm partner mode or another, you know CEO role in a startup, or my own startup. I mean, I never, I don't know right now I'm super happy but you never know, you know where your drive might go. And I also want to be able to very deliberately be in a role where I can continue to mentor and support up and coming women in tech. >> Well, you got the smarts but you got really the building mentality, the curiosity and the confidence really sets you up nicely. Dominique great story, great inspiration. You're a role model for many women, young girls out there and women in tech and in celebration. It's a great day and thank you for sharing that story and all the good nuggets there. Appreciate you coming on theCUBE, and it's been my pleasure. Thanks for coming on. >> Thank you, John. Thank you so much for having me. >> Okay, theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE here in Palo Alto getting all the content, check out the other interviews some amazing stories, lessons learned, and some, you know some funny stories and some serious stories. So have some fun and enjoy the rest of the videos here for International Women's Days, thanks for watching. (gentle inspirational music)

(bright upbeat music) >> Hey everyone. Welcome to theCUBE Special Program series: Women of the Cloud brought to you by AWS. I'm your host for the series, Lisa Martin. Very pleased to welcome Kesha Williams, senior principal at Slalom who joins me next. Kesha, great to have you. Thank you so much for your time today. >> Thank you for having me Lisa. >> Tell me a little bit about you and your role at Slalom. >> Hi everyone. I've been in tech for 26 years working across several industries like the airline industry, healthcare, hospitality and several government agencies. I really built a solid foundation in the Java software engineering space. A few years ago I added on AWS in the cloud and I really haven't looked back since. Throughout my career, I realized that I had a heart to teach and mentor, and that's what really brought me to Slalom. I currently serve as a program director in our AWS Cloud Residency program, which is a career accelerator for cloud engineers. >> 26 years. So you've had some great experiences and talk along that journey. You've grown your career as well. I love that you have that heart for teaching and mentoring. I think that's fantastic. Talk about, for the audience, some of the tactical recommendations that you have for those watching to be able to follow in your footsteps and grow their careers in tech. >> Well, tech is a very broad category. I always recommend that people really figure out what they enjoy doing to help narrow that focus into a specific domain in technology. For example, do you enjoy coding? Then you would look to be a software engineer. Do you enjoy telling people what to do? Then you may enjoy technical project management, and there are so many disciplines. I also recommend for people just getting started in tech to really consider the cloud. There is a huge demand for cloud engineers and people that are cloud-literate and not enough people to fill that demand. If you're looking to start a career in the cloud, I always recommend starting with learning the foundations, so going after your AWS Certified Cloud Practitioner exam. And once you understand the foundations, then start to build that hands on experience and build that portfolio so that you can speak to what you've developed in the past. And once you have that understanding, start to think about your specialty area. Do you want to specialize in machine learning or security or networking, and then continue to go after those more advanced certifications? >> That is brilliant advice that you really walked the audience through very strategically. I love how you think about it in that sense. I'd love to get into now you've grown your career over 26 years, as you said, some of the success stories that you've had in cloud. Can you share a few of those with us that you think really demonstrate the value of that foundation that you've built? >> Sure. I think a lot about success stories that really hit home and the first one that comes to mind is Georgia State University. That hits home because I'm from Georgia. It also hits home because my son attended Georgia State University. And Slalom joined Georgia State to really help them adopt this serverless approach and implement DevOps practices, and what that brings with serverless, you're able to really think less about the infrastructure management, and focus on building solutions and capabilities in Georgia State's example, really helping students achieve what they're trying to achieve. And I think that just the serverless model helps organizations move faster and deliver faster and innovate faster, and that's what we saw at Georgia State University. I'm happy when I think about that project because now Georgia State is ranked as the fourth most innovative university in the country, and I believe it's because we were able to help them shift and move some of their key applications to the cloud and really realize the benefits of what the cloud brings. >> And so, I love that. The fourth most innovative university in the country. That's a pretty impressive pedigree to be able to have there and you've shown the value of that. There's value across the organization, right? Across the staff, the educators, the students, the prospective students, and of course they have such great technology foundation with which they can use to learn and grow. You've got a second great example at Securian. I'd love to hear that success story and how you really helped that organization transform itself. >> Right. Securian, that case study really speaks to me because I'm all about teaching and mentoring, and empowering people to really realize the benefits of the cloud, and we were able to do that at Securian. We came in and really helped them define their cloud strategy, define that adoption strategy, define how they're going to migrate their applications to the cloud, and then we worked right alongside them to help them do that migration. But as a part of that, we talked about talent development and really help them up level their skills to be able to maintain what we've developed from an ongoing long-term perspective. >> The talent focus, the demand for talent, your focus on that is it can be such a flywheel for organizations in terms of innovation, evolution, that in upskilling is something that every organization I think regardless of industry should be focused on. Talk to me a little bit more about the heart that you have for helping organizations to attract that talent, to retain that talent by being able to be embracing of technology in emerging technologies in their organization, and how does that help them attract talent? >> Well, when you think about the mindset of engineers and the people in tech, we always have this goal to be at the leading edge and keep our skills current and have an opportunity to experiment with the latest and greatest technologies. And there is a huge appetite for cloud engineering skills from an engineer perspective and just from a demand perspective in the industry. So when companies are utilizing these really leading edge technologies that have shifted how we build applications, how we support applications, it really attracts top talent. >> Absolutely, and that should be a focus of every organization. Speaking of talent, one of the things that is talked about tremendously in organizations is diversity. But talk to me about some of the things that you see from a diversity lens through your eyes and what are some of the challenges today? There's so much talk about it, but yet dot dot dot to be continued. >> Right, Right. I am super excited that there is a huge focus on diversity in tech. Like I mentioned before, I've been in tech for 26 years, and I remember when a lot of organizations didn't care about diversity. So I'm appreciative that now there's a huge focus. But with that, there's also a need and a desire to focus on what we call inclusion and equity. So we're seeing organizations hire diverse candidates, but when those people come in, they're not in an environment that's welcoming. They're not in an environment where they feel included. And so there can be a retention problem if there isn't a focus on also inclusion and equity, which I call the other side of diversity. >> Yeah, the other side of the coin there. That's a great point that inclusion and equity are so critical to that diversity piece. In fact, they're really kind of engines to help make it successful so that organizations can attract diverse talent, but also retain them, make them feel welcome. Talk to me about some of the commitments that Slalom has to really a DEI approach. >> Right. At Slalom, we work really hard to build a culture where employees can bring their a authentic selves to work and be authentic, and really enjoy equitable opportunities in a welcoming environment that celebrates authenticity. For example, our employees have access to a multitude of employee resource groups. Those types of groups, we call them ERGs, they really help with a sense of inclusion and a sense of belonging. When I think about the cloud residency, we do the same thing. We have a focus on diversity, so our leadership team is diverse, the residents in the program are diverse. So we have diversity from the bottom to the top. We also practice equity and inclusion in how we staff our residents on projects and how we make sure really I call it an even playing field for everyone, and really think about and understand some of the barriers that people face. And like I said, try to make it an even playing field. >> Wouldn't that be nice one day if there actually is an even playing field and we don't have to focus on this so much? That's kind of a nirvana, I think, for us to get to, but so much productivity comes when people are treated fairly. And to your point, I love that you said getting to be their authentic selves. I think that's what everybody wants in every walk of life, in every aspect of life. Let me being my authentic self and employer, I'm going to be far more productive as a result for you. I just think they're linked like this. >> I totally agree. Like you mentioned, it helps bring retention. And when people have that sense of belonging, that sense of inclusion and they know that the organization they work for really cares and values those those things. >> Speaking of authenticity, the organization needs to be authentic. That's a whole other conversation, Kesha, we could have I'm sure. But I want to ask you a final question. I can't believe you have 26 years experience in tech. Don't look at for one, but you have had- I appreciate that- >> such opportunities to grow and expand your career. You've left our audience with some fantastic strategic advice, tactical recommendations for how they can really climb that ladder. What do you see as next for the evolution in the cloud and where do you think your role is going to go? >> I definitely see this growing demand and need for machine learning. The use of how we're applying machine learning really in every area of life is just exploding. And I see just next this supercharged focus on truly democratizing machine learning and putting it in the hands of everyone: technical people, business people, non-technical people. And when I think about AWS and some of their newer services, it really seeks to do just that. And when I think about my role and in the Cloud Residency and how that role will evolve, it's just very important for me to lead the team to be intentional in building cloud engineers that can quickly jumpstart their machine learning journey to help fill that demand and better serve our clients. I also see my role really evolving into one that truly stays in line with the trends that we're seeing in the tech industry, and bringing those trends back and really preparing our cloud engineers to succeed. >> It's all about being intentional, intentional in DEI, intentional in cloud engineering, intentional in democratizing machine learning. Kesha, it's been such a pleasure to have you on the program, Women of Cloud. Thank you so much for sharing your insights and your advice with the audience. I know they appreciate it. >> Thank you for having me. >> My pleasure. For Kesha Williams, I'm Lisa Martin. You're watching this special CUBE program series, Women of the Cloud brought to you by AWS. We thank you so much for watching and we'll see you soon. (bright upbeat music)

(soft instrumental music) >> Welcome back everyone, to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, your host of theCUBE. We're here in person at a live physical event with real people. Of course, it's a hybrid event. Great stuff online. Check it out on the Amazon site, as well as theCUBE zone. We've got great guests, talking about the cloud vision for getting talent in to the marketplace, in being productive and for society Accenture always great content. Denise Reese, Managing Director of the South Market Unit Lead at Accenture, AABG, which stands for "Accenture Area Business Group" and Gina Gina Fratarcangeli who is also the managing director of Midwest sales leader. Ladies, thanks for coming, I appreciate you coming on and talking about the vision of talent. >> I guess >> Thanks for having us. >> Yes, absolutely. It's a pleasure to be here. >> So, Amazon's got this dangerous goal, to train 29 million people. Maureen Lonergan came on yesterday, who I've known for a long time, doing a great job. It's hard to get the talent in. First of all, it sounds harder than it really is, that's my opinion. You know, you get some training certifications and you're up and running. So, talent's a big thing. What do you guys do? Give us the overview. >> Sure. Well, we're having a lot of activity at Accenture trying to get talent in. Across the entire country we're spending a tremendous amount of effort to do that. A couple of critical things we're doing in the Midwest is bringing in and searching for different talent streams that we haven't typically done in the past. For instance, one thing that we're doing is, we set up an apprentice program where we're reaching out into the market to find diverse talent, who aren't coming through the critical normal college path and bringing folks in like that. And we've got 1200 people that we've brought in that way, just in the Midwest. Which has been a phenomenal new talent stream for us. And supporting our inclusion and diversity. One of the other exciting things is what we call "The Mom Project", where we're intentionally working with an organization called the Mom Project, to bring women back into the workplace who may have left while they were taking care of their families and helping them get certified in all the new cloud technology and getting back to work. >> I love how you guys are going after this whole places that not everyone's looking at, because what I love about Cloud is that, it's a level up kind of opportunity where you don't really have to have that pedigree, or that big-big school. Of course, I went to a different school. So, I have a little chip on my shoulder. I didn't go to MIT, wasn't North-east but still good school. But, I mean, you could really level up from anywhere. >> Gina: That's right. >> And the opportunities with Cloud are so great. This is like a huge thing. No I'm surprised no one knows about it. >> Absolutely. I would add to that. So, we've in the South, in Georgia in particular. We've just launched an initiative with the technical college system of Georgia and AWS. So, it's a public-private partnership, where we're actually helping to set the curriculum for those students that are going through programs, through the technical colleges. It's one of the largest parts of the university system of Georgia. And, we're actually helping to frame the curriculum. And, giving folks what they need, to your point. It is an opportunity to level up. It's a great way to get talent in non-traditional spaces. It helps us to achieve our inclusion and diversity roles or goals, rather. But, then it also allows us to really continue to fill that pipeline with folks that we may not have had access to otherwise. >> Is there a best practice that you see developing in the acquisition of talent? Or enticing people to come in? Because that's just economics you know, Maureen was telling me that it was this person she was unemployed, and she got certified and she's making six figures. >> Both: Yeah. >> She's like oh my God, this is great. So, that's the Cloud growth. Is there a way to entice people? Is there a pattern? Is it more economic? Is it more, hey, be part of something. What's the data showing? >> There's definitely a war for talent out there. And so in this space we continuously hear from our clients that they can't hire enough people. So in the past, in the technology space, a lot of clients were hiring their own teams and here they just can't get the skills fast enough. So we're spending a tremendous amount of time being proactive. We started a women in Cloud organization where we're proactively reaching out to the community to bring women in, let them know that we will help them get those certifications and partnering with organizations like Women in Cloud, which is a global organization to create new funnels of talent. >> I think the women angle is great. The mom network coming out of the work for back into the workforce, because things change. Like we were talking about how Amazon just changed over the past five years now that this architectural approach is changing. So that's cool. Also we were involved in the women in data science, out of Stanford University, they have that great symposium. This is power technical women. >> Yes >> And it's got a global following. So the women networks that are developing are phenomenal. So that's not just an Accenture thing, right? That's outside of Accenture. >> I think it's a combination because I think we do a really good job inside of Accenture to create opportunities for women of various ethnicities lived experiences to be able to come together to network internally, but then also to pour some of that talent that they have into the communities where we live and we all do business as well. So I think I'm seeing definitely a two-pronged approach there. >> Let me ask you a question, I don't mean to put you on the spot, but I kind of will, Accenture's known as a pretty great firm. So working at Accenture is kind of a big deal. Does that scare people? Because if you could work at a Accenture I mean, that's good pedigree right there. So like, when you're trying to get people coming into the cloud, do they get the Accenture mojo or does it work for them? And can you share your experiences on that? >> I've been here five years and it's been a phenomenal ride for me. I've really enjoyed the fact having a female CEO, I think, and having a CEO who is so committed to diversity on all aspects, right? Her commitment is 50% diversity parody by 2025 at every level of our organization. And that doesn't happen without really intentional efforts at the entry-level and everywhere through the process to ensure that women are not only promoted, but really given the support network among all of our leaders and mentorship to be successful. And it's not just words, it's something that we're really spending a lot of time doing with intention. And that word is out in the space now, as women come in, they're loving it and they're recruiting their other women into the organization and diverse groups as well as what I'm seeing. >> And so I actually just started at Accenture in March. So I've been around eight months. I actually joined from AWS, interestingly enough. And I can tell you from my own experience, the intentionality that Gina spoke to you is it's evident at all levels. I feel like the way that I was courted to the firm was nothing short of amazing. That's another story for another day, but I feel like my being where I am, being hired in as a managing director, as an experienced hire, I think my presence is a testament to the focus that Accenture has on inclusion diversity and the equity component as well. And then also in Atlanta, we are exceptionally fortunate. We have close to 30 black and Latin X managing directors and senior managing directors out of the Atlanta office. So what we're doing there is pretty magical and it's something that I've never experienced in my 25 years. >> It's contagious I hope, the magic is contagious. >> Yeah. >> Yes, absolutely. >> And it's exciting because we're known as a management consulting business, right? So our product is the people >> That's right. >> And so there is intention from day one as to what you want from your career and setting your career plan. So everyone is given those career counselors and the expectation that someone is thinking about your business and your personal business, and what is your role today and what should your role be in two years, and what skills do you need to get there? Which is awesome, it's a lot of fun. >> It's also walking the talk too, right? I mean, Amazon here, they had a 50% women on stage. I don't know if you noticed on the keynote, they was two men and two women, 50%. Of course the United Airlines, it's got to be three. We got to get a 51%,, 'cause technically 51% So it should be three to one, but yeah, like, okay, that was cute notice but that's good. But this is real, I've been a big proponent of software development. Customers are women too that's 51%. So I think this whole representation thing has to be more real and more intentional. And so I want to ask you, how would you share the best practice of making that real from the essential playbook? What could people learn and what mistakes should they avoid? I think people who do want to try with it, but they don't know what to do. >> You know, I think get started, right. Do the work. I feel like since I started in technology, we've been having this conversation about diversity and inclusion and bringing more people into the space. And now it's time for us to just do that. And I feel like Accenture is doing that in spades. I think also again, I've been using this word. I was on a breakout panel yesterday talking about our partnership with AWS and intentionality keeps coming up. But I think also it helps to have a CEO who's creating diversity as an imperative at the most senior levels of the firm and folks are being incentivized as a result. So you've got to put the mechanisms in place to ensure that folks understand that this is not just lip service. >> That's a great point. It's not only just the people, but the mechanisms. And one of the things that I've been saying early on in the top of the interview was Cloud is an instant leveler there, because if you can be so capable so fast. So like when you start thinking about getting people in the market, producing talent, this notion of meritocracy isn't lip service, because if you have the capabilities and the people side lineup, then it truly can be like that. 'Cause your game does the talking, right. >> And we're doing it with intention at every level in the organization so much though, that every people leader, one of their metrics is the diversity. And as we look at the promotions, making sure that that parody is there, but every person who's managing people has diversity as a metric that they're being measured on. And so I think that's really critical as well as having the people who are being the advocates and being the allies and really asking the questions as the teams are getting put together. You know, my job is to review all the deals in the Midwest. And when the teams come forward, I say, "Great where are the women on the team? Who are we putting it?" We're all talking about the diversity. So when we're going to a client meeting, where are the women who are you're taking to that meeting? And if the answer is well, there's not one who's technical yet, the most senior, the most technical, well, great bring her on and use this as a training opportunity. We need to walk the walk and talk the talk and show that to our clients. >> I think that's really good. You guys are senior leaders, one can do that, demonstrate that, but also you're in the field for Accenture. You're in front of your customers. What are you seeing out there and what excites you about being in these industry? >> Yeah, I love the fact that there are so many more women in this space. I love that we're having so many women out there with intention. We've had six female CEOs do women in Cloud panel discussions with us and with our team. So you made the comment early about cloud moving so fast. That's the most exciting thing for me and the fact that it is moving at such a pace that no one client is going to be able to get the skills fast enough. They need companies like Accenture. They need companies like AWS to help them where we're leveraging all the knowledge from our own other clients and bringing that together so we can help them accelerate their development. What about you? >> Absolutely. Now I would echo that as we used to say at AWS plus one to that. But I'm really hopeful because what I'm seeing is the number of folks with my lived experience better at senior executive levels, not only within Accenture and AWS, but in our customers. And I think going back to the point that you were making earlier regarding Cloud being a level up and giving folks opportunity, folks have to be able to see a path, right? It's one thing to just get a certification and tick a box, that's great. But if you don't see a pathway to being able to utilize that in a way that allows you to move up and seeing where we are now, just as a firm, just really, really excites me that every time I get onto a call and I see another strong, amazing woman, I'm like, man, this is amazing. And it's something that... I think it's a phenomenon that I've started to see maybe within the last like five years or so. And probably even within the last two to three years, I've started to see that even more so, so that really excites me. >> Well, first of all, you guys are great. You're contagious, okay? Which is good, a good thing. I love how you brought the whole path thing because path finders was a big part of Adam's Leslie's keynote, and it must be really fun to see people taking the path that you guys are pioneering- >> We're ploughing, we're ploughing >> Yes we are. We're ploughing and you know what else we're doing? We're lifting, as we climb. That is important. I would say that, we don't have all of these amazing opportunities and blessings just to talk about what we have, but if you're not actually bringing somebody else along and giving those opportunities to folks, then it's all for not. >> You got people and the Cloud, to get them people, which is, we're humans and the mechanisms software to bring it together, magic. >> Absolutely >> Congratulations. Thanks for coming on theCUBE. >> Both: Thanks for having us. >> Okay this is theCUBE, I'm John Furrier, host of theCUBE. You're watching theCUBE, the leader in global tech coverage from re:Invent 2021 AWS web services. Thanks for watching (soft instrumental music)

>>Yeah. Hey, everyone, Welcome to the cubes. Continuous coverage of AWS Re invent 2021. I'm Lisa Martin with John Furrier were running one of the industry's largest and most important hybrid tech events with AWS and massive ecosystem of partners. Right now there are two live cube sets to remote sets over 100 guests on the programme and we're pleased to welcome back one of our alum I to talk about the next generation and cloud innovation. Georgia Lisa is joins John to me, the director of product management for EC two edge at A. W S George. Welcome to the programme. >>Glad to be here in person. Thanks Great to be here in person. Awesome to be here in person. Finally, >>one of the things that is very clear is the US flywheel of innovation and there was no slowdown with what's happened in the last 22 months. Amazing announcements, new leadership. We talked a little bit about five g yesterday, but let's talk more about that. Everyone is excited about five g consumers businesses. What's going on? >>So, yeah, I wanted to talk to you today about the new service that we launched called AWS Private. Five g. Essentially, it's a service that allows any AWS customer to build their own private five g network and what we try to do with the services make it that simple and cost effective for anyone without any telco experience or expertise, really, to build their own private five g network. So you just have to go to your AWS console. Um, describe the parameters for network simple stuff like, Where do you want it to be located? The throughput, the number of devices and AWS will build a plan for your network and seep you everything that you need. Just plug it together. Uh, turn it on and the network automatically configures itself. All you got to do is popular sim cards that we send you into your mobile devices and you have a private five g network working in your your premise is >>one of the things that we know and love about AWS is its customer obsession. It's focused on the customer's that whole flywheel of all the innovation that comes out as Adam was saying yesterday to the customers, we deliver this, but but you wanted more. We said we deliver this, but you wanted more. Talk to me a little bit about some of the customer catalysts for private five G. >>Actually, one of the good examples is where we are right now. More and more AWS customers need to connect an increased number of devices, and these devices become more data hungry. You know they need to push data around. They also become more and more wireless, right? Uh, so when you are trying to connect devices in the manufacturing floor, bit sensors, you know, connect the tracks, forklifts or in a convention centre. You look at how many devices there are around us. When you're trying to connect these devices with a wired network, you quickly run into physical problems like it's. It's hard to lay cable anywhere, and customers try to use for many of these use cases. But as a number of devices grows into the thousands and you know you need to put more and more data around, you quickly reach the limitations of what the WiFi technology and also WiFi is not really great at covering really open, large space. So that's where these customers, you know, think of college campuses, convention centres, manufacturing floors, all of these customers. Really? What they need to be able to do is to level the power of the mobile networks. However, doing that by yourself is pretty hard. So that's what we aim to to enable here we are waiting to enable these customers to build very easily and cost effectively their own. Uh, >>Okay, George. So I have to ask. I'm truly curious. I love this announcement. Um, because it brings together kind of the edge story. But also, I'm a band with love. I love more broad. Give me more broadband. Faster, cheaper and more broadband. How does it work? So take me through the use case of what do I need to deploy? Do I need to have a back haul connection? What does that look like? Is there a certain band with requirements? How big is the footprint? What's the radius? Just walk me through. How do I roll this out? >>Yeah, sure. Some of that stuff actually depends on your requirements, right. How How big? How much of a space do you want to cover? Basically, what we see, if you were in preview right now, so we're sipping you. The simplest configuration, which is basically these things called small cells there, you know, radio units and antennas. And all you have to do is connect them to your local. The network has Internet access. These things connect and automatically had, you know, connect home to the cloud and basically integrate and build up your whole network. All all you need is that Internet connection, and I don't know what to do. Now, how big is the network? You can You can make it pretty big. You can cover hundreds of thousands of square feet with with cellular networks with mobile networks. Um, you know, the bigger you they especially want to cover the more of these radio units. We're gonna stop you, uh, >>classic wireless radios. >>Yes. You >>light up the area with five g connected to the network. That's your choke point. The big of the pipe >>took the bigger pipe. That toxic. I mean, well, there, there's two. There's two things to consider here. There is local connectivity. So devices talking to each other, and there was connectivity back to somewhere else, like the Internet or the cloud. There are use cases, for example. Let's say data video feeds that you want to push up to do some inference in the cloud. In these use cases, you're basically pushing all of the data up. There is no left. There's no East West connectivity locally, and that's where our simplest configuration works best. There are other, uh, use cases where there is a lot of connectivity and devices talk to each other locally, like in this place, for example, right in this. In these cases, we can sip you that second configuration where we actually see Pew, a managed hardware WS managed hardware on premises, and that runs the smart of the network and allows all of your data traffic to remain local. That's >>wavelength Outpost, or both. >>A different configuration of A. W s private five G. It's a managed service. We take. We take care of it. You basically it's very It has a pricing model, which is very customer friendly because you like multi W services. You can start with no upfront fees. You can scale and pay as you scale because >>it's designed to deploy easily. >>Yep, deploys the >>footprint. Just I'm just curious if the poll is it like, it's like an antenna. Is it like so and >>yeah, well, the antenna is, you know, the small cell. They call them small cells in, you know, in in cellular land there, this big. And you can you can hide this. There is actually a demo in the Venetian of the private service. So you can you can actually see it in action, but yeah, that thing can cover 10,000 square feet, just one of them. So you can >>go out and put a five g network downtown and be like the king. >>You could Yes. You could have your own private network. You can monetise that next >>on the Q. >>Great stuff. >>So in terms of industries adopting this, you gave us some examples. Obviously. Convention centres, campuses, universities. I'm just curious, given the amount of acceleration that we've seen in every industry the last 22 months where organisations must become digital. They depend on that for their livelihood. And we saw this all these pivots, right? 22 months ago. How do we survive this? How do we thrive? Are consumers now are whether it's an injury or consumer or enterprise. Have this expectation that we're gonna be able to communicate no matter where we are 24 by seven. Whether it's health care, financial services. I'm just curious if you're seeing any industries in particular that you think are really prime for this private five >>G. Yeah. So manufacturing is a is a really great example because you have to cover large spaces. You have thousands of devices, sensors, etcetera and using other solutions like WiFi does not provide you the depth of capabilities like, for example, you know, advanced security capabilities or even capabilities to prioritise traffic from some devices over others, which is what a five G network can do for you. But also, you know, it involves large spaces both indoors and outdoors. We, you know, actually, Amazon is a really great example of you know of using this. We're working with Amazon fulfilment centres. These are the warehouses that fulfil your orders when you order online. Um, and they are a mix of indoor space and outer space, and you can think of, you know, I don't know if you've seen pictures or videos. There's robots running around their sensors everywhere. There is packing lines, etcetera, all of these things in order to operate performantly, but also securely and safely for the people that are around. You need to be well connected at a very high reliability rate. Right? So, uh, Amazon for two networks is actually using private A W s private five G to connect all of these devices. The really key thing here is you don't have to go drop 1000 of these access points we're talking about you. Can you can. You can probably cover your space with 5 10 of these. So your operational expenses, your maintenance goes down and there is less interruption of your normal operations like you can't. You don't have to stop your manufacturing line for someone to come in and fix your WiFi access. >>It's great for campuses like college campuses, college >>campuses, a great one. We you know, we've worked with college campuses, including the CME University in the past two, you know, with some of our partners to, uh, to to deploy. So >>that's how close you have these distribution, gas systems, distribution, whatever they call it accelerate whatever amplifies into get extra coverage, this seems to be a good fit. Um, for that how you mentioned in the preview? How do people get involved? Is there like a criteria. How was it going to >>be available to get priority? Don't get you >>tell them ready to jump in. Take us through the programme. What's the plants? >>So currently we're you know, we're in that preview mode. So we're keeping you this small configuration, the simpler configuration. You can sign up on the AWS website and you know, we, as we scale our operations are supply chain. Because this involves also, you know, hardware, etcetera. We're gonna go to general availability g A over the next few months and we have both configurations open. So I I encourage everyone who is interested go to the W s website and sign up. We're asking to get that in customers' hands because we're getting overwhelmingly positive feedback on what we built. >>This is transformative. I mean, clearly what you're talking about here is going to transform industry and help organisations transform themselves and outpaced the competitors that are in the rear view mirror Aren't going to be able to take advantage of this were on the show floor. We've got lots of people here. Where can people actually go and see this preview tested up? >>There is an actual demo in the Venetian. I can't remember. Sorry, I can't remember the room. I think it's on the Yes, actually, it's on the floor on the third floor where the meeting rooms are on outside 35 or one. If anyone wants to go, we're >>going to start buying lunch time. >>Yes. Yeah, you can see it in action. And, you know, you could You could see a future where everything, You know, you look around. There's thousands of devices here. You could power all of these devices with a single cell and, you know, really scaled throughput >>in the five G. Just curious, um on the range is better than wifi >>ranges. Better outdoors, >>obviously, or factories. What's the throughput on the >>depending on the spectrum that you choose? And that's actually a really good save way. The device, the service that we built, its spectrum agnostic so it can be used on right now. We're using it on what we call C BRS spectrum, which is the free for all you can. You know, you can you can use it yourself. But also, customers can bring their own spectrum. And we're working with a batch of, uh, CSP operators to build advanced bundles where you can work this on licence spectrum. So if you're going up the spectrum in what they called millimetre wave >>spectrum owner to bring your own licence, >>you could So telco right? You could be a telco, bring your, you know, and work with us as a partner or some actually, actually, manufacturing customers have purchased rights to small spectrum bands so they can use those in combination with this service to deploy. So to your original question, as you're going back up the spectrum, you can drive more and more throughput. You it's not. It's not unheard of to drive one gig. You know what's so >>The low hanging fruit is the the use cases that have critical need for edge connectivity manufacturing? Um, certainly the retail or whatever that they help do the deployment >>we can. We can. We can see this being applicable because because you can start super small. You can see this being applicable even to branch offices, right? Like, uh, let's say I was talking to a customer yesterday. They were thinking or have all these branch offices. I don't even I don't even want to have I thought either he just wants something that's very quickly and easily. You know, I can manage centrally and it just connects. >>Can I should have fixed wireless shot to the wavelength order to have back all with wire >>too. Oh, they actually we are planning to. You know, I talked about where the smarts of the network live in the they can live in a region, they can live in the locals, and they can live in a wave election. So we're combining more and more of these products as well. And it's computing, obviously, is a is an obvious thing that, you know, we should be working on >>incredible work, George, that you and the team have done transforming industries. And I don't know if a feeling there might be a cube to Is it? Would it be too dot >>Oh, John, >>he's ready. Big George, Thank you so much for joining joining me today. It's great >>to be here. Thanks for having that >>for John Ferrier. I'm Lisa Martin. You're watching the Cube, the global leader in live coverage. Mhm

(upbeat music) >> Welcome back to Las Vegas Lisa Martin live here with David Nicholson. We're at AWS reinvent 2021, this an outstanding event. There's a lot of people here, tens of thousands. And this is probably one of the most important and largest hybrid tech events that we're doing this year with AWS and its massive ecosystem of partners. We're going to be covering this two live sets, two remote studios, over 100 guests on the CUBE at this re-invent and David and I are pleased to welcome Giorgio Vanzini next the vice president and global head of partners and alliances at DXC, Georgia Welcome to the program. >> Thank you for having me. >> Talk to us about what's going on at DXC, what are you in AWS doing together with what's the scoop? >> Yes Well, some exciting things are happening between AWS and DXC, which is we're really focusing on our customers that we have especially in the banking and capital markets, but also automotive. And then also we were a launch partner today with the AWS mainframe modernization right, and so we're focusing on mainframes as well. So exciting spaces for us to go collaborate and work with AWS, for our customers. >> Talk to me about some of the things you know the last 22 months have been quite challenging, quite dynamic and we've seen such a massive acceleration to the cloud. What have you seen from your perspective? Are you seeing customers in every industry that have really figured we've got to do this now because if we don't, we're going to be out of business? >> Yes, you're absolutely correct. We've seen a dramatic acceleration of people wanting or customers wanting to move to the cloud public and private, and an acceleration of assistance that they were requesting from a global systems integrator. So what we've seen is you know, part of our clouds ride strategy that we have, really understanding what does the customer need from a strategy perspective, from a business value perspective and the technology perspective, and AWS has been a great partner with us to actually accommodate all of these kinds of things and the announcements that you had today, you know, just substantiate kind of that fact as well. >> Can you double click on the Cloud Right approach, talk to us about what that is, why it's important and what are some of the outcomes that it's helping customers to generate? >> Absolutely love to Cloud Right is really DXC's strategy to take the customers on the journey from the mainframe to the cloud, and to customize this because every customer is different. They have different requirements, different environments, different business strategies. So therefore the Cloud Right approach is really customizing it for the customer. What is the right business strategy? What is the right technology strategy? And then migrating them over into the cloud as well. Keeping in mind that again, customers are specific, industries are specific. You know, data requirements are different analytics are different, you know, government requirements are different. So you need to those in mind when you transition customers over into the cloud space. >> Right, from a data residency, data sovereignty and all of the different rules and regulations that are popping up that are kind of similar to GDPR for example, that's a big challenge, but one of the things too that's happening Giorgio is that every company to be competitive these days has to become a data company, right? There's no choice, you've got to be data-driven, you've got to have a data strategy at the core of the business, otherwise there's a competitor in the rear view mirror, who's ready to take your place. >> That is absolutely correct, and so that's part of our Cloud Right strategy is understanding what are the business requirements from the customer? Understanding their competitive edge and migrating them over. Because in many instances, to your point, they have huge reams of data, petabytes of information of data, but really making sense of it, so running the analytics on it and having the business insights. So helping the customers understand that, but then also understanding of like, what are the key business requirements that they have? Which applications to migrate and which not to migrate? >> So I'm curious, you mentioned that you're a launch partner for mainframe modernization. That's sort of one slice of and very important slice of some organization's business and migration strategy to cloud. I'm curious what the DXC blend is between standardized offerings and bespoke services and how you manage that? Do you have a thought about that? Wouldn't it be great to have small, medium and large and have people click on it? >> Yes here's a T-shirt for you, which size are you? Now I'm actually glad you asked me that question because that's exactly going to the core of the Cloud Right strategy, and the Cloud Right really means that it's like, which T-shirt size is correct for you? Right. This is the question that we just addressed which is it has to be bespoke because one size does not fit all. And so understanding the customer requirements of do we need to move the data to the cloud? Or do we move to need a subset to the cloud? Do we need to move part of the business applications and which ones and in which order? Right? And so that's why I think we bring something to the table in the AWS mainframe modernization, which is unique because we have an end to end kind of approach from a planning to implementation, to execution and running as well. So I think DEX is uniquely positioned with our Cloud Right strategy. >> One of the things AWS Giorgio talks about is not being custom but being purpose-built. Talk to me about kind of compare contrast that with bespoke solutions, industry specific, obviously customers have specificities. Do you see a difference there between purpose-built under bespoke or are they aligned from your perspective? >> Yes, I do agree that a to technology layers are definitely common layers, horizontal layers, right Where I think you have bespoken limitations on the business strategy and the business rules. And so you have to understand what business is the customer really in and how to implement the business rules into the technology stack as well, and bringing it all together. So while the technology I think goes horizontal to your point right, you know, compute and storage is the same. Wherever you go the bits are the same, however how they're utilized and how you use them for your customers and your interaction is completely different from customer to customer and industry to industry, as you guys know as well. >> You know, it can be, it can be really disheartening working in this space when you think of 475 different kinds of instances and how important it is to get that right for a customer and how much they don't care. Ultimately they don't want to hear about it, they don't want to know, but they want you to get it right, so that it doesn't matter. So it's this irony of all of the work that people have to do like at DXC to make those details not matter. Any thoughts on that? Do you, are you a dejected because of that at all? >> Well, that is part of the value that we bring, right? >> David: Sure. >> To your point, absolutely the customer doesn't care in quotes, right? Just make it work for us and run it smoothly. On the other hand, we're on the hook to make sure that all the different partners that we have, that we integrate including AWS, right. Run smoothly and coherent and are up, you know, 99.999% of the time obviously right. And so the customers do care about our you know, interaction with them as well while AWS is always there. >> One of the things that we talked about a little bit ago is every industry had to pivot right. Dramatically the last 22 months or so. And we've seen every industry cloud is no longer a nice to have We've got to be able to get there, but you mentioned a focus in banking, and I think automotive, I'd love to get your perspectives on what some of the things are the opportunities that DXC sees in those particular industries, as opportunities to modernize. >> Yes, we latched on to banking and automotive because those are ripe for transition and the customers are willing to take the steps there as well. It doesn't mean that other industries are not relevant like, you know, consumer or retail or you know, technology and, and manufacturing. However, especially in automotive I think we have a unique positioning where we have the majority of the OAMs car manufacturers worldwide as customers, and when you think about AWS, you think about the utilization of the information that comes back from telematics information and customization, right. Petabytes of information that comes back from every device, which is a car and what kind of service you can provide there. So it's an industry you know, we talked about Tesla early on as well, right It's an industry that ripe for software and software updates. very similar you see a lot of things happening in the banking capital market space, where they're moving you know their customer base into new spaces as well. Just think about all the NFTs, those are happening, all the FinTech that's happening, right. So the, the banking capital markets companies have to, you know, have an evolution going on right, and assisting them in this evolution is as part of our strategy. >> So you're responsible for global partnerships and alliances DXC would be considered a large global systems integrator. The world is obviously moving in the direction of cloud. We've got the three big players AWS, and the other two I can't think of their names while I'm sitting here in Vegas right now, how do you balance what you do with those, with a variety of providers, for customers, and are you going to market primarily as DXC with the DXC relationship with the customer? Or in support of those cloud vendors that have essentially technology that if left unimplemented is essentially worthless, right I mean you, you bridge the divide between the technology and the true value of the technology, but are you the primary seat holder at the customer table, or is AWS the primary seat holder? Or is it a little of both? Long-winded question I apologize but I think you understand what I'm saying. It's an interesting world that we live in now. >> It definitely is, and if I wouldn't know you better I would say it's a trick question, but in all seriousness, we really are customer driven just like AWS as well right so, we really are trying to do the right thing for the customer. Hence our Cloud Right strategy, where we don't have a cookie cutter approach or saying just go do the following five things and you're going to be fine. We really want to look at the customer and say, what is important to you? What is the timeframe you're looking at? What is the strategic imperative that you have? What data do you have to move? You know, what system do you have to leave behind? And then do the right thing for the customer literally right. And so in this instance, absolutely you know, in my role AWS plays a huge role as you know is one of our core hyper scaler partners, a very good partner, we love AWS. And so making sure that they're always going to be there as part of that infrastructure is part of our strategy. >> You mentioned, oh sorry Dave >> No, I was just saying it makes sense. >> It does make sense in terms of being customer first, we talk with AWS, you can't kind of have an interview with, with one of their folks without talking about that. We work backwards from the customer first. This customer obsession, it sounds like from a cultural perspective, there's pretty strong alignment there with DXC. >> Exactly right, so I think from that perspective we share the same DNA where we look first to the customer and then say okay, how do we deduct what is right for the customer and implement it that way right, Because in many instances as you know, you mentioned the, the two other hyper scaler that we don't talk about, customers usually don't have a single source kind of approach, right They usually have a dual approach. And so while we have to work with that, there's preferred vendors that we engage with, right. And so clearly AWS is one of our preferred vendors that we engage with. >> Can you share an example? I'd love to know a customer that's taken the Cloud Right approach applied really kind of in a textbook way that you think really shows the value of DXC. Any customers, but even by industry if you don't want to name them, come to mind that really show the value of that approach. >> Yeah, So we, we just concluded a major migration from one of our leading insurance companies, a global big company that you know is similar with my birthplace. But what we really did is a Cloud Right approach of migrating them from their legacy mainframe and virtualized systems that they had, to a cloud approach. And in the process of doing this you know, we reduced their overall operating expenses, their cap X expenses obviously but also reduced their overall budget about 30% reduction by moving them to the cloud. Again during the Cloud Right approach of understanding what exactly to move in, which timeframe and what to leave behind right, Because in many instances, customers don't have an exit strategy. They rush to the cloud, but then leave their you know old legacy behind and like oh, what are you going to do with this? And so you need to have a comprehensive end to end system strategy of like, what do you want to leave behind? When do you want to sunset it? And when do you want to migrate certain things over as well? >> That's got to be quite challenging for I would assume a legacy historied insurance company been around for a long time, lots of data, but culturally very different than the cloud mindset. >> You bring up one of those soft skills, right. Which is the cultural aspect of talking with the customers of how do we migrate you? It's not just, and that's why I said it's not just a business decision or a technology decision. In many instances, you affect people's life as well. When you think about old systems administrators that were working on mainframes. Now if you move everything to the clouds, they become obsolete. So rescaling the workforce and having a comprehensive plan is part of the soft skills right, Where you think more comprehensive about the customer, it's not just technology it's really is the full experience right At 360 what happens to the people? How do we migrate the people? But also setting expectations with top management, for example right of saying, how is this going to change our business? What new opportunities are going to be there? So those are all the soft kind of skills as well. >> One of the things that struck me this morning during the AWS keynote is just all of the innovation that that goes on. But AWS really is a flywheel of the customer and all the opportunities that their customers create for AWS, and the opportunities then that AWS technologies create for the customers across industries I just thought that I just kind of really felt that flywheel this morning when Adam was talking about all of the things that they're revealing, you must feel the same as a partner. >> I do, and I I'm a tech geek, so I'm totally excited about this, and it you know it feeds my soul because I can remember when, you know, when we first had analytics with you know Redshift rights and then customers are coming back and going like, well could we do something that is real time? Because we have requirements in this, and then CAFCA came out right, as a new service and I'm like okay, great right, and so we're really there to embrace you know, every new service that comes out from AWS. Which is fantastic, right I mean the speed and agility that comes out with AWS and we totally embraced that for our customers. >> Awesome, Georgia thank you for joining David and me today talking about what's going on with DXC, your partnership with AWS, Cloud Right, and how you're helping customers get Cloud Right. We appreciate your insights and your time. >> Thank you, I appreciate it too, thank you. >> All right. For David Nicholson, I'm Lisa Martin. You're watching the cube, the leader in global alive tech coverage. (upbeat music)

>>Mhm. Hey, everyone, welcome back to the cubes. Continuous coverage of AWS Re Invent 2021. Live from Las Vegas. Lisa Martin with John Ferrier We have to live sets to remote studios over 100 guests on the Cube at this year's show and we're really excited to get to the next decade in cloud innovation and welcome from the keynote stage. Mark Ruin the Chief Network Officer Andy VPs Dish Network Mark, Welcome to the Cube. >>Thank you. >>Enjoyed your keynote this morning. So big news coming from AWS and dish you guys announced in the spring telecom industry First dish in AWS have formed a strategic collaboration to reinvent, reinvent five G connectivity and innovation. Let's let's really kind of dig into the AWS dish partnership. >>Yeah, you know, we're putting our network in the cloud, which allows us to have a different speed of innovation and a much more corroborative way of bringing new technology. And then we have access to all the developer ecosystem of AWS. So that's but as you say, it's a world first to put the telco in the cloud. >>And so the first time the five g network is going to be in the cloud, and it was also announced I'm curious, uh, that Las Vegas is going to be the first city live here. We are sitting in Las Vegas. What's the any status you can give us on >>that? So we're building across the US and Las Vegas is a place that we've built and we better testing. So that's where we have all run and we're testing all sorts of traffic and capability with our people and partners live here at the same time that we have the reinvent and, uh, Bianco around. We're also starting to test new capabilities like orchestration, slicing things that we've never seen any industry. So that's pretty exciting, I >>have to ask you. In the telecom industry, there has been an inflexion point around cloud and cloud Impact Ran is opening up new opportunities. What is the telecom industry getting and missing at the same time? Because it seems to be two schools of thought cloud pro cloud ran and then hold onto the old way. >>I think everybody would like to go to Iran and the cloud, but it's not as easy if you have a big installed base. So for us. You know, we all knew it. It's easy so we can adopt the best technology and the newest. But of course, if you have a big instal base, there is going to be a transformation, if you wish. So you know, people are starting trying to set the expectation of how much time it will take. But for us, you know we are. We're moving ahead because we're building a completely new network. >>It's a lot easier than well, it's a relative term. It's >>really much more fun. And we can We don't have to make compromises, right? So but it's still a lot of work, you know, we're discovering we're learning a lot of things. We're partners. >>What if you have a clean sheet of paper or Greenfield? What's the playbook to roll this out across the campus for a large geographic area? >>Yeah, so pretty much You have the same capability in terms of coverage and capabilities than anybody else, but we can do it in an automated manner. We can do it with much thinner and efficient hardware, pretty much hardware with a few accelerators, so a bit of jargon. But, you know, we just have access to a larger ecosystem and much more silicon and all the good things that are coming with the cloud >>talk to us about some of the unique challenges of five G that make running it in the cloud so much more helpful. And then also, why did you decide to partner with AWS? Clearly you have choice, but I'd love to know the backstory on that. >>Yeah, I've been in the telco industry forever, and I've always seen that our speed of innovation was to slow. The telco is very good at reliability. You know, your phone always works. Um, it's very reliable. You can have massive traffic, but the speed of innovation is not fast enough. And the the applications that are coming on the clouds are much faster. So what we wanted to marry is the reliability of the telco and and all the knowledge that exists with the speed of the cloud. And that's what we're doing with bringing their ecosystem into our ecosystem to get the best of two worlds. >>Lots of transformation in the vertical industries. We heard from Adam today on stage vertical with ai machine learning. How does that apply in the telco world because it's an edge you got. See, sports stadiums, for instance. You're seeing all kinds of home impact. How is vertical specialisation? >>Yeah. So what is unique about the cloud is that you can observe a lot of things, you know, in the cloud you have access to data, so you see what's happening, and then you use a lot of algorithms. We call it Machine Learning Analytics to make decisions. Now, for us, it means if you're a stadium, you're going to have a much better visibility of what's happening. Where is the traffic? You know, people moving in and moving out? Are they going to buy some food awards? So you see the traffic and you can adapt the way you steal the traffic the way you distribute video, the way you distribute entertainment to how people are moving because you can observe what is happening in the network, which you can't do in a classic or legacy five g network. So once you observe, you can have plenty of ideas, right? And you can start innovation again, mix a lot of things and offer new services. >>In this last 22 months, when we saw this rapid pivot to work from home. And now it's work from anywhere, right? We talk about hybrid cloud hybrid events here, but this hybrid work environment talk to me about the impact that that decision A W s are going to have on all of those companies and people who are going to be remote and working from the edge for maybe permanently. >>Yes, you say, You know what is important is that people want to have access to the to the cloud to the services, the enterprise from wherever they are. So as a software architect, I need to make sure that we can follow them and offer that service from wherever they are in a similar manner today. If you're making a phone call, you don't have to think if you're connecting to the Web, you know, through WiFi through this and that, you have to think we want to make it as simple as making a phone call. In the past, where you always connected, you always secured. You always have access to your data. So that's really the ambition we have. And, of course, with the new remote abbots, the video conferencing that's the perfect time to come with a new offer. >>And the Strand also is moving towards policy based. You mentioned understanding video and patterns. Having that differentiated services capability in real time is a big deal. >>Yeah, that's a big deal. Actually, what enterprise want? They want to manage their policy, so they want to decide what traffic gets, a premium access and what traffic can be put in the background. You want to update your computers? Maybe that's not a premium price for that. You can do it at any time, but you want to have real time, customer service and support. You want premium? And who am I to decide for an enterprise? Enterprises want to decide. So what we offer them is the tools to create their policy, and their policy will be a competitive advantage for them when they can different change. >>And this brings up another point. I want to ask you. You brought this up earlier about this. The ideas, the creativity that enables with cloud you mentioned ideas will come out. These are this is where the developers now can really encode. This is the whole theme of this Pathfinders keynote. You were up on stage. This is a real opportunity to add value. Doing all the heavy lifting in the top of the stack and enabling new use cases, new applications, new expectations. >>You know what I tell to my engineers? My dream as an engineer is to be, uh, developer friendly. I want people to come to us because it's fun to work in our environment and try things. And a lot of the ideas that developers will have won't work. But if they can spin it off very fast, they will move to that killer application of killer service very fast. So my job is to bring that to them so that it's very easy to consume and and trying to live And, you know, just like bringing >>candy to a baby here. >>Yeah, cause right And have fun and, uh, and discover it for yourself and decide for yourself. >>I gotta ask your questions in the Telecom for a while. We've been seeing on the Cube earlier in our intro keynote analysis that we're now living in an era with SAS applications. No more shelf where now, with purpose built applications that you're seeing now and horizontally scalable, vertically integrated machine learning. You can't hide the ball anymore around what's working. You can't put a project out there and say no, you can't justify. You can't put you can put lipstick on that. You can't know you're seeing on >>that bad cake. Yeah, it's all the point of beta testing and market adoption. You try, you put it there. It works. You say the brake doesn't work. You try again, right? That's the way it works. And and in Telco, you're right. We were cooking for a year or two years, Three years and saying, Oh, you know what? That's what you need. It doesn't work like this faster now. Yeah, Yeah. And people want to be able to influence and they want to say, I like it. I don't like it. And the market is deciding. >>Speaking of influence, one of the things we know we talk a lot about with A W S and their guests is their customer. First customer obsession focused. You know, the whole reason we're here is that is to serve the customer, talk to me about how customers and joint customers are influencing some of the design choices that you guys are making as you're bringing five due to the cloud. >>So what is important for us? We have to dreams, right? The first one is for consumers. We want consumers to have access to the network so that they feel that they are VIP and often I know you and I, sometimes when we're connected to the network with tropical, we don't get the feeling where a V i p So that's something that's a journey for us to make people feel like they get the service and the network is following them and caring about them for the enterprises. You want to let them decide what they want. You were talking about policy building. They want to come with their own rating engine. They want to come with their own geographical maps. Like here. I have traffic here. I don't need coverage. So we want to open up so that the enterprise decide how they invest, how they spend the money on the network >>giving control back to the end user. Whether that's a consumer or enterprise, >>absolutely giving control to the end user and the enterprises. And we're there to support and accelerate the service for them. >>Mark, I want to ask you about leadership. You mentioned all these new things. Are there your dreams? And it's happening Giving engineers the canvas to paint their own future. It's gonna be fun is fun as you're affecting that change. What can people do as leaders to create that momentum to bring the whole organisation along is their tricks of the trade. Is their best practises >>Absolutely their best practises? Um, we were very much following develops where, you know, as a leader, you don't know, you're just learning and you're exposing and you're sharing. Uh, we're also creating an open world where we're asking all our partners to be open. Sometimes, you know, they feel like a bit challenge. Like, do I want to show what I'm doing? And I would say, Yeah, sure, because you're benefiting between each other. Um, And then you want to give tools to your engineers and your marketers to be fast speed, speed, speed, speed so that they can just play and learn. And at the end of the day, you said it. It's all about fun. You know, if it's fun, it's easy to do >>that. We're having fun here. >>That is true. We always have fun here. Last question for you is talk about some of the things that AWS announced this morning. Lots of stuff going on in Adam's keynote. What excites you about this continued partnership between AWS and Dish? >>Yeah, we were. We were surprised and so happy about AWS answer to when we came in with the first one to come big time in the telco and the Cloud was not ready. To be honest, it was Enterprise and Data Club and AWS. When is going all the way, we've asked to transform their cloud to make it a telco frantic, loud. So we have a lot of discussions about networking, routing, service level agreements and a lot of things that are very technical. And there are a true partner innovating with us. We have a road map with ideas and that's pretty unique. So, great partner, >>I was going to say it sounds like a really true >>trust and partnership. We're sharing ideas and challenging each other all the time, so that's really great. >>Awesome and users benefit consumers Benefit enterprises benefit Mark Thank you for joining Joining me on the programme today. Georgia Keynote enjoyed hearing more about dish and AWS. And what are you doing to power? The future. We appreciate your time. >>Thank you. Thank you >>for John Ferrier. I'm Lisa Martin. You're watching the Cube? The global leader in tech coverage, So mhm. Yeah.

(upbeat music) >> Welcome to theCube's continuous coverage of AWS re:Invent 2021. I'm Dave Nicholson, and we are running one of the industry's most important and largest hybrid tech events this year with AWS and its partners with two live sets on the scene. In addition to two remote studios. And we'll have somewhere in the neighborhood of a hundred guests on the program this year at re:Invent. I'm extremely delighted to welcome a very, very special guest. Right now. He served as the director of the NSA under two presidents, and was the first commander of the U.S Cyber Command. He's a Cube alumni, he's founder and co-CEO of IronNet Cybersecurity. General Keith Alexander. Thanks for joining us today General. >> Thanks, David. It's an honor to be here at re:Invent, you know, with AWS. All that they're doing and all they're making possible for us to defend sector states, companies and nations in cyber. So an honor to be here. >> Well, welcome back to theCube. Let's dive right in. I'd like to know how you would describe the current cyber threat landscape that we face. >> Well, I think it's growing. Well, let's start right out. You know, the good news or the bad news, the bad news is getting worse. We're seeing that. If you think about SolarWinds, you think about the Hafnium attacks on Microsoft. You think about this rapid growth in ransomware. We're seeing criminals and nation states engaging in ways that we've never seen in the past. It's more blatant. They're going after more quickly, they're using cyber as an element of national power. Let's break that down just a little bit. Do you go back to two, July. Xi Jinping, talked about breaking heads in bloodshed when he was referring to the United States and Taiwan. And this has gone hot and cold, that's a red line for him. They will do anything to keep Taiwan from breaking away. And this is a huge existential threat to us into the region. And when this comes up, they're going to use cyber to go after it. Perhaps even more important and closer right now is what's going on with Russia in the Donbas region of eastern Ukraine. We saw this in 2014, when Russia took over the Crimea. The way they did it, staging troops. They did that in 2008 against Georgia. And now there are, by some reports over a hundred thousand troops on the border of Eastern Ukraine. Some call it an exercise, but that's exactly what they did in Georgia. That's what they did in the Crimea. And in both those cases, they preceded those attacks, those physical attacks with cyber attacks. If you go to 2017, when Russia hit the Ukrainian government with the NotPetya attack that had global repercussions. Russia was responsible for SolarWinds, they have attacked our infrastructure to find out what our government is doing and they continue going. This is getting worse. You know, it's interesting when you think about, so what do you do about something like that? How do we stop that? And the answer is we've got to work together. You know, Its slam commissioner addressed it. The meeting with the president on August 25th. This is a great statement by the CEO and chairman of Southern Company, Tom Fanning. He said this, "the war is being waged on our nation's critical infrastructure in particular, our energy sector, our telecommunications sector and financial sector." The private sector owns and operates 87% of the critical infrastructure in the United States, making collaboration between industry and the federal government imperative too, for these attacks. SO >> General, I want to dig just a little bit on that point that you make for generations, people have understood that the term is 'kinetic war', right? Not everyone has heard that phrase, but for generations we've understood the concept of someone dropping a bomb on a building as being an attack. You've just mentioned that, that a lot of these attacks are directed towards the private sector. The private sector doesn't have an army to respond to those attacks. Number one, that's our government's responsibility. So the question I have is, how seriously are people taking these kinds of threats when compared to the threat of kinetic war? Because my gosh, you can take down the entire electrical grid now. That's not something you can do with a single bomb. What are your, what are your thoughts on that? >> So you're hitting on a key point, a theoretical and an operational point. If you look back, what's the intent of warfare? It's to get the mass of people to give up. The army protects the mass of people in that fight. In cyber, there's no protection. Our critical infrastructure is exposed to our adversaries. That's the problem that we face. And because it's exposed, we have a tremendous vulnerability. So those who wish us harm, imagine the Colonial Pipeline attack an order of magnitude or two orders of magnitude bigger. The impact on our country would paralyze much of what we do today. We are not ready for that. That's the issue that Tom Fanning and others have brought up. We don't practice between the public sector and the private sector working together to defend this country. We need to do that. That's the issue that we have to really get our hands around. And when we talk about practice, what do we mean? It means we have to let that federal government, the ones that are going to protect us, see what's going on. There is no radar picture. Now, since we're at re:Invent, the cloud, where AWS and others have done, is create an infrastructure that allows us to build that bridge between the public and private sector and scale it. It's amazing what we can now do. We couldn't do that when I was running Cyber Command. And running Cyber Command, we couldn't see threats on the government. And we couldn't see threats on critical infrastructure. We couldn't see threats on the private sector. And so it all went and all the government did was say, after the fact you've been attacked. That's not helpful. >> So >> It's like they dropped a bomb. We didn't know. >> Yeah, so what does IronNet doing to kind of create this radar capability? >> So, well, thanks. That's a great question because there's four things that you really got to do. First. You've got to be able to detect the SolarWinds type attacks, which we did. You've got to have a hunt platform that can see what it is. You've got to be able to use machine learning and AI to really cut down the number of events. And the most important you need to be able to anonymize and share that into the cloud and see where those attacks are going to create that radar picture. So behavioral analytics, then you use signature based as well, but you need those sets of analytics to really see what's going on. Machine learning, AI, a hunt platform, and cloud. And then analytics in the cloud to see what's going on, creates that air traffic control, picture radar, picture for cyber. That's what we're doing. You see, I think that's the important part. And that's why we really value the partnership with AWS. They've been a partner with us for six years, helping us build through that. You can see what we can do in the cloud. We could never do in hardware alone. Just imagine trying to push out equipment and then do that for hundreds of companies. It's not viable. So SaaS, what we are as a SaaS company, you can now do that at scale, and you can push this out and we can create, we can defend this nation in cyber if we work together. And that's the thing, you know, I really, had a great time in the military. One of the things I learned in the military, you need to train how you're going to fight. They're really good at that. We did that in the eighties, and you can see what happened in 1990 in the Gulf war. We need to now do that between the public and private sector. We have to have those training. We need to continuously uplift our capabilities. And that's where the cloud and all these other things make that possible. That's the future of cybersecurity. You know, it's interesting David, our country developed the internet. We're the ones that pioneered that. We ought to be the first to secure. >> Seems to make sense. And when you talk about collective defense in this private public partnership, that needs to happen, you get examples of some folks in private industry and what they're doing, but, but talk a little bit more about, maybe what isn't happening yet. What do we need to do? I don't want you to necessarily get political and start making budgetary suggestions, but unless you want to, but what, but where do you see, where do we really need to push forward from a public perspective in order to make these connections? And then how is that connection actually happen? This isn't someone from the IronNet security service desk, getting on a red phone and calling the White House, how are the actual connections made? >> So it has to be, the connections have to be just like we do radar. You know, when you think about radars across our nation or radar operator doesn't call up one of the towers and say, you've got an aircraft coming at you at such and such a speed. I hope you can distinguish between those two aircraft and make sure they don't bump into each other. They get a picture and they get a way of tracking it. And multiple people can see that radar picture at a speed. And that's how we do air traffic control safety. We need the same thing in cyber, where the government has a picture. The private sector has a picture and they can see what's going on. The private sector's role is I'm going to do everything I can, you know, and this is where the energy sector, I use that quote from Tom Fanning, because what they're saying is, "it's our job to keep the grid up." And they're putting the resources to do it. So they're actually jumping on that in a great way. And what they're saying is "we'll share that with the government", both the DHS and DOD. Now we have to have that same picture created for DHS and DOD. I think one of the things that we're doing is we're pioneering the building of that picture. So that's what we do. We build the picture to bring people together. So think of that is that's the capability. Everybody's going to own a piece of that, and everybody's going to be operating in it. But if you can share that picture, what you can begin to do is say, I've got an attack coming against company A. Company A now sees what it has to do. It can get fellow companies to help them defend, collective defense, knowledge sharing, crowdsourcing. At the same time, the government can see that attack going on and say, "my job is to stop that." If it's DHS, I could see what I have to do. Within the country, DOD can say, "my job is to shoot the archers." How do we go do what we're authorized to do under rules of engagement? So now you have a way of the government and the private sector working together to create that picture. Then we train them and we train them. We should never have had an event like SolarWinds happen in the future. We got to get out in front. And if we do that, think of the downstream consequences, not only can we detect who's doing it, we can hold them accountable and make them pay a price. Right now. It's pretty free. They get in, pap, that didn't work. They get away free. That didn't work, we get away free. Or we broke in, we got, what? 18,000 companies in 30,000 companies. No consequences. In the future there should be consequences. >> And in addition to the idea of consequences, you know, in the tech sector, we have this concept of a co-op petition, where we're often cooperating and competing. The adversaries from, U.S perspective are also great partners, trading partners. So in a sense, it sounds like what you're doing is also kind of adhering to the old adage that, that good fences make for great neighbors. If we all know that our respective infrastructures are secure, we can sort of get on with the honest business of being partners, because you want to make the cost of cyber war too expensive. Is that, is that a fair statement? >> Yes. And I would take that analogy and bend it slightly to the following. Today every company defends itself. So you take 90 companies with 10 people, each doing everything they can to defend themselves. Imagine in the world we trying to build, those 90 companies work together. You have now 900 people working together for the collective defense. If you're in the C-suite or the board of those companies, which would rather have? 900 help new security or 10? This isn't hard. And so what we say is, yes. That neighborhood watch program for cyber has tremendous value. And beyond neighborhood watch, I can also share collaboration because, I might not have the best people in every area of cyber, but in those 900, there will be, and we can share knowledge crowdsource. So it's actually let's work together. I would call it Americans working together to defend America. That's what we need to do. And the states we going to have a similar thing what they're doing, and that's how we'll work this together. >> Yeah. That makes a lot of sense. General Alexander it's been a pleasure. Thanks so much for coming on to theCube as part of our 2021 AWS re:Invent coverage. Are you going to get a chance to spend time during the conference in Las Vegas? So you just flying in, flying out. Any chance? >> Actually yeah. >> It's there, we're still negotiating working that. I've registered, but I just don't know I'm in New York city for two meetings and seeing if I can get to Las Vegas. A lot of friends, you know, Adam Solski >> Yes >> and the entire AWS team. They're amazing. And we really liked this partnership. I'd love to see you there. You're going to be there, David? Absolutely. Yes, absolutely. And I look forward to that, so I hope hopefully we get that chance again. Thank you so much, General Alexander, and also thank you to our title sponsor AMD for sponsoring this year's re:Invent. Keep it right here for more action on theCube, you're leader in hybrid tech event coverage, I'm Dave Nicholson for the Cube. Thanks. (upbeat music)

>>Earlier this week, Oracle announced the new X nine M generation of exit data platforms for its cloud at customer and legacy on prem deployments. And the company made some enhancements to its zero data loss, recovery appliance. CLRA something we've covered quite often since its announcement. We had a video exclusive with one Louisa who was the executive vice president of mission critical database technologies. At Oracle. We did that on the day of the announcement who got his take on it. And I asked Oracle, Hey, can we get some subject matter experts, some technical gurus to dig deeper and get more details on the architecture because we want to better understand some of the performance claims that Oracle is making. And with me today is Susan. Who's the vice president of product management for exit data database machine. Bob tome is the vice president of product management for exit data cloud at customer. And Tim chin is the senior director of product management for DRA folks. Welcome to this power panel and welcome to the cube. >>Thank you, Dave. >>Can we start with you? Um, Juan and I, we talked about the X nine M a that Oracle just launched a couple of days ago. Maybe you could give us a recap, some of the, what do we need to know? The, especially I'm interested in the big numbers once more so we can just understand the claims you're making around this announcement. We can dig into that. >>Absolutely. They've very excited to do that. In a nutshell, we have the world's fastest database machine for both LTP and analytics, and we made that even faster, not just simply faster, but for all LPP we made it 70% faster and we took the oil PPV ops all the way up to 27.6 million read IOPS and mind you, this is being measured at the sequel layer for analytics. We did pretty much the same thing, an 87% increase in analytics. And we broke through that one terabyte per second barrier, absolutely phenomenal stuff. Now, while all those numbers by themselves are fascinating, here's something that's even more fascinating in my mind, 80% of the product development work for extra data, X nine M was done during COVID, which means all of us were remote. And what that meant was extreme levels of teamwork between the development teams, manufacturing teams, procurement teams, software teams, the works. I mean, everybody coming together as one to deliver this product, I think it's kudos to everybody who touched this product in one way or the other extremely proud of it. >>Thank you for making that point. And I'm laughing because it's like you the same bolt of a mission-critical OLT T O LTP performance. You had the world record, and now you're saying, adding on top of that. Um, but, okay. But, so there are customers that still, you know, build the builder and they're trying to build their own exit data. What they do is they buy their own servers and storage and networking components. And I do that when I talk to them, they'll say, look, they want to maintain their independence. They don't want to get locked in Oracle, or maybe they believe it's cheaper. You know, maybe they're sort of focused on the, the, the CapEx the CFO has him in the headlock, or they might, sometimes they talk about, they want a platform that can support, you know, horizontal, uh, apps, maybe not Oracle stuff, or, or maybe they're just trying to preserve their job. I don't know, but why shouldn't these customers roll their own and why can't they get similar results just using standard off the shelf technologies? >>Great question. It's going to require a little involved answer, but let's just look at the statistics to begin with. Oracle's exit data was first productized in Delaware to the market in 2008. And at that point in time itself, we had industry leadership across a number of metrics. Today, we are at the 11th generation of exit data, and we are way far ahead than the competition, like 50 X, faster hundred X faster, right? I mean, we are talking orders of magnitude faster. How did we achieve this? And I think the answer to your question is going to lie in what are we doing at the engineering level to make these magical numbers come to, uh, for right first, it starts with the hardware. Oracle has its own hardware server design team, where we are embedding in capabilities towards increasing performance, reliability, security, and scalability down at the hardware level, the database, which is a user level process talks to the hardware directly. >>The only reason we can do this is because we own the source code for pretty much everything in between, starting with the database, going into the operating system, the hypervisor. And as I, as I just mentioned the hardware, and then we also worked with the former elements on this entire thing, the key to making extra data, the best Oracle database machine lies in that engineering, where we take the operating system, make it fit like tongue and groove into, uh, a bit with the opera, with the hardware, and then do the same with the database. And because we have got this deep insight into what are the workloads that are, that are running at any given point in time on the compute side of extra data, we can then do micromanagement at the software layers of how traffic flows are flowing through the entire system and do things like, you know, prioritize all PP transactions on a very specific, uh, you know, queue on the RDMA. >>We'll converse Ethan at be able to do smart scan, use the compute elements in the storage tier to be able to offload SQL processing. They call them the longer I used formats of data, extend them into flash, just a whole bunch of things that we've been doing over the last 12 years, because we have this deep engineering, you can try to cobble a system together, which sort of looks like an extra data. It's got a network and it's got storage, tiering compute here, but you're not going to be able to achieve anything close to what we are doing. The biggest deal in my mind, apart from the performance and the high availability is the security, because we are testing the stack top to bottom. When you're trying to build your own best of breed kind of stuff. You're not going to be able to do that because it depended on the server that had to do something and HP to do something else or Dell to do something else and a Brocade switch to do something it's not possible. We can do this, we've done it. We've proven it. We've delivered it for over a decade. End of story. For as far as I'm concerned, >>I mean, you know, at this fine, remember when Oracle purchased Sohn and I know a big part of that purchase was to get Java, but I remember saying at the time it was a brilliant acquisition. I was looking at it from a financial standpoint. I think you paid seven and a half billion for it. And it automatically, when you're, when Safra was able to get back to sort of pre acquisition margins, you got the Oracle uplift in terms of revenue multiples. So then that standpoint, it was a no brainer, but the other thing is back in the Unix days, it was like HP. Oracle was the standard. And, and in terms of all the benchmarks and performance, but even then, I'm sure you work closely with HP, but it was like to get the stuff to work together, you know, make sure that it was going to be able to recover according to your standards, but you couldn't actually do that deep engineering that you just described now earlier, Subin you, you, you, you stated that the X sign now in M you get, oh, LTP IO, IOP reads at 27 million IOPS. Uh, you got 19 microseconds latency, so pretty impressive stuff, impressive numbers. And you kind of just went there. Um, but how are you measuring these numbers versus other performance claims from your competitors? What what's, you know, are you, are you stacking the deck? Can you give you share with us there? >>Sure. So Shada incidents, we are mentioning it at the sequel layer. This is not some kind of an ion meter or a micro benchmark. That's looking at just a flash subsystem or just a persistent memory subsystem. This is measured at the compute, not doing an entire set of transactions. And how many times can you finish that? Right? So that's how it's being measured. Now. Most people cannot measure it like that because of the disparity and the number of vendors that are involved in that particular solution, right? You've got servers from vendor a and storage from vendor B, the storage network from vendor C, the operating system from vendor D. How do you tune all of these things on your own? You cannot write. I mean, there's only certain bells and whistles and knobs that are available for you to tune, but so that's how we are measuring the 19 microseconds is at the sequel layer. >>What that means is this a real world customer running a real world. Workload is guaranteed to get that kind of a latency. None of the other suppliers can make that claim. This is the real world capability. Now let's take a look at that 19 microseconds we boast and we say, Hey, we had an order of magnitude two orders of magnitude faster than everybody else. When it comes down to latency. And one things that this is we'll do our magic while it is magical. The magic is really grounded in deep engineering and deep physics and science. The way we implement this is we, first of all, put the persistent memory tier in the storage. And that way it's shared across all of the database instances that are running on the compute tier. Then we have this ultra fast hundred gigabit ethernet RDMA over converged ethernet fabric. >>With this, what we have been able to do is at the hardware level between two network interface guides that are resident on that fabric, we create paths that enable high priority low-latency communication between any two end points on that fabric. And then given the fact that we implemented persistent memory in the storage tier, what that means is with that persistent memory, sitting on the memory bus of the processor in the storage tier, we can perform it remote direct memory access operation from the compute tier to memory address spaces in the persistent memory of the storage tier, without the involvement of the operating system on either end, no context, switches, knowing processing latencies and all of that. So it's hardware to hardware, communication with security built in, which is immutable, right? So all of this is built into the hardware itself. So there's no software involved. You perform a read, the data comes back 19 microseconds, boom. End of story. >>Yeah. So that's key to my next topic, which is security because if you're not getting the OSTP involved and that's, you know, very oftentimes if I can get access to the OSTP, I get privileged. Like I can really take advantage of that as a hacker. But so, but, but before I go there, like Oracle talks about, it's got a huge percentage of the Gayety 7% of the fortune 100 companies run their mission, critical workloads on exit data. But so that's not only important to the companies, but they're serving consumer me, right. I'm going to my ATM or I'm swiping my credit card. And Juan mentioned that you use a layered security model. I just sort of inferred anyway, that, that having this stuff in hardware and not have to involve access to the OS actually contributes to better security. But can you describe this in a bit more detail? >>So yeah, what Brian was talking about was this layered security set differently. It is defense in depth, and that's been our mantra and philosophy for several years now. So what does that entail? As I mentioned earlier, we designed our own servers. We do this for performance. We also do it for security. We've got a number of features that are built into the hardware that make sure that we've got immutable areas of form where we, for instance, let me give you this example. If you take an article x86 server, just a standard x86 server, not even express in the form of an extra data system, even if you had super user privileges sitting on top of an operating system, you cannot modify the bias as a user, as a super user that has to be done through the system management network. So we put gates and protection modes, et cetera, right in the hardware itself. >>Now, of course the security of that hardware goes all the way back to the fact that we own the design. We've got a global supply chain, but we are making sure that our supply chain is protected monitored. And, uh, we also protect the last mile of the supply chain, which is we can detect if there's been any tampering of form where that's been, uh, that's occurred in the hardware while the hardware shipped from our factory to the customers, uh, docks. Right? So we, we know that something's been tampered with the moment it comes back up on the customer. So that's on the hardware. Let's take a look at the operating system, Oracle Linux, we own article the next, the entire source code. And what shipping on exit data is the unbreakable enterprise Connell, the carnal and the operating system itself have been reduced in terms of eliminating all unnecessary packages from that operating system bundle. >>When we deliver it in the form of the data, let's put some real numbers on that. A standard Oracle Linux or a standard Linux distribution has got about 5,000 plus packages. These things include like print servers, web servers, a whole bunch of stuff that you're not absolutely going to use at all on exit data. Why ship those? Because the moment you ship more stuff than you need, you are increasing the, uh, the target, uh, that attackers can get to. So on AXA data, there are only 701 packages. So compare this 5,413 packages on a standard Linux, 701 and exit data. So we reduced the attack surface another aspect on this, when we, we do our own STIG, uh, ASCAP benchmarking. If you take a standard Linux and you run that ASCAP benchmark, you'll get about a 30% pass score on exit data. It's 90 plus percent. >>So which means we are doing the heavy lifting of doing the security checks on the operating system before it even goes out to the factory. And then you layer on Oracle database, transparent data encryption. We've got all kinds of protection capabilities, data reduction, being able to do an authentication on a user ID basis, being able to log it, being able to track it, being able to determine who access the system when and log back. So it's basically defend at every single layer. And then of course the customer's responsibility. It doesn't just stop by getting this high secure, uh, environment. They have to do their own job of them securing their network perimeters, securing who has physical access to the system and everything else. So it's a giant responsibility. And as you mentioned, you know, you as a consumer going to an ATM machine and withdrawing money, you would do 200. You don't want to see 5,000 deducted from your account. And so all of this is made possible with exited and the amount of security focus that we have on the system >>And the bank doesn't want to see it the other way. So I'm geeking out here in the cube, but I got one more question for you. Juan talked about X nine M best system for database consolidation. So I, I kinda, you know, it was built to handle all LTP analytics, et cetera. So I want to push you a little bit on this because I can make an argument that, that this is kind of a Swiss army knife versus the best screwdriver or the best knife. How do you respond to that concern and how, how do you respond to the concern that you're putting too many eggs in one basket? Like, what do you tell people to fear you're consolidating workloads to save money, but you're also narrowing the blast radius. Isn't that a problem? >>Very good question there. So, yes. So this is an interesting problem, and it is a balancing act. As you correctly pointed out, you want to have the economies of scale that you get when you consolidate more and more databases, but at the same time, when something happens when hardware fails or there's an attack, you want to make sure that you have business continuity. So what we are doing on exit data, first of all, as I mentioned, we are designing our own hardware and a building in reliability into the system and at the hardware layer, that means having redundancy, redundancy for fans, power supplies. We even have the ability to isolate faulty cores on the processor. And we've got this a tremendous amount of sweeping that's going on by the system management stack, looking for problem areas and trying to contain them as much as possible within the hardware itself. >>Then you take it up to the software layer. We used our reliability to then build high availability. What that implies is, and that's fundamental to the exited architecture is this entire scale out model, our based system, you cannot go smaller than having two database nodes and three storage cells. Why is that? That's because you want to have high availability of your database instances. So if something happens to one server hardware, software, whatever you got another server that's ready to take on that load. And then with real application clusters, you can then switch over between these two, why three storage cells. We want to make sure that when you have got duplicate copies of data, because you at least want to have one additional copy of your data in case something happens to the disc that has got that only that one copy, right? So the reason we have got three is because then you can Stripe data across these three different servers and deliver high availability. >>Now you take that up to the rack level. A lot of things happen. Now, when you're really talking about the blast radius, you want to make sure that if something physically happens to this data center, that you have infrastructure that's available for it to function for business continuity, we maintain, which is why we have the maximum availability architecture. So with components like golden gate and active data guard, and other ways by which we can keep to this distant systems in sync is extremely critical for us to deliver these high availability paths that make, uh, the whole equation about how many eggs in one basket versus containing the containment of the blast radius. A lot easier to grapple with because business continuity is something which is paramount to us. I mean, Oracle, the enterprise is running on Xcel data. Our high value cloud customers are running on extra data. And I'm sure Bob's going to talk a lot more about the cloud piece of it. So I think we have all the tools in place to, to go after that optimization on how many eggs in one basket was his blast radius. It's a question of working through the solution and the criticalities of that particular instance. >>Okay, great. Thank you for that detailed soup. We're going to give you a break. You go take a breath, get a, get a drink of water. Maybe we'll come back to you. If we have time, let's go to Bob, Bob, Bob tome, X data cloud at customer X nine M earlier this week, Juan said kinda, kinda cocky. What we're bothering, comparing exit data against your cloud, a customer against outpost or Azure stack. Can you elaborate on, on why that is? >>Sure. Or you, you know, first of all, I want to say, I love, I love baby. We go south posts. You know why it affirms everything that we've been doing for the past four and a half years with clouded customer. It affirms that cloud is running that running cloud services in customers' data center is a large and important market, large and important enough that AWS felt that the need provide these, um, you know, these customers with an AWS option, even if it only supports a sliver of the functionality that they provide in the public cloud. And that's what they're doing. They're giving it a sliver and they're not exactly leading with the best they could offer. So for that reason, you know, that reason alone, there's really nothing to compare. And so we, we give them the benefit of the doubt and we actually are using their public cloud solutions. >>Another point most customers are looking to deploy to Oracle cloud, a customer they're looking for a per performance, scalable, secure, and highly available platform to deploy. What's offered their most critical databases. Most often they are Oracle databases does outposts for an Oracle database. No. Does outpost run a comparable database? Not really does outposts run Amazon's top OTP and analytics database services, the ones that are top in their cloud public cloud. No, that we couldn't find anything that runs outposts that's worth comparing against X data clouded customer, which is why the comparisons are against their public cloud products. And even with that still we're looking at numbers like 50 times a hundred times slower, right? So then there's the Azure stack. One of the key benefits to, um, you know, that customers love about the cloud that I think is really under, appreciated it under appreciated is really that it's a single vendor solution, right? You have a problem with cloud service could be I as pass SAS doesn't matter. And there's a single vendor responsible for fixing your issue as your stack is missing big here, because they're a multi-vendor cloud solution like AWS outposts. Also, they don't exactly offer the same services in the cloud that they offer on prem. And from what I hear, it can be a management nightmare requiring specialized administrators to keep that beast running. >>Okay. So, well, thanks for that. I'll I'll grant you that, first of all, granted that Oracle was the first with that same, same vision. I always tell people that, you know, if they say, well, we were first I'm like, well, actually, no, Oracle's first having said that, Bob and I hear you that, that right now, outpost is a one Datto version. It doesn't have all the bells and whistles, but neither did your cloud when you first launched your cloud. So let's, let's let it bake for a while and we'll come back in a couple of years and see how things compare. So if you're up for it. Yeah. >>Just remember that we're still in the oven too. Right. >>Okay. All right. Good. I love it. I love the, the chutzpah. One also talked about Deutsche bank. Um, and that, I, I mean, I saw that Deutsche bank announcement, how they're working with Oracle, they're modernizing their infrastructure around database. They're building other services around that and kind of building their own sort of version of a cloud for their customers. How does exit data cloud a customer fit in to that whole Deutsche bank deal? Is, is this solution unique to Deutsche bank? Do you see other organizations adopting clouded customer for similar reasons and use cases? >>Yeah, I'll start with that. First. I want to say that I don't think Georgia bank is unique. They want what all customers want. They want to be able to run their most important workloads. The ones today running their data center on exit eight as a non other high-end systems in a cloud environment where they can benefit from things like cloud economics, cloud operations, cloud automations, but they can't move to public cloud. They need to maintain the service levels, the performance, the scalability of the security and the availability that their business has. It has come to depend on most clouds can't provide that. Although actually Oracle's cloud can our public cloud Ken, because our public cloud does run exit data, but still even with that, they can't do it because as a bank, they're subject to lots of rules and regulations, they cannot move their 40 petabytes of data to a point outside the control of their data center. >>They have thousands of interconnected databases, right? And applications. It's like a rat's nest, right? And this is similar many large customers have this problem. How do you move that to the cloud? You can move it piecemeal. Uh, I'm going to move these apps and, you know, not move those apps. Um, but suddenly ended up with these things where some pieces are up here. Some pieces are down here. The thing just dies because of the long latency over a land connection, it just doesn't work. Right. So you can also shut it down. Let's shut it down on, on Friday and move everything all at once. Unfortunately, when you're looking at it, a state decides that most customers have, you're not going to be able to, you're going to be down for a month, right? Who can, who can tolerate that? So it's a big challenge and exited cloud a customer let's then move to the cloud without losing control of their data. >>And without unhappy having to untangle that thousands of interconnected databases. So, you know, that's why these customers are choosing X data, clouded customer. More importantly, it sets them up for the future with exited cloud at customer, they can run not just in their data center, but they could also run in public cloud, adjacent sites, giving them a path to moving some work out of the data center and ultimately into the public cloud. You know, as I said, they're not unique. Other banks are watching and some are acting and it's not just banks. Just last week. Telefonica telco in Spain announced their intent to migrate the bulk of their Oracle databases to excavate a cloud at customer. This will be the key cloud platform running. They're running in their data center to support both new services, as well as mission critical and operational systems. And one last important point exited cloud a customer can also run autonomous database. Even if customers aren't today ready to adopt this. A lot of them are interested in it. They see it as a key piece of the puzzle moving forward in the future and customers know that they can easily start to migrate to autonomous in the future as they're ready. And this of course is going to drive additional efficiencies and additional cost savings. >>So, Bob, I got a question for you because you know, Oracle's playing both sides, right? You've got a cloud, you know, you've got a true public cloud now. And, and obviously you have a huge on-premise state. When I talk to companies that don't own a cloud, uh, whether it's Dell or HPE, Cisco, et cetera, they have made, they make the point. And I agree with them by the way that the world is hybrid, not everything's going into the, to the cloud. However, I had a lot of respect for folks at Amazon as well. And they believed long-term, they'll say this, they've got them on record of saying this, that they believe long-term ultimately all workloads are going to be running in the cloud. Now, I guess it depends on how you define the cloud. The cloud is expanding and all that other stuff. But my question to you, because again, you kind of on both sides, here are our hybrid solutions like cloud at customer. Do you see them as a stepping stone to the cloud, or is cloud in your data center, sort of a continuous sort of permanent, you know, essential play >>That. That's a great question. As I recall, people debated this a few years back when we first introduced clouded customer. And at that point, some people I'm talking about even internal Oracle, right? Some people saw this as a stop gap measure to let people leverage cloud benefits until they're really ready for the public cloud. But I think over the past four and a half years, the changing the thinking has changed a little bit on this. And everyone kind of agrees that clouded customer may be a stepping stone for some customers, but others see that as the end game, right? Not every workload can run in the public cloud, not at least not given the, um, you know, today's regulations and the issues that are faced by many of these regulated industries. These industries move very, very slowly and customers are content to, and in many cases required to retain complete control of their data and they will be running under their control. They'll be running with that data under their control and the data center for the foreseeable future. >>Oh, I got another question for kind of just, if I could take a little tangent, cause the other thing I hear from the, on the, the, the on-prem don't own, the cloud folks is it's actually cheaper to run in on-prem, uh, because they're getting better at automation, et cetera. When you get the exact opposite from the cloud guys, they roll their eyes. Are you kidding me? It's way cheaper to run it in the cloud, which is more cost-effective is it one of those? It depends, Bob. >>Um, you know, the great thing about numbers is you can make, you can, you can kind of twist them to show anything that you want, right? That's a have spreadsheet. Can I, can, I can sell you on anything? Um, I think that there's, there's customers who look at it and they say, oh, on-premise sheet is cheaper. And there's customers who look at it and say, the cloud is cheaper. If you, um, you know, there's a lot of ways that you may incur savings in the cloud. A lot of it has to do with the cloud economics, the ability to pay for what you're using and only what you're using. If you were to kind of, you know, if you, if you size something for your peak workload and then, you know, on prem, you probably put a little bit of a buffer in it, right? >>If you size everything for that, you're gonna find that you're paying, you know, this much, right? All the time you're paying for peak workload all the time with the cloud, of course, we support scaling up, scaling down. We supply, we support you're paying for what you use and you can scale up and scale down. That's where the big savings is now. There's also additional savings associated with you. Don't have the cloud vendors like work. Well, we manage that infrastructure for you. You no longer have to worry about it. Um, we have a lot of automation, things that you use to either, you know, probably what used to happen is you used to have to spend hours and hours or years or whatever, scripting these things yourselves. We now have this automation to do it. We have, um, you eyes that make things ad hoc things, as simple as point and click and, uh, you know, that eliminates errors. And, and it's often difficult to put a cost on those things. And I think the more enlightened customers can put a cost on all of those. So the people that were saying it's cheaper to run on prem, uh, they, they either, you know, have a very stable workload that never changes and their environment never changes, um, or more likely. They just really haven't thought through the, all the hidden costs out there. >>All right, you got some new features. Thank you for that. By the way, you got some new features in, in cloud, a customer, a what are those? Do I have to upgrade to X nine M to, to get >>All right. So, you know, we're always introducing new features for clouded customer, but two significant things that we've rolled out recently are operator access control and elastic storage expansion. As we discussed, many organizations are using Axeda cloud a customer they're attracting the cloud economics, the operational benefits, but they're required by regulations to retain control and visibility of their data, as well as any infrastructure that sits inside their data center with operator access control, enabled cloud operations, staff members must request access to a customer system, a customer, it team grants, a designated person, specific access to a specific component for a specific period of time with specific privileges, they can then kind of view audit controls in real time. And if they see something they don't like, you know, Hey, what's this guy doing? It looks like he's, he's stealing my data or doing something I don't like, boom. >>They can kill that operators, access the session, the connections, everything right away. And this gives everyone, especially customers that need to, you know, regulate remote access to their infrastructure. It gives them the confidence that they need to use exit data cloud, uh, conduct, customer service. And, and the other thing that's new is, um, elastic storage expansion. Customers could out add additional service to their system either at initial deployment or after the fact. And this really provides two important benefits. The first is that they can right size their configuration if they need only the minimum compute capacity, but they don't need the maximum number of storage servers to get that capacity. They don't need to subscribe to kind of a fixed shape. We used to have fixed shapes, I guess, with hundreds of unnecessary database cores, just to get the storage capacity, they can select a smaller system. >>And then incrementally add on that storage. The second benefit is the, is kind of key for many customers. You are at a storage, guess what you can add more. And that way, when you're out of storage, that's really important. Now they'll get to your last part of that question. Do you need a deck, a new, uh, exit aquatic customer XIM system to get these features? No they're available for all gen two exited clouded customer systems. That's really one of the best things about cloud. The service you subscribed to today just keeps getting better and better. And unless there's some technical limitation that, you know, we, and it, which is rare, most new features are available even for the oldest cloud customer systems. >>Cool. And you can bring that in on from my, my last question for you, Bob is a, another one on security. Obviously, again, we talked to Susan about this. It's a big deal. How can customer data be secure if it's in the cloud, if somebody, other than the, their own vetted employees are managing the underlying infrastructure, is is that a concern you hear a lot and how do you handle that? >>You know, it's, it's only something because a lot of these customers, they have big, you know, security people and it's their job to be concerned about that kind of stuff. And security. However, is one of the biggest, but least appreciate appreciated benefits of cloud cloud vendors, such as Oracle hire the best and brightest security experts to ensure that their clouds are secure. Something that only the largest customers can afford to do. You're a small, small shop. You're not going to be able to, you know, hire some of this expertise. So you're better off being in the cloud. Customers who are running in the Oracle cloud can also use articles, data, safe tool, which we provide, which basically lets you inspect your databases, insurance. Sure that everything is locked down and secure and your data is secure. But your question is actually a little bit different. >>It was about potential internal threats to company's data. Given the cloud vendor, not the customer's employees have access to the infrastructure that sits beneath the databases and really the first and most important thing we do to protect customers' data is we encrypt that database by default. Actually Subin listed a whole laundry list of things, but that's the one thing I want to point out. We encrypt your database. It's, you know, it's, it's encrypted. Yes. It sits on our infrastructure. Yes. Our operations persons can actually see those data files sitting on the infrastructure, but guess what? They can't see the data. The data is encrypted. All they see as kind of a big encrypted blob. Um, so they can't access the data themselves. And you know, as you'd expect, we have very tight controls over operations access to the infrastructure. They need to securely log in using mechanisms by stuff to present, prevent unauthorized access. >>And then all access is logged and suspicious. Activities are investigated, but that still may not be enough for some customers, especially the ones I mentioned earlier, the regulated industries. And that's why we offer app operator access control. As I mentioned, that gives customers complete control over the access to the infrastructure. The, when the, what ops can do, how long can they do it? Customers can monitor in real time. And if they see something they don't like they stop it immediately. Lastly, I just want to mention Oracle's data ball feature. This prevents administrators from accessing data, protecting data from road operators, robot, world operations, whether they be from Oracle or from the customer's own it staff, this database option. A lot of ball is sorry. Database ball data vault is included when running a license included service on exited clouded customer. So basically to get it with the service. Got it. >>Hi Tom. Thank you so much. It's unbelievable, Bob. I mean, we've got a lot to unpack there, but uh, we're going to give you a break now and go to Tim, Tim chin, zero data loss, recovery appliance. We always love that name. The big guy we think named it, but nobody will tell us, but we've been talking about security. There's been a lot of news around ransomware attacks. Every industry around the globe, any knucklehead with, uh, with a high school diploma could become a ransomware attack or go in the dark web, get, get ransomware as a service stick, a, put a stick in and take a piece of the VIG and hopefully get arrested. Um, with, when you think about database, how do you deal with the ransomware challenge? >>Yeah, Dave, um, that's an extremely important and timely question. Um, we are hearing this from our customers. We just talk about ha and backup strategies and ransomware, um, has been coming up more and more. Um, and the unfortunate thing that these ransoms are actually paid, um, uh, in the hope of the re you know, the, uh, the ability to access the data again. So what that means it tells me is that today's recovery solutions and processes are not sufficient to get these systems back in a reliable and timely manner. Um, and so you have to pay the ransom, right, to get, uh, to get the, even a hope of getting the data back now for databases. This can have a huge impact because we're talking about transactional workloads. And so even a compromise of just a few minutes, a blip, um, can affect hundreds or even thousands of transactions. This can literally represent hundreds of lost orders, right? If you're a big manufacturing company or even like millions of dollars worth of, uh, financial transactions in a bank. Right. Um, and that's why protecting databases at a transaction level is especially critical, um, for ransomware. And that's a huge contrast to traditional backup approaches. Okay. >>So how do you approach that? What do you, what do you do specifically for ransomware protection for the database? >>Yeah, so we have the zero data loss recovery appliance, which we announced the X nine M generation. Um, it is really the only solution in the market, which offers that transaction level of protection, which allows all transactions to be recovered with zero RPO, zero again, and this is only possible because Oracle has very innovative and unique technology called real-time redo, which captures all the transactional changes from the databases by the appliance, and then stored as well by the appliance, moreover, the appliance validates all these backups and reading. So you want to make sure that you can recover them after you've sent them, right? So it's not just a file level integrity check on a file system. That's actual database level of validation that the Oracle blocks and the redo that I mentioned can be restored and recovered as a usable database, any kind of, um, malicious attack or modification of that backup data and transmit that, or if it's even stored on the appliance and it was compromised would be immediately detected and reported by that validation. >>So this allows administrators to take action. This is removing that system from the network. And so it's a huge leap in terms of what customers can get today. The last thing I just want to point out is we call our cyber vault deployment, right? Um, a lot of customers in the industry are creating what we call air gapped environments, where they have a separate location where their backup copies are stored physically network separated from the production systems. And so this prevents ransomware for possibly infiltrating that last good copy of backups. So you can deploy recovery appliance in a cyber vault and have it synchronized at random times when the network's available, uh, to, to keep it in sync. Right. Um, so that combined with our transaction level zero data loss validation, it's a nice package and really a game changer in protecting and recovering your databases from modern day cyber threats. >>Okay, great. Thank you for clarifying that air gap piece. Cause I, there was some confusion about that. Every data protection and backup company that I know as a ransomware solution, it's like the hottest topic going, you got newer players in, in, in recovery and backup like rubric Cohesity. They raised a ton of dough. Dell has got solutions, HPE just acquired Zerto to deal with this problem. And other things IBM has got stuff. Veem seems to be doing pretty well. Veritas got a range of, of recovery solutions. They're sort of all out there. What's your take on these and their strategy and how do you differentiate? >>Yeah, it's a pretty crowded market, like you said. Um, I think the first thing you really have to keep in mind and understand that these vendors, these new and up and coming, um, uh, uh, vendors start in the copy data management, we call CDN space and they're not traditional backup recovery designed are purpose built for the purpose of CDM products is to provide these fast point in time copies for test dev non-production use, and that's a viable problem and it needs a solution. So you create these one time copy and then you create snapshots. Um, after you apply these incremental changes to that copy, and then the snapshot can be quickly restored and presented as like it's a fully populated, uh, file. And this is all done through the underlying storage of block pointers. So all of this kind of sounds really cool and modern, right? It's like new and upcoming and lots of people in the market doing this. Well, it's really not that modern because we've, we know storage, snapshot technologies has been around for years. Right. Um, what these new vendors have been doing is essentially repackaging the old technology for backup and recovery use cases and having sort of an easier to use automation interface wrapped around it. >>Yeah. So you mentioned a copy data management, uh, last year, active FIO. Uh, they started that whole space from what I recall at one point there, they value more than a billion dollars. They were acquired by Google. Uh, and as I say, they kind of created that, that category. So fast forward a little bit, nine months a year, whatever it's been, do you see that Google active FIO offer in, in, in customer engagements? Is that something that you run into? >>We really don't. Um, yeah, it was really popular and known some years ago, but we really don't hear about it anymore. Um, after the acquisition, you look at all the collateral and the marketing, they are really a CDM and backup solution exclusively for Google cloud use cases. And they're not being positioned as for on premises or any other use cases outside of Google cloud. That's what, 90, 90 plus percent of your market there that isn't addressable now by Activia. So really we don't see them in any of our engagements at this time. >>I want to come back and push it a little bit, uh, on some of the tech that you said, it's kind of really not that modern. Uh, I mean it's, if they certainly position it as modern, a lot of the engineers who are building there's new sort of backup and recovery capabilities came from the hyperscalers, whether it's copy data management, you know, the bot mock quote, unquote modern backup recovery, it's kind of a data management, sort of this nice all in one solution seems pretty compelling. How does recovery clients specifically stack up? You know, a lot of people think it's a niche product for, for really high end use cases. Is that fair? How do you see a town? >>Yeah. Yeah. So it's, I think it's so important to just, you know, understand, again, the fundamental use of this technology is to create data copies for test W's right. Um, and that's really different than operational backup recovery in which you must have this ability to do full and point in time recoverability in any production outage or Dr. Situation. Um, and then more importantly, after you recover and your applications are back in business, that performance must continue to meet servers levels as before. And when you look at a CDM product, um, and you restore a snapshot and you say with that product and the application is brought up on that restored snapshot, what happens or your production application is now running on actual read rideable snapshots on backup storage. Remember they don't restore all the data back to the production, uh, level stores. They're restoring it as a snapshot okay. >>Onto their storage. And so you have a huge difference in performance. Now running these applications where they instantly recovered, if you will database. So to meet these true operational requirements, you have to fully restore the files to production storage period. And so recovery appliance was first and foremost designed to accomplish this. It's an operational recovery solution, right? We accomplish that. Like I mentioned, with this real-time transaction protection, we have incremental forever backup strategies. So that you're just taking just the changes every day. And you, you can create these virtual full backups that are quickly restored, fully restored, if you will, at 24 terabytes an hour. And we validate and document that performance very clearly in our website. And of course we provide that continuous recovery validation for all the backups that are stored on the system. So it's, um, it's a very nice, complete solution. >>It scales to meet your demands, hundreds of thousands of databases, you know, it's, um, you know, these CDM products might seem great and they work well for a few databases, but then you put a real enterprise load and these hundreds of databases, and we've seen a lot of times where it just buckles, you know, it can't handle that kind of load in that, uh, in that scale. Uh, and, and this is important because customers read their marketing and read the collateral like, Hey, instant recovery. Why wouldn't I want that? Well, it's, you know, nicer than it looks, you know, it always sounds better. Right. Um, and so we have to educate them and about exactly what that means for the database, especially backup recovery use cases. And they're not really handled well, um, with their products. >>I know I'm like way over. I had a lot of questions on this announcement and I was gonna, I was gonna let you go, Tim, but you just mentioned something that, that gave me one more question if I may. So you talked about, uh, supporting hundreds of thousands of databases. You petabytes, you have real world use cases that, that actually leverage the, the appliance in these types of environments. Where does it really shine? >>Yeah. Let me just give you just two real quick ones. You know, we have a company energy transfer, the major natural gas and pipeline operator in the U S so they are a big part of our country's critical infrastructure services. We know ransomware, and these kinds of threats are, you know, are very much viable. We saw the colonial pipeline incident that happened, right? And so the attack, right, critical services while energy transfer was running, lots of databases and their legacy backup environments just couldn't keep up with their enterprise needs. They had backups taking like, well, over a day, they had restores taking several hours. Um, and so they had problems and they couldn't meet their SLS. They moved to the recovery appliance and now they're seeing backwards complete with that incremental forever in just 15 minutes. So that's like a 48 times improvement in backup time. >>And they're also seeing restores completing in about 30 minutes, right. Versus several hours. So it's a, it's a huge difference for them. And they also get that nice recovery validation and monitoring by the system. They know the health of their enterprise at their fingertips. The second quick one is just a global financial services customer. Um, and they have like over 10,000 databases globally and they, they really couldn't find a solution other than throw more hardware kind of approach to, uh, to fix their backups. Well, this, uh, not that the failures and not as the issues. So they moved to recovery appliance and they saw their failed backup rates go down for Matta plea. They saw four times better backup and restore performance. Um, and they have also a very nice centralized way to monitor and manage the system. Uh, real-time view if you will, that data protection health for their entire environment. Uh, and they can show this to the executive management and auditing teams. This is great for compliance reporting. Um, and so they finally done that. They have north of 50 plus, um, recovery appliances a day across that on global enterprise. >>Love it. Thank you for that. Um, uh, guys, great power panel. We have a lot of Oracle customers in our community and the best way to, to help them is to, I get to ask you a bunch of questions and get the experts to answer. So I wonder if you could bring us home, maybe you could just sort of give us the, the top takeaways that you want to your customers to remember in our audience to remember from this announcement. >>Sure, sorry. Uh, I want to actually pick up from where Tim left off and talk about a real customer use case. This is hot off the press. One of the largest banks in the United States, they decided to, that they needed to update. So performance software update on 3000 of their database instances, which are spanning 68, exited a clusters, massive undertaking, correct. They finished the entire task in three hours, three hours to update 3000 databases and 68 exited a clusters. Talk about availability, try doing this on any other infrastructure, no way anyone's going to be able to achieve this. So that's on terms of the availability, right? We are engineering in all of the aspects of database management, performance, security availability, being able to provide redundancy at every single level is all part of the design philosophy and how we are engineering this product. And as far as we are concerned, the, the goal is for forever. >>We are just going to continue to go down this path of increasing performance, increasing the security aspect of the, uh, of the infrastructure, as well as our Oracle database and keep going on this. You know, this, while these have been great results that we've delivered with extra data X nine M the, the journey is on and to our customers. The biggest advantage that you're going to get from the kind of performance metrics that we are driving with extra data is consolidation consolidate more, move, more database instances onto the extended platform, gain the benefits from that consolidation, reduce your operational expenses, reduce your capital expenses. They use your management expenses, all of those, bring it down to accelerator. Your total cost of ownership is guaranteed to go down. Those are my key takeaways, Dave >>Guys, you've been really generous with your time. Uh Subin uh, uh, uh, Bob, Tim, I appreciate you taking my questions and we'll willingness to go toe to toe, really? Thanks for your time. >>You're welcome, David. Thank you. Thank you. >>And thank you for watching this video exclusive from the cube. This is Dave Volante, and we'll see you next time. Be well.

(bright music) >> Welcome to this next session of AWS Storage Day. I'm your host, Dave Vellante of theCUBE. And right now we're going to explore how to simplify and evolve your data lake backup disaster recovery and analytics in the cloud. And we're joined by Kevin Miller who's the general manager of Amazon S3. Kevin, welcome. >> Thanks Dave. Great to see you again. >> Good to see you too. So listen, S3 started as like a small ripple in the pond and over the last 15 years, I mean, it's fundamentally changed the storage market. We used to think about storage as, you know, a box of disc drives that either store data in blocks or file formats and then object storage at the time it was, kind of used in archival storage, it needed specialized application interfaces, S3 changed all that. Why do you think that happened? >> Well, I think first and foremost, it's really just, the customers appreciated the value of S3 and being fully managed where, you know, we manage capacity. Capacity is always available for our customers to bring new data into S3 and really therefore to remove a lot of the constraints around building their applications and deploying new workloads and testing new workloads where they know that if something works great, it can scale up by a 100x or a 1000x. And if it doesn't work, they can remove the data and move on to the next application or next experiment they want to try. And so, you know, really, it's exciting to me. Really exciting when I see businesses across essentially every industry, every geography, you know, innovate and really use data in new and really interesting ways within their business to really drive actual business results. So it's not just about building data, having data to build a report and have a human look at a report, but actually really drive the day-to-day operations of their business. So that can include things like personalization or doing deeper analytics in industrial and manufacturing. A customer like Georgia-Pacific for example, I think is one of the great examples where they use a big data lake and collect a lot of sensor data, IoT sensor data off of their paper manufacturing machines. So they can run them at just the right speed to avoid tearing the paper as it's going through, which really just keeps their machines running more and therefore, you know, just reduce their downtime and costs associated with it. So you know, it's just that transformation again, across many industries, almost every industry that I can think of. That's really what's been exciting to see and continue to see. I think we're still in the really early days of what we're going to see as far as that innovation goes. >> Yeah, I got to agree. I mean, it's been pretty remarkable. Maybe you could talk about the pace of innovation for S3. I mean, if anything, it seems to be accelerating. How Kevin, does AWS, how has it thought about innovation over the past decade plus and where do you see it headed? >> Yeah, that's a great question Dave, really innovation is at our core as part of our core DNA. S3 launched more than 15 years ago, almost 16 years old. We're going to get a learner's permit for it next year. But, you know, as it's grown to exabytes of storage and trillions of objects, we've seen almost every use case you can imagine. I'm sure there's a new one coming that we haven't seen yet, but we've learned a lot from those use cases. And every year we just think about what can we do next to further simplify. And so you've seen that as we've launched over the last few years, things like S3 Intelligent Tiering, which was really the clouds first storage class to automatically optimize and reduce customer's costs for storage, for data that they were storing for a long time. And based on, you know, variable access patterns. We launched S3 Access Points to provide a simpler way to have different applications operating on shared data sets. And we launched earlier this year S3 Object Lambda, which really is, I think, cool technology. We're just starting to see how it can be applied to simplify serverless application development. Really the next wave, I think, of application development that doesn't need, not only is the storage fully managed, but the compute is fully managed as well. Really just simplify that whole end to end application development. >> Okay, so we heard this morning in the keynote, some exciting news. What can you tell us, Kevin? >> Yeah, so this morning we launched S3 Multi-Region Access Points and these are access points that give you a single global endpoint to access data sets that can span multiple S3 buckets in different AWS regions around the world. And so this allows you to build these multi-region applications and multi-region architectures with, you know, with the same approach that you use in a single region and then run these applications anywhere around the world. >> Okay. So if I interpret this correctly, it's a good fit for organizations with clients or operations around the globe. So for instance, gaming, news outlets, think of content delivery types of customers. Should we think about this as multi-region storage and why is that so important in your view? >> Absolutely. Yeah, that is multi-region storage. And what we're hearing is seeing as customers grow and we have multinational customers who have operations all around the world. And so as they've grown and their data needs grow around the world, they need to be using multiple AWS regions to store and access that data. Sometimes it's for low latency so that it can be closer to their end users or their customers, other times it's for regions where they just have a particular need to have data in a particular geography. But this is really a simple way of having one endpoint in front of data, across multiple buckets. So for applications it's quite easy, they just have that one end point and then the data, the requests are automatically routed to the nearest region. >> Now earlier this year, S3 turned 15. What makes S3 different, Kevin in your view? >> Yeah, it turned 15. It'll be 16 soon, you know, S3 really, I think part of the difference is it just operates at really an unprecedented scale with, you know, more than a hundred trillion objects and regularly peaking to tens of millions of requests per second. But it's really about the resiliency and availability and durability that are our responsibility and we focus every single day on protecting those characteristics for customers so that they don't have to. So that they can focus on building the businesses and applications that they need to really run their business and not worry about the details of running highly available storage. And so I think that's really one of the key differences with S3. >> You know, I first heard the term data lake, it was early last decade. I think it was around 2011, 2012 and obviously the phrase has stuck. How are S3 and data lakes simpatico, and how have data lakes on S3 changed or evolved over the years? >> Yeah. You know, the idea of data lakes, obviously, as you say, came around nine or 10 years ago, but I actually still think it's really early days for data lakes. And just from the standpoint of, you know, originally nine or 10 years ago, when we talked about data lakes, we were looking at maybe tens of terabytes, hundreds of terabytes, or a low number of petabytes and for a lot of data lakes, we're still seeing that that's the kind of scale that currently they're operating at, but I'm also seeing a class of data lakes where you're talking about tens or hundreds of petabytes or even more, and really just being used to drive critical aspects of customer's businesses. And so I really think S3, it's been a great place to run data lakes and continues to be. We've added a lot of capability over the last several years, you know, specifically for that data lake use case. And we're going to continue to do that and grow the feature set for data lakes, you know, over the next many years as well. But really, it goes back to the fundamentals of S3 providing that 11 9s of durability, the resiliency of having three independent data centers within regions. So the customers can use that storage knowing their data is protected. And again, just focus on the applications on top of that data lake and also run multiple applications, right? The idea of a data lake is you're not limited to one access pattern or one set of applications. If you want to try out a new machine learning application or something, do some advanced analytics, that's all possible while running the in-flight operational tools that you also have against that data. So it allows for that experimentation and for transforming businesses through new ideas. >> Yeah. I mean, to your point, if you go back to the early days of cloud, we were talking about storing, you know, gigabytes, maybe tens of terabytes that was big. Today, we're talking about hundreds and hundreds of terabytes, petabytes. And so you've got huge amount of information customers that are of that size and that scale, they have to optimize costs. Really that's top of mind, how are you helping customers save on storage costs? >> Absolutely. Dave, I mean, cost optimization is one of the key things we look at every single year to help customers reduce their costs for storage. And so that led to things like the introduction of S3 Intelligent Tiering, 10 years ago. And that's really the only cloud storage class that just delivers the automatic storage cost savings, as data access patterns change. And, you know, we deliver this without performance impact or any kind of operational overhead. It's really intended to be, you know, intelligent where customers put the data in. And then we optimize the storage cost. Or for example, last year we launched S3 Storage Lens, which is really the first and only service in the cloud that provides organization-wide visibility into where customers are storing their data, what the request rates are and so forth against their storage. So when you talk about these data lakes of hundreds of petabytes or even smaller, these tools are just really invaluable to help customers reduce their storage costs year after year. And actually, Dave I'm pleased, you know, today we're also announcing the launch of some improvements to S3 Intelligent Tiering, to actually further automate the cost savings. And what we're doing is we're actually removing the minimum storage duration. Previously, Intelligent Tiering had a 30 day minimum storage duration, and we're also eliminating our monitoring and automation charge for small objects. So previously there was that monitoring and automation charge applied to all objects independent of size. And now any object less than 120 kilobytes is not charged at that charge. So, and I think some pretty critical innovations on Intelligent Tiering that will help customers use that for an even wider set of data lake and other applications. >> That's three, it's ubiquitous. The innovation continues. You can learn more by attending the Storage Day S3 deep dive right after this interview. Thank you, Kevin Miller. Great to have you on the program. >> Yeah, Dave, thanks for having me. Great to see you. >> You're welcome, this is Dave Vellante and you're watching theCUBE's coverage of AWS Storage Day. Keep it right there. (bright music)

(upbeat music) >> Welcome to transforming ideas into insights, presented with theCUBE and made possible by Cloudera. My name is Dave Vellante from theCUBE and I'll be your host for today. In the next hundred minutes, you're going to hear how to turn your best ideas into action using data and we're going to share the real-world examples of 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing efficiencies, better forecast retail demand, transform analytics, improve public sector service and so much more. How we use data is rapidly evolving. That is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to, rather we use terms like, digital transformation and digital business. But you think about it. What is a digital business? How is that different from just a business? Well, a digital business is a data business and it differentiates itself by the way it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such, the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings, but increasingly insights are leading to the development of data products and services that can be monetized. Or as you'll hear in our industry examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. Self-service investing, filing insurance claims on our smart phones and so many examples. IOT systems that communicate and act machine to machine. Real-time pricing actions, these are all examples of products and services that drive revenue, cut costs or create other value and they all rely on data. Now, while many business leaders sometimes express frustration that their investments in data, people and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data transformation and leadership. One thing is certain, the next 10 years of data and digital transformation won't be like the last 10. So let's into it. Please join us in the chat. You can ask questions. You can share your comments. Hit us up on Twitter. Right now, it's my pleasure to welcome Mick Holliston and he's the president of Cloudera. Mick, great to see you. >> Great to see you as well, Dave. >> Hey, so I call it the new abnormal, right? The world is kind of out of whack. Offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations, line cooks at restaurants. Everything that we consumers have missed, but here's the one thing, it seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling, their pricing algorithms, commodity prices, we don't know. Is inflation transitory? Is it a long-term threat, trying to forecast GDP? It seems like we have to reset all of our assumptions and Mick, I feel a quality data is going to be a key here. How do you see the current state of the industry in the role data plays to get us into a more predictable and stable future? >> Well, I can sure tell you this, Dave, out of whack is definitely right. I don't know if you know or not, but I happened to be coming to you live today from Atlanta and as a native of Atlanta, I can tell you there's a lot to be known about the airport here. It's often said that whether you're going to heaven or hell, you got to change planes in Atlanta and after 40 minutes waiting on an algorithm to be right for baggage claim last night, I finally managed to get some bag and to be able to show up, dressed appropriately for you today. Here's one thing that I know for sure though, Dave. Clean, consistent and safe data will be essential to getting the world and businesses as we know it back on track again. Without well-managed data, we're certain to get very inconsistent outcomes. Quality data will be the normalizing factor because one thing really hasn't changed about computing since the dawn of time, back when I was taking computer classes at Georgia Tech here in Atlanta and that's what we used to refer to as garbage in, garbage out. In other words, you'll never get quality data-driven insights from a poor dataset. This is especially important today for machine learning and AI. You can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid. As AI is increasingly used in every business app, you must build a solid data foundation. >> Mick, let's talk about hybrid. Every CXO that I talked to, they're trying to get hybrid right. Whether it's hybrid work, hybrid events, which is our business, hybrid cloud. How are you thinking about the hybrid everything, what's your point of view? >> With all those prescriptions of hybrid and everything, there was one item you might not have quite hit on, Dave and that's hybrid data. >> Oh yeah, you're right, Mick, I did miss that. What do you mean by hybrid data? >> Well, Dave, in Cloudera, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now, every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises, in a private cloud, in public cloud or perhaps even in a new open data exchange. Now, this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud. But either way, security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch or read a recent news story. Data breaches are at an all time high and the ethics of AI applications are being called into question everyday. And understanding lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know, Dave, that's the business Cloudera is in. On a serious note, from Cloudera's perspective, adopting a hybrid data strategy is central to every business' digital transformation. It will enable rapid adoption of new technologies and optimize economic models, while ensuring the security and privacy of every bit of data. >> Okay, Mick, I'm glad you brought in that notion of hybrid data because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You got the economics, the physics, the local laws come into play, so what about the rest of hybrid? >> Yeah, that's a great question, Dave and certainly, Cloudera itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind, the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office ethernet may not be happening quite so fast in somebody's rural home in the middle of Nebraska somewhere. So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, involve us kind of slowly coming back to work, beginning this fall. And we're looking forward to being able to shake hands and see one another again for the first time, in many cases, for more than a year and a half. But yes, hybrid work and hybrid data are playing an increasingly important role for every kind of business. >> Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, here's how I think about it. I mean, some industries have transformed. You think about retail, for example, it's pretty clear. Although, every physical retail brand I know has not only beefed up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence. And reverse, we see Amazon building out physical assets, so there's more hybrid going on. But when you look at healthcare, for example, it's just starting with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control of payment systems. In manufacturing, the pandemic highlighted, America's reliance on China as a manufacturing partner and supply chain. And so my point is, it seems at different industries, they're in different stages of transformation, but two things look really clear. One, you got to put data at the core of the business model, that's compulsory. It seems like embedding AI into the applications, the data, the business process, that's going to become increasingly important. So how do you see that? >> Wow, there's a lot packed into that question there, Dave. But yeah, at Cloudera, I happened to be leading our own digital transformation as a technology company and what I would tell you there that's been an interesting process. The shift from being largely a subscription-based model to a consumption-based model requires a completely different level of instrumentation in our products and data collection that takes place in real-time, both for billing for our customers and to be able to check on the health and wellness, if you will, of their Cloudera implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed the rate and pace of getting vaccines to market or we've been assisting with testing process that's taken place. Because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and healthy and safe outcomes for everyone. And Cloudera has been underneath a great deal of that type of work. And the financial services industry you pointed out, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are helping those kinds of organizations get through those difficult challenges. You also happened to mention public sector and in public sector, we're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. And while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, you can't build great ML apps unless you've got a strong data foundation underneath. It's back to that garbage in, garbage out comment that I made previously. And so, in order to do that, you've got to have a great hybrid data management platform at your disposal to ensure that your data is clean and organized and up to date. Just as importantly from that, that's kind of the freedom side of things. On the security side of things, you've got to ensure that you can see who's touched not just the data itself, Dave, but actually the machine learning models. And organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage in addition to data lineage. In other words, who's had access to the machine learning models? When and where and at what time and what decisions were made perhaps, by the humans, perhaps by the machines that may have led to a particular outcome? So, every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models, just as they can track the lineage of data. So, lots going on there across industries. Lots going on as those various industries think about how AI can be applied to their businesses. >> It's a pretty interesting concept you're bringing into the discussion, the hybrid data, sort of, I think new to a lot of people. And this idea of model lineage is a great point because people want to talk about AI ethics, transparency of AI. When you start putting those models into machines to do real-time inferencing at the edge, it starts to get really complicated. I wonder if we could talk, we're still on that theme of industry transformation. I felt like coming into the pre-pandemic, there was just a lot of complacency. Yeah, digital transformation and a lot of buzz words and then we had this forced march to digital, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? >> There definitely is a lot of a POC limbo or I think some of us internally have referred to as POC purgatory, just getting in that phase, not being able to get from point A to point B in digital transformation. And for every industry, transformation, change in general, is difficult and it takes time and money and thoughtfulness. But like with all things, what we've found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts. To say it another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts, as it relates to the underlying technology here and to bring it home a little bit more practically, I guess I would say. At Cloudera, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, right close to home. In place, they can kind of experiment a little bit more safely and economically and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplished, but kind of starting small and then drawing fast from there on customer's journey to the cloud. >> Well Mick, we've covered a lot of ground. Last question, what do you want people to leave this event, this session with and thinking about sort of the next era of data that we're entering? >> Well, it's a great question, but I think it could be summed up in two words. I want them to think about a hybrid data strategy. So, really hybrid data is a concept that we're bringing forward on this show really, for the first time, arguably. And we really do think that it enables customers to experience what we refer to, Dave, as the power of ANT. That is freedom and security and in a world where we're all still trying to decide whether each day when we walk out, each building we walk into, whether we're free to come in and out with a mask, without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe for ourselves and for others. And the same is true of organization's IT strategies. They want the freedom to choose, to run workloads and applications in the best and most economical place possible, but they also want to do that with certainty that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So, hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole. >> Nick, thanks so much, great conversation. I really appreciate the insights that you're bringing to this event, into the industry, really. Thank you for your time. >> You bet, Dave, pleasure being with you.

>>Have you ever wondered how we sequence the human genome, how your smartphone is so well smart, how we will ever analyze all the patient data for the new vaccines or even how we plan to send humans to Mars? Well, at Cloudera, we believe that data can make what is impossible today possible tomorrow we are the enterprise data cloud company. In fact, we provide analytics and machine learning technology that does everything from making your smartphone smarter, to helping scientists ensure that new vaccines are both safe and effective, big data, no problem out era, the enterprise data cloud company. >>So I think for a long time in this country, we've known that there's a great disparity between minority populations and the majority of population in terms of disease burden. And depending on where you live, your zip code has more to do with your health than almost anything else. But there are a lot of smaller, um, safety net facilities, as well as small academic medical colleges within the United States. And those in those smaller environments don't have the access, you know, to the technologies that the larger ones have. And, you know, I call that, uh, digital disparity. So I'm, Harry's in academic scientist center and our mission is to train diverse health care providers and researchers, but also provide services to underserved populations. As part of the reason that I think is so important for me hearing medical college, to do data science. One of the things that, you know, both Cloudera and Claire sensor very passionate about is bringing those height in technologies to, um, to the smaller organizations. >>It's very expensive to go to the cloud for these small organizations. So now with the partnership with Cloudera and Claire sets a clear sense, clients now enjoy those same technologies and really honestly have a technological advantage over some of the larger organizations. The reason being is they can move fast. So we were able to do this on our own without having to, um, hire data scientists. Uh, we probably cut three to five years off of our studies. I grew up in a small town in Arkansas and is one of those towns where the railroad tracks divided the blacks and the whites. My father died without getting much healthcare at all. And as an 11 year old, I did not understand why my father could not get medical attention because he was very sick. >>Since we come at my Harry are looking to serve populations that reflect themselves or affect the population. He came from. A lot of the data you find or research you find health is usually based on white men. And obviously not everybody who needs a medical provider is going to be a white male. >>One of the things that we're concerned about in healthcare is that there's bias in treatment already. We want to make sure those same biases do not enter into the algorithms. >>The issue is how do we get ahead of them to try to prevent these disparities? >>One of the great things about our dataset is that it contains a very diverse group of patients. >>Instead of just saying, everyone will have these results. You can break it down by race, class, cholesterol, level, other kinds of factors that play a role. So you can make the treatments in the long run. More specifically, >>Researchers are now able to use these technologies and really take those hypotheses from, from bench to bedside. >>We're able to overall improve the health of not just the person in front of you, but the population that, yeah, >>Well, the future is now. I love a quote by William Gibson who said the future is already here. It's just not evenly distributed. If we think hard enough and we apply things properly, uh, we can again take these technologies to, you know, underserved environments, um, in healthcare. Nobody should be technologically disadvantage. >>When is a car not just a car when it's a connected data driven ecosystem, dozens of sensors and edge devices gathering up data from just about anything road, infrastructure, other vehicles, and even pedestrians to create safer vehicles, smarter logistics, and more actionable insights. All the data from the connected car supports an entire ecosystem from manufacturers, building safer vehicles and fleet managers, tracking assets to insurers monitoring, driving behaviors to make roads safer. Now you can control the data journey from edge to AI. With Cloudera in the connected car, data is captured, consolidated and enriched with Cloudera data flow cloud Dara's data engineering, operational database and data warehouse provide the foundation to develop service center applications, sales reports, and engineering dashboards. With data science workbench data scientists can continuously train AI models and use data flow to push the models back to the edge, to enhance the car's performance as the industry's first enterprise data cloud Cloudera supports on-premise public and multi-cloud deployments delivering multifunction analytics on data anywhere with common security governance and metadata management powered by Cloudera SDX, an open platform built on open source, working with open compute architectures and open data stores all the way from edge to AI powering the connected car. >>The future has arrived. >>The Dawn of a retail Renaissance is here and shopping will never be the same again. Today's connected. Consumers are always on and didn't control. It's the era of smart retail, smart shelves, digital signage, and smart mirrors offer an immersive customer experience while delivering product information, personalized offers and recommendations, video analytics, capture customer emotions and gestures to better understand and respond to in-store shopping experiences. Beacons sensors, and streaming video provide valuable data into in-store traffic patterns, hotspots and dwell times. This helps retailers build visual heat maps to better understand custom journeys, conversion rates, and promotional effectiveness in our robots automate routine tasks like capturing inventory levels, identifying out of stocks and alerting in store personnel to replenish shelves. When it comes to checking out automated e-commerce pickup stations and frictionless checkouts will soon be the norm making standing in line. A thing of the past data and analytics are truly reshaping. >>The everyday shopping experience outside the store, smart trucks connect the supply chain, providing new levels of inventory visibility, not just into the precise location, but also the condition of those goods. All in real time, convenience is key and customers today have the power to get their goods delivered at the curbside to their doorstep, or even to their refrigerators. Smart retail is indeed here. And Cloudera makes all of this possible using Cloudera data can be captured from a variety of sources, then stored, processed, and analyzed to drive insights and action. In real time, data scientists can continuously build and train new machine learning models and put these models back to the edge for delivering those moment of truth customer experiences. This is the enterprise data cloud powered by Cloudera enabling smart retail from the edge to AI. The future has arrived >>For is a global automotive supplier. We have three business groups, automotive seating in studios, and then emission control technologies or biggest automotive customers are Volkswagen for the NPSA. And we have, uh, more than 300 sites. And in 75 countries >>Today, we are generating tons of data, more and more data on the manufacturing intelligence. We are trying to reduce the, the defective parts or anticipate the detection of the, of the defective part. And this is where we can get savings. I would say our goal in manufacturing is zero defects. The cost of downtime in a plant could be around the a hundred thousand euros. So with predictive maintenance, we are identifying correlations and patterns and try to anticipate, and maybe to replace a component before the machine is broken. We are in the range of about 2000 machines and we can have up to 300 different variables from pressure from vibration and temperatures. And the real-time data collection is key, and this is something we cannot achieve in a classical data warehouse approach. So with the be data and with clouded approach, what we are able to use really to put all the data, all the sources together in the classical way of working with that at our house, we need to spend weeks or months to set up the model with the Cloudera data lake. We can start working on from days to weeks. We think that predictive or machine learning could also improve on the estimation or NTC patient forecasting of what we'll need to brilliance with all this knowledge around internet of things and data collection. We are applying into the predictive convene and the cockpit of the future. So we can work in the self driving car and provide a better experience for the driver in the car. >>The Cloudera data platform makes it easy to say yes to any analytic workload from the edge to AI, yes. To enterprise grade security and governance, yes. To the analytics your people want to use yes. To operating on any cloud. Your business requires yes to the future with a cloud native platform that flexes to meet your needs today and tomorrow say yes to CDP and say goodbye to shadow it, take a tour of CDP and see how it's an easier, faster and safer enterprise analytics and data management platform with a new approach to data. Finally, a data platform that lets you say yes, >>Welcome to transforming ideas into insights, presented with the cube and made possible by cloud era. My name is Dave Volante from the cube, and I'll be your host for today. And the next hundred minutes, you're going to hear how to turn your best ideas into action using data. And we're going to share the real world examples and 12 industry use cases that apply modern data techniques to improve customer experience, reduce fraud, drive manufacturing, efficiencies, better forecast, retail demand, transform analytics, improve public sector service, and so much more how we use data is rapidly evolving as is the language that we use to describe data. I mean, for example, we don't really use the term big data as often as we used to rather we use terms like digital transformation and digital business, but you think about it. What is a digital business? How is that different from just a business? >>Well, digital business is a data business and it differentiates itself by the way, it uses data to compete. So whether we call it data, big data or digital, our belief is we're entering the next decade of a world that puts data at the core of our organizations. And as such the way we use insights is also rapidly evolving. You know, of course we get value from enabling humans to act with confidence on let's call it near perfect information or capitalize on non-intuitive findings. But increasingly insights are leading to the development of data, products and services that can be monetized, or as you'll hear in our industry, examples, data is enabling machines to take cognitive actions on our behalf. Examples are everywhere in the forms of apps and products and services, all built on data. Think about a real-time fraud detection, know your customer and finance, personal health apps that monitor our heart rates. >>Self-service investing, filing insurance claims and our smart phones. And so many examples, IOT systems that communicate and act machine and machine real-time pricing actions. These are all examples of products and services that drive revenue cut costs or create other value. And they all rely on data. Now while many business leaders sometimes express frustration that their investments in data, people, and process and technologies haven't delivered the full results they desire. The truth is that the investments that they've made over the past several years should be thought of as a step on the data journey. Key learnings and expertise from these efforts are now part of the organizational DNA that can catapult us into this next era of data, transformation and leadership. One thing is certain the next 10 years of data and digital transformation, won't be like the last 10. So let's get into it. Please join us in the chat. >>You can ask questions. You can share your comments, hit us up on Twitter right now. It's my pleasure to welcome Mick Holliston in he's the president of Cloudera mic. Great to see you. Great to see you as well, Dave, Hey, so I call it the new abnormal, right? The world is kind of out of whack offices are reopening again. We're seeing travel coming back. There's all this pent up demand for cars and vacations line cooks at restaurants. Everything that we consumers have missed, but here's the one thing. It seems like the algorithms are off. Whether it's retail's fulfillment capabilities, airline scheduling their pricing algorithms, you know, commodity prices we don't know is inflation. Transitory. Is it a long-term threat trying to forecast GDP? It's just seems like we have to reset all of our assumptions and make a feel a quality data is going to be a key here. How do you see the current state of the industry and the role data plays to get us into a more predictable and stable future? Well, I >>Can sure tell you this, Dave, uh, out of whack is definitely right. I don't know if you know or not, but I happen to be coming to you live today from Atlanta and, uh, as a native of Atlanta, I can, I can tell you there's a lot to be known about the airport here. It's often said that, uh, whether you're going to heaven or hell, you got to change planes in Atlanta and, uh, after 40 minutes waiting on algorithm to be right for baggage claim when I was not, I finally managed to get some bag and to be able to show up dressed appropriately for you today. Um, here's one thing that I know for sure though, Dave, clean, consistent, and safe data will be essential to getting the world and businesses as we know it back on track again, um, without well-managed data, we're certain to get very inconsistent outcomes, quality data will the normalizing factor because one thing really hasn't changed about computing since the Dawn of time. Back when I was taking computer classes at Georgia tech here in Atlanta, and that's what we used to refer to as garbage in garbage out. In other words, you'll never get quality data-driven insights from a poor data set. This is especially important today for machine learning and AI, you can build the most amazing models and algorithms, but none of it will matter if the underlying data isn't rock solid as AI is increasingly used in every business app, you must build a solid data foundation mic. Let's >>Talk about hybrid. Every CXO that I talked to, they're trying to get hybrid, right? Whether it's hybrid work hybrid events, which is our business hybrid cloud, how are you thinking about the hybrid? Everything, what's your point of view with >>All those descriptions of hybrid? Everything there, one item you might not have quite hit on Dave and that's hybrid data. >>Oh yeah, you're right. Mick. I did miss that. What, what do you mean by hybrid data? Well, >>David in cloud era, we think hybrid data is all about the juxtaposition of two things, freedom and security. Now every business wants to be more agile. They want the freedom to work with their data, wherever it happens to work best for them, whether that's on premises in a private cloud and public cloud, or perhaps even in a new open data exchange. Now this matters to businesses because not all data applications are created equal. Some apps are best suited to be run in the cloud because of their transitory nature. Others may be more economical if they're running a private cloud, but either way security, regulatory compliance and increasingly data sovereignty are playing a bigger and more important role in every industry. If you don't believe me, just watch her read a recent news story. Data breaches are at an all time high. And the ethics of AI applications are being called into question every day and understanding the lineage of machine learning algorithms is now paramount for every business. So how in the heck do you get both the freedom and security that you're looking for? Well, the answer is actually pretty straightforward. The key is developing a hybrid data strategy. And what do you know Dave? That's the business cloud era? Is it on a serious note from cloud era's perspective? Adopting a hybrid data strategy is central to every business's digital transformation. It will enable rapid adoption of new technologies and optimize economic models while ensuring the security and privacy of every bit of data. What can >>Make, I'm glad you brought in that notion of hybrid data, because when you think about things, especially remote work, it really changes a lot of the assumptions. You talked about security, the data flows are going to change. You've got the economics, the physics, the local laws come into play. So what about the rest of hybrid? Yeah, >>It's a great question, Dave and certainly cloud era itself as a business and all of our customers are feeling this in a big way. We now have the overwhelming majority of our workforce working from home. And in other words, we've got a much larger surface area from a security perspective to keep in mind the rate and pace of data, just generating a report that might've happened very quickly and rapidly on the office. Uh, ether net may not be happening quite so fast in somebody's rural home in, uh, in, in the middle of Nebraska somewhere. Right? So it doesn't really matter whether you're talking about the speed of business or securing data, any way you look at it. Uh, hybrid I think is going to play a more important role in how work is conducted and what percentage of people are working in the office and are not, I know our plans, Dave, uh, involve us kind of slowly coming back to work, begin in this fall. And we're looking forward to being able to shake hands and see one another again for the first time in many cases for more than a year and a half, but, uh, yes, hybrid work, uh, and hybrid data are playing an increasingly important role for every kind of business. >>Thanks for that. I wonder if we could talk about industry transformation for a moment because it's a major theme of course, of this event. So, and the case. Here's how I think about it. It makes, I mean, some industries have transformed. You think about retail, for example, it's pretty clear, although although every physical retail brand I know has, you know, not only peaked up its online presence, but they also have an Amazon war room strategy because they're trying to take greater advantage of that physical presence, uh, and ended up reverse. We see Amazon building out physical assets so that there's more hybrid going on. But when you look at healthcare, for example, it's just starting, you know, with such highly regulated industry. It seems that there's some hurdles there. Financial services is always been data savvy, but you're seeing the emergence of FinTech and some other challenges there in terms of control, mint control of payment systems in manufacturing, you know, the pandemic highlighted America's reliance on China as a manufacturing partner and, and supply chain. Uh it's so my point is it seems that different industries they're in different stages of transformation, but two things look really clear. One, you've got to put data at the core of the business model that's compulsory. It seems like embedding AI into the applications, the data, the business process that's going to become increasingly important. So how do you see that? >>Wow, there's a lot packed into that question there, Dave, but, uh, yeah, we, we, uh, you know, at Cloudera I happened to be leading our own digital transformation as a technology company and what I would, what I would tell you there that's been arresting for us is the shift from being largely a subscription-based, uh, model to a consumption-based model requires a completely different level of instrumentation and our products and data collection that takes place in real, both for billing, for our, uh, for our customers. And to be able to check on the health and wellness, if you will, of their cloud era implementations. But it's clearly not just impacting the technology industry. You mentioned healthcare and we've been helping a number of different organizations in the life sciences realm, either speed, the rate and pace of getting vaccines, uh, to market, uh, or we've been assisting with testing process. >>That's taken place because you can imagine the quantity of data that's been generated as we've tried to study the efficacy of these vaccines on millions of people and try to ensure that they were going to deliver great outcomes and, and healthy and safe outcomes for everyone. And cloud era has been underneath a great deal of that type of work and the financial services industry you pointed out. Uh, we continue to be central to the large banks, meeting their compliance and regulatory requirements around the globe. And in many parts of the world, those are becoming more stringent than ever. And Cloudera solutions are really helping those kinds of organizations get through those difficult challenges. You, you also happened to mention, uh, you know, public sector and in public sector. We're also playing a key role in working with government entities around the world and applying AI to some of the most challenging missions that those organizations face. >>Um, and while I've made the kind of pivot between the industry conversation and the AI conversation, what I'll share with you about AI, I touched upon a little bit earlier. You can't build great AI, can't grow, build great ML apps, unless you've got a strong data foundation underneath is back to that garbage in garbage out comment that I made previously. And so in order to do that, you've got to have a great hybrid dated management platform at your disposal to ensure that your data is clean and organized and up to date. Uh, just as importantly from that, that's kind of the freedom side of things on the security side of things. You've got to ensure that you can see who just touched, not just the data itself, Dave, but actually the machine learning models and organizations around the globe are now being challenged. It's kind of on the topic of the ethics of AI to produce model lineage. >>In addition to data lineage. In other words, who's had access to the machine learning models when and where, and at what time and what decisions were made perhaps by the humans, perhaps by the machines that may have led to a particular outcome. So every kind of business that is deploying AI applications should be thinking long and hard about whether or not they can track the full lineage of those machine learning models just as they can track the lineage of data. So lots going on there across industries, lots going on as those various industries think about how AI can be applied to their businesses. Pretty >>Interesting concepts. You bring it into the discussion, the hybrid data, uh, sort of new, I think, new to a lot of people. And th this idea of model lineage is a great point because people want to talk about AI, ethics, transparency of AI. When you start putting those models into, into machines to do real time inferencing at the edge, it starts to get really complicated. I wonder if we could talk about you still on that theme of industry transformation? I felt like coming into the pandemic pre pandemic, there was just a lot of complacency. Yeah. Digital transformation and a lot of buzz words. And then we had this forced March to digital, um, and it's, but, but people are now being more planful, but there's still a lot of sort of POC limbo going on. How do you see that? Can you help accelerate that and get people out of that state? It definitely >>Is a lot of a POC limbo or a, I think some of us internally have referred to as POC purgatory, just getting stuck in that phase, not being able to get from point a to point B in digital transformation and, um, you know, for every industry transformation, uh, change in general is difficult and it takes time and money and thoughtfulness, but like with all things, what we found is small wins work best and done quickly. So trying to get to quick, easy successes where you can identify a clear goal and a clear objective and then accomplish it in rapid fashion is sort of the way to build your way towards those larger transformative efforts set. Another way, Dave, it's not wise to try to boil the ocean with your digital transformation efforts as it relates to the underlying technology here. And to bring it home a little bit more practically, I guess I would say at cloud era, we tend to recommend that companies begin to adopt cloud infrastructure, for example, containerization. >>And they begin to deploy that on-prem and then they start to look at how they may move those containerized workloads into the public cloud. That'll give them an opportunity to work with the data and the underlying applications themselves, uh, right close to home in place. They can kind of experiment a little bit more safely and economically, and then determine which workloads are best suited for the public cloud and which ones should remain on prem. That's a way in which a hybrid data strategy can help get a digital transformation accomplish, but kind of starting small and then drawing fast from there on customer's journey to the we'll make we've >>Covered a lot of ground. Uh, last question. Uh, w what, what do you want people to leave this event, the session with, and thinking about sort of the next era of data that we're entering? >>Well, it's a great question, but, uh, you know, I think it could be summed up in, uh, in two words. I want them to think about a hybrid data, uh, strategy. So, uh, you know, really hybrid data is a concept that we're bringing forward on this show really for the, for the first time, arguably, and we really do think that it enables customers to experience what we refer to Dave as the power of, and that is freedom, uh, and security, and in a world where we're all still trying to decide whether each day when we walk out each building, we walk into, uh, whether we're free to come in and out with a mask without a mask, that sort of thing, we all want freedom, but we also also want to be safe and feel safe, uh, for ourselves and for others. And the same is true of organizations. It strategies. They want the freedom to choose, to run workloads and applications and the best and most economical place possible. But they also want to do that with certainty, that they're going to be able to deploy those applications in a safe and secure way that meets the regulatory requirements of their particular industry. So hybrid data we think is key to accomplishing both freedom and security for your data and for your business as a whole, >>Nick, thanks so much great conversation and really appreciate the insights that you're bringing to this event into the industry. Really thank you for your time. >>You bet Dave pleasure being with you. Okay. >>We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid, right? So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manny veer, DAS. Who's the head of enterprise computing at Nvidia. And before I hand it off to Robin, I just want to say for those of you who follow me at the cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise, and it's being driven by the emergence of data, intensive applications and workloads no longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like Nvidia. So let's learn more about this collaboration and what it means to your data business. Rob, thanks, >>Mick and Dave, that was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy and accelerating the path to value and hybrid environments. And I want to drill down on this aspect today. Every business is facing accelerating everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor. Now, every engagement with coworkers, customers and partners is virtual from website metrics to customer service records, and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? A cloud era? We believe this onslaught of data offers an opportunity to make better business decisions faster. >>And we want to make that easier for everyone, whether it's fraud, detection, demand, forecasting, preventative maintenance, or customer churn, whether the goal is to save money or produce income every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit they cloud provides and with security and edge to AI data intimacy. That's why the partnership between cloud air and Nvidia together means so much. And it starts with the shared vision making data-driven, decision-making a reality for every business and our customers will now be able to leverage virtually unlimited quantities of varieties, of data, to power, an order of magnitude faster decision-making and together we turbo charge the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. >>We're joined today by NVIDIA's Mandy veer dos, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, man, you're veer. Thank you for joining us over the unit. >>Thank you, Rob, for having me. It's a pleasure to be here on behalf of Nvidia. We are so excited about this partnership with Cloudera. Uh, you know, when, when, uh, when Nvidia started many years ago, we started as a chip company focused on graphics, but as you know, over the last decade, we've really become a full stack accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, uh, AI being a prime example. And when we think about Cloudera, uh, and your company, a great company, there's three things we see Rob. Uh, the first one is that for the companies that will already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. >>And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about in various mission, going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies today who have been the early adopters, uh, using the power acceleration by changing the technology in their stacks. But more and more, we see the opportunity of meeting customers, where they are with tools that they're familiar with with partners that they trust. And of course, Cloudera being a great example of that. Uh, the second, uh, part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through, but as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. >>And so again, the power of your platform, uh, is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute the machine learning compute needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where literally they took the workflow. They had, they took the servers, they had, they added GPS into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >>My name's Joanne salty. I'm the branch chief of the technical branch and RAs. It's actually the research division research and statistical division of the IRS. Basically the mission that RAs has is we do statistical and research on all things related to taxes, compliance issues, uh, fraud issues, you know, anything that you can think of. Basically we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So it's our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those Agra algorithms, the of parameters each of those algorithms have. >>So that's, that's really been our challenge. Now the expectation was that with Nvidia in cloud, there is help. And with the cluster, we actually build out the test this on the actual fraud, a fraud detection algorithm on our expectation was we were definitely going to see some speed up in prom, computational processing times. And just to give you context, the size of the data set that we were, uh, the SMI was actually working, um, the algorithm against Liz around four terabytes. If I recall correctly, we'd had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them? It was really, really quick. Uh, the definite now term short term what's next is going to be the subject matter expert is actually going to take our algorithm run with that. >>So that's definitely the now term thing we want to do going down, go looking forward, maybe out a couple of months, we're also looking at curing some, a 100 cards to actually test those out. As you guys can guess our datasets are just getting bigger and bigger and bigger, and it demands, um, to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward. And then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run them, you know, come onto our art's desire, wherever imagination takes our skis to actually develop solutions, know how the platforms to run them on just kind of the close out. >>I rarely would be very missed. I've worked with a lot of, you know, companies through the year and most of them been spectacular. And, uh, you guys are definitely in that category. The, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't. Thank you guys. So thank you for the opportunity to, and fantastic. And I'd have to also, I want to thank my guys. My, uh, my staff, David worked on this Richie worked on this Lex and Tony just, they did a fantastic job and I want to publicly thank him for all the work they did with you guys and Chev, obviously also. Who's fantastic. So thank you everyone. >>Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and Nvidia? Is it primarily go to market or you do an engineering work? What's the story there? >>It's really both. It's both go to market and engineering and engineering focus is to optimize and take advantage of invidious platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both >>Great. Thank you. Many of Eric, maybe you could talk a little bit more about why can't we just existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do Nvidia and cloud era bring to the table that goes beyond the conventional systems that we've known for many years? >>Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now Nvidia has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform. So that regardless of the technique, the customer's using to get insight from that data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >>So I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going toward doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive, uh, things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start, you think about the AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems and real time, AI inference, at least even at the edge, huge potential for business value and a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the like, and so you're putting AI into these data intensive apps within the enterprise. >>The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >>Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint and new platforms like these being developed by cloud air and Nvidia will dramatically lower the cost, uh, of enabling this type of workload to be done. Um, and what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation, engine chain management, drug province, and increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots that AR VR and manufacturing. So driving quality, better quality in the power grid management, automated retail IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >>I mean, this is like your wheelhouse. Maybe you could add something to that. >>Yeah. I mean, I agree with Rob. I mean he listed some really good use cases. You know, the way we see this at Nvidia, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled, uh, use cases, particular use cases like a chat bot, uh, uh, from the ground up with the hardware and the software almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. I think we are in the first phase of the democratization, uh, for example, the work we did with Cloudera, which is, uh, for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. >>And you still come home and assemble it, but all the parts are there. The instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought, bought a table and it showed up and somebody placed it in the right spot. Right. And they didn't really have to learn, uh, how to do AI. So these are the phases. And I think they're very excited to be going there. Yeah. You know, >>Rob, the great thing about for, for your customers is they don't have to build out the AI. They can, they can buy it. And, and just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations and Mick and I talked about this, the guy go problem that we've all studied in college, uh, you know, garbage in, garbage out. Uh, but, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob over the next several years? >>So yeah, the combination of massive amounts of data that have been gathered across the enterprise in the past 10 years with an open API APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency, you know, and that's allowing us as an industry to democratize the data access while at the same time, delivering the federated governance and security models and hybrid technologies are playing a key role in making this a reality and enabling data access to be hybridized, meaning access and treated in a substantially similar way, your respect to the physical location of where that data actually resides. >>That's great. That is really the value layer that you guys are building out on top of that, all this great infrastructure that the hyperscalers have have given us, I mean, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you can go first and then manufacture. You could bring us home. Where do you guys want to see the relationship go between cloud era and Nvidia? In other words, how should we, as outside observers be, be thinking about and measuring your project specifically and in the industry's progress generally? >>Yeah, I think we're very aligned on this and for cloud era, it's all about helping companies move forward, leverage every bit of their data and all the places that it may, uh, be hosted and partnering with our customers, working closely with our technology ecosystem of partners means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >>Yeah. And I agree with Robin and for us at Nvidia, you know, we, this partnership started, uh, with data analytics, um, as you know, a spark is a very powerful technology for data analytics, uh, people who use spark rely on Cloudera for that. And the first thing we did together was to really accelerate spark in a seamless manner, but we're accelerating machine learning. We accelerating artificial intelligence together. And I think for Nvidia it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity. >>Okay. Now we're going to dig into the data landscape and cloud of course. And talk a little bit more about that with drew Allen. He's a managing director at Accenture drew. Welcome. Great to see you. Thank you. So let's talk a little bit about, you know, you've been in this game for a number of years. Uh, you've got particular expertise in, in data and finance and insurance. I mean, you know, you think about it within the data and analytics world, even our language is changing. You know, we don't say talk about big data so much anymore. We talk more about digital, you know, or, or, or data driven when you think about sort of where we've come from and where we're going. What are the puts and takes that you have with regard to what's going on in the business today? >>Well, thanks for having me. Um, you know, I think some of the trends we're seeing in terms of challenges and puts some takes are that a lot of companies are already on this digital journey. Um, they focused on customer experience is kind of table stakes. Everyone wants to focus on that and kind of digitizing their channels. But a lot of them are seeing that, you know, a lot of them don't even own their, their channels necessarily. So like we're working with a big cruise line, right. And yes, they've invested in digitizing what they own, but a lot of the channels that they sell through, they don't even own, right. It's the travel agencies or third party, real sellers. So having the data to know where, you know, where those agencies are, that that's something that they've discovered. And so there's a lot of big focus on not just digitizing, but also really understanding your customers and going across products because a lot of the data has built, been built up in individual channels and in digital products. >>And so bringing that data together is something that customers that have really figured out in the last few years is a big differentiator. And what we're seeing too, is that a big trend that the data rich are getting richer. So companies that have really invested in data, um, are having, uh, an outside market share and outside earnings per share and outside revenue growth. And it's really being a big differentiator. And I think for companies just getting started in this, the thing to think about is one of the missteps is to not try to capture all the data at once. The average company has, you know, 10,000, 20,000 data elements individually, when you want to start out, you know, 500, 300 critical data elements, about 5% of the data of a company drives 90% of the business value. So focusing on those key critical data elements is really what you need to govern first and really invest in first. And so that's something we, we tell companies at the beginning of their data strategy is first focus on those critical data elements, really get a handle on governing that data, organizing that data and building data products around >>That day. You can't boil the ocean. Right. And so, and I, I feel like pre pandemic, there was a lot of complacency. Oh yeah, we'll get to that. You know, not on my watch, I'll be retired before that, you know, is it becomes a minute. And then of course the pandemic was, I call it sometimes a forced March to digital. So in many respects, it wasn't planned. It just ha you know, you had to do it. And so now I feel like people are stepping back and saying, okay, let's now really rethink this and do it right. But is there, is there a sense of urgency, do you think? Absolutely. >>I think with COVID, you know, we were working with, um, a retailer where they had 12,000 stores across the U S and they had didn't have the insights where they could drill down and understand, you know, with the riots and with COVID was the store operational, you know, with the supply chain of the, having multiple distributors, what did they have in stock? So there are millions of data points that you need to drill down at the cell level, at the store level to really understand how's my business performing. And we like to think about it for like a CEO and his leadership team of it, like, think of it as a digital cockpit, right? You think about a pilot, they have a cockpit with all these dials and, um, dashboards, essentially understanding the performance of their business. And they should be able to drill down and understand for each individual, you know, unit of their work, how are they performing? That's really what we want to see for businesses. Can they get down to that individual performance to really understand how their business >>Is performing good, the ability to connect those dots and traverse those data points and not have to go in and come back out and go into a new system and come back out. And that's really been a lot of the frustration. W where does machine intelligence and AI fit in? Is that sort of a dot connector, if you will, and an enabler, I mean, we saw, you know, decades of the, the AI winter, and then, you know, there's been a lot of talk about it, but it feels like with the amount of data that we've collected over the last decade and the, the, the low costs of processing that data now, it feels like it's, it's real. Where do you see AI fitting? Yeah, >>I mean, I think there's been a lot of innovation in the last 10 years with, um, the low cost of storage and computing and these algorithms in non-linear, um, you know, knowledge graphs, and, um, um, a whole bunch of opportunities in cloud where what I think the, the big opportunity is, you know, you can apply AI in areas where a human just couldn't have the scale to do that alone. So back to the example of a cruise lines, you know, you may have a ship being built that has 4,000 cabins on the single cruise line, and it's going to multiple deaths that destinations over its 30 year life cycle. Each one of those cabins is being priced individually for each individual destination. It's physically impossible for a human to calculate the dynamic pricing across all those destinations. You need a machine to actually do that pricing. And so really what a machine is leveraging is all that data to really calculate and assist the human, essentially with all these opportunities where you wouldn't have a human being able to scale up to that amount of data >>Alone. You know, it's interesting. One of the things we talked to Nicolson about earlier was just the everybody's algorithms are out of whack. You know, you look at the airline pricing, you look at hotels it's as a consumer, you would be able to kind of game the system and predict that they can't even predict these days. And I feel as though that the data and AI are actually going to bring us back into some kind of normalcy and predictability, uh, what do you see in that regard? Yeah, I think it's, >>I mean, we're definitely not at a point where, when I talked to, you know, the top AI engineers and data scientists, we're not at a point where we have what they call broad AI, right? You can get machines to solve general knowledge problems, where they can solve one problem and then a distinctly different problem, right? That's still many years away, but narrow why AI, there's still tons of use cases out there that can really drive tons of business performance challenges, tons of accuracy challenges. So for example, in the insurance industry, commercial lines, where I work a lot of the time, the biggest leakage of loss experience in pricing for commercial insurers is, um, people will go in as an agent and they'll select an industry to say, you know what, I'm a restaurant business. Um, I'll select this industry code to quote out a policy, but there's, let's say, you know, 12 dozen permutations, you could be an outdoor restaurant. >>You could be a bar, you could be a caterer and all of that leads to different loss experience. So what this does is they built a machine learning algorithm. We've helped them do this, that actually at the time that they're putting in their name and address, it's crawling across the web and predicting in real time, you know, is this a address actually, you know, a business that's a restaurant with indoor dining, does it have a bar? Is it outdoor dining? And it's that that's able to accurately more price the policy and reduce the loss experience. So there's a lot of that you can do even with narrow AI that can really drive top line of business results. >>Yeah. I liked that term, narrow AI, because getting things done is important. Let's talk about cloud a little bit because people talk about cloud first public cloud first doesn't necessarily mean public cloud only, of course. So where do you see things like what's the right operating model, the right regime hybrid cloud. We talked earlier about hybrid data help us squint through the cloud landscape. Yeah. I mean, I think for most right, most >>Fortune 500 companies, they can't just snap their fingers and say, let's move all of our data centers to the cloud. They've got to move, you know, gradually. And it's usually a journey that's taking more than two to three plus years, even more than that in some cases. So they're have, they have to move their data, uh, incrementally to the cloud. And what that means is that, that they have to move to a hybrid perspective where some of their data is on premise and some of it is publicly on the cloud. And so that's the term hybrid cloud essentially. And so what they've had to think about is from an intelligence perspective, the privacy of that data, where is it being moved? Can they reduce the replication of that data? Because ultimately you like, uh, replicating the data from on-premise to the cloud that introduces, you know, errors and data quality issues. So thinking about how do you manage, uh, you know, uh on-premise and, um, public as a transition is something that Accenture thinks, thinks, and helps our clients do quite a bit. And how do you move them in a manner that's well-organized and well thought of? >>Yeah. So I've been a big proponent of sort of line of business lines of business becoming much more involved in, in the data pipeline, if you will, the data process, if you think about our major operational systems, they all have sort of line of business context in them. And then the salespeople, they know the CRM data and, you know, logistics folks there they're very much in tune with ERP, almost feel like for the past decade, the lines of business have been somewhat removed from the, the data team, if you will. And that, that seems to be changing. What are you seeing in terms of the line of line of business being much more involved in sort of end to end ownership, if you will, if I can use that term of, uh, of the data and sort of determining things like helping determine anyway, the data quality and things of that nature. Yeah. I >>Mean, I think this is where thinking about your data operating model and thinking about ideas of a chief data officer and having data on the CEO agenda, that's really important to get the lines of business, to really think about data sharing and reuse, and really getting them to, you know, kind of unlock the data because they do think about their data as a fiefdom data has value, but you've got to really get organizations in their silos to open it up and bring that data together because that's where the value is. You know, data doesn't operate. When you think about a customer, they don't operate in their journey across the business in silo channels. They don't think about, you know, I use only the web and then I use the call center, right? They think about that as just one experience and that data is a single journey. >>So we like to think about data as a product. You know, you should think about a data in the same way. You think about your products as, as products, you know, data as a product, you should have the idea of like every two weeks you have releases to it. You have an operational resiliency to it. So thinking about that, where you can have a very product mindset to delivering your data, I think is very important for the success. And that's where kind of, there's not just the things about critical data elements and having the right platform architecture, but there's a soft stuff as well, like a, a product mindset to data, having the right data, culture, and business adoption and having the right value set mindset for, for data, I think is really >>Important. I think data as a product is a very powerful concept and I think it maybe is uncomfortable to some people sometimes. And I think in the early days of big data, if you will, people thought, okay, data is a product going to sell my data and that's not necessarily what you mean, thinking about products or data that can fuel products that you can then monetize maybe as a product or as a, as, as a service. And I like to think about a new metric in the industry, which is how long does it take me to get from idea I'm a business person. I have an idea for a data product. How long does it take me to get from idea to monetization? And that's going to be something that ultimately as a business person, I'm going to use to determine the success of my data team and my data architecture. Is that kind of thinking starting to really hit the marketplace? Absolutely. >>I mean, I insurers now are working, partnering with, you know, auto manufacturers to monetize, um, driver usage data, you know, on telematics to see, you know, driver behavior on how, you know, how auto manufacturers are using that data. That's very important to insurers, you know, so how an auto manufacturer can monetize that data is very important and also an insurance, you know, cyber insurance, um, are there news new ways we can look at how companies are being attacked with viruses and malware. And is there a way we can somehow monetize that information? So companies that are able to agily, you know, think about how can we collect this data, bring it together, think about it as a product, and then potentially, you know, sell it as a service is something that, um, company, successful companies, you're doing great examples >>Of data products, and it might be revenue generating, or it might be in the case of, you know, cyber, maybe it reduces my expected loss and exactly. Then it drops right to my bottom line. What's the relationship between Accenture and cloud era? Do you, I presume you guys meet at the customer, but maybe you could give us some insight. >>Yeah. So, um, I, I'm in the executive sponsor for, um, the Accenture Cloudera partnership on the Accenture side. Uh, we do quite a lot of business together and, um, you know, Cloudera has been a great partner for us. Um, and they've got a great product in terms of the Cloudera data platform where, you know, what we do is as a big systems integrator for them, we help, um, you know, configure and we have a number of engineers across the world that come in and help in terms of, um, engineer architects and install, uh, cloud errors, data platform, and think about what are some of those, you know, value cases where you can really think about organizing data and bringing it together for all these different types of use cases. And really just as the examples we thought about. So the telematics, you know, um, in order to realize something like that, you're bringing in petabytes and huge scales of data that, you know, you just couldn't bring on a normal, uh, platform. You need to think about cloud. You need to think about speed of, of data and real-time insights and cloud era is the right data platform for that. So, um, >>Having a cloud Cloudera ushered in the modern big data era, we kind of all know that, and it was, which of course early on, it was very services intensive. You guys were right there helping people think through there weren't enough data scientists. We've sort of all, all been through that. And of course in your wheelhouse industries, you know, financial services and insurance, they were some of the early adopters, weren't they? Yeah, absolutely. >>Um, so, you know, an insurance, you've got huge amounts of data with loss history and, um, a lot with IOT. So in insurance, there's a whole thing of like sensorized thing in, uh, you know, taking the physical world and digitizing it. So, um, there's a big thing in insurance where, um, it's not just about, um, pricing out the risk of a loss experience, but actual reducing the loss before it even happens. So it's called risk control or loss control, you know, can we actually put sensors on oil pipelines or on elevators and, you know, reduce, um, you know, accidents before they happen. So we're, you know, working with an insurer to actually, um, listen to elevators as they move up and down and are there signals in just listening to the audio of an elevator over time that says, you know what, this elevator is going to need maintenance, you know, before a critical accident could happen. So there's huge applications, not just in structured data, but in unstructured data like voice and audio and video where a partner like Cloudera has a huge role to play. >>Great example of it. So again, narrow sort of use case for machine intelligence, but, but real value. True. We'll leave it like that. Thanks so much for taking some time. Yes. Thank you so much. Okay. We continue now with the theme of turning ideas into insights. So ultimately you can take action. We heard earlier that public cloud first doesn't mean public cloud only, and a winning strategy comprises data, irrespective of physical location on prem, across multiple clouds at the edge where real time inference is going to drive a lot of incremental value. Data is going to help the world come back to normal. We heard, or at least semi normal as we begin to better understand and forecast demand and supply and balances and economic forces. AI is becoming embedded into every aspect of our business, our people, our processes, and applications. And now we're going to get into some of the foundational principles that support the data and insights centric processes, which are fundamental to digital transformation initiatives. And it's my pleasure to welcome two great guests, Michelle Goetz. Who's a Kuba woman, VP and principal analyst at Forrester, and doing some groundbreaking work in this area. And Cindy, Mikey, who is the vice president of industry solutions and value management at Cloudera. Welcome to both of >>You. Welcome. Thank you. Thanks Dave. >>All right, Michelle, let's get into it. Maybe you could talk about your foundational core principles. You start with data. What are the important aspects of this first principle that are achievable today? >>It's really about democratization. If you can't make your data accessible, um, it's not usable. Nobody's able to understand what's happening in the business and they don't understand, um, what insights can be gained or what are the signals that are occurring that are going to help them with decisions, create stronger value or create deeper relationships, their customers, um, due to their experiences. So it really begins with how do you make data available and bring it to where the consumer of the data is rather than trying to hunt and Peck around within your ecosystem to find what it is that's important. Great. >>Thank you for that. So, Cindy, I wonder in hearing what Michelle just said, what are your thoughts on this? And when you work with customers at Cloudera, does, are there any that stand out that perhaps embody the fundamentals that Michelle just shared? >>Yeah, there's, there's quite a few. And especially as we look across, um, all the industries that we're actually working with customers in, you know, a few that stand out in top of mind for me is one is IQ via and what they're doing with real-world evidence and bringing together data across the entire, um, healthcare and life sciences ecosystems, bringing it together in different shapes and formats, making the ed accessible by both internally, as well as for their, um, the entire extended ecosystem. And then for SIA, who's working to solve some predictive maintenance issues within, there are a European car manufacturer and how do they make sure that they have, you know, efficient and effective processes when it comes to, uh, fixing equipment and so forth. And then also, um, there's, uh, an Indonesian based, um, uh, telecommunications company tech, the smell, um, who's bringing together, um, over the last five years, all their data about their customers and how do they enhance our customer experience? How do they make information accessible, especially in these pandemic and post pandemic times, um, uh, you know, just getting better insights into what customers need and when do they need it? >>Cindy platform is another core principle. How should we be thinking about data platforms in this day and age? I mean, where does, where do things like hybrid fit in? Um, what's cloud era's point >>Of view platforms are truly an enabler, um, and data needs to be accessible in many different fashions. Um, and also what's right for the business. When, you know, I want it in a cost and efficient and effective manner. So, you know, data needs to be, um, data resides everywhere. Data is developed and it's brought together. So you need to be able to balance both real time, you know, our batch historical information. It all depends upon what your analytical workloads are. Um, and what types of analytical methods you're going to use to drive those business insights. So putting and placing data, um, landing it, making it accessible, analyzing it needs to be done in any accessible platform, whether it be, you know, a public cloud doing it on-prem or a hybrid of the two is typically what we're seeing, being the most successful. >>Great. Thank you, Michelle. Let's move on a little bit and talk about practices and practices and processes as the next core principles. Maybe you could provide some insight as to how you think about balancing practices and processes while at the same time managing agility. >>Yeah, it's a really great question because it's pretty complex. When you have to start to connect your data to your business, the first thing to really gravitate towards is what are you trying to do? And what Cindy was describing with those customer examples is that they're all based off of business goals off of very specific use cases that helps kind of set the agenda about what is the data and what are the data domains that are important to really understanding and recognizing what's happening within that business activity and the way that you can affect that either in, you know, near time or real time, or later on, as you're doing your strategic planning, what that's balancing against is also being able to not only see how that business is evolving, but also be able to go back and say, well, can I also measure the outcomes from those processes and using data and using insight? >>Can I also get intelligence about the data to know that it's actually satisfying my objectives to influence my customers in my market? Or is there some sort of data drift or detraction in my, um, analytic capabilities that are allowing me to be effective in those environments, but everything else revolves around that and really thinking succinctly about a strategy that isn't just data aware, what data do I have and how do I use it, but coming in more from that business perspective to then start to be, data-driven recognizing that every activity you do from a business perspective leads to thinking about information that supports that and supports your decisions, and ultimately getting to the point of being insight driven, where you're able to both, uh, describe what you want your business to be with your data, using analytics, to then execute on that fluidly and in real time. And then ultimately bringing that back with linking to business outcomes and doing that in a continuous cycle where you can test and you can learn, you can improve, you can optimize, and you can innovate because you can see your business as it's happening. And you have the right signals and intelligence that allow you to make great decisions. >>I like how you said near time or real time, because it is a spectrum. And you know, one of the spectrum, autonomous vehicles, you've got to make a decision in real time, but, but, but near real-time, or real-time, it's, it's in the eyes of the holder, if you will, it's it might be before you lose the customer before the market changes. So it's really defined on a case by case basis. Um, I wonder Michelle, if you could talk about in working with a number of organizations, I see folks, they sometimes get twisted up and understanding the dependencies that technology generally, and the technologies around data specifically can have on critical business processes. Can you maybe give some guidance as to where customers should start, where, you know, where can we find some of the quick wins and high return, it >>Comes first down to how does your business operate? So you're going to take a look at the business processes and value stream itself. And if you can understand how people and customers, partners, and automation are driving that step by step approach to your business activities, to realize those business outcomes, it's way easier to start thinking about what is the information necessary to see that particular step in the process, and then take the next step of saying what information is necessary to make a decision at that current point in the process, or are you collecting information asking for information that is going to help satisfy a downstream process step or a downstream decision. So constantly making sure that you are mapping out your business processes and activities, aligning your data process to that helps you now rationalize. Do you need that real time near real time, or do you want to start grading greater consistency by bringing all of those signals together, um, in a centralized area to eventually oversee the entire operations and outcomes as they happen? It's the process and the decision points and acting on those decision points for the best outcome that really determines are you going to move in more of a real-time, uh, streaming capacity, or are you going to push back into more of a batch oriented approach? Because it depends on the amount of information and the aggregate of which provides the best insight from that. >>Got it. Let's, let's bring Cindy back into the conversation in your city. We often talk about people process and technology and the roles they play in creating a data strategy. That's that's logical and sound. Can you speak to the broader ecosystem and the importance of creating both internal and external partners within an organization? Yeah. >>And that's, uh, you know, kind of building upon what Michelle was talking about. If you think about datas and I hate to use the phrase almost, but you know, the fuel behind the process, um, and how do you actually become insight-driven? And, you know, you look at the capabilities that you're needing to enable from that business process, that insight process, um, you're extended ecosystem on, on how do I make that happen? You know, partners, um, and, and picking the right partner is important because a partner is one that actually helps under or helps you implement what your decisions are. Um, so, um, looking for a partner that has the capability that believes in being insight-driven and making sure that when you're leveraging data, um, you know, for within process on that, if you need to do it in a time fashion, that they can actually meet those needs of the business, um, and enabling on those, those process activities. So the ecosystem looking at how you, um, look at, you know, your vendors are, and fundamentally they need to be that trusted partner. Um, do they bring those same principles of value of being insight driven? So they have to have those core values themselves in order to help you as a, um, an end of business person enable those capabilities. So, so yeah, I'm >>Cool with fuel, but it's like super fuel when you talk about data, cause it's not scarce, right? You're never going to run out. So Michelle, let's talk about leadership. W w who leads, what does so-called leadership look like in an organization that's insight driven? >>So I think the really interesting thing that is starting to evolve as late is that organizations enterprises are really recognizing that not just that data is an asset and data has value, but exactly what we're talking about here, data really does drive what your business outcomes are going to be data driving into the insight or the raw data itself has the ability to set in motion. What's going to happen in your business processes and your customer experiences. And so, as you kind of think about that, you're now starting to see your CEO, your CMO, um, your CRO coming back and saying, I need better data. I need information. That's representative of what's happening in my business. I need to be better adaptive to what's going on with my customers. And ultimately that means I need to be smarter and have clearer forecasting into what's about ready to come, not just, you know, one month, two months, three months or a year from now, but in a week or tomorrow. >>And so that's, how is having a trickle down effect to then looking at two other types of roles that are elevating from technical capacity to more business capacity, you have your chief data officer that is shaping the exp the experiences, uh, with data and with insight and reconciling, what type of information is necessary with it within the context of answering these questions and creating a future fit organization that is adaptive and resilient to things that are happening. And you also have a chief digital officer who is participating because they're providing the experience and shaping the information and the way that you're going to interact and execute on those business activities, and either running that autonomously or as part of an assistance for your employees and for your customers. So really to go from not just data aware to data driven, but ultimately to be insight driven, you're seeing way more, um, participation, uh, and leadership at that C-suite level. And just underneath, because that's where the subject matter expertise is coming in to know how to create a data strategy that is tightly connected to your business strategy. >>Right. Thank you. Let's wrap. And I've got a question for both of you, maybe Cindy, you could start and then Michelle bring us home. You know, a lot of customers, they want to understand what's achievable. So it's helpful to paint a picture of a, of a maturity model. Uh, you know, I'd love to go there, but I'm not going to get there anytime soon, but I want to take some baby steps. So when you're performing an analysis on, on insight driven organization, city, what do you see as the major characteristics that define the differences between sort of the, the early, you know, beginners, the sort of fat middle, if you will, and then the more advanced, uh, constituents. >>Yeah, I'm going to build upon, you know, what Michelle was talking about as data as an asset. And I think, you know, also being data where, and, you know, trying to actually become, you know, insight driven, um, companies can also have data and they can have data as a liability. And so when you're data aware, sometimes data can still be a liability to your organization. If you're not making business decisions on the most recent and relevant data, um, you know, you're not going to be insight driven. So you've got to move beyond that, that data awareness, where you're looking at data just from an operational reporting, but data's fundamentally driving the decisions that you make. Um, as a business, you're using data in real time. You're, um, you're, you know, leveraging data to actually help you make and drive those decisions. So when we use the term you're, data-driven, you can't just use the term, you know, tongue in cheek. It actually means that I'm using the recent, the relevant and the accuracy of data to actually make the decisions for me, because we're all advancing upon. We're talking about, you know, artificial intelligence and so forth. Being able to do that, if you're just data where I would not be embracing on leveraging artificial intelligence, because that means I probably haven't embedded data into my processes. It's data could very well still be a liability in your organization. So how do you actually make it an asset? Yeah, I think data >>Where it's like cable ready. So, so Michelle, maybe you could, you could, you could, uh, add to what Cindy just said and maybe add as well, any advice that you have around creating and defining a data strategy. >>So every data strategy has a component of being data aware. This is like building the data museum. How do you capture everything that's available to you? How do you maintain that memory of your business? You know, bringing in data from your applications, your partners, third parties, wherever that information is available, you want to ensure that you're capturing and you're managing and you're maintaining it. And this is really where you're starting to think about the fact that it is an asset. It has value, but you may not necessarily know what that value is. Yet. If you move into a category of data driven, what starts to shift and change there is you're starting to classify label, organize the information in context of how you're making decisions and how you do business. It could start from being more, um, proficient from an analytic purpose. You also might start to introduce some early stages of data science in there. >>So you can do some predictions and some data mining to start to weed out some of those signals. And you might have some simple types of algorithms that you're deploying to do a next next best action for example. And that's what data-driven is really about. You're starting to get value out of it. The data itself is starting to make sense in context of your business, but what you haven't done quite yet, which is what insight driven businesses are, is really starting to take away. Um, the gap between when you see it, know it and then get the most value and really exploit what that insight is at the time when it's right. So in the moment we talk about this in terms of perishable insights, data and insights are ephemeral. And we want to ensure that the way that we're managing that and delivering on that data and insights is in time with our decisions and the highest value outcome we're going to have, that that insight can provide us. >>So are we just introducing it as data-driven organizations where we could see, you know, spreadsheets and PowerPoint presentations and lots of mapping to help make sort of longer strategic decisions, or are those insights coming up and being activated in an automated fashion within our business processes that are either assisting those human decisions at the point when they're needed, or an automated decisions for the types of digital experiences and capabilities that we're driving in our organization. So it's going from, I'm a data hoarder. If I'm data aware to I'm interested in what's happening as a data-driven organization and understanding my data. And then lastly being insight driven is really where light between business, data and insight. There is none it's all coming together for the best outcomes, >>Right? So people are acting on perfect or near perfect information or machines or, or, uh, doing so with a high degree of confidence, great advice and insights. And thank you both for sharing your thoughts with our audience today. It's great to have you. Thank you. Thank you. Okay. Now we're going to go into our industry. Deep dives. There are six industry breakouts, financial services, insurance, manufacturing, retail communications, and public sector. Now each breakout is going to cover two distinct use cases for a total of essentially 12 really detailed segments that each of these is going to be available on demand, but you can scan the calendar on the homepage and navigate to your breakout session for choice of choice or for more information, click on the agenda page and take a look to see which session is the best fit for you. And then dive in, join the chat and feel free to ask questions or contribute your knowledge, opinions, and data. Thanks so much for being part of the community and enjoy the rest of the day.

(bright upbeat music) >> Hi well, this is Dave Vellante. We're digging deeper into the world of database. You know, there are a lot of ways to skin a cat and different vendors take different approaches and we're reaching out to the technologists to get their perspective on the major trends that they're seeing in the market, 'cause we want to understand the different ways in which you can solve problems. So look, if you have thoughts and the technical chops on this topic, I'd love to interview you. Just ping me at at DVellante, on Twitter, a lot of ways to get ahold of me. Anyway, we recently spoke with Andrew Mendelsohn, who is Oracle's EVP and he's responsible for database server technologies. And we talked a lot about Oracle's ADW, Autonomous Data Warehouse. And we looked at the cloud database strategy that Oracle is taking and the company's plans and how they're different maybe from other solutions in the marketplace, but I wanted to dig deeper. And so today we have two members of Mendelsohn's team on The Cube, and we're going to probe a little bit. George Lumpkin, is the Vice President of Autonomous Data Warehouse. And Neil Mendelson is the VP of Modern Data Warehouse, that business for Oracle. They're both 20-year veterans of Oracle. When I reached out to Steve Savannah, who's a colleague of mine for many years, he's always telling me how great Oracle is relative to the competition. So I said, okay, come on The Cube and talk about this, give me your best people. And he said, whatever these two don't know about cloud data warehouse, it isn't worth knowing anyway. So with that said gentlemen, welcome to The Cube. Thanks so much for coming on. >> Thank you. >> Hey, glad to be here. >> So George, let's start with you. And maybe we could recap for some of the viewers who might not be familiar with the interview that I did with Andy. In your words, what exactly is an Autonomous Data Warehouse? Is this cloud native? Is it an Oracle buzzword? What is it? >> Well, I mean, Autonomous Data Warehouse is Oracle's cloud data warehouse. It's a service that built to allow business users to get more value from their data. That's what the cloud data warehouse market is. Autonomous Data Warehouse is absolutely cloud native. This is a huge misconception that people might have when they first sort of hear about something, this service because they think this is a Oracle database, right? Oracle makes databases. This is the same old database I knew from 10 years ago. And that's absolutely not true. We built a cloud native service or data warehousing built it with cloud features. You know, if your understanding of the cloud data warehouse market is based upon how you thought things look 10 years ago, like Snowflake wouldn't have even existed, right? You can't base your understanding of Oracle based upon that. We have a modern service that's highly elastic, provides cloud capabilities like online patching and it's fully autonomous. It's really built the business users so they don't need to worry about administering their database. >> So I want to come back and actually ask you some questions about that, but let me follow up and talk about some of the evolution of the ADW. And where did you start? I think it was 2018, maybe where you came from, where you are today, maybe you can take us through the technological progression and maybe the path you took to get here. >> And so 2018, was when we released the service and made generally available, but of course, you know we started much earlier than that. And this was started within my product management team, and other organization. So we really sat down with a blank sheet of paper and we said, what should the data warehouse in the cloud look like? You know, let's put aside everything that Oracle does for its on-prem customers and think about how the cloud should be different. And the first thing that we said was, well, you know, if Oracle writes the database software, and Oracle builds its own hardware, and Oracle has created its own cloud, why do we need customers to manage a database? And that's where the idea of autonomous database came from. That Oracle is managing the entire ecosystem. And therefore we built a database that we believe it's far and away the simplest to use simplest data warehouse in the market. And that's been our focus since we started with 2018. And that continues to be our focus, looking at more ways that we can make an Autonomous Data Warehouse as simpler and easier for business users to get more value out of their data. >> Awesome, one more question. And actually Neil, you might want to chime in on this as well. So just from a technical perspective, you know forget the marketing claims and all the BS. How do you compare ADW to the so-called born in the cloud data warehouses? You mentioned Snowflake, you know Redshift, is Redshift born in the cloud. Well, it was par XL but Amazon's done some good work around Redshift. I think big query is maybe probably a better example 'cause it was, you know, like Snowflake started in the cloud but how do you compare ADW to some of these other so-called born in the cloud data warehouses? >> I think part of this, you mentioned Redshift wasn't important in the cloud. It was, you know, a code base taken from a prior company that was on-premise company. So they adapted it to the cloud, right? And you know, we have done, as George said, much of the same, which is, you know, our starting point was not you know another company's code base, but our starting point was our own code base. But as George said, it's less about the starting point and it's more about where you envision the end point, right? Which is that, you know, whatever your starting point is, I think we have a fundamental different view of the endpoint. Amazon talks about how they're literally built for you know, a cloud built for developers, right? You know, builders, right? And you know Oracle wasn't first in the infrastructure business, we entered through applications business. And all of a sudden, you know we began taking on 100s of 1000s and 100s of even more customers that were SAS customers. Underneath was the database and all the infrastructure. One of the things that we took away from that was that we couldn't possibly hire enough people DBA, to manage all the infrastructure below our applications customers. So one of the things that influenced this is that, you know customers expect SAS applications to just take care of themselves, right? So we had to essentially modify the infrastructure to allow it to do so as well, right? And we're bringing that capability to those people who, you know, may or may not have an application, but their interest is, you know more of this self-service agility type of aspect. >> So it seems to me and Georgia was sort of alluding to this before. I mean, when you mentioned Snowflake a couple of times, and then Neil, something you just said, I'm going to pick up on is you've been around for a long time. And you know, when I talked to the Snowflake people, they know Oracle, a lot of them came from Oracle. They understand I think how you can't just build Oracle overnight and build in the capabilities that Oracle has and the recovery. And you talk to customers and you know you are the gold standard of, you know especially mission critical databases, so I get that. But now you just sort of hit on it, is it takes a lot of people and skill to run the database. So that's the problem that you're saying you were attacking, is that, am I getting that right? >> Right, right, so the people that you talked about who originally built Snowflake came from Oracle, but they came from Oracle more than a decade ago. So their context is over a decade old, right? In the meantime, we've been busy, you know building a economies and many other capabilities, right? Their view of Oracle is that view that was back more than 10 years ago, right? They're still adding capability. So a really good example of this illustration is Oracle as you said, it's the most capable system that's out there and has been for many years. We've been focusing on how do we simplify that and how do we use machine learning embedded within the system itself? Because core to the concept of autonomous is that inside, is this machine learning system that's continually improving, right? That's the whole notion. Where in Snowflakes case, they're still adding functionality. Last year, they added masking which you know functionality they didn't have, but when they added the capability, they added it without, you know, the ability for a business user to actually take advantage of it. There's no capability for a business user to actually find the information that needs to be masked. And then after the information is found, you require a technical person to actually implement the mask. In Oracle's case, we've had masking and those capabilities for a long time, our focus was to be able to provide a simple tool that a business user can use that doesn't need technical or security experience. Find the data that needs to be masked PII data, and then hit a button and have it masked for you. So, you know, they're still, you know, without this notion of a strategy to move toward the system to heal itself and to manage itself, they're just going to continue. As they continue to add more capability, they will in turn add more complexity. What we're trying to do is take complexity out while others are adding it in, its an ironic twist. >> It is an ironic twist. It is interesting to look at it. And I don't want to make this about Snowflake. But I mean, Hey, I like what they're doing. I like them. I know the management, they're growing like crazy and you know and the customers tell me, hey, this is really simple. And it's simple by design. I mean, to your point over time it's going to get, you know, more and more complex. I was talking to Andy, I think it was Andy. He was saying, you know, they've got the different sizes you've got to shape some, you know, they call it t-shirt sizes. And I was like, okay, I got a small, I got a medium and a large, maybe that's okay. But you guys would say, we give more granular you know, a scaling, I guess is the point there, right? I mean George, I don't know if you can comment on that. It just a different strategy. You've got a company that was founded well, I guess, 2015 versus one that was founded in 1977. So you would think the latter has, you know way more function than the former, but George, anything you'd add to this conversation? >> Yeah, I mean, I'm always amazed that there are these database systems that are perceived as cloud native and they do things like sell you database sizes by t-shirt sizes, as you described. I mean, if you look at Snowflake, it's small, medium, large extra large too extra large, but they're all factors of two. You're getting a size of your database of two, four, eight, six, 32, et cetera. Or if you look at AWS Redshift, you're buying your database by the nodes. You say, how many nodes do you want? And in both those cases, this is a cloud native. This is saying we have some hardware underneath our database and we need you, Mr. Customer, to tell us how many servers you want. That's not the way the clouds should work, right? And I think this is one of the things that we did with Autonomous Data Warehouse. We said, no, that's not how the rules should work. We still run our database on hardware, we still have nodes and servers. We should tell the customer, how many CPU's you would like for your data warehouse? You want 16? Sounds good. You want 18? Yeah, we can give you 18. We're not, you know, we're not selling these to you in bundles of eight or bundles of six or powers of two. We'll sell you what you need. That's what cloud elasticity should be. Not this idea that oh, we are a database that should be managed by IT. IT already knows about servers and nodes. Therefore it's okay if we tell people your cloud data warehouse runs on nodes. Within Oracle as Neil said, we wouldn't. The data warehouse should be used by the people who want to actually analyze their data, should be used by the business users. >> Well, and so the other piece of cloud native that has become popular, is this idea of separating compute from storage and being able to scale those two independent of each other which is pretty important, right? Because you don't want to have to pay for a chunk of compute if you don't need the storage and vice versa. Maybe you could talk about that, how you solve that problem, to the extent that you solve that problem. >> Absolutely, we do separate compute print storage with Autonomous Data Warehouse. When you come in and you say, I need 10 CPU's for my data warehouse and I need two terabytes of storage. Those are two dependent decisions that you make. So they're not tied together in any way. And, you are exactly right, Dave, this is how things should work in the cloud. You should pay for what you need, pay for what you use, not be constrained by having big sets of storage you have to use for a given amount CPU or vice versa. >> Okay, go ahead Neil, please. >> Oh, just to add on to that, you know, the other aspect that comes into play is that, you know, so your starting point is X, whatever that happens to be. Over time that changes. And we all know that workloads vary right throughout the day throughout the month, throughout the year by various events that occur maybe the close of the year, close of business at the end of the quarter, it maybe you know, holiday season for retailers and so forth. So, you know, it's not only the starting point, but how do you actually manage the growth, right? scaling up and scaling down, right? In our case, we tried, as George said, we abstracted that completely for the customer basically said check a box, which has auto scale. So, if the system is required more resources, will apply more resources. And we do so instantaneously without any downtime whatsoever, right? Because you know, again, you know, people think in terms of these systems have now become business critical. So if the business critical, you can't just shut down to expand. Imagine during the holiday season is your business is ramping up. And then all of a sudden you have to scale, right? And your system either shuts down, reboots itself, right? Or it slows down to the point that it's a crawl and all your customers get frustrated. We don't do that. You click a button, auto scale and we take care of it for you smoothing out those lumps, right? Without any technical assistance. And again, if you look at Redshift, you look at all these various systems, they require technical assistance to be able to figure out not only your initial data, but how you scale out over time. >> Interesting, okay. So all is said, you know, a lot of companies are using Azure, AWS Google for infrastructure, why would these customers not just use their database? Why would they switch to Oracle or ADW? >> Well, I think Neil will probably add something. I want to start by saying a huge number of our existing Autonomous Data Warehouse customers today are customers of AWS and Azure. They are pulling data from AWS and Azure and bringing it into an Oracle Autonomous Data Warehouse. And we built feature Joe, I focused on product managers. We feel featured for that. And so it's perfectly viable and it it's almost commonplace, that the very largest enterprises to be doing that. But then coming to the question of why would they want to do it? I don't know, Neil, you want to take that? >> Yeah, yeah, so one of the things that we've really see emerge here is you know, a data warehouse doesn't generate the transactions on itself, right? So the data has to come from somewhere, right? And you ask yourself, well, where does the data come from? Well, in a lot of cases, that data is coming from applications and increasingly SAS applications that the company has deployed. And those are, you know, HR applications, you know, CRM applications, you know ERP applications and many vertical applications. In Oracle's case, what we've done is we say, okay, well, we have the application, this transactional thing, we have the infrastructure from the economist data warehouse, why don't we just make it really, really easy? And if you're an Oracle applications customer, that's already running on the Oracle cloud, we will essentially provide you the ability to create a data warehouse from that information, right? With a clicker, with largely either with a product and service or quick start kit. You don't start from scratch, you start from where you are. And there are many cases that where you are has data, very much as George mentioned before telcos, banks, insurance companies, governments, all of the data that they want to analyze, a lot of that data guess where it's coming from, it's coming from Oracle applications. So it makes sense to be able to have both the data that's generated and the data that's being analyzed close to the same place. Because at the end of the day, the payoff pitch for any form of analysis is not coming up with an insight, oh, I realized X, Y, Z, but it's rather putting the insight directly into production. And that's where, when you have this stuff spread all over God's greener trying to go from insight into action can take months, if not years. The reason that a lot of customers are now turning to us is that they need to be much more agile and they need to be able to turn that insight into action immediately without it being a science project. >> Okay, thank you for that. So let's tick them off. Like what are the top things that customers can get from Oracle Autonomous Data Warehouse, that they couldn't get from say a Snowflake or Redshift or Big query or SQL server or something yet. I appreciate you guys' willingness to talk about the competition. Let's tick them off. What are the most important things that we should know about that they can't get elsewhere? >> So first, I mean, we already talked about a couple of what we think are really the major themes of Autonomous Data Warehouse. The services is autonomous. You don't need to worry about managing it, anyone can manage the data warehouse. The service is elastic. You can buy and pay for what you use. You know, those are just what we think of as being the general characteristics of Autonomous Data Warehouse. But you know, when you come to your question of, hey, what do we give that other vendors don't provide? And I think the one angle that Autonomous Data Warehouse does a really good job is and Neil was just discussing this, it focuses on the business problems, right? We have years and years of experience with not just database security, but data security, right? You know, every cloud vendor can say, oh we encrypt all your data, we have these compliance certifications, all of these things. And what they're saying is, we are securing your database, we are securing your database infrastructure. At Oracle of course has to do those as well. But where we go further, is we say, hey, no, no, no, no, no, we know what business users want. They want to secure their data. What kind of data am I storing? Do I have PII data? Could you detect whether there's PII data and tell me about it in case some user loaded something that I wasn't aware of? What kind of privileges did I give my users? Can you make sure that those privileges are right? And can you tell me if users were given privileges that they're not using maybe I need to take them away. These are the problems that Oracle's tackled in security over the last 20 years. It's really more about the business problem. Yeah, some other, oh, go ahead. >> Oh, I'm sorry, I got so many questions for you guys. We'll get back to that 'cause it sounds like there's a long list. (laughs) >> We have nowhere to go.(laughs) I want to pick up with George on something you said about elasticity. Is it true pay by the drink? Do you have a consumption pricing? I mean, can I dial it up and dial it down whenever I want? How does that work? >> Yes, I mean not to be too many technical details, but you say, I want 14 CPU's that's what your database runs at. You can change that default number anytime you want online, right? You can say, okay, I'm coming up on my quarter end, I'm going to raise my database 20 CPU. We just do it on the ply. We just adjust the size--- >> What about the other way? What about coming down? Can I go down to one? >> You go down, you can go down to one--- >> And you're not going to charge me for 14 if I go down to one? >> No, if you set it down to one, you get charged for one, right? >> Okay, that's good, that's good. >> In the background, you know we are also allowing levels of auto scaling. You say, if you say hey, I want to charged for 14 and Oracle, can you take care of all those scaling for me? So if a bunch of people jump on at 5:00 PM, to run some queries, 'cause the executive said, hey, I need a report by tomorrow morning. We'll take care of that for you. We'll let you go beyond 14 and only charge you for exactly what you use for those extra CPU's beyond 14. >> Okay, thank you. Go ahead, Neil. >> And maybe, if we add, you know, Andy talked about this when he was on that show with you last week, right? And you know, he talked about this concept of a converged database, but let me talk about it in the way that we see it from a business point of view, right? You know, business users are looking to, you know ask a variety of questions, right? And those questions need to be able to relate to both you know, the customer themselves, the relationship that the customer might have with others. You know, today we talk about like the social network and who are influencers within that, and then where they actually conduct business. Which is really, you know, in every case, it's on some form of increasingly on a mobile device. So in that case, you want to be able to ask questions, which is not only, you know, who should I focus on, but who are the key influencers within this community, right? That could influence others? And does that happen in a particular place in time? Meaning, you know, let's say pre COVID, it might happen at a coffee shop or somewhere else. We can answer all of those questions and more inside of the autonomous system without having to replicate the data out to one system that does graph and another system that does spatial, a third system that does this. It's like a business user. It's like, wait a minute, come on, you're trying to tell me that I need a separate system and replicate the data just be able to understand location? The answer in many cases is yes, you have to have separate, which a business person says, well, that's absurd. Can't I just do this all in one system? You can with Oracle. >> So look, I'm not trying to be the snarky journalist or analyst here but I want to keep pushing on this issue. So here we are, it's 2021. It's April. We're like a third of the way through the year. And so far, nobody has come out and said, okay, we're going to deliver Autonomous Data Warehouse just like Oracle. So I asked myself, well, why is Oracle doing this? You guys answered, you know, to reduce the labor cost. But I asked myself, is this how they're solving the problem of keeping relevant a database that spans five decades? And you guys said, no, no, this is cloud native born in the cloud, you know started essentially with a new mindset. But is this a trend that others are going to follow? You know, and if so, why haven't we seen it this idea of a self-driving databases? Why is it right now unique to Oracle? What's really going on here? >> So I think there's a really interesting thing that's happening, it's not visible outside of Oracle. It's very visible for those of us who work inside of the development organization. You know, if you look at Oracle, I can tell you bad. I mean, I think it's safe to presume Oracle has the largest database development organization on the planet, right? I mean, it was kind of the largest database or large most used database for the past two decades. And what's happened is we pivoted to building a cloud platform. We're not just building a database, we're taking all of these resources that we have with all these expertise of building database software. We were saying, we now have to build the platform to run and manage the database software in the cloud, right? And it's a little bit like, you know I think to make people relate to it a little better, there was a really good quote from Elon Musk couple of years ago, talking about Tesla. Like everyone looks at the car, right? Tesla, the car is really great. The hard part of this, is building the factory, and that's analogy holds for Oracle. What we're building is the cloud battery. And what we have transitioned is our database development organization is now building as robust a cloud as possible. So that you know, when we increase the number of databases by 10 X, we don't add 10 X, more cloud ops people to manage it. We are ramping up developer building features to automate the management of our cloud infrastructure. And with that automation, we get better ability, less errors, more security. We give benefits to our cloud data warehouse customers with it. And I think this something really important to realize, right? We build database software. We build, you know, an engineered system built for databases called exit data, and we build a cloud platform. And these are really equal tiers in what we are building and developing today in 2021 from Oracle database development organization. >> Well, you mentioned exit data, I want to shift gears here a little bit and talk about we're seeing this hybrid cloud on-premises clouds, they're finally gaining some traction. I got to give props Oracle's cloud of customers really the early to that game. I think it was the first in my view anyway, true same same vision, took you guys a little while to get there but it was the right vision. And the thing I always say about Oracle people don't understand is Oracle invest in R and D, your chairman is also the CTO. You guys are serious about technical investment so you know, that's where innovation comes from. But, and we heard during your recent earnings call, we heard some positive comments on this. So what's your take on delivering autonomous data warehouse on-prem and how do you compare with say Snowflake and AWS in that area? Snowflake, Frank Slootman, I've had him on record saying we're not going to do that halfway house. Forget it, we are always going to be in the cloud. We're never going to do an on-prem installation. AWS, we'll see to date. Yeah, I don't think you can get a Redshift for instance in outposts, but maybe that'll come. But, how do you see that emerging? What's your difference there? Maybe Neil, you could talk about that. >> Yeah, so, you know, I think, you know, customers had a lot of regulated industries, right? Still have concerns about the public cloud. And I think that when you hear statements like, you know, we're never going to do, you know, on-prem. Well, economist cloud at customer, it's not a classic on-prem solution. What it is, it's a piece of our cloud delivered in your data center. It's still the cloud software. Oracle manages it, Oracle, you know, the system itself manages itself and we take care of that responsibility so you don't have to. The differences is that we can make that available in a public cloud as well as in a private cloud, right? And there are so many use cases, you know, that you can imagine from a regulatory point of view, or just from a comfort point of view, where customers are choosing, they want the ability to decide for themselves where to place this stuff as compared to only having one option, right? And you know, you look at a lot of what's happening in the emerging world where, you know, there are a lot of places in the world that may not have, you know, really really high-speed internet connections to make, you know a public cloud feasible. Well, in that case, whether you're talking about, you know an oil rig or you're talking about something else, right? We can put that capability where it needs to be close to the operation that you're talking about, irrespective of the deployment option. >> Well, let me just follow up on that because I think it's interesting that, you know Frank Slootman said that to me, I oftentimes around AWS I say, never say never 'cause they'll surprise you, right? And I've learned that with Andy Jassy, but one of the things that seems difficult for on-prem, would be to separate that compute from storage because you have to actually physically move in resources. I think about Vertica Xeon mode. It's not quite the same, same. So, I mean, in that regard, maybe you're not the same same. And maybe that dogma makes sense for some companies. For Oracle, obviously you've got a huge on-prem state, thoughts on that. >> So, you know, clearly, you know, so typically what we'll do is that we'll provide additional hardware beyond what the customer might expect and that allows them to use the capabilities of expansion, right? We also have the ability to allow the customer to expand from their cloud of customer into the public cloud as well, of which we have a lot of those situations. So we can provide a level of elasticity, even on-premises by over provisioning the systems, well not charging the customer until they use only based on what they consume, right? Combined together with the ability for us to augment their usage in the public cloud as well, right? Where others, again are constraint, right? Because they only have a single option. >> Right, well, you've got the capital resources to do that as well which is not to be overlooked. Okay, I mean, I've blown our time here but you guys are so awesome. (laughs) I appreciate the candor. So last question and George, if you want to throw in a couple of those other tick boxes, you know the differentiators, please feel free, but for both of you, if you can leave customers with the one key point or the top key points on how Oracle Autonomous Data Warehouse can really help them improve their business in the near term, what would they be? Maybe George, you could start and then Neil you bring us home. >> Yeah, I mean, I think that, as I said before, our starting point with Autonomous Data Warehouse, is how can we build a better customer experience in the cloud? And I think, and this continues throughout 2021, and I think that the big theme here is the business users should be able to get value directly from their data warehouses. We talked a few times about how a line of business user should be able to manage their own data, should be able to load their own data warehouse, should be able to start to work with their own data, should be able to run machine learning, model of build machine learning, models against that data and all of that built in, and delivered in Autonomous Data Warehouse. And we think that this is, you know we see our customer organizations large and small, the light bulbs starting to go on how easy the services to use to and how completed it is for helping business users get value from their data. And just adding onto what George said, you know, the development organization has done a tremendous job of really simplifying this cooperation. What we also tried to do that on the business side. You know, when a customer has an on-prem situation, they're looking at moving to the cloud, whether lift and shift or modernized, they're looking at costs, they're looking at risk and they're looking at time. So one of the things we look at is how do we mitigate that? How do we mitigate the cost, the risk and the time? Well, this week, I think we announced our new cloud lift program and the cloud lift program is what Oracle will provide to its cloud engineering resources around the world is that we will do, we will take the cost, the risk and the time out of the equation and Oracle will work directly with the customer or the customer's partner of choice, maybe an Accenture or Deloitte, and we will move them, right? You know, at little or no cost, most cases there's no cost whatsoever, right? We mitigate the risk because we're taking the risk on. And we've built a lot of automated tools to make that go very quickly, right? And securely, and then finally, we do it in a very very short amount of time as compared to what you would need to do with, you know 'cause there is no Redshift on-premises. There is no Snowflake on-premises. You have to convert from what you already have to that, right? And, but the company beyond the technological barriers that George talked about were also trying to smooth the operation so that a business itself can make a decision that not only did they not need the technical people to operate it, they won't need an entire consulting contract with millions of dollars in order to actually do the movement to the cloud. >> Well, guys, I really appreciate you coming on the program and again, your candor to speak openly about you know, your approach, the competitors. And so it's great having you, really really thank you for, for your time. >> Appreciate it. >> And thank you for watching everybody. Look, if you guys want to come back, go toe to toe with these guys, say the word you're always welcome to come on The Cube. One thing for sure, Oracle are serious, when it comes to database. Thank you for watching. This is Dave Vellante. We'll see you next time. (bright music)

(lighthearted music) >> Okay. We're here with Keith White, Senior Vice President and General Manager for GreenLake at HPE, and George Hope, who's the Worldwide Head of Partner Sales at Hewlett Packard Enterprise. Welcome gentlemen. Good to see you. >> Awesome to be here. >> Yeah. Thanks so much. >> You're welcome. Keith, last we spoke, we talked about how you guys were enabling high performance computing workloads to get GreenLake right, for enterprise markets. And you got some news today which we're going to get to, but you guys, you put out a pretty bold position with GreenLake, basically staking a claim, if you will. The Edge, Cloud, as a service, all in. How are you thinking about its impacts for your customers so far? >> You know, the impact has been amazing. And, you know, in essence, I think the pandemic has really brought forward this real need to accelerate our customers' digital transformation, their modernization efforts, and, you know, frankly help them solve what was amounting to a bunch of new business problems. And so, you know, this manifests itself in a set of workloads, a set of solutions, and across all industries, across all customer types. And as you mentioned, you know, GreenLake is really bringing that value to them. It brings the Cloud to the customer in their data center, in their Colo or at the Edge. And so frankly, being able to do that with that full Cloud experience all as a pay per use, you know, fully consumption-based scenario, all managed for them, so they get that, as I mentioned, true Cloud experience, it's really sort of landing really well with customers. And we continue to see accelerated growth. We're adding new customers, we're adding new technology and we're adding a whole new set of partner ecosystem folks as well that we'll talk about. >> You know, it's interesting, you mentioned that, just as a quick aside. The definition of cloud is evolving, and it's because customers ... It's the way customers look at it. It's not just vendor marketing. It's what customers want, that experience across Cloud, Edge, you know, multi clouds on prem. So George, what's your take? Anything you'd add to Keith's response? >> I would, you've heard Antonio Neri say it several times and you probably see it again for yourself. The cloud is an experience. It's not a destination and digital transformation is pushing new business models and that demands more flexible IT. The first round of digital transformation focused on a Cloud first strategy, where our customers were looking to get more agility. As Keith mentioned, the next phase of transformation will be characterized by bringing the Cloud speed, the agility to all apps and data, regardless of where they live. According to IDC, by the end of 2021 80% of the businesses will have some mechanism in place to shift the cloud centric, infrastructure and apps, and twice as fast as before the pandemic. So the pandemic has actually accelerated the impact of the digital divide. Specifically in the small and medium companies, which are adapting to technology change even faster and emerging stronger as a result. You know, they, the analyst degree cloud computing and digitalization will be key differentiators for small and medium business in years to come and speed and automation will be pivotal as well. And by 2022, at least 30% of the lagging SMBs will accelerate digitalization. But the focus will be on internal processes and operations the digital leaders, however, will differentiate by delivering their customers dynamic experience. And with our partner ecosystem we're helping our customers embrace our as a service vision and stand out wherever they are on their transformation journey. >> Well thanks for those stats. I always liked the data. I mean, look, if you're not a digital business today I feel like you're out of business and-- I'm sure there's some exceptions but you got to get on the, on the digital bandwagon. I think pre pandemic, a lot of times people really didn't know what it meant. We know now what it means. Okay, Keith. Let's get into the news when we do these things. I love that you guys always have som-- something new to share. What do you have? >> No, you got it. And you know, as we said, you know the world is hybrid and the world is multi-cloud and so customers are expecting these solutions. And so we're continuing to really drive up the innovation and we're adding additional cloud services to GreenLake. We just recently went to a general availability of our ML ops, mach-- machine learning operations and our containers for cloud services along with our virtual desktop which has become very big in a pandemic world where a lot more people are working from home. And then we have shipped our SAP HEC customer edition which allows SAP customers to run on their premise whether it's the data center or the Colo. And then today we're introducing our new bare metal capabilities as well as containers on bare metal as a service, for those folks that are running cloud native applications that don't require any sort of hypervisor. So we're really excited about that. And then second, I'd say similar to that HPC as a service experience, we talked about before where we were bringing HPC down to a broader set of customers. We're expanding the entry point for our private cloud which is virtual machines, containers, storage compute type capabilities in workload optimized systems. So again, this is one of the key benefits that HPE brings is it combines all of the best of our hardware, software, third-party software and our services and financial services into a package. And we've workload optimized this for small, medium, large and extra large. So we have a real sort of broader base for our customers to take advantage of and to really get that cloud experience through HPE GreenLake. And, you know, from a partner standpoint we also want to make sure that we continue to make this super easy. So we're adding self service capabilities or integrating into our distributors through a core set of APIs to to make sure that it plugs in for a very smooth customer experience. And this expands our reach to over a hundred thousand additional value add resellers. And, you know, we saw just fantastic growth in the channel in Q1 over 118% year over year growth for GreenLake cloud services through the channel. And we're continuing to expand our ex-- extend and expand our partner ecosystem with additional key partnerships. Like our Colos, that co-location centers are really key. So Equinix, Cirrus 1 and others that we're working with. And I'll let George talk more about that. >> Yeah. I wonder if you could pick up on that George I mean, look, if I'm a partner and and I mean, I see that I see opportunity here. Maybe, you know, I made a lot of money in the in the old days moving iron, but I got to move. I got to pivot my business. You know, COVID is actually, you know accelerating a lot of those changes, but, but there's a lot of complexity out there and partners can be critical in in helping customers make that journey. What do you see this meaning to partners, Georgia? >> So I completely agree with Keith the-- through and through in with our partners, we we give our customers choice, right? They don't have to worry about security or cost as they would with public cloud or the hyperscalers we're driving special initiatives via Cloud 28, which we run which is the World's largest Cloud aggregator. And also in collaboration with our distributors and their marketplaces. As, as Keith mentioned, in addition customers can leverage our expertise and support of our service provider ecosystem, our SIs, our ISBs to find the right mix of hybrid IT and decide where each application or workload should be hosted. Because customers are now demanding robust ecosystems, cloud adjacency, and efficient, low latency networks and the modern workload demands, secure compliant highly available, and cost optimized environments. And Keith touched on co-location, we're partnering with co-location facilities to provide our customers the ability to expand bandwidth, reduced latency and get access to a robust ecosystem of adjacent providers. We touched on Equinix a bit as one of them but we're partnering with them to enable customers to connect to multiple clouds with private on demand interconnections from hundreds of data center locations around the globe. We continue to invest in the partner and customer experience, you know making ourselves easier to do business with we've now fully integrated partners in GreenLake central. And can provide their customers end to end support in managing the entire hybrid IT estate. And lastly, we're providing partners with dedicated and exclusive enablement opportunities. So customers can rely on both HPE and partner experts and we have a competent team of specialists that can help them transform and differentiate themselves. >> Yeah. So I'm hearing a theme of simplicity. You know, I talked earlier about this being customer driven to me what the customer wants is they want to come in. They want simple, like you mentioned, self-serve. I don't care if it's on prem in the cloud, across clouds at the edge, abstract, all that complexity away from me make it simple to do not only the technology to work you know, you figure out where the workload should run and let the metadata decide. And that's a, that's a bold vision and then make it easy to do business. Let me buy as a service if that's the way I want to consume. And, and partners are all about, you know, making, you know reducing friction and driving that. So anyway guys, final thoughts. Maybe Keith, you can close it out here and maybe George-- >> Yeah. You summed it up really nice. You know, we're excited to continue to provide what we view as the largest and most flexible hybrid cloud for our customers apps, data, workloads, and solutions and really being that leading on-prem solution to meet our customer's needs. At the same time, we're going to continue to innovate. You know, our ears are wide open and we're listening to our customers on what their needs are, what their requirements are. So we're going to expand the use cases, expand the solution sets that we provide in these workload optimized offerings to a very very broad set of customers as they drive forward with that digital transformation and modernization efforts. >> Great. George, any final thoughts? >> Yeah, I would say, you know, with our partners we work as one team and continue to hone our skills in and embrace our confidence. We're looking to help them evolve their businesses and thrive, and we're here to help now more than ever. So, you know, please reach out to our team and our partners so we can show you where we've already been successful together. >> So that's great. We're seeing the expanding GreenLake portfolio partners are key part of it. We're seeing new tools for them and then this ecosystem evolution and build out an expansion. Guys, thanks so much. >> You bet, thank you. >> Thank you. Appreciate it. >> You're welcome.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel AWS and our community partners. Welcome to the cubes Coverage of AWS reinvent 2020. The digital version I'm Lisa Martin and I'm joined by a couple of guests from Unisys. Please welcome unprompted high BP and Cloud CTO on income. Great to have you on the program. Thanks for joining me today. >>Great to be here leader >>and a new pre or a new Ram Raj, VP of Cloud Services. A new welcome. Great to have you on a swell. Great >>to be here in this virtual AWS being that great. >>Thank you. Very socially Distance We're following all the guidelines here. A new Let's start with you. I'd love to get just kind of Ah, you know, a vision of the AWS Unisys partnership. I know you guys are advanced consulting partner MSP. Tell me about that partnership. >>Absolutely. Lisa, we see our clients on a cloud journey which we accelerate with Unisys Cloud Services and AWS partnership is a big piece of that again. Way thorough. We have bean rated in aws MSP partner Come out very, very highly from those msb audited our, uh and we're investing in multiple competencies across the boat as well. So and we work very closely with AWS in terms off innovating in sharing our platform cloud 44 world map In looking at what our customers looking around the corner, what services could be co developed. So we're looking at some potential I o T engagements to jointly with AWS is, well, eso you're always co inventing and it's a great partnership with a W s >>excellent. And you let's stick with you Following on hybrid Cloud Journey you mentioned the Cloud Forte platform. I wanted to understand what that platform is, how your co developing that with AWS and how your customers are benefiting >>absolutely s. Um, every year Unisys does a cloud barometer study across thousands of our clients and and we got some interesting takeaways from that. Essentially two thirds of her clients that have started this cloud journey believe they don't really realize the benefits out of that and up thio 53% off. The the respondents said they needed some help with cloud security. And this is where I believe that Unisys Cloud Services has a strong viewpoint and can find their AWS, um, journey, no matter where, what challenges they're facing, whether it's budgetary challenges on optimizing AWS and whether it's getting I t operations right when you move your applications to AWS. Um, and is it is it getting the that I have seen cops models established? So no matter where clients are in the A journey, we look to accelerate with our set of solutions and services, and we're very proud about the fact that we respond very me to make sure our clients can innovate and achieve the business outcomes that they need. For example, with California Stink City, we were able to work with them on the AWS. John Pretty set up a native other lake and analytics on top of it so we could actually predict and influence graduation rates with students. Our scores are higher than any off are coming because of the outcomes that we deliver for our clients. And it's really about business outcomes and 40 platform, which helps us drive those outcomes. I mean, probably do you want to add on without cloud 40 platform? >>Sure, I know eso, as as I knew was saying cloud for the platform provides AH set off capabilities that allows us to create an offer highly differentiated services with Unisys Pipe and, as was mentioned earlier, our cloud solutions are are able to help customers no matter where they are in their car, in their cloud journeys, whether it's ah Greenfield opportunity, where they where the customers are intending to move to the cloud, or if it's a brownfield opportunity where they already have adopted the cloud and are looking to manage and operate and optimize their deployments. Cloud Forte Platform and our Cloud Solutions are able to provide, uh, customized solution for that customer context to really deliver the solution that addresses some of the pain points that you talked about. The keeping points really relate to security to get secured. It also relates to cost optimization and then optimizing the cloud purse, a cloud deployment hybrid cloud deployment of the key requirement. So our cloud 40 platform health drives the key use cases. The key pain points that our customers are looking for through a combination off accelerators, the number of cloud photo accelerators that enable customers to rapidly prove it provisioned customers and to rapidly migrate to the cloud with God rails so that they're the secure, their compliant. And then we've got the the Cloud Cloud 40 Cloud management platform for ensuring provisioning onda management and operations, along with cost optimization capabilities and the eyelid operations. So it's a comprehensive suite off services and solutions that addresses the key business outcomes. There are customers are are looking for >>outcomes. Focused is absolutely critical, especially these days. I knew I wanted to go back to you for a second. You talked about the Unisys Barometer study, and I like the name of that. When was that done? And I'm just wondering if there are certain things that you saw this year from a customer. Cloud journey. Need perspective because of the pandemic that have really influenced that barometer >>Wait Question. Hey said and development is study. The last version of it was done late last year, and we're still waiting on the ones from this year. So, but we're starting to see some of the trends that were influenced by the pandemic. We saw rush to cloud when the pandemic hit because business adopt to to remote workers to do more digital selling and then seeing our CEO is kind of struggle with optimizing and maximizing the results off their cloud. Spend right, So So that's a unique challenge that that we're seeing based on our tryingto interaction. So the rush to the cloud and the ask for more spend optimization and in terms of spend optimization, that's an interesting facet because, uh, it cuts through my multiple angles. It's it's cuts through having the platforms around, being able to dio right predictions on where you spend is going, and then it also it's across collaborative effort. Finn ops. As we see it, we call it as a synopsis of is that we bring to our clients it's passing with multiple organizations, including finance, to sometimes figure out. Where will this business be? Where should you spend be? What should be the reserved instance buys right. So combining cloud knowledge with financial knowledge and organizational and business knowledge. And that's the service that we bring to our clients with our phenoms services. At least a great question about how how is I kind of making the current business climate affecting our operating models? Um, like we said, there's increased ask for Finn ops is an increase. Ask for security ops because security threats have only amplified. And then the entire cloud ups model. I think hybrid cloud operations its's prompted us to rethink a lot off. How do we do? I t operations and and we're investing a lot in terms of automation and then underpinning that by ai led operation. So, um, you talked about the client management platform making sure we've got the best automation and processes which are repeatable around all the way from just doing provisioning to data operations to optimization. Just making all of that robust and repeatable um, is such a value. Add to clients because then they can see SOS can sleep at night knowing that everything is taken care off and, uh, the CIA, the CEOs can be rest assured that hey, they're not going to get that AWS bill that's going to make them hit the roof. So making sure we've got the right checks and balances and approval flow is all a part of our child management platform. And at that point, I know you really passionate AI and the role that it plays in operations and the entire cloud management platform and cloud for day platform So your thoughts in the poem? >>Yes, sir. No, thank you. But so yeah, yeah, I led operations is really part off the bigger question and the pain point that customers are faced with, which is I've reached the cloud. Now, how do I optimized and get benefits from the cloud on the benefits is around. You know, uh, utility for on demand access to resource is, uh, this cost optimization potential and the security, uh, cloud security potential that, if not managed properly, can really blow up in the face. And unfortunately, you know that in the case on the AI ops led Operation Side, that's again a huge foretell area where Unisys Investor is investing a lot off a lot off i p and creating a lot of differentiation. And the objective there is to ask Customers adopt cloud for day as they adopt Unisys Cloud services. They're able to take advantage off cost optimization capabilities, which essentially looks at historical usage on predicts future usage, based on a number off a I artificial intelligence and machine learning technologies that that is able to give you predictions that otherwise very hard to hard to get and, uh, in the cloud environment because of the sheer velocity volume and variety of the data. Doing that in a manual fashion is very, very hard. So automated machine learning driven approach is very productive is very effective on, you know, some of the outcomes that we've achieved is is just amazing. We've been able to save up to 25% off infrastructure costs through the island operations. About 40% off infrastructure incidents have bean reduced due to root cause analysis. Eso onda up to 35% off meantime, to resolution improvements in time. So huge customer benefits driven by e I led operations. The I am a approaches to following the problem. >>Let me see him If I could stick with you for a second big numbers that you just talked about and we talked a few minutes ago about outcomes. It's all about outcomes right now with this rush to cloud as as a new set. And we talked about this on the Cuba all the time. We've seen that the last eight months there is an acceleration of this digital transformation. I'm just curious una come from your perspective as the VP and CTO cloud how are you? What are some of the things that you advise customers to do if they need to rush to the cloud 21 just, you know, move their business quickly and not have the stay on life support. What are some of the things that you advise them to do when they're in this? Maybe a few months ago, when they were in the beginning of this? >>Yeah, that's that's a very interesting question, and lot off our clients are faced with that question as they either they're already in the cloud or the deciding to migrate to the cloud on the whole journey. Customer journeys for either stepping on the cloud or managing and operating the optimizing the cloud deployments is very key. So if you look at the market research that's out there and what we hear from our customers, the key challenges are really, really around. How do I migrate to the cloud without facing a lot of bottlenecks and challenges, and how do I overcome them? So that's the keeping pain point and again cloud for the advisory services and the cloud services that we offer allows customers to take up uh, toe work with us, and we work with the customer to ensure that they're able to do that on and then rapidly migrating to the cloud, managing and operating their operations. The hybrid cloud operations in optimized fashion is a huge challenge. How do they migrate? How do they migrate with security and compliance not being compromised once they're in the cloud, ensuring cloud security is and compliance is is maintained. Ensuring that the cost structure is is optimized so that they're not being mawr wants to move to the cloud compared to on premises and and then taking advantage of the whole cloud. Deployments to ensure you're looking at data are nothing the data to derive meaningful business outcomes. So if the entire end to end customer journey that needs to be looked at optimized. And that's where Unisys comes in with a cloud for the platform where we work with the customers to enhance the journeys. And in this case I want to mention CSU, which is, uh, the California State University, where the approach Unisys to really work with them to deliver uh, cloud services by enhancing the the objective was to enhance the student learning experience to enable adoption off off the technology by the students but also to achieve better performance, better adoption cost savings on we were able to deliver about 30% better performance help realize about 30 33% savings on 40% plus growth in adoption. On this was for about half a million student bodies. The 50,000 plus faculty staff spread across 23 campuses. So deploying, optimizing on and managing the infrastructure is something that Unisys does. Does that. And this is an example of that. I know you want to add anything to that. >>Absolutely Any Permanente's really well and, >>uh, >>it Z also securing, making sure securities with the >>journey >>it Z O Keefe or hybrid cloud. Um, uh, at least I'm sure you're aware of the Unisys tagline is securing tomorrow. So who better s so we really, really take that really, really seriously in terms of making sure we seek clients cloud journeys, and >>you >>probably heard the statistic from her. About 80% off cloud breaches are due to mis configuration, and this could have bean prevented. And and it doesn't. There's an element of the human angle in there. You believe strongly that can automate using our platform. So we've got 2000 plus security policies, which makes sure which again enables our clients to be compliant as well. So no matter what compliant standards, we've got several off our clients, for example, in the financial sector that are hosted on AWS and that we managed and they have to, especially the US They have to comply with Y de f s, the New York Department of Financial Services and making sure that they compliant with all the standards out there, which is next plus plus in this case. So that's part of what we do and enabling those journeys and then just keeping up with the rate of change like on different was talking about the variety and velocity of the data and and the rate of change of the applications out there, especially as businesses react to the pandemic and have to cope with the changing business paradigms out there. They have to be quick. Um, so we've got a drugmaker, one of the most premium drug makers in the US, who is who is against it on AWS, and, uh, they're racing for the cure and they are always looking at How do they get drugs quicker to the market? And that means accelerating applications. And we know that based on research by the Dora study, that if you adopt develops paradigms, you can accelerate 200 times faster than if you didn't. But then you have to underpin backward security as well. So really helping this adopt deaths are cops in all their deployments to AWS so that they can really race for the cure. That's the kind of business outcomes that we really, uh, are really, really proud to drive for our clients. >>Excellent on a pound. Let's wrap this up with you. We've just got about 30 seconds left sticking on the security front. It's such a huge topic right now. It has been for a long time, but even more so during these unprecedented times when you're talking with customers, what makes Unisys unique from a security perspective? >>So first thing is to understand what it takes to solve the hybrid cloud security problem. Like you said earlier, that's the biggest pain point that we hear from customers from our clients on. It's all over the market research all the breaches that have happened, like the zoom breach that happened that compromised about half a million, you know, user log ins. And then there was also the the Marriott breach, where about half a billion users names and credential for legal legal. So it Zaveri easy for customers, potential customers to become like a headline. And our our job really are the companies to make sure that they're not the next capital one or the next Marriott, uh, showing up in the newspaper. So we kind of look at their customer deployments situation on. We put together a comprehensive into an hybrid cloud solution, hybrid cloud security and compliance solution that includes look, securing their cloud infrastructure, their cloud workloads in terms of applications that they might have secured, and also to look at securing their applications, which may or may not be running on the cloud. So we kind of take a very holistic approach, using our homegrown solutions and partner solutions to create a comprehensive, robust hybrid cloud solution that really fits the customer context and and so we we are essentially a trusted adviser for our for our clients to create the solution, which again, at the cloud 40 ashore, which is a cloud security posture management solution. We have a cloud worker protection solution on then stealth, which is a full stack security solution if combined together with the other cloud Forte platform components on. We wrap this up in a matter of security services offering that allows US customers to have complete peace of mind as we take care off assessment remediation monitoring on, then continues Posture, posture, management. I know. Do you want to add anything to that? >>If I'm think in terms of closing, I think like you covered it well, we've got platform competence and services that run the gamut off the off the life cycle from migrations to two transformations. And one thing that I think in terms of outcomes of these, uh, when the service built around it have really helped us. Dr is, um is kind of responding especially to our public sector clients, very passionate about enabling cloud journeys for our public sector clients. And we'll take the example of Georgia Technology s So this is the G t A. Is the technology agency for all services are 14 of the agencies in Georgia and many of these public sector agencies had to quickly adopt cloud to deal with the report workers. Whether it was v D I whether it was chatbots on cloud, um, it was it was, ah, brand new world out there, the new normal. And it was just using the cloud management platform that anyone was refering to. We were able to kind of take them from taking three months. Plus to be able to provision workloads Thio thio less than 30 minutes to provision workloads. And this is this is across hybrid cloud. So and this is >>a big outcome, especially in this time where things were changing so quickly. Well, I wish we had more time, guys because I could tell you have a lot more that you can share. You're just gonna have to come back. And I like that. The tagline securing tomorrow. Adding on to what Anu Pump said So your customers don't become the next headline. I think they would all appreciate that. Thank you both. So much for joining me on the Cube today and sharing what's the latest with Unisys. We appreciate your time. Thank you. Thank >>you for having us >>aren't my pleasure for my guests. I'm Lisa Martin. And you're watching the Cube? Yeah,

>> Announcer: From around the globe. It's theCube with digital coverage of AWS re:Invent 2020 special coverage sponsored by AWS Worldwide Public Sector. >> Hi, and welcome to theCube Virtual in our coverage of AWS re:Invent. I'm your host Rebecca Knight. Today we are joined by Shawn Snyder. She is the managing director at Deloitte and Cloud Migration market leader. Thanks for coming on the show Shawn. >> Thank you, Rebecca. I'm glad to be here. >> So we're talking today about cloud migration in the public sector in the COVID era, but I want to start by having you introduce yourself to our viewers tell them a little bit about what you do at Deloitte. >> Sure, I'm Shawn Snyder. I'm a managing director based out of Atlanta. I lead our cloud migration offering for our government and public sector clients. So that really means that I serve clients in the government, both public sector local government agencies, as well as federal agencies and helping them move to the cloud, and I'm also responsible for building out our capabilities, our tools, our resources, and people to help clients do that in a very fast and accelerated way. >> So even putting aside the pandemic for a second, shifting to the cloud is such a big and daunting undertaking for so many organizations, including federal agencies. How do you help CIOs and clients think through the processes and what they need to do and how they need to do it? >> Yeah, I mean, it all starts with where are they at on this journey, right? We actually have a show our clients like a typical journey to the cloud and, you know, we have a method and set of tools that we can work with them depending on where they are but if they're just in the initial stages of exploring, moving to cloud, it typically starts with a strategy and really understanding what, you know, how engaged is the mission and the agencies in supporting this. Are they really looking to continue to build their own talent? What is the end state look like? Do they want to build cloud skills and cloud engineering skills within their organization, or are they looking to do more of a managed service model? So a lot of these conversations happen and also around what platforms they want to use and then we typically look at their portfolio of applications. So it could be, you know, they're looking to move out of a data center and go more to a cloud virtual environment. It could be that they're looking to move a couple of mission critical applications that are highly complex with lots of data and sensitive information, so. It really kind of depends on what they're trying to achieve and what is the business result that they're looking to gain. >> And how do you help them think through the business case for this? Because I know that that is definitely an imperative. >> So we take a couple of, I can give you an example. So when we were working with a state in local agency, looking at a big mission critical integrated eligibility system, they wanted to be able to move because they were, the technology was getting a little dated. It was eating inflexible to maintain and when they were looking at the maintenance costs that they were spending on both the infrastructure and the application, it was starting to, you know, take up to 90% of the budget and so the lack of ability to be able to do new capabilities and new innovation when you're talking about especially post COVID, which I know we haven't gotten into, but when they're looking, there's actually more and more products and aid that's being made available. So they need more flexibility, and so what we did was we actually did a bunch of analysis around what does that technology stack look like? What's the cost drivers and then we built out what the future would look like on the, in this particular case was the AWS platform. How could they take advantage of some native services and reduce some of their licensing costs? How could they upgrade through our products? We have a seamless way to upgrade to cloud suitable operating systems. So in this case, they were on an outdated Windows and Linux platforms. We were able to update that to cloud suitable, which allowed them to, you know, save a lot of money in terms of their infrastructure costs to maintain some of that outdated infrastructure and then we get them on end state tools around security monitoring, around infrastructure monitoring and so they can really streamline some of those infrastructure costs as they are spending tremendous amount of money just on the tools when they're managing all of that on-prem, on a complex system. >> So thinking about now we are in this pandemic, which has changed everything about the way we live and the way we work, moving to the cloud was a business goal. Something that a lot of organizations sort of had, in they're two and three year, two and five-year plan. Now it is an absolute mandate. What are you seeing? What are you hearing? What are organizations saying to you now? >> There's just such a, there's such a demand for speed and doing it at scale very fast. So prior to COVID, like you said, it was a multi-year journey. We'll get to it when we can, but there were other priorities that automatic, always got in the way of that and also just the cost justification, right? When you're talking about migration and a lot of times these systems that's portfolio systems are outdated, they're not cloud suitable. So how do you have to refactor them? That can get pretty costly pretty quickly. Now our clients want to move fast and they have a virtual work workforce, they need more scale. They need more storage for some of the data. They need to be able to integrate with other partners, especially in the healthcare space, whether it's at the state and local agency level or in the federal space, that ability to create that ecosystem of being able to transmit and share data in a very secure way at a very large volume is becoming, you know, mission critical with combating COVID with being able to protect our citizens. >> Speed is the name of the game, as you're saying. So what, how is Deloitte investing in automation and what kinds of migration accelerators are you bringing to clients now? >> So a few different things. One, we are partnering with AWS, both on a professional services perspective, as well as with some programs. So we've integrated our methodologies and we've been certified by AWS for our methodology around migration acceleration program. So that's the map because of our qualifications of the amount of migrations we do globally, as well as our methodology and tool set, we're able to offer this joint map program, which allows us to team with AWS. Go on site in quickly use our tools to diagnose what applications are actually at cloud ready to move, how fast can they move? And it gives a lot of information around technical configurations, what servers they reside on, and all of basically the affinities, all of the information you would need to be able to move those applications and if it's not cloud suitable, we can detect if it, how quickly we could get it cloud suitable. What would need to be done is an application code, or is it database, or is it operating system? What are those things that need to get upgraded to move it to the cloud? And is it worth moving to the cloud? So we actually look at the business value that each of these applications are providing and saying, you know, this might be more suited to stay on-prem for now. So we work with them through this map program to really come up with that detailed migration schedule and plan and we then use that information that we collected during that diagnostic phase feeds into our migration tools. So the migration is actually automated with the information that was collected during the diagnostics and the landing zones, and all of the sizing of the infrastructures able to be sized appropriately based on the information that was collected. >> I want to ask you about innovation. In a lot of these Cube Virtual conversations that we're having, we're hearing from a lot of executives that the pandemic has been a forcing mechanism in sort of forcing people to think more resourcefully, more ingenuitively about how they solve these pressing problems. What have you experienced, and have you seen in particular examples of innovation that have been inspiring and exciting for you? >> Yes, absolutely. So I actually work in the federal health space most, and our ability to be able to stand up an application or a service, whether it's a Salesforce service, the AWS platform, but we've been able to stand up contact tracing for local agencies, for state agencies. We've been able to set up cloud native services that allow the data that's getting collected across these different organizations to be able to make meaningful information using machine learning and some of the other native services that are available within cloud and they can be stood up very quickly and very cost-effectively and I think that's the other value that cloud is unlocking for organizations and really now starting to realize that they can move towards innovation and start to spend much more money on innovation than what they were doing previously on spending most of the budget on maintenance. >> When you're talking to clients now about the future, what are they thinking? What's on their minds in this sort of this 12 to 24 month plan? Are they just thinking we just need to get through this next period and cope with this uncertainty? Or are they thinking about the future. >> Moving to cloud isn't just an infrastructure move. I think that's getting your head around what does it mean? What does your workforce have to look like? What does, how do you collaborate with the business? What are the, what is the future innovation use cases? What is going to, how do you actually start to use those use cases to demonstrate early value and start to do things much more in an agile and iterative way instead of, you know, delivering something in a, you know, several months or years. So it, it really is shifting, it's a transformation for how the office of the CIO or how they actually operate. It's creating integrated teams within the CIO organization. We're actually embedding different disciplines like engineering, infrastructure, IT operations, security operations, risk management, financial management, these disciplines as part of these, what we call DevOps DevSecOps type teams, and be able to deliver an end-to-end product on a particular platform in a very agile way. >> In thinking about the future of the workforce and how the pandemic is changing people's careers. I know that you serve as the technology campus champion at Georgia Tech, and you're very active in recruiting bright young business talent. Can you talk to our viewers a little bit about the changes that you foresee in terms of how people plan their careers and their professional development and anything in particular that Deloitte is doing to make sure that the pandemic does not have such a damaging effect, you know, from a lot of statistics that women are dropping out of the workforce in large numbers. >> Yes, so let me unpack your question a couple of ways. So, you know, first of all, you know, I'm really passionate about talent development and recruiting, and I've learned recruiting efforts at the undergrad for many, many years, and I've always been a technologist. So now, like just seeing how technology is embedded in all of the business that we do and it's so mission critical, you now, I'm very focused on making sure there's more women and more minorities going into technology oriented degrees. There's so much you can do with a technology degree and the of career careers that are available, you know, are unlimited. We can't hire enough people that have the right skills. There's just a war on talent for people that have the right security and cybersecurity skills, cloud engineering skills, and just the analytical skills. I mean, this is very complex stuff that you're trying to, you know, build stuff and create stuff that hasn't been created before. So I find it extremely fascinating and I hope that people can see the creative side of things and the scientific it's really bringing it both together and that's what I try to mentor a lot of the recruits on campus. In addition to that, so I think that there's tremendous amount of opportunity for folks going into those types of degrees, as well as for women I, you know, it's been a challenge because people are, you know, some schools aren't closed are not open. If you have a dual working family, it can be a big challenge if you're taking care of children or elderly parents, for example. So at Deloitte, we actually recently implemented a dependent care policy for folks that could take advantage of additional stipend to subsidize, you know, childcare or dependent care. So that's helped a little bit, we're also really focused on diversity inclusion. So, you know, really having candid conversations, individual conversations around what are your boundaries at work right now? Can, do you have to be off right now from, you know, dinner time till bedtime? What does that look like? And we're trying to really help people have the tools and feel comfortable about having those conversations, 'cause it's not just women, it's men, too. I mean, this, these are difficult situations that we're all, you know, co living with our spouses and our significant others and our children, and potentially, you know, extended family members and trying to work in the same environment and is very challenging, and so we're trying to create space for people to be able to have those conversations and make it work for them. >> Don't I know it's Shawn. So just in terms of thinking about the future and what is next for Deloitte, and you've just talked about how you are a technologist at heart, and you see so much excitement about bringing in different disciplines, different functions to solve these urgent and pressing problems. What do you foresee for yourself and for Deloitte over these next couple of years, as we emerge hopefully out of this crisis situation. >> I think Deloitte, you know, one reason I've stayed at Deloitte for so long is that we've always been really focused on how does the technology solve the business problem, the mission problem? And so we have a real opportunity to continue to be able to bring the IT and the technology enablement and make sure it aligns to the business strategy and so the business use cases, you know, we've invested a lot in our labs Capabilities where we're able to bring different disciplines, whether it's, you know, HR and talent thinking about workforce of the future, you know, that technology stack and the architects together, as well as the thinking about across the ecosystem, what are some of the future use cases that you're not even thinking about? So we're able to bring a lot of these different disciplines or subject matter experts together. Now I'll be in a very virtual way, but we've been able to take these lab concepts and it really helps kind of get that out of the possible defined and really strong alignment across these different constituents across the enterprise. So that is really exciting to me. I also think the investment that we're making in our cloud engineering practice, in our alliances with companies like AWS, it really gives us insight into where the technology is going and making sure our staff and our tools and our resources available to us are aligned to that more than investments are being made in the technology. >> So well Shawn thank you so much for coming on theCube Virtual. It's a pleasure having you on the show. >> Thank you very much Rebecca. >> I'm Rebecca Knight stay tuned for more of theCube Virtual's coverage of AWS re:Invent 2020.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent Executive Summit 2020 sponsored by Accenture and AWS. What? Welcome, everyone to the Cube Virtual and our coverage of the Accenture Executive Summit, part of AWS reinvent 2020. I'm your host, Rebecca Knight. Today we're talking about the power of three. And what happens when you bring together the scientific know how of a global bias Bio pharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS and Accenture's ability to innovate, execute and deliver innovation, Joining me to talk about these things we have Aaron. Sorry. Arjun, baby. He is the senior managing director and chairman of Accenture's Diamond Leadership Council. Welcome margin, you Carl Hick. He is the chief digital and information officer at Takeda. >>Pleasure to be here. Thank you. Rebecca >>and Brian Bowen, global director and head of the Accenture AWS Business Group at Amazon Web services. Thanks so much for coming. Thank you. So, as I said, we're talking today about this relationship between your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason Why? Why I moved to the cloud and why now? >>Yeah. No, thank you for the question. So you know as ah, bio pharmaceutical leader were committed toe bringing better health and a brighter future to our patients. We're doing that by translating science and toe some really innovative and life transporting therapies. But throughout, you know, we believe that there's, ah responsible use of technology of data and of innovation. And those three ingredients air really key to helping us deliver on that promise. And so, you know, while I think I'll call it this Cloud Journeys already has always been a part of our strategy. Andi have made some pretty steady progress over the last years with a number of local it diverse approaches to the digital in AI. We just weren't seeing the impact at scale that we wanted to see. Andi, I think that you know, there's a there's a need ultimately to accelerate and broaden that shift. And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire being the most pressing example, but also the global pandemic. Both of those highlight the need for us to move faster at the speed of cloud ultimately on. So we started thinking outside of the box because it was taking us too long and we decided to leverage the strategic partner model on. It's giving us a chance to think about our challenges very differently. We call this the power of three on. Ultimately, our focus is singularly on our patients. I mean, they're waiting for us. We need Thio. Get there faster. It can take years. And so I think that there is a focus on innovation at a rapid speed so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about? About what you're seeing so far? >>Yeah. No, it's a great question. So I mean, look, maybe right before I highlight some of the key insights, I would say that, you know, with Cloud now as the as a launchpad for innovation, you know, our vision all along has been that in less than 10 years we want every single to Kito associate. We're employees to be empowered by an AI assistant. And I think that, you know that's gonna help us make faster, better decisions that will help us. Uh, fundamentally, you know, deliver transformative therapies and better experiences to to that ecosystem, to our patients, to positions to payers, etcetera much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful or call it data fabric is gonna help us to create this this really time. I'll call it the digital ecosystem. The data has to flow ultimately seamlessly between our patients and providers or partners or researchers. Etcetera. Uh, and so we've been thinking about this, Uh, call it. We call it sort of this pyramid. Um, that helps us describe our vision on a lot of it has to do with ultimately modernizing the foundation, modernizing and re architect ing the platforms that drive the company, heightening our focus on data, which means that there's an accelerated shift towards enterprise data platforms and digital products. And then, ultimately, a, you know, really an engine for innovation. Sitting at the very top, um, and So I think with that, you know, there's a few different I'll call it insights that you know are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately and build a connected digital ecosystem with the right partners and technologies? Externally, I think the second component that maybe people don't think as much about but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture, certainly as a large biopharmaceutical, very differently. And then, lastly, you've touched on it already. Which is, you know, innovation at the speed of cloud. How do we re imagine that you know how Doe ideas go from getting tested in months? That kind of getting tested in days, you know, how do we collaborate very differently on So I think those air three, perhaps of the larger chocolate insights that you know the three of us are spending a lot of time thinking about right now. >>So, Arjun, I want to bring you into this conversation a little bit. Let's let's delve into those a bit. Talk first about the collaboration that Carl was referencing there. How how have you seen that it is enabling colleagues and teams to communicate differently, interact in new and different ways, both internally and externally. As Carl said, >>No, thank you for that. And I've got to give called a lot of credit because as we started to think about this journey, it was clear was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the concept of the power of three that Karl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward? And to me, the unique ways of collaboration means three things. The first one is that what is expected is that the three parties they're going to come together, and it's more than just the sum of our resource is, and by that I mean that we have to bring all of ourselves all of our collective capabilities as an example. Amazon has amazing supply chain capabilities there. One of the best at supply chain. So in addition to Resource is when we have supply chain innovations, that's something that they're bringing in addition to just talent and assets. Similarly, for Accenture, right, we do a lot in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So as we think about this, so that's that's the first one. The second one is about shared success. Very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at it as the basis for this success shared success model. And we continue to hold that sort of in the forefront as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEO's that get together every couple of months to think about this partnership or it is the governance model that Karl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group so that we can keep that front and center. And what this, I think, ultimately has enabled us to do Is it allowed us to move its speed, be more flexible and ultimately all be looking at the target the same way the North south? The same way. >>Brian. What? What about you? What have you observed? What are you thinking about? In terms of how this is helping teams collaborate differently? >>Yeah, absolutely. And Georgia made some great points there. And I think if you really think about what he's talking about, it's that diversity of talent, diversity of skill and viewpoint and even culture. Right? And so we see that in the power of three. And I think if we drilled down into what we see at Takeda and frankly, Takeda was really, I think, pretty visionary and on their way here, right, and taking this kind of cross functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about, we're gonna be organized around a product or service or capability that we're gonna provide to our customers are patients or donors. In this case, it implies a different structure, although altogether in a different way of thinking. Right, because now you've got technical people in business experts and marketing experts all working together in This is sort of a cross collaboration, and what's great about that is it's really the only way to succeed with Cloud, right, because the old ways of thinking where you've got application people in infrastructure, people and business people is sub optimal, right, because we can all access this tools and capabilities. And the best way to do that isn't across kind of a cross collaborative way. And so this is product oriented mindset of Takeda was already on, I think is allowed us to move faster in those areas. >>Carl, I wanna go back to this idea of unlocking talent and culture, and this is something that both Brian and origin have talked about. Two people are are an essential part of their at the heart of your organization. How will their experience of work change and how are you helping reimagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah, that's a great question. And it's something that, you know, I think we all have to think a lot about. I mean, I think, you know, driving this this call this this digital and data kind of capability building takes a lot of a lot of thinking. So I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing. And it's not just for the technology organization or for those actors that that we're innovating with. But it's really across, you know, all of Takeda. We're working through ways of raising what I'll call the overall digital leaders literacy of the organization. You know, what are the, You know, what are the skills that are needed almost at a baseline level, even for, ah, global biopharmaceutical company? And how do we deploy? I'll call it Those learning resource is very broadly, and then secondly, I think that, you know, we're very clear that there's a number of areas where they're very specialized skills that are needed. Uh, my organization is one of those, and so, you know, we're fostering ways in which you know, were very kind of quickly kind of creating avenues, excitement for for associates in that space. So one example specifically is we use, you know, during these very much sort of remote sort of days, we use what we call global it me days, and we set a day aside every single month and this last Friday. Um, you know, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, Data Analytics Cloud. Uh, in this last month, we've been doing this for months and months now, but in his last month, more than 50% of my organization participated. And there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them on. So I think that that's, you know, 11 element that can be considered. And then thirdly, of course, every organization has to work on. How do you prioritize talent, acquisition and management and competencies that you can't re skill? I mean, there's just some new capabilities that we don't have, And so there's a large focus that I have with our executive team in our CEO and thinking through those critical roles that we need to activate in order kind of thio build on this, uh, this business led cloud transformation and lastly, probably the hardest one. But the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Andi, I think there, you know, this is where the power of three is really kind of coming together nicely. E mean, we're working on things like, you know, how do we create this patient obsessed curiosity? Um, and really kind of unlock innovation with a really kind of a growth mindset, Uh, and the level of curiosity that's needed not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus. We're having the agility toe act just faster. I mean, toe worry less. I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that ah, partner like AWS works? Or how do we collaborate across the number of boundaries, you know, and I think origin spoke eloquently to a number of partnerships that we can build so we can break down some of these barriers and use these networks. Um, whether it's within our own internal ecosystem or externally, to help to create value faster. So a lot of energy around ways of working we'll have to check back in. But, I mean, we're early in on this mindset and behavioral shift, but a lot of good early momentum. >>Carl, you've given me a good segue to talk to Brian about innovation because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously. Now the world has its eyes on drug development, and we've all learned a lot about it in the past few months. And accelerating drug development is all of is of great interest to all of us. Brian How does a transformation like this help a company's ability to become more agile and more innovative? Add quicker speed to >>Yeah, No, absolutely. And I think some of the things that Karl talked about just now are critical to that. Right? I think, where sometimes you know, folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the Silver Bullet, where, in fact it is. The culture it is is the talent, and it's the focus on that. That's going to be, you know, the determinant of success. And I will say, You know, in this power of three arrangement, Karl talked a lot about the pyramid, um, talent and culture and that change. And that kind of thinking about that has been a first class citizen since the very beginning. Right? That absolutely is critical for being there. Um and so that's been that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? So we're kind of obsessive about builders, Onda. We mean what we mean by that is way at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset. Right? When you're a builder, you have that curiosity. You have that ownership. You have that steak and whatever I am creating. I'm going to be a co owner of this product or the service right getting back to that kind of product oriented mindset. And it's not just the technical people or the I t. People who are builders. It is also the business people, as Karl talked about right. So when we start thinking about innovation again, where we see folks kind of get into a little bit of innovation, pilot paralysis is that you can focus on the technology. But if you're not focusing on the talent and the culture and the processes and the mechanisms, you're gonna be putting out technology. But you're not gonna have an organization that's ready to take it and scale and accelerated right, and so that's that's been absolutely critical. So just a couple of things we've been doing with with Takeda indicate, has really been leading the way is think about a mechanism and a process, and it's really been working backwards from the customer, right? In this case again, the patient and the donor. And that was an easy one because a key value of decadas is to be a patient focused biopharmaceutical, right? So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well in eccentrics. And so we're able to bring that together. The other one is, is getting used to experimenting and even perhaps failing right and being able to reiterate and fail fast and experiment and understanding that you know some decisions, what we call it at Amazon or to a doors meaning you could go through that door not like what you see and turn around and go back. And cloud really helps there. Because the cost of experimenting and the cost of failure is so much lower than it's ever been. You could do it much faster, and the implications there so much less so just a couple of things that we've been really driving with a kid around innovation that's been really critical. >>Carl, where are you already seeing signs of success? >>Yeah, No, it's a great question. And so we chose, you know, with our focus on innovation to try to unleash maybe the power of data digital in uh, focusing on what I call sort of a maid. And so we chose our plasma derived therapy business. Um and you know, the plasma drive therapy business unit? It develops critical lifesaving therapies for patients with a rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating called State of the art digitally connected donation centers. And we're really modernizing. You know, the donor experience right now we're trying Thio improve. Also, I'll call it the overall Plasma Collection process. And so we've selected a number of uncle at very high speed pilots that were working through right now specifically in this in this area, and we're seeing really great results already on DSO. That's that's one specific area of focus. >>Arjun, I want you to close this out here. Any ideas? Any best practices advice you would have for other pharmaceutical companies that are that are at the early stage of their cloud journey. >>Sorry. Was that for me? >>Yes. Sorry. Urgent? >>Yeah. No, I was breaking up a bit. No, I think the key is what sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation at innovating at scale. And if you think about that, right and all the components that you need, ultimately, that's where the value is for the company, right? Because, yes, you're gonna get some cost synergies, and that's great. But the true value is And how do we transform the organization? The case of Takeda and a life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation, opportunity. You think about the commercial aspect, lots of innovation can come that the plasma derived therapy is a great example of how we're gonna really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula the cocktail that Takeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Thank you. It's been a lot of >>fun. Thank you. >>Uh, been fun. Thanks, Rebecca. >>And thank you for tuning into the Cube. Virtual is coverage of the Accenture Executive Summit.

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to you by Dell Technologies. Hey, welcome back. You're ready. Jeffrey here with the Cube. Welcome back to our ongoing coverage of Dell Technology World 2020. The Digital Experience. I'm coming to you from Palo Alto. It's a digital event, just like everything else in 2020. But we're excited to have our next guest. I think he's coming in all the way from Atlanta, Georgia. He's Jim Shook, the director of cyber security and compliance practice at Del Technology. Jim, Great to see you. >>Thanks, Jeff. It's quite the title there. Thanks for getting all that out. >>I have a big posted notes so that, uh, that's very helpful. But, you know, it's it's actually kind of an interesting thing because you have compliance and cybersecurity and your title, and it's it's It's interesting relationship between compliance as a motivator of behavior versus you know, you need to go a lot further than just what the compliance says. So I'm curious if you can talk about that relationship between yeah, we need to be compliant, and we need to follow the rules. But you need to think a lot bigger than that. >>Yeah, definitely. I mean, there's so many different standards out there and requirements. So typically, what we'll see on the regulatory side is very much a minimum baseline, and leading the way, as usual in the cybersecurity space, will be financial and health care organizations. That's particularly true in the US, but pretty much globally, at least on the financial side. So they'll set some baselines. A lot of industries don't really have many. And so what we look at many times is just general risk to the business. And, of course, if you're a publicly traded company, that might trigger some SEC requirements or other things like that. But again, we really look at those requirements as minimum baselines, and you have to work up from there based on the organization's risk profile. >>Yeah, yeah, and we see that we see that, too, with privacy and a whole a whole bunch of stuff where traditionally the regs and the compliance kind of lag, you know where the technologies and where the markets moving. So let's before we get too deep into it. Let's let's talk about the cove it impact because obviously a huge thing. Insecurity, Uh, you know, a light switch moment in mid March when everybody had to work from home. So suddenly your tax surfaces increase exponentially. People are working out of home environments that you don't necessarily know what's going on there. Who's going on there, The shared networks with the spouse and the kids and and everybody else. And but now we're, you know, 678 months into this. This is something that's going to be going on for a while, and even the new normal will have some type of a hybrid relationship with with, you know, an increased level of remote remote work once they work from home. But it's really work from anywhere. So I wonder if you could share your thoughts about how things have transitioned from you know, what happened in mid March, taking care of your own business and your own people to, you know, then taking care of your customers and the emergencies that they had. But now really thinking in terms of more of kind of a long term, fundamental shift in the security profile that people have with all their data and information >>Yeah. Gosh, it's been really interesting. I think organizations have done an amazing job when you think about the things that they've had to get done just really overnight. So a lot has been written about the pandemic, and you mentioned Jeff to really that expanded threats surface. All of a sudden, you've got people working from home. There wasn't enough VPN capacity. A lot of places. I talked to some organizations. Employees just took their desktop off of their desk and brought it home so it wasn't really ready toe work at a remote location. But organizations really adapted well to it. Meanwhile, that was opportunity for the criminals, and they've taken it. But Jeff, one of the things that I think about two is to an extent, this is the new normal, not necessarily the work from home, but the shift that's going to consistently happen in cybersecurity. Things change. The criminals air really smart, they adapt. So that was work from home. What's the next thing going to be? There's I O T. There's remote devices. There will be some vulnerabilities. We just have to get used to this pace and continue it. Unfortunately, >>right, right, right Yeah, it's always it's always a little bit of, Ah, a cat and mouse game, Right? But what? And then one of the other trends that we're seeing, I don't know, maybe more visibility or maybe higher profile is is the ransomware attacks, right? So we've seen, you know, kind of this thing really interesting continuation of different types of security threats between just the the local kid who's just trying to do it because it's fun versus, you know, competitive stuff where people are trying to take out their competitors versus nation states and nation states being, um, you know, kind of driving these attacks. But the ransom, the ransom where we've seen before, but it seems to be increasing in frequency. Maybe we're just hearing about it. What's special about ransom, where as a specific type of security threat. >>So I started this practice about five years ago, and at that point, ransom or was just barely a blip, it was really about destruction and the way that we talk about it in the cybersecurity spaces. There's this triad, these three components of our data that we're trying to protect. So one of those is confidentiality, and that traces back to the attacks you're talking about. That's when somebody steals your data. You don't want them to do that. That breaks the confidentiality of the data. And that's really where the cybersecurity controls kind of grew up around, that you didn't want credit cards, intellectual property, healthcare information. And that's still a problem with ransom, where they're affecting the availability of the data or the integrity of the data. And those were the other two prongs that go with confidentiality. And so these attacks. That's why they feel different. Their impact in your ability to access the data, which in many cases can shut a business down. There have been headlines over the last couple of months. Some businesses that really were closed off for components of their business that were shut down, and it's because they didn't have their data or their systems, and then eventually they either found a way to recover them. Or perhaps in many cases, the speculation is they paid the ransom to get the data back, >>right. And of course, the problem with ever paying a ransom, um, is that you don't necessarily know you're going to get the data back. That you may just be encouraging them to hit you again. Eso paying the ransom is is not necessarily the best solution. And then then, in talking about this thing, turns out that in fact, not only may it not be the right solution, you may be breaking the law. This is a pretty interesting thing. I had no idea that there's really laws dictating, you know, I guess responding to a criminal threat. What? Where does that go? What's that from? >>Yeah, that's we've talked about this for a while. But it wasn't until about two weeks ago that some information was released from the Department of Treasury. So the idea here is that every not every country, many countries, the US among them have lists of countries and organizations that you can't do business with. So essentially a prohibited or sanctions list. And, as it turns out, many of the ransomware bad actors and Jeff is actually real name of one of them evil court. It sounds like a movie or a book, but that's one of the ransomware bad actors there on those lists. So if you get attacked by an organization that's on the list and you pay them. You have now completed a transaction with a prohibited entity and you're subject to potential sanctions. There was a lot written about this being a new law, or the US came up with this law, and that's not the case. The laws have been on the books for a while. It was the Department of Treasury, kind of issuing some guidance, just nudging people. Hey, by the way, you shouldn't be doing this and some of the research I've done a lot of countries have these laws. So while it's just the US that came out with this advisory, which was very public and certainly a big wake up call, these laws exist in a lot of other countries. So organizations really need to be prepared for what they're going to do if they get hit with the Ransomware attack. Not really counting on paying the ransom for the reasons that you said, Plus, it may be against the law. >>And just to make sure I understand you, it's against the law because you're effectively doing business by having a financial transaction with one of these, prohibited either organizations or they're in a prohibited country complete. >>That's correct Yeah, mostly about the organization, um, and then an interesting component of this and we won't get into too much of the weeds on the legal side. But the law is actually a strict liability. So that means it doesn't matter whether you knew or should have known that the entity was on a prohibited list. The mere fact of having that transaction makes you liable. And then the way that the the regulations are written, you can't get someone else to do your dirty work for you. So if you are facilitating that transaction anyway, you may be running afoul of those laws. >>Jesus. One more thing to worry about where you're trying to get business. You're trying to get your business back up and running, but specifically with with with ransomware and why it's different. I mean, there's been business continuity, planning forever. You know, you guys have backup and recovery solutions. Uh, you know, there's so much effort around that What's different here? Is it just because of the time in which you have to respond the availability of those backups toe to come back and get in production? What makes Ransomware so special from a business continuity perspective besides the fact that you're not allowed to pay him because it might be breaking the law. >>Ah, lot, You hit on a couple things there. So we've known forever that with D R. Disaster recovery One of the major things you're doing there is your replicating data quickly so that if you lose sight A you can pop up its site B With ransomware, you're replicating the corrupted data, so you lose that with backups. The bad guys know, just like you mentioned that if you have a backup, you could use that to recover. So they are more frequently now gathering their credentials and attacking the backup. So many cases we see the backups being deleted or otherwise destroyed. And that's really where we have focused with our power. Protect cyber recovery solution is creating a new, extra offline air gapped copy of the most critical applications. That's not going to be susceptible to the attack or the follow up attack that deletes the data. >>So let's jump into that a little bit, um, in a little bit more detailed. So this is a special solution, really targeted, um, as a defense against Ransomware because of the special attributes that ransom where, uh, e guess threatens threatens or the fact that they they also go after your backup in recovery at the same time, knowing you're gonna use that to basically lower the value of their ransom attack. That's crazy. >>Yeah, they're smart. You know, these these Attackers air smart. There's billions of dollars at stake. E think organizations like Evil Corp estimates are they could be making hundreds of millions of dollars. So they're they're not even small businesses. They're almost industries unto themselves. They have advanced tactics, They're leveraging capabilities, and they have. They have products, essentially. So when you think about your production data, your backups, your disaster recovery, those air, all in environments, that they're not accessible on the Internet. But that's where you're doing business. So there is access there. There's employees that have access, and the bad guys find ways to get in through spear phishing attacks, where they're sending emails that look like they're from somebody else and they get a foothold. Once they have that foothold, they can leverage that access to get throughout that production environment. They have access to that data, and they deleted with cyber recovery. What we're doing is we're creating a vaulted environment that's offline. They can't get there from from where they are, so they can't get access to that data. We lock it down, we analyze it, we make sure that it's good and then this happens automatically and day over day. So you've always got that copy of data. If your worst case scenario develops and you lose your production environment, that happens. You've got this copy of data for your most critical applications. You don't want to copy everything in there, but you can use to actually recover and that recover capability. Jeff is one of the pillars of a cyber security structure, so we focus a lot, kind of like you said before. What's different about these attacks? We focus a lot on protecting data and detecting bad guys. This is the recover capability that is part of all these frameworks, >>right? So there's a lot to unpack there before we get into the recovery. And kinda actually, why don't we just start there and then I want to get into the air gap because that's a great That's a great thing to dig in on the recovery what's kind of your targeted s l A Is it based on the size of the application? Um, is it based on on, you know, a different level of service. I mean, what is what is the hope? If I buy into this this solution that I can get my recovery and get back into business if I choose, not toe to pay these guys? What? What does it? What does that kind of look like? >>Most of the time, we're providing a product that our customers are deploying, and then we have some partners that will deployed as a service to, so the SLS may vary, but what we're targeting is a very secure environment, and you can look at how it's architected and think about the technologies. If it's properly operated, you can't get there. You can't get to the data. So the points that we're really looking at is how frequently do we want to update that data? So in other words, how much data can you afford to lose? And then how long will it take you to recover? And both of those? You can leverage the technologies to shorten those up to kind of your requirements. So loosely speaking, the in the shorter you make the time may cost you a little bit more money, a little bit more effort. But you can tighten those up pretty much what your requirements are going to be, >>right? Right? And then let's talk about air gaps because air gaps. That means something very, very specific. It literally means classically right, an air gap. There is a space in between these systems until electrons learn how to jump. Um, they're they're they're physically separated. Um, but that's harder and harder to do, right, because everything is now a P I based, and everything is an app that's based on a bunch of other APS, and there's calls and there's, you know, everything is so interconnected now. But you talked about something specifically said, an automated air gap. And you also said that you know, we're putting this data where it is not connected for some period of time. So I wonder if you could explain a little bit more detail how that works, how it's usually configured, um t to reintroduce an air gap into this crazy connected world. >>Yeah, it's kind of going backward to go forward in a lot of ways. When we're careful about the term, we'll use the term logical air gap because you're right, Jeff on Air Gap is there's a gap, and what we're doing is we're manipulating that air gap in a way that most of the time that data are are safe. Data are vaulted, data is on the other side of the air gap, so you can't get there. But we'll bring it up in air. Gap will logically enable that air gap so that there is a connection which enables us to update the data that's in the vault, and then we'll bring that connection back down. And the way that we've architected the solution is that even when it's enabled like that, we've minimized the capability to get into the vault. So, really, if you're a bad actor, if you know everything that's going on, you might be able to prevent the update. But you can't get into the vault unless you're physically there. And, of course, we put some controls on that so that even insiders are very limited what they can do if they get inside the vault and the A. P. T s, the advanced persistent threats. People who are coming from other countries. Since they're not physically there, they can't access that data. >>That's good. So it's on its off, but it's usually off most of the time, so the bad guys can't get across there. >>Yeah, and again it's It's important that even when it's on it za minimal exposure there. So you think about our triad, the confidentiality, integrity, availability. You know, we're blocking them from getting in so they can maybe do a denial of service type of attack. But that's it. They can't get into break into the vault and break things and destroy the data like they would in production. >>I want to shift gears a little bit gym, and I've I've gone to our essay, I think, for the last three or four years of fact, I think it was the last big live event we did in 2020 before everything came to a screeching halt. And, you know, one of the things I find interesting about the security industry is this one of these opportunities for cooperative Shin um within the security industry that even though you might work for a company that competes with another company. You know there's opportunities to work with your peers at other companies. So you have more of a unified front against the bad guys as well as learn from what's going on. Uh, with some of the other you know, people. So you can learn from the from the attacks that they're surfacing. There's interesting, uh, organization called Sheltered Harbor that it came across and doing research for this. You guys have joined it. It was basically it looks like it was built around 100 30. This this article is from earlier in the years. Probably groaning is from February 130 participating financial institutions, which collectively hold 72% of all deposit accounts and 71% of all U. S retail brokerage assets. It's a big organization focused on security, Del joined not as a financial institution but as a vendor. I wonder if you can share what this organizations all about. Why did you guys join and what? Where you see some of the benefits both for you as well as your customers? >>Yeah, there's a lot there, Jeff. I've been part of that process for a little bit over two years and kicked it off after we identified. Sheltered Harbor is an organization that we wanted to work with. So, as you said, founded by some of the banks and credit unions and other financial institutions in the US, and what's unique about it is it's designed to protect the U. S. Financial system and consumer confidence. It's not actually designed to protect the bank. So of course, that's an outcome there if you're protecting consumer confidence than it's better for the banks. But that's really the goal. And so it's a standards based organization that looked at the problem of what happens if a bank it's attacked, what happens to the customers. So they actually came up with the specifications, which follows so closely to what we do with cyber recovery. They identified important data. They built requirements, not technologies, but capabilities that a vault would need to have to protect that data. And then the process is to recover that data if an event occurred. So we talked to the team for a while. We're very proud of what we've been able to accomplish with them is the only solution provider in their advisory program, and the work that we've done with the power protect cyber recovery solution. We have some more news coming out. I'm not permitted toe announce it yet. It's pretty soon, so stay tuned, and it's just been a really great initiative for us to work with, and the team over there is fantastic. >>So I just one or two. If you can share your thoughts as as the role of security has changed over the last several years from, you know, kind of a perimeter based point of view and you know, protection and walls and, uh, firewalls and and and all these things which is completely broken down now to more of a integrated security approach and baking security into your data to your encryption to your applications, your access devices, etcetera and really integrating security more into the broader flow of product development and and delivery and and how that's impacted the security of the of the customers and impacted professionals like you that are trying to look down the road and get ahead of the next. You know, kind of two or three bad things that are coming. How is that security posture really benefited everybody out there? >>It gets a really difficult problem that we just keep working at it again. We don't have a goal, because if we're targeting here, the threat actors is a bad actors. They're gonna be here. I was reading an article today about how they're already the bad actors already employing machine learning to improve what they're doing and how they target their phishing attacks and things like that. So thinking about things like security by design is great. We have millions billions of devices, and if we start from the ground up that those devices have security built in, it makes the rest of the job a lot easier. But that whole integration process is really important to I mentioned before the recovery capability and protect and detect Well, if you look at the nice cybersecurity framework has five pillars that have capabilities within each one, and we need to keep focusing on our capabilities in those space, we can't do one and not the other. So we do multi factor authentication. But we need to look at encryption for our devices. We need to build from the ground up. We need to have those recover capabilities. It's just kind of a never ending process. But I feel like one of the most important things that we've done over the last year, partly driven by the changes that we've had, is that we're finally recognizing that cyber security is a business issue. It's not a nightie issue. So if your digital and your assets are digital, how can you confine this to a nightie group? It's It's the business. It's risk. Let's understand what risk is acceptable cover the risk that isn't and treated like a business process that it ISS. >>That's great, because because I always often wonder, you know, if you think of it as an insurance problem, you know, then you're gonna be in trouble because you can't You can't just lock everything down, right? You gotta you gotta do business. And you always think of the, you know, ships or safest, uh, at harbor. But that's not what ships are built for, right? You can't just lock everything down, but if you take it more of a business approach, so you're you're measuring investments and risk and putting dollar amounts on it. Then you can start to figure out how much should I invest in security because you can't spend ah, 100% of your revenue on security. What is the happy medium? How do you decide and how do you apply that investment where, you know, it's kind of a portfolio strategy problem >>it is. And and that's one of the areas that again my five years in the building, the practice we've seen organizations start to move to. So you want to protect your most important assets the best. And then there are things that you still want to protect, but you can't afford the time, the budget, the operational expense of protecting everything. So let's understand what really drives this business if I'm a law firm might be my billion and document management systems and health care. It's a electronic medical record and manufacturing the manufacturing systems. So let's protect the most important things the best and then kind of moved down from there. We have to understand what those systems are before we can actually protect them. And that's where the business really needs to work more closely. And they are with the I T teams with cyber security teams, >>right, and like, I like a lot of big problems, right? You gotta break it down. You gotta You gotta prioritize. You gotta, you know, start just knocking off what's important and not so overwhelmed by, you know, trying to protect everything to the same degree. This is not practical, and it's not not a good investment. >>That's exactly the case. And there's the ongoing discussions about shortage of people in the cybersecurity space, which there are. But there are things that we can do that to really maximize what those people do, get them to focus on the higher level capabilities and let the tools do some of the things that the tools air good at. >>Right. So, you know, you triggered one last point and we'll wrap on this, but I'll give you the last word. Aziz, you look forward. Two things like automation and two things like artificial intelligence and machine learning that you can apply to make those professionals more effective on automate some stuff. Um, how do you see that evolving? And does that give you big smiles or frowns as you think about your use of AI in a nml versus the bad guys, they have some of the same tools as well. >>They dio and look, we have to use those to keep up. I'll give you example with with power, protect cyber recovery. We already use AI and ML to analyze the data that's in our vault. So how do you know that the data is good? We're not gonna have somebody in the vault looking through the files by leveraging those capabilities. We could give a verdict on that data. And so you know that it's good. I think we we have to continue to be careful that we understand what the tools are. We deploy them in the right way. You can't deploy tool just to deploy honor because it's hot or because it's interesting that goes back to understanding the systems that we need to protect the risks that we can accept or perhaps cover with insurance and the risks that gosh, we really can't accept. We need to make sure that the business continues to operate here, so I think it's great. Um, the communities have really come together. There's more information sharing than ever has gone on. And that's really one of our big weapons against the bad actors. >>All right, Well, Jim, thank you so much for sharing your insight. I think your job security is locked in for the foreseeable future. We didn't even get into five G and I o t and ever increasing attack, surface and sophistication of the bad guys. So thank you for doing what you do and helping keep us safe. Keep your data safe and keeping our companies running. >>Thank you for the opportunity. >>Alright, He's Jim. Mom. Jeff. Thanks for watching the cubes. Continuous coverage of Dell Technology World 2020. The Digital Experience. Thanks for watching. We'll see you next time.