>>Hey everyone. Lisa Martin here with John farrier. Welcome to the women in tech global event, featuring international women's day. John, this is an exciting day, March 8th, 2022. How did this all get started? >>Well, we started it out when we realized there was more stories to be told with virtual, with COVID. The virtualization of virtual events allowed us to do more stories. So we've been on this new format where we're creating seasons and episodic events, meaning you can still do an event and do 30 interviews like we're doing here for international women's day from around the world. We could have done a hundred there's enough stories out there. There's thousands of stories out there that need to be told, need to be scaled. And so we're just scratching the surface. So we are just starting to do is celebrate international women's day with as many videos we could do in a week, which is 30 and be part of widths and Stanford here in California, as part of their events with Stanford. And we're going to continue with international women's day. >>It's the big celebration, it's the big day, but then when it's over, we're going to continue with more episodes. So this is technically, I guess, season one episode, one of the international women's community site portal is going to be open and open to everyone. Who's going to be a community vibe and, uh, we'll get sponsors, but overall it's about bringing people together, creating tribes, letting people form their own communities and hopefully, uh, making the world a better place and supporting the mission, which is a great mission. Diversity inclusion and equity is a big mission. Uh, it's good for everyone. Everyone wins. >>Everyone does win. What are some of the interesting conversations that you've had with our international women's day guests that really were poignant to you? >>Well, the, one of the things was interesting by region. They had different kind of, um, feelings. The Asia Pacific was heavily skewed on a lot of international diversity around culture. Latin America was just all cloud computing. For instance, I felt that to be very technical, uh, more than agents in the interviews. Um, um, more diversity I study in Asia Pacific and Amy. It was really interesting because you have a lot going on there right now in Europe. So, um, and I'll see from a technical standpoint, data sovereignty and sustainability are two big themes. So from a tech trend standpoint, it was really amazing leaders. We interviewed, um, from technical, uh, folks to analysts, to senior executives in the C-suite. So it really good mix of people in the program. Uh, for today, >>We also had a young girl that I had the chance to speak with her and her father. And it was such a lovely conversation cause it reminded me of my dad's relationship with me. But she was told in high school age, no, you can't do physics. No, you can't do computer science. So the parents pulled her out of school. And so the, and she's brand new in her career path. And it was so nice to hear, to see that, that family, the role models within the family saying she wants to do physics and computer science. Let's find a place for her to be able to do that and have her start being able to, to build her own personal board of directors. At the age of like 22, 23, >>We hit an entrepreneur down in New Zealand. I interviewed she was from indigenous area and she had no milk or food on the table. They were so poor. They could barely get food. She worked her way through it and went to school. Education was number when it goes, she was so persistent, she got her education. And now she's the CEO of an AI company, amazing person. And she's like, Hey, there's no wall I can't run through. So that attitude was just so refreshing. And that was a consistent this year and it wasn't an in your face. It was just more of we're here, we're kicking butt. So let's keep it going. So on the entrepreneurial side, I found that really awesome on the senior leadership side, it was very much, um, community oriented, very open about sharing their experiences and also being a sponsor. So you're going to hear a lot about breaking the bias, but it's also about sponsoring opportunities and then helping people get involved so that they can get understand biases because everyone brings biases to the table. So I personally learned a lot this, this, this, uh, event. >>Yeah. I think the, the light that was shined on the bias was incredibly important. You know, the break, the bias, as you said, is the theme of this year's international women's day. And I, and I asked everybody that I spoke with, what does that mean to you? And where do you think we are on that journey? A world free of bias and stereotypes and discrimination. Obviously we're not there yet, but a lot of the women talked about the fact that that light is shining brightly, that the awareness is there, that for diversity equity and inclusion and having that awareness, there is a great launching launching pad, if you will, for being able to make more progress on actually breaking the bias. >>Yeah. That was a great point. I would also say to add to that by saying a lot of comments were on the same theme of check your bias when you fall, you speak in meetings. And it was just a lot of like protocol tactical, uh, ways to do things like, think about other people in the room versus just barreling ahead. Most guys do that actually. Um, and so that was another instructful thing. I think the other thing too was is that there was, again, more and more sharing. I mean, we had one person that you interviewed, her name was Anne green. Yeah. She's doing her own series. Uh, we're content. She's interviewing people, she's being a mentor and sharing it through content, Manny theory of AWS in Singapore, she's in space and Aero science talking about how the satellites are helping in the Ukraine, give information to everyone on the ground, not just governments and that's helping democracy. And that she's really excited that that contributes to some good there. Um, and she fled from a town where it was bombed. She was in a war zone and she escaped and got educated. So education's a theme. Um, don't let anyone tell you, you can't do it. Uh, and don't think there's only one pathway, right? This is tons of opportunities for participating in the tech economy for good, uh, in, in, in tech. So those are the keys. >>That's always been one of my favorite themes when we do women in tech events, John is that there is no direct pathway necessarily. I always love understanding those stories, but this year, one of the things that also was really clear was that women feeling what can't I do. And that sentiment was really echoed throughout. I think everybody that I spoke with that there was no, can I do this? Why can't I Not confidence? Which is palpable. Even when you're doing an interview by zoom, you can feel it. You can be inspired by, >>Well, at least a year, you do all the, a lot of the interviews. You're the face I had, you know, step aside for you because you're amazing. But one of the things you, you get appreciate this and love to get your reaction. One of the things I observed this year was because it was international focus, there was huge cube demand to be come to their region. We had one of the guests that won from Bahrain. She's like, I'll do the cube here. I'll be the host. So I think there was a real appetite for this kind of open dialogue conversations where they want the cube to come to their area. And so I know anyone watching wants to be a cube host in those areas, let us know, um, we're open. And to me that was more refreshing. Cause you know, me, I always wanna see the cube global go everywhere. But this year people are actually turning on their own cameras. They're doing their own interviews. They're sharing content and content creates community and bonding. And that was the big experience I saw this year was a lot more user generated activity engagement with each other in the group. >>I think that may have even been a product of the last two years of the pandemic of people really understanding the importance of community and collaboration and that it can be done via if you're only limited to video, you can do that. You can build a community and grow it and foster it in that way and create the content that really helps support it. >>That's a great point. That's actually one of the guests said COVID polled the future forward and digital. We see the value and other on the cyber side, um, Sally, as I mentioned there, um, earlier who we interviewed before, she's a cyber policy analyst and she's so smart. She's like, yeah, this is putting fold forward. And people understand cyber now, cyber misinformation, cyber war, the role of working at home, being isolated versus community. These are core societal issues that need to be solved and it's not just code that solves them. So it's going to be solved by the community. And that's really, that was the key. One of the key messages. It was very refreshing. >>It was very refreshing. I always love hearing the stories. I, the more personal the story, the more real it is and the more opportunities I think that it unlocks for the audience watching. Yeah, >>I mean, we had one person said she did a project on the side. It's going to be your big initiative within Amazon. You know, Amazon, one of our sponsors has a slogan think big, but deep dive deep. And she took a project on about educating, um, young girls and young women. And it turned out to be basically a build lab inside schools. And it took off. It is so successful side project, side hustle gone, gone big. So again, sparks of creativity, innovation can come from anywhere. It's just great stories. >>Another thing that came up in several of the conversations that I had was the data, the data that support that organizations that have at least 30% females at the executive level are better performing organizations. They are more profitable as well. So it was fun to kind of call out if we're talking about data science, what not the data that supports why international women's day is what it is, why it's becoming even bigger than that and the importance of showcasing those voices so that she can be what she can see. >>Yeah. Amazing stories. I got to say it again. I think the virtual studios where we have now with the pandemic is going to give us much more opportunities to get those stories out. And Lisa, you've done an amazing job. Your interviews were awesome. Thank you. And we can do a hundred. We'll give you a hundred interviews a week. >>We can, are you setting me up? No, it was fun. The international influence this year was fun. I mean, I think I started one of my interview days at 6:00 AM and it was just exciting to be able to connect to different parts of the world and to hear these stories and for the cube to be able to be the platform that is sharing all of that >>And the diversity of the interviews itself and the diversity of the environments that for instance, in Asia Pacific and your are diverse areas and they see it it's much further along. They live it every day. They know the benefits. So that again, that was another aha moment for us, I think this year. >>So how many, how many segments do we have for international women's day John >>30 segments, uh, 32 counting our little segments here. So 32 interviews. Um, we're going to probably add a section on the site for people to submit stories like a directory, uh, this, a zillion things going on, women of web three, Sandy, Carter's putting on an event. I know there's a security called. She S she scarcity events, she security, uh, going on women in security. Um, there's tons of activities it's vibrant tomorrow. Today. It'll be very much bumping up. So we'll try to curate as much links as possible. >>Awesome. John has been great doing this program with you. I look forward to seeing the interviews and being inspired by the many, many stories. You're going to be watching the cubes coverage of women in tech global event, featuring international women's day for John furrier. I'm Lisa Martin. We'll see you soon.

>>Yeah. Hello and welcome to the Cubes Presentation of Women in text. Global event Celebrating International Women's Day I'm John for a host of the Cube were with Sally E. Senior Policy Advisor Global Foundation for Cyber Studies and Research. Sally, great to see you. Thanks for coming on the cue for International Women's Day. Appreciate it. >>Pleasure, John. Great speech again. >>Love your title. Global Foundation for Cyber Studies. Um, global is a big part of the theme this year. Uh, cyber studies. We're seeing a lot of cyber activity all around the world, networks, communities coming together, the role of data. I mean, everything is touching our lives. There are no boundaries anymore. What does it all mean? There's so much to talk about your in the middle of it before we get into it. Tell us about your career and your history. How you got interested in tech and what you're working on. >>Absolutely. I love it. Kind of this age of convergence coming together right now, isn't it? That's how I would describe it. And that's kind of a bit like my career. I think in many ways as well. So for the audience, really great to be here and share about that today, and I kind of say, three main palace, so one would be emergent technologies. So, you know, I started off right through from coding to advisory to CTO type roles as well also change management. And now I'm more advisors right across from a I to five G to to Iot and security, for example as well. Also passionate about education checking education for me. They always go hand in hand, some a professor at a number of universities and in my non for profit, we really do a lot of outreach around educational opportunities as well. And that third pillar opponent hinted at it already will be social impact. So really passionate about how we can use tech as a force for good things around sustainability right at the heart of that, but also around diversity equity and inclusion. So we do a lot of pro project your locally and globally around kind of reframing what a tech career looks like, giving people more democratised access. Those tech opportunities outside of that a bit like yourself, you know, podcast host and writer and speaker and things as well, so very much going to building that community around key tech topics. >>Well, folks watching should check it out on Twitter. She's that great content you mentioned Mobile World Congress. Before we get on camera, you mentioned convergence. I mean, we're at a time now. I got to ask you while I got you here before we get into the whole schools and career tech thing, we've seen this movie before, but never at this scale. The convergence and the confluence of education and scale of cloud computing, the ability to level up and get, um, I won't say democratised. That's kind of overused. But I'm just talking about like with cloud computing could be educated and in market with a job instantly. Um, the barriers just seem to be moving away because of the the openings and the roles are changing. So, more than ever, this whole new tech scene comes together in a way. Can you share your thoughts and vision because to me, we're seeing this happening at such a scale unprecedented in my career? >>It is. And that's one of those words that the part had been overused, unprecedented, but right now it really, really is. It's not just a speed of change. I think it's a scale of change as well. You know, I think previously we've talked about disciplines in silos to a certain extent. Haven't we know in terms of like, an AI special is, um or five g one or other disciplines as well? But really, now that convergence about what one tech enables another, it really is that smart technology coming together for more and more different use cases, but that residents around how important education is alongside that alongside process alongside culture and shared values as well it really is. It's kind of holistic integration of everything that matters at the moment. And it's evolving business models as well. You know, shared values rights centre stage around that MWC just come back from that, And the key topics there weren't just by G, it was the importance of ecosystem collaboration. For example, there are less tracks that were isolated on one technology. It was more this conflation of these different technologies coming together and what we can achieve from that from business but also for society so really exciting focus areas now things that maybe once or a few years ago, more than periphery. They're now absolutely centre stage. So it's good to see that progress in that area. And I love to advocate around that. >>And the education piece is so important, and we always stay here in Cuba. It's a data problem, right? Everything's a data problem when you look at schools and education is structured and unstructured data kind of our our systems right, So structured as schools, institutions, those kinds of career paths or education pathways. And then you haven't structured freeform communities, seeing a lot more education going on within groups. Um, off structured environments like schools, Can you and you do a lot with schools? Can you share more how you're doing? Um uh, work with schools specifically on the structured side to get girls into careers faster and tech? And then can you also comment on the other side? What's going on in the communities because it's it's kind of going on in parallel, but they're not mutually exclusive. >>No, absolutely community, absolutely key word that I love that, and I think when we're talking about diversity and technology, it's not just what we're doing now with what we're looking at is looking ahead, but also looking at future pipeline as well. So for me, I use this express a little bit. But change the narrative. That's what springs to mind for me when we're talking about that, and particularly for girls going into technology but also more broadly, diversity of experience. More broadly, we do have these drop offs, so UK is one example, but it is really representative of the global trends that we're seeing. Now. We get a drop off of girls in particular, taking ice subjects at GCSE level so kind of that subject choice choice at 12 to 14, that kind of area. We get the same thing at a level that's equivalent of 16 to 18 and then even safer university or even apprenticeships, whichever both equally valid. But even if people are taking those types of skills, they're not then choosing to apply them in their careers. So we're seeing these kind of three pillars where we need to intervene earlier. So for me, the more that we can do things you know from dedicated educational offers, but equally partnering with tech companies to do outreach around this area. We need to go in younger and younger is so important to address that. Why? Why are people thinking they can't? Why is his career not for me, for example, so addressing that is huge. And that's one of the things we do with my nonprofit that's called aspirational futures. We go into schools and two universities, but equally do things with older adults and re Skilling and up Skilling as well. Because again, we can't leave that behind either. There's something for all different kind of age groups and backgrounds here, but specifically, I think, in terms of getting people interested in this career, curiosity matters. You know, I think it's an underrated skills. So it's changing the narrative again. And what the tech career actually is, what skills are valid? You know, I mentioned, I have a coding background as a starter. But not all tech careers involve coding, particularly the rise of low code or no code, for example as well. So really valued skill. But so many other skills are valid as well, you know, creativity or emotional intelligence problem solving skills. So for me, I like to drive forward. All those skills can make a difference as an individual, as a team, so your you know your tech career. All those skills are valid and you can make a huge difference. And I also think, you know, just kind of really bringing to the fore what different types of projects you can be involved in in tech as well. And I found really resonating when you can talk about tech for good projects and show how you're making a difference about some of those big challenges. Um, that's kind of really kind of resonating responsible people as well. So again, the more we can show tangible projects where you can make a difference and the whole range of skills that are involved in that it really helps people to think differently and gain that skills confidence. So it's like, >>Well, that's awesome insight. I want to just double click on that for a second, because one the drop off. Can you just repeat the ages where you see the drop off with the drop offs are >>absolutely yeah, no problem, John. So it's kind of when you're making your first choices around your first kind of qualifications. Between that 12 to 14 age group, 16 to 18 and then 18 to 21 I think we've really got to tackle that So again the earlier we can go in the better and again supporting people within organisations as well. So I do a lot of work like internally, with organisations as well people looking to up skill and re skill. You mentioned about data and the importance of data literacy earlier on in the conversation as well. For example, going into organisations and really helping to support people in all roles, not just tech facing roles develop that skills, confidence as well. So for me it's access to skills really bringing forward the difference. You can make that holistic range of skills that makes a difference, but also the confidence to apply them as well. You know, we talk about agility, of organisations, a lot areas, one of those kind of words in the last 12 months. But maybe we don't talk about personal agility and team agility as well. So I kind of talked about it. This little toolbox, if we can give people more and more things to draw from it, the only constant is this rate of change. If you've got more things in your armoury to cope with that and be an agile to that. It takes that fear away about what happens next because you feel you've got more skills to dip into it and to apply. So for me, it's that that confidence, not just the access to the skills >>and the other thing, too, I thought was insightful. I want to just reiterate and bring to the surface again as skills, right? So you don't have to be a coder. And I see I have two daughters just with my family. Yeah, I do python. They kind of put their toe in the water cause it's cool. Maybe that's a path, and they kind of don't like, maybe get into it. But it's not about coding anymore because you said low code, no code. Certainly. Maybe AI writes the code. We all see that happening. It's problem solving. It's you could be in health care and you could be nerd native, as we say, as on some of the other interviews of that year at the problem, solving the aperture of skills is much broader now. Can >>you share more than >>more than because with your with your programme and your nonprofit, I know you're in the middle of it, and this is important to get that out there. >>Absolutely so skills. You know, I think we need to change the focus on what skills make a difference if you see what I mean. I think you're absolutely right. There's some misconceptions about, you know, you want to go into tech, you need to be a coda. And you're right with the upscale around low Skilling. Sorry, Low code and the code opportunities. Um, I think the niches around being a specialist. Koda. We're gonna get more roles in that area, but in other areas, we need to look at different skills gap. So I'm advising people to look at where the gaps are now. So cyber security is a key example of that testing architecture. Those gaps are getting bigger. Their amazing skills, opportunities. They're so focused on a particular discipline. But it's all those skills that surround that that make a difference as well. So as I mentioned, you know, e Q creativity, communication skills, because it's not just about having the skills to build the future, knew that imagination to refocus about what that could even be. You know, that was one of the MWC 20 to refrain, reimagine and I love to kind of galvanise that spirit and people that you can be part of that, you know, wherever you are now. And I actually run a little series called 365, and you mentioned something right at the start of our conversation about International Women's Day being such an important focus area. But also we need to think about this beyond that as well. So hence that's the title of the series that I run because it's a focus on that every single day of the year. You know, I interviewed people that could be a C suite roles, but equally I've had some amazing interviews with 12 to 14 year olds, even younger, the youngest of the seven year old. He's doing like an amazing project in their kitchen with a three D printer working with local school or a hospice doing something around Ukraine. Another project we're doing at the moment, actually, and it's so resonating it's trying to show people wherever you are now, wherever you want to be, there's somebody relatable that you can make. You can see whatever sector, in whatever age, whatever background, and I think it's to give that inspiration. Hey, you know what I can do that that can be me. So visibility of role models, it really matters. And to really broaden out what role model looks like, you know? >>And then I think people out there you see yourself. I mean, this is what we been >>proven right? >>It's proven I want to get into the aspirational futures thing that you have going on, and I know this is important to you, but also something else you said was, is that there's more jobs open and say cybersecurity than ever before. And you're seeing this trend where all these new roles are emerging because of the tech that weren't around years ago, right? And so we've been having conversations in the Cube saying, Hey, all these roles are new, but also problems are new to these New new problems are surfacing because of the this new environment we're in. So these new roles still have to solve problems, so we need people to solve those problems. This is the future. This is the conversation that people are trying to get zero in on misinformation, cybersecurity, you name it. Society is changing with >>new. You >>have new new problems and new opportunities. Could you share your aspirational future? How you vector into that? >>Yeah, absolutely. And for me it's just again that we're convergence around people in technology and partnership, and that's what we aim to do. We do projects at a very local level, but equally we do them at national and international level as well. And one of our kind of people assume I'm talking pillars a lot, but I like it as a framework. So one of those esteem learning. So putting an equal value on the arts as well as science, technology, engineering, mathematics because I think they are. You know, as I mentioned before, hand that imagination, creativity, curiosity, collaboration, skills. They're equally valid as a different types of tech skills as well. We need an equal value and all of them. I think that's hugely important, important today. I think over the last 5 to 10 years, maybe there's been less of a focus within curriculums on the arts area than the other areas. So for me, putting that equal focus back is hugely important to navigate change, you know, I think that's that's that's absolutely key. So we focus on that area and we do a whole range of tech for good projects, and that's the way we help people to learn, you know, for example, data 90% at the moment of data isn't touched again when it's archived after three months. How can we turn that into a learning opportunity? For example? Some of the projects we use some of this is not going to be used again. We do it in a very safe, secure way, but we use that as one of our training aids, and then we apply them for local projects. We have initiatives from hackathons and ideation right through to very tangible hubs that we've actually built out where people can go, learn up skill and kind of learn through play and experimentation as well. Because again, I think that sometimes under explored that type of value and that freedom to be able to do that. And we also do things, change management skills. We talk about agile learning, agile technology need agile change management as well. So it's a very holistic skills. Look at what you need to navigate that future and have the confidence to apply them. So steam is very much our focus, applying them for tech for good projects and doing that externally, but also within organisations as well. So that very much is shared value approach to good business, but good for society as well. So yes, that this toolbox, that technology I applied earlier we really try and give people that support. To be able to do that, to move forward with confidence and optimism. >>I think adding the aid to stem really for steam is really smart because entrepreneurship or any problem solving creativity is the spark of innovation. >>And that's a super >>important skill. And we've seen it, whether it's startup or in a big company or in society, so super, super insightful. So I got to ask you, as a policy senior policy advisor on cyber studies globally, what are the core issues you're looking at right now? What are you shutting the light on and what's the most important thing you're working on? And then what's the most important thing you're working that people aren't talking about, that people should pay attention to >>Absolutely so. One of my key roles of the foundation is is kind of share of global trust. Essentially, um, and again trust is that one of the key issues of our time? One thing that people are talking about so much that relates with that actually is there's there's research from a group called The Woman. They've been looking at this for about 17 years or so. The research that came out most recently and I've got some original research that kind of support this as well is that for the first time ever, consumers are looking at organisations like tech organisations and other large organisations, in particular the enterprise level, really, as the bastions of trust to a bigger extent than NGOs or even governments. And that's the first time we've seen it at that level. So trust really really matters. It's one of the biggest differentiators of our time, so we're trying to help people. How do you establish trust? How do you build transparency, commitment and accountability, particularly in areas where there's currently confusion, so as one example going back Security zero Trust That phrase is used an awful lot, isn't it? But it's sometimes causing some confusion. Actually, it against what it's trying to deliver if you see what to me. So now I just do something recently with SMB s in particular and there is a confusion that effectively, you know, you could You could buy off the shelf and it's once and done. Um, And then we're sorted for the zero Trust security. And obviously it's not like that. It's an ongoing journey, and there's so many different constituent parts. So there's some things I'm seeing at the moment in the market with there's confusion around around certain language, for example. So again it goes back to backing things up with the technology but also research and awareness so we can see where those skills gaps are. You can see where there's awareness gaps are we can help to fill them. So that's an important part of that particular role bringing the technology in the culture and the education hand in hand together. So it's something I'm really passionate about, and for me sort of related to this, Um, I do a lot of work around S G, um, to the sustainable development goals. In particular, environmental and social governance is something that's becoming much more of a bigger kind of centre stage conversation. I'm an action point in a moment which is fantastic because this is something I've been involved in kind as long as I can remember. So I work directly with organisations like, um Unesco, lots of different professional bodies. It's kind of a huge driver for me. So one thing to kind of look out for that's coming very soon. I'm seeing an issue around around measurement in this area. You know, we're seeing consumers becoming more and more conscious and employees, you know you want to work for by from advocate organisations that have that same value alignment that you have personally and professionally, hugely important. We're seeing some great reports coming out around better e S g measurement. But it can be hard to compare between different organisations, so we are getting more transparency. But it's difficult sometimes to make fare comparisons. Um, so what I'm trying to do a lot of work on at the moment is how you go beyond that transparency to commitment to accountability and that deeper level and that comparability. So I would say kind of to the audience moment, Look out for a bit of a new index. It's going to help people, I think, make those conscious choices make informed choices. So it's something I'm super, super passionate about. I want to try and take that to next level in terms of its actualisation. >>That's awesome. And certainly we'll link to it on our site. All the work you're doing on interviews will put links there as well. We'll make sure we'll follow up on that. Great to have you on. You're such an inspiration. Amazing work, cutting edge work. And I'm I'm super impressed with the cyber studies, and I think this is really important. I have to ask you a final question because you're in the middle of it again with covid and the unfortunate situations we've been living with Covid. And now, obviously with this Ukraine situation that the cyber has been pulled to the front of the agenda and you're seeing a cultural shift. You certainly got Web three. Cyber is now part of everyone's life, and they can see it. They've been seeing it living it. Everything's been pulled forward as a cultural shift happening, okay, and and it's really interesting right now, and I want to get your thoughts because this now people are now aware what cyberwar means cyber security cyber. At home, I have remote work. Cyber has become front and centre or digital. However you want to call it in our lives pulled forward. >>So I'm not even sure in some >>cases, maybe rightfully so, and others. What's your view on this whole cultural cyber being pulled forward? >>It is. It's really, really interesting. And so one of the things I do is I am now ready to a Cyber Insights magazine as well. So we're developing a lot of content pieces around this and lots of things I'm seeing here. So your covid point, I think one of the most interesting things there is around literacy. For example, you remember when we went back to 18 months ago? We're having daily briefings, whether that's from from UK Parliament or the U. S. Equivalent. And different phrases were coming into everyday language driven by the curve or driven by the data. And they're coming into everyday life and people family kitchen table. It was something that hasn't been spoken about before, but suddenly it was driving everyday decision making and what you could and couldn't do. And that's raised awareness. And I think it helped people to ask better questions and to challenge things that they're seeing. And where has that data come from? How has it been presented to have seen that there? I think similarly, where we're having that same understanding and raise of questioning around what we're hearing around cyber as well. You're looking at where that source has come from, and how can we look at that in a different way? So again, I think it's raising that awareness, which is really, really crucial, >>the >>other thing as well around cyber security in particular. And again, I don't think this is talked about as much. When we talk about aspects around inclusion, we talk about diversity equity. Um, I'll see inclusion. I talk about belonging a lot as well. I think there's other aspects around sustainability that Inter relate as well, because when we find, for example, communities that are not included, they tend to be more adversely affected by, for example, climate factors as well. There's an interrelation. They're equally We find that people that haven't got, for example, the same level of cybersecurity protection are also in that same. There's an interrelation across all those elements were not talking about that either. So that's the other thing. I want to kind of bring attention to their again. They aren't separate conversations is a huge crossover between these different conversations and actions that we can do to make a difference. So there's some positive aspects about things that have happened over the last period of time and also some challenges that if we're aware of them, we can work together again, that collaboration piece to be able to overcome them. You know, I've got I've got a book coming out, all for charity called Tech for Good and one of my kind of tag lines. There is around contagion of positive change. Again, let's reframe the language around what's been happening. And let's kind of put that together is something that's far more positive. >>Language is super important, great >>content here. So >>thanks so much for coming. I really appreciate all the great insight and taking the time out of your busy day to to join us here in the Cube. Women in tech Global Event. Thank you so much. >>My absolute pleasure. Thank you. Thank you all for watching. >>Okay. The cubes presentation of women in text. Global event Celebrating International Women's Day. I'm John for a host of the Cube. Thanks for watching

>>Welcome back to the cubes coverage of women in data science, 2022. We've been live all day at Stanford at the Arriaga alumni center. Lisa Martin, John furrier joins me next, trying to, to cure your FOMO that you have. >>I love this events. My favorite events is 2015. We've been coming, growing community over 60 countries, 500 ambassadors and growing so many members. Widths has become a global phenomenon. And it's so exciting to be part of just being part of the ride. Judy and Karen, the team have been amazing partners and it's been fun to watch the progression and international women's day is tomorrow. And just the overall environment's changed a lot since then. It's gotten better. I'm still a lot more work to do, but we're getting the word out, but this year seems different. It seems more like a tipping point is happening and real-time cultural change. A lot of problems. COVID pulled forward. A lot of things, there's a war going on in Europe. It's just really weird time. And it's just seems like it's a tipping point. >>I think that's what we felt today was that it was a tipping point. There was a lot of our guests on the program that are first time with attendees. So in seven, just seven short years, this is the seventh annual width it's gone from this one day technical conference to this global movement, as you talked about. And I think that we definitely felt that women of all ages and men that are here as well understand we're at that tipping point and what needs to be done next to push it over the edge. >>Well, I'm super excited that you are able to do all the amazing interviews. I watched some of them online. I had to come by and, and join the team because I have FOMO. I love doing the interviews, but they're including me. I'm happy to be included, but I got to ask you, I mean, what was different this year? Because it was interesting. It's a hybrid event. It's in part, they didn't have it in person last year, right? So it's hybrid. I showed the streams where everywhere good interviews, what was some of the highlights? >>Just a very inspiring stories of women who really this morning's conversation that I got to hear before I came to set was about mentors and sponsors and how important it is for women of any age and anybody really to build their own personal board of directors with mentors and sponsors. And they were very clear in the difference between a mentor and a sponsor and John something. I didn't understand the difference between the two until a few years ago. I think it was at a VMware event and it really surprised me that I have mentors do ask sponsors. And so that was a discussion that everybody on this onset talked about. >>It was interesting. We're doing also the international women's day tomorrow, big 24 interviews, including the winds of content, as well as global women leaders around the world and to new J Randori, who runs all of AWS, Amy are your maps. And she told me the same thing. She's like, there's too many mentors, not enough sponsors. And she said that out loud. I felt, wow. That was a defining moment because he or she is so impressive. Worked at McKinsey, okay. Was an operator in, in running businesses. Now she heads up AWS saying out loud, we have too many mentors, this get down to business and get sponsors. And I asked her the same thing and she said, sponsors, create opportunities. Mentors, give feedback. And mentors go both ways. And she said, my S my teenage son is a mentor to me for some of the cool new stuff, but ventures can go both ways. Sponsors is specifically about opportunities, and I'm like, I felt like that comment hit home. >>It's so important, but it's also important to teach girls. And especially the there's younger girls here this year, there's high school and middle, I think even middle school girls here, how to have the confidence to, to find those mentors, those sponsors and cultivate those relationships. That's a whole, those are skills that are incredibly important, as important as it is to understand AI data science, machine learning. It's to be able to, to have the confidence in a capability to create that and find those sponsors to help you unlock those opportunities. >>You know, I feel lucky to do the interviews, certainly being included as a male, but you've been doing a lot of the interviews as females and females. I got to ask you what was the biggest, because every story is different. Some people will it's about taking charge of their career. Sometimes it's maybe doing something different. What some of the story themes did you see in your interviews out there? What were some of the, the coverings personal? Yeah. >>Yeah. A lot of, a lot of the guests had stem backgrounds and were interested in the stem studies from when they were quite young and had strong family backgrounds that helps to nurture that. I >>Also heard that role models. Yes, >>Exactly, exactly. A strong family backgrounds. I did talk to a few women who come from different backgrounds, like international business and, but loved data and wanted to be able to apply that and really learn data analytics and understand data science and understand the opportunities that, that it brings. And also some of the challenges there. Everybody had an inspiring story. >>Yeah. It's interesting. One of the senior women I interviewed, she was from Singapore and she fled India during a bombing war and then ended up getting her PhD. Now she's in space and weld and all that stuff. And she said, we're now living in nerd, native environment, me and the younger generation they're nerds. And I, you know, were at Stanford dirt nation. Of course we're Stanford, it's nerd nerd nation here. But her point is, is that everything's digital now. So the younger generation, they're not necessarily looking for programmers, certainly coding. Great. But if you're not into coding, you can still solve society problems. There's plenty of jobs that are open for the first time that weren't around years ago, which means there's problems that are new to that need new minds and new, fresh perspectives. So I thought that aperture of surface area of opportunities to contribute in women in tech is not just coding. No, and that was a huge, >>That was, and we also, this morning, I got to hear, and we've talked about, we talked with several of the women before the event about data science in healthcare, data science, in transportation equity. That was a new thing for me, John, that I didn't know, I didn't, I never thought about transient equity and transportation or lack thereof. And so w what this conference showed, I think this year is that the it's not just coding, but it's every industry. As we know, every company is a data company. Every company is a tech company. If they're not, they're not going to be here for a long. So the opportunities for women is the door is just blown. >>And I said, from my interviews, it's a data problem. That's our line. We always say in the cube, people who know our program programming, we say that, but it actually, when we get the data on the pipeline and the pipeline, it has data points where the ages of drop-off of girls and young women is 12 to 14 and 16 to 18, where the drop-off is significant. So attack the pipelining problem is one that I heard a lot of. And the other one that comes out a lot, it's kind of common sense, and it's talked about it, but it's nuanced, but it became very elevated this year in the breaking, the bias theme, which was role models are huge. So seeing powerful women in leadership positions is really a focus and that's inspires people and they can see themselves. And so I think when people see role models of women and, and folks on in positions, not just coded, but even at the executive suite huge focus. So I think that's going to be a next step function in my mind. That's that's, if I had to predict the trend, it would be you see a lot more role modeling, flexing that big time. >>Good that's definitely needed. You know, we, we often used to say she can't be what she can't see, but one of the interviews that I had said, she can be what she can see. And I loved the pivot on that because it put a positive light, but to your point, there needs to be more female role models that, that girls can look up to. So they can see, I can do this. Like she's doing leading, you know, YouTube, for example, or Sheryl Sandberg of Facebook. We need more of these role models to show the tremendous amount of opportunities that are there, and to help those, not just the younger girls, those even that are maybe more mature find that confidence to build. >>And I think that was another king that came out role models from family members, dad, or a relative, or someone that could see was a big one. The other common thread was, yeah. I tend to break stuff and like to put it together. So at a young age, they kind of realized that they were kind of nerdy and they like to do stuff very engineering, but mind is where math or science. And that was interesting. Sally eaves from in the UK brought this up, she's a professor and does cyber policy. She said, it's a stems gray, but put the arts in there, make it steam. So steam and stem are in two acronyms. Stem is, is obviously the technical, but adding arts because of the creativity needs, we need creativity and problem solving with technical. Yes. So it's not just stem it's theme. We've heard that before, but not as much this year, it's amplified big >>Time. Sally's great. I had the chance to interview her in the last couple of months. And you, you bring up creativity, which is an incredibly important point. You know, there are the, obviously the hard skills, the technical skills that are needed, but there's also creativity. Curiosity being curious to ask a question, there's probably many questions that we haven't even thought to ask yet. So encouraging that curiosity, that natural curiosity is as important as maybe someone say as the actual technical knowledge, >>What was the biggest thing you saw this year? If you zoom out and you look at the forest from the trees, what was the big observation for you this year? >>I think it's the growth of woods. We've decided seven years. It's now in 60 countries, 200 events, 500 ambassadors, probably 500 plus. And the number of people that I had on the program, John, that this is their first woods. So just the fact that it's growing, we, we we've seen it for years, but I think we really saw a lot of the fresh faces and heard from them today had stories of how they got involved and how they met Margo, how she found them. I had a younger Alon who'd just graduated from Harvard back in the spring. So maybe not even a year ago, working at Skydio, doing drone work and had a great perspective on why it's important to have women in the drone industry, the opportunities Jones for good. And it was just nice to hear that fresh perspective. And also to S to hear the women who are new to woods, get it immediately. You walk into the Arriaga alumni center in the morning and you feel the energy and the support and that it was just perpetuated year after year. >>Yeah, it's awesome. I think one of the things I think it was reflecting on this morning was how many women we've interviewed in our cube alumni database now. And we yet are massing quite the database of really amazing people and there's more coming in. So that was kind of on a personal kind of reflection on the cube and what we've been working on together. All of us, the other thing that jumped out at me was the international aspect this year. It just seems like there's a community of tribal vibe where it's not just the tech industry, you know, saying rod, rod, it's a complete call to arms around more stories, tell your story. Yes. More enthusiasm outside of the corporate kind of swim lanes into like more of, Hey, let's get the stories out there. And the catalyst from an interview turned into follow up on LinkedIn, just a lot more like viral network effect so much more this year than ever before. So, you know, we just got to get the stories. >>Absolutely. And I think people given what we've been through the last two years are just really hungry for that. In-person collaboration, the opportunity to see more leadership to get inspired and any level of their career. I think the women here this today have had that opportunity and it's been overwhelmingly positive as you can imagine as it is every year. But I agree. I think it's been more international and definitely much more focused on teaching some of the other skills, the confidence, the creativity, the curiosity. >>Well, Lisa, as of right now, it's March 8th in Japan. So today, officially is kicking off right now. It's kicking off international women's day, March 8th, and the cube has a four region portal that we're going to make open, thanks to the sponsors with widths and Stanford and AWS supporting our mission. We're going to have Latin America, AMIA Asia Pacific and north America content pumping on the cube all day today, tomorrow. >>Exactly. And we've had such great conversations. I really enjoyed talking to the women. I always, I love hearing the stories as you talked about, we need more stories to make it personal, to humanize it, to learn from these people who either had some of them had linear paths, but a lot of emergency zig-zaggy, as you would say. And I always find that so interesting to understand how they got to where they are. Was it zig-zaggy, was it zig-zaggy intentionally? Yes. Some of the women that I talked to had very intentional pivots in their career to get them where they are, but I still thought that story was a very, >>And I like how you're here at Stanford university with winds the day before international Wednesday, technically now in Asia, it's starting, this is going to be a yearly trend. This is season one episode, one of the cube covering international women's day, and then every day for the rest of the year, right? >>What were some of your takeaways from some of the international women's day conversations that you had? >>Number one thing was community. The number one vibe was besides the message of more roles or available role models are important. You don't have to be a coder, but community was inherently the fabric of every conversation. The people were high energy, highly knowledgeable about on being on point around the core issue. It wasn't really politicized was much more of about this is really goodness and real examples of force multipliers of diversity, inclusion and equity, when, what works together as a competitive advantage. And, you know, as a student of business, that is a real change. I think, you know, the people who do it are going to have a competitive advantage. So community competitive advantage and just, and just overall break that bias through the mentoring and the sponsorships. >>And we've had a lot of great conversations about, I loved the theme of international women's day, this year breaking the bias. I asked everybody that I spoke with for international women's day and for width. What does that mean to you? And where are we on that journey? And everyone had a really insightful stories to share about where we are with that in their opinions, in their fields industries. Why, and ultimately, I think the general theme was we have the awareness now that we need, we have the awareness from an equity perspective, that's absolutely needed. We have to start there, shine the light on it so that the bias can be broken and opportunities for everybody can just proliferate >>Global community is going to rise and it's going to tend to rise. The tide is rising. It's going to get better and better. It was a fun year this year. And I think it was relief that COVID kind of going out, people getting back into physical events has been, been really, really great. >>Yep, absolutely. So, John, I, I appreciate all the opportunities that you've given me as a female anchor on the show. International women's day coverage was fantastic. Widths 2022 coming to an end was fantastic. Look forward to next year. >>Well, Margo, Judy and Karen who put this together, had a vision and that vision was right and it was this working and when it gets going, it has escape, velocity unstoppable. >>It's a rocket ship. That's a rocket. I love that. I love to be part of John. Thanks for joining me on the wrap. We want to thank you for watching the cubes coverage of international women's day. The women's showcase as well as women in data science, 2022. We'll see you next time.

(upbeat music) >> Hey everyone, welcome back to theCUBE's continuous coverage of AWS reinvent 2021, I'm Lisa Martin. This is day four for theCUBE. We have two live sets, I'm here with Dave Nicholson, Dave two live sets, 100 guests on theCUBE for AWS Re:Invent 2021. >> Not all at the same time. >> Not all-- That's a good, he brings up a good point, not all at the same time, we are pleased to welcome Gretchen Peri who's going to be sitting down and chatting with Dave with me next. She is from Slalom, at the US State Local and Education, SLED leader. We're going to be talking about Slalom and AWS digital innovation in the public sector. Gretchen, it's a pleasure to have you on the program. >> Thank you for having me. >> For the audience that might not be familiar with Slalom before we dig into AWS and SLED in particular, talk to us about Slalom and what it is that you guys do. >> I'd love to. So Slalom's a modern business and technology consulting firm. We're headquartered in Seattle Washington, we have about 11,000 employees across 40 markets globally. And what's different about Slalom is we're local model firm, so our consultants live and work in the same locale, which means we're personally invested in our client's outcomes because they impact us directly in the communities in which we live. >> And you've been in a leader in SLED for a long time, talk to us about what's going on on SLED these days. Obviously the last 18, 22 months have been quite dynamic, but what's going on in the market? >> Absolutely. What we're seeing is an extra emphasis on data data data, obviously, data is king and data is queen right now, right? So when the pandemic hit, we saw a ton of digital innovation, as our SLED clients needed to get their services online. That had been going on for a long time but it absolutely accelerated when then pandemic it and then it was a public health hazard, to ask people to come into the location. So what we saw was for constituents, we saw just absolute blast of omni-channel service delivery, so we saw the advent of SMS and chat bots and the more tech services, right? Leveraging AWS Lex and Transcribe and other services of AWS really helped our SLED clients react to the pandemic and respond to make sure that their constituents were receiving the digital services they needed, and their employees were able to be productive at home. >> Well, that was one of the keys the employee productivity, the student productivity, when everything's went remote overnight, one of the most challenging things was the demand for collaboration tools. Then of course, there's security challenges, there was concerns there, but talk to us about, and we've seen so much innovation out of AWS in the last, I mean always, but even what they announced the last couple of days, the innovation flywheel of AWS is probably stronger than ever enabling organizations like SLED, FED, private sector, public sector to be data-driven. >> Absolutely. One thing that's really exciting right now is to see the evolution of how our SLED customers are thinking about data. So we've been working on like integrated visions in SLED for a long time, integrated justice, integrated health care, integrated eligibility, how do we bring all this information together so that we can supply the right information to the right people at the right time to deliver the right outcomes? And AWS has been a huge part of that. It's not the journey to get to the cloud, it's the destination once you get there, right? Because then you can leverage all their AIML tools, IOT, edge, container, blockchain. And so our customers, who have already made that switch to AWS, they're able to take advantage of that. It's not what you can do in the cloud anymore is what you can't do without it really, right? So we're seeing tons of advances, intelligent document processing is one area I'm really excited about for our SLED clients, and working very closely with AWS to make sure that we see our clients adopt that and achieve the value out of it. >> AWS is dominating the IT space, although what five to 15% of IT is in the cloud, which means the vast majority is still on premises. So there's a huge potential for growth. In this sort of wild, wild west that we're in, there are all sorts of different kinds of services and consultancy partners, that are seeking to bridge the gap between the technology that AWS delivers and the outcomes that customers desire. >> Right. >> Now I've had a couple of experiences actually with Slalom folks, that were very, very positive. And what I saw was that the Slalom people were embedded in a way that you don't see some other consultancies embedded. You mentioned that something that piqued my interest, you talked about the local nature, is that your superpower? Because it sure seemed to be powerful to see this person where some of these very, very large global companies had no idea who Slalom was, until they realized that Sally was the one who had the best relationship with the customer. So Sally's a fictitious name that I just came up with, but I want to hear a little more about Slalom and your superpower and your differentiation. 'Cause it's a crowded space, you've got global systems integrators, you got all kinds of people. What makes you special? >> It's really the breadth of professional services that we provide, combined with AWS's cloud technologies and services. What we do I think a little bit differently is whereas AWS works back from the customer, we work back from our customer's vision. And so what we do with our, especially with our SLED clients, but with all of our commercial clients, is we say, what is your business strategy and your business vision, and how do we design the technology solutions, working back from that. So you're able to answer the business questions through data-driven tech technology, that's really important to you. And when we look at that, it's not just generating data to create information to then garner insights, but let's go one step further. And how do we create knowledge and how do we create wisdom this space, right? Where we understand situational awareness, common operating pictures, that's really what we want to do. When we talk about criminal justice and public safety, I love how we're thinking about joining data in new and different ways. It's not necessarily applications anymore, right? How do we create data as a service? How do we create documents as a service? Where we're pulling out the exact information that we need from semi-structured, structured and unstructured data and providing it to the right people to make the right decisions. >> Talk to us about intelligent document processing, a lot of buzz going on with that. What is it? Where are public sector agencies in terms of embracing it, adopting it and having it be part of that vision? >> Yeah, the promise is huge for IDP. What IDP is basically is leveraging AWS AI services to create intelligent automation solutions that help extract information from printed documents, digital documents, paper documents, right? So leveraging AWS services like Amazon Textract, Comprehend, Augmented AI, things like, and Kendra. What that does in combination, is it helps our clients unlock the data from, you can imagine government, it's heavy, heavy documents, and in criminal justice and public safety in particular, these documents represent key milestones and processes, right? So we're never going to get rid of documents in SLED, they're going to be used in perpetuity, it's important for accessibility and practicality and everything else. But what this does is it lets us unlock the data from those kind of stale documents and create it into usable formats for so that people can make decisions. >> That's critical because there's, I mean, we talk about in Amazon, AWS been this week have been talking about it and Dave, we have too. Every company, public sector, private sector, it needs to be a data-driven company, but they need to be able to extract that value from the data and the data isn't just digital. And that's something that, to your point, that's going to be persistent within SLED, they have to be able to extract the value from it quickly. >> Yes. >> To be able to see what new products and services can we deliver? What directions should we be going? And what outcomes should we be driving based on that visibility? And that visibility is critical. >> Exactly. And right now we absolutely have to support our communities. And we have a lot of our slide clients who are talking about this is a time where we don't just respond in a way that helps people kind of navigate this pandemic, we have to build resiliency as well in our communities and we do that through helping people through these hard times and making sure that we're moving our services to places where people can access them, in any language from wherever they are, right? We're having to actually go into people's homes on their couches, to deliver government services. Where we used to bring them into a single location. >> Right. >> Typically public sector has often been seen as lagging behind the private sector in some ways, the pandemic, as I'm sure ignited a fire with, especially with federal acknowledgement of things that need to happen, budgets flowing, are you seeing even more of an awakening from a cloud perspective within public sector? >> We are, we are and we're seeing really interesting initiatives pop up like, behavioral health initiatives, that are meant to address some really serious concerns in our country like nationwide 988 suicide prevention projects, right? And the federal government is providing a lot of funding to states and local governments so that they can help take care of our communities and also make sure that we're moving our services online so everyone can access them. >> I'm curious about that point, the funding. >> Yeah. >> Do you find yourself almost in the position of prize patrol? Where were some of the state local governments aren't necessarily as aware as Slalom might be of programs that are coming down immediately. Is that part of the conversation? >> It is part of the conv-- That's a great point because what we do is we look at what's coming down from the federal government, how is it going to flow to the states? How is it going to land ultimately, and then helping governments come up with a strategy for how to spend that money in the right way is really important, right? And we saw with some of the funding that come out, that there were delays on getting like eviction prevention funding out to folks. And so making sure that we have the technology to support those outcomes. >> It's all about outcomes. >> Yes. >> Speaking of outcomes, something I want to congratulate Slalom on is winning the first ever National Essay Partner of the Year for the US. >> Yes. >> Nice. >> That's awesome, congratulations. >> What does that mean for Slalom and what direction can we expect the Slalom and AWS partnership to go? >> Up and up. >> To the right? >> Yes. For us it's about validating the relationship that we have, right? It's really, when we walk into a client conversation, what we want to do is develop trust that our clients know we're looking for their best interest and their best outcomes. We're not trying to sell them something we're trying to solve their problems together. And it validates that for us, our partnership with AWS obviously is so important. And what we're doing in terms of making sure that we have a strong bench full of certifications and we can go to market together in the right way for our clients. This is a huge award and the recognition is very powerful for us. >> Well, congratulations. And so last question, you mentioned AWS and we always talk about when we talk with them at their event, we talk about their customer obsession, right? They work backwards, as you said, from the customer. And you guys from customer vision. Talk to me about when you go in jointly together, work with the customer, what does that alignment look like? >> Absolutely. So what we typically do is, Slalom will focus on what is the business outcome that we want to generate? And we will help design, how are we going to go about solving that problem? And how is AWS going to help support us with enabling technology? And so we will go into client conversations together, say, what is the outcome we want from this initiative together? And how are both partners going to get aligned to support the client in that conversation, in that product. >> That alignment is (indistinct). Gretchen, thank you for joining Dave and me today, talking about Slalom, what you guys are doing, how you're really helping organizations in SLED transform and not just survive challenging time but really thrive and be data-driven. We appreciate your insights and congratulations again on the National Essay Partner of The Year. >> Thank you so much. >> All right. For Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (lively music)

(soft upbeat music) >> Hello and welcome to this Cube Conversation I'm Lisa Martin. This is going to be a great conversation about corporate social responsibility, and I'm very pleased to have two great guests here with me today. Karen McCloskey joins us the director of internal communications and corporate philanthropy at NETSCOUT and Professor Sally Eaves is here as well the CEO of Aspirational Futures. She's also a professor of emerging tech and a CTO by background. Ladies welcome to the program it's great to have you on today. >> Thank you. >> Absolute pleasure. Thank you, great to join you both. >> We're going to get some great perspectives here. As I mentioned corporate social responsibility we're seeing that emerge across every industry and every company is really focused on that. Karen I want to start with you where tech companies are concerned we see corporate social responsibility really aligning with STEM and STEAM. Why is that? >> There is probably a couple of reasons, I sort of wrap it up as it's what employees do, it's part of their jobs, so they get excited about it and they want to share what they do with the next generation. And the other aspect that helps it align with tech is it involves the educational aspect. So we're teaching and we need up and coming students and employees and entrepreneurs with those skills. And the other part about STEM is when you think of it, it's typically K to 12 and then it rolls into college and it's working with students and the next generation. So the education and the pipeline or the education and the students speak to the pipeline aspect and then you add in people getting excited about their job and what they do and that's the employee engagement aspect so it really brings the two pieces together. >> I want to dig into that employee engagement in a minute but Sally I would like to get your perspective. Tell us a little bit about Aspirational Futures and then let's talk about the alignment between that and STEM and STEAM. >> Absolutely, so yeah, Aspirational Futures, is a non-profit kind of working across tech education and social impact and really looking at kind of opening up opportunities to the industry to a diversity of experience and using tech and data as a force for good. We do projects locally and across the world I'm kind of breaking down those barriers. It's going to be all about democratization of opportunity I would say. And in terms of STEM to STEAM that's where I see the journey going at the moment and effectively with that STEAM focus you're bringing the arts to an equal stage to the tech skills as well. So for me that's really important because it comes down to curiosity, encouraging people to get into the sector, showing what you can do, building creative confidence, emotional intelligence, those types of skills alongside the tech skills to actually build it. So it's that combination There's complimentary factors that come together. So for me STEAM is a great way to get holistic learning for life With the rate of change we've got at the moment kind of gives you that tool set to work from to be empowered and confident for the future. >> That confidence is so critical. >> Its really. >> For anybody of any age, right? But one of the things that we've seen that is in the inaugural ESG report that NETSCOUT just published is this digital divide. We've seen it for quite a while now but we also saw it grow during the pandemic, Sally from your perspective, what is that and how can tech companies help to fill that gap? >> It's a great point. I think one other thing that the pandemic did was made it more visible as well. So I think particularly we're working in certain spaces we've seen it more, but I think for everybody it's affected our daily lives in education from home, for example for the first time it's made gaps more visible. So absolutely huge to focus on that. And I think we're seeing it from the organizational perspective as well. We're seeing gaps around certain types of roles. We're seeing higher churn because of a lack of data literacy skills. So it's becoming something that's becoming a CUBE Conversation, you know, in day-to-day family life but in organizations across the world as well. And also it's about challenging assumptions. And it just a few weeks ago there was some research that came out at the University of Reading in the UK in conglomerate with other universities as well. And it was kind of showing that actually you can't make the assumption, for example, that teenagers that kind of call digital natures all the time actually have full confidence in using data either, It was actually showing there were gaps there too. So we've got to challenge assumptions. So literacy in all its forms whether it's data, whether it's financial is absolutely key and we've got to start earlier. So what I'm seeing more of is better outreach from tech companies and other organizations in the primary schools through to universities as well kind of internships and placements, but also another really interesting area that we do with the nonprofit is looking at data waste as well. You know, 90% of data there's archive isn't touched again after kind of three months, you think about the amount of data we're producing at the moment how can we reuse that as a force for good as a training opportunity? So let's think creatively let's be pragmatic address some of these data literacy gaps, but we have to do it at all levels of the community and also for adult learners too. That's usually important. >> Right, there's no, it knows no age and you're right that the visibility on it I think it can be a very good thing shining that light finally going we've got to do something. Karen talked to us about what NETSCOUT is doing. The digital divide is there you guys are really focused on helping to mitigate that. >> That's right. That's right. So as guardians of the connected world, that's our job with our customers and our products, but also with our people in our communities is getting people connected and how can we do that? And in what ways are we able to do that? And recently we engaged with Tech Goes Home which is based in Boston and they provide those first three pillars that everybody needs access to a device, access to the internet and skills to use that. And they work with families and students and they say their programs go from nine to 90. So they've got everybody covered. And what's exciting for us is it kind of falls from a volunteer perspective right in our wheelhouse. So they had to transition from in-person to distance learning with the pandemic and suddenly their program materials needed to be online and they needed to get people up and running without the benefit of an in-person class. What NETSCOUT volunteers were able to do was create those tutorials and those programs that they needed and we also have people all over the world and then we translated them into a bunch of different languages and they were able to then move forward with their programs. So Tech Goes Home and programs like that are really that first step in bridging the digital divide. And then once you've got the basics, the toolkit and the skills what else can you do? And Sally mentioned visibility it's what are the opportunities? What can I do now? I didn't realize there was a career path here, I need these skills to build a business help me learn more. So then there's that whole other aspect of furthering what they can do now that they have those skills and the learning and something like a hackathon might be a fun way to engage kids in those skills and help them go a little further with the tools they have. >> And NETSCOUT has done a number of hackathon programs last year I know you had an All-Girls Hackathon virtually in 2020. Talk to me about some of that and then I want to get Sally I'm going to get your perspectives on what you're doing as well. So our hackathons and I'll try and keep this brief because we've done a lot. There were actually brought forward as an employee idea. So that also speaks to our culture. It's like, hey, we should do more of this. We have partner with Shooting Star Foundation and one of our employees is one of their, or is their board chair. And the hackathons what they do and these are beginners hackathons. So we're talking middle high school and the theme is civic. So something good for society. And what we do is over a course of 12 hours not to mention all the pre-planning. When we had the in-person ones they were in our office they got to see employees up close run around the building to the extent that they could and build their project. And Sally I think you had also mentioned that creativity in that confidence. I mean what those kids did in a day was amazing. You know, they came in and they're all kind of looking around and they don't really know what to do. And at the end of the they had made new friends, they were standing up in front of executive judges, presenting their idea, and they all felt really good about it and they had fun. So I think it can be a fun impactful way to both engage employees because it's a heck of a team building experience and sort of bring students in and give them that visibility to what's possible in their tech career. >> And that confidence. Sally talked to me about hackathons from your perspective and what you're involved in? >> Absolutely, funny now I've just come from one. So I'm a Cop 26 at the moment and I've been involved in one with a university again, using that talent and building that empowerment around STG challenges. So in this particular case around sustainability, so absolutely love that and really echo Karen's thoughts there about how this is a reciprocal relationship, it's also super rewarding for all the employees as well, we're all learning and learning from each other's, which I think is a fantastic thing. And also another point about visibility. Now seeing someone in a role that you might want to do in the future, I think is hugely important as well. So as part of the nonprofit I run a series called 365 and that's all about putting visibility on role models in tech every single day of the year. So not for example just like International Women's Day or Girls in ICT Day, but every single day and for a diversity of experience, because I think it's really important to interview people for C-suite level. But equally I just did an interview with a 14 year old. He did an amazing project in their community to support a local hospital using a 3D printer. It makes it relatable, you can see yourself in that particular role in the future, and you can also show how tech can be used for good business, but also for good for society at the same time. I think that can challenge assumptions and show there's lots of different roles, there's lots of different skills that make a difference in a tech career. So coding could be really important but so is empathy, and so is communication skills. So again, going back to that STEAM focus there's something for everyone. I think that's really important to kind of knock down those boundaries, challenge assumptions, and drop the the STEM drop off we say make it a little bit more STEAM focused I think that can help challenge those assumptions and get more people curious, creative, confident about tech. >> I couldn't agree more, curious, creative and confident. The three Cs that will help anyone and also to sell it to your point showing the breadth and diversity of roles within tech coding is one of them. >> Sally: Absolutely. >> As might be the one of the ones that's the most known but there's so many opportunities to allow these kids to be able to see what they can be is game-changing, especially in today's climate. Karen talk to me about you mentioned in the beginning of our interview Karen, the employee engagement, I know that that environmental social governance is core to NETSCOUT's DNA but we're talking over 2,400 employees in 35 countries. Your folks really want to be engaged and have a purpose. Talk to me about how you got the employees together, it sounds like it was maybe from within. >> That's absolutely right. We have a to support employees when they bring forth these good ideas and the hackathon was one example of that. And the cool thing about the hackathons is that it leads to all these other community connections and people bring forth other ideas. So we had an in-person hackathon at our Allen office in 2019. Some of the employees there met staff from Collin College who were said, "Hey, we'd like to bring this hackathon to us." So then the employees said, "Hey, can we do a hackathon with Collin College?" It's so really it's employee driven, employee organized, supported by the company with the resources and other employees love to be part of that. And the event at Collin College brought out all those skills from the students. It was on climate change so relatively hot topic. And they did a fantastic job while they were there, but that employee engagement as you said, it comes from within. So they have the idea we have a way and a path that they can find what is needed in their community and deliver on that. And it really becomes a sense of pride and accomplishment that it wasn't a top-down mandate that you must go volunteer or paint this wall. They identified the need in the community, propose the project, get the volunteers, get the corporate support and go forth and do it. And it's really amazing to see what people do in their community. >> Well, it's incredibly rewarding and fulfilling but also very symbiotic. There's one thing that's great about the students or those that are from nine to 90, like you said, having a mentor or mentors and sponsors but it's also another thing for employees to be even more productive and proud of themselves to be able to mentor and sponsor those folks in the next generations coming up. I can imagine that employee productivity would likely increase because the employees are able to fulfill have something fulfilling or rewarding with these programs. Karen talk to me a little bit about employee productivity as a kind of a side benefit of this. >> Well, I was going to say during the hackathons I don't know how productive we are 'cause there's a lot of planning and pre-work that goes into it. But I think what happens is it's an incredible team building experience across the company. So you reaching out to executives hey would you be a judge for this event? And you know you're explaining what it is and where it is. And you're roping your coworkers into spending 12 hours with you on a Sunday. And then you're finding somebody who has access to a speaker. So you're talking to people about it it's outside your day-to-day job. And then when it's over, you're like, "Oh yeah, hey, I know somebody in that group I worked with them on the hackathon or I can go up and talk to this executive because we hung out in the hackathon room for X many hours on a Saturday." So it's another way to build those relationships which in the end make you more or help you be more productive as a whole across the company. >> Absolutely relationship building, networking, those are all critical components to having a successful career. Whether we're talking about STEAM or not. I want to unpack something Sally that you said in our remaining few minutes you talked about challenging assumptions. And I guess suppose I'm one of those ones that always assumes if I see a gen Z or they're going to know way more about how to use my phone than I do but you bring up a really good point that there are these assumptions that we need to focus on, shine the light on, address them and crack them wide open to show these folks from nine to 90 that there are so many opportunities out there, there are limitless out there I would say. >> Absolutely, it's all about breaking down those barriers. And that research I mentioned something like 43% of teenagers about kind of 16 to 21 years of age we're saying they don't feel data literate. And that assumption is incorrect so gain so making sure we include everyone in this conversation. So going as young as possible in terms of introducing people to these opportunities but making sure we don't leave any particular age group behind it's that breadth of engagement with all ages is absolutely key. But again showing there are so many different routes into tech as a career. There isn't one linear path, you can come from a different area and those skills will be hugely valid in a tech career. So absolutely challenging assumptions, changing the narrative about what a tech career looks like, I think is absolutely hugely important hence why I do that series because you want to see someone that's relatable to you, at your next level potentially, it's something you need a three steps ahead. It just makes it so important. So for me democratization of opportunity, breaking down barriers, showing that you can go around different ways and it's absolutely fine. And you know what that would probably you can learn from that experience, you can learn from mistakes all those things make a difference so don't be put off and don't let anyone hold you back and reach out for mentor. You mentioned sponsorship earlier on as well I think that's another thing as well kind of using the sphere of influence we develop in our careers and maybe through social media and can helping people along the way not just through mentorship but through active sponsorship as well. There's so many things we can do together. I think organizations are really listening to this is better embedding around DEI initiatives now than ever before and as Karen has been describing fantastic outreach into communities through hackathons, through linking up with schools. So I think we're getting a real contagion of change that's positive here. And I think the pandemic has helped. It's helped us all to kind of pause and reflect, what we stand for as people, as organizations all the way through and I'm really excited that we can really harness this energy and take it forward and really make a difference here by coming together. >> And that is such a great silver lining all of those points Sally that you mentioned. Karen, I want to wrap with you. There's great momentum within NETSCOUT I mentioned, over 2,400 employees actively so many people in the employee community actively engaging in the hackathons and the opportunities to show from nine year olds to 90 year olds the opportunities that STEAM delivers. So what's next for NETSCOUT, what can we anticipate? >> More hackathons, more focused on the digital divide. I just want to, as Sally was speaking, something occurred to me when you said it's never a clear path on the tech journey. I would love to be listening to one of those conversations 10 years from now and have somebody say, oh, when you were asked that question that you're always asked what got you on your journey? What started? I'd love to hear someone say, "Oh, I went to this hackathon once "and it is something and ever since then I got interested in it." That would be a lot of fun. I would love to see that. And for NETSCOUT we're going to continue to do what we do best. We focus on where we can make a difference, we go in wholeheartedly, we engage with volunteers and we'll just keep doing what we're doing. >> Excellent ladies what a great conversation. I love the lights that you're shining on these very important topics there. You're right, I talked to a lot of people about their career paths and they're very, zig-zaggy. Its the exception to find one, you know, that we're studying computer science or engineering, but Karen I have no doubt with the focus that NETSCOUT's putting that Sally that your organization is putting on things like hackathons, getting people out there, educated becoming data literate that no doubt that the narrative will change in the next few years that I went to this hackathon that NETSCOUT did and here I am now. So great work, very important work. I think the pandemic has brought some silver linings there to what your organizations are both doing and look forward to seeing the next generation that you're inspiring. >> Thank you so much. >> Thank you. >> Real pleasure. >> Likewise. For Sally Eaves and Karen McCloskey, I'm Lisa Martin you're watching theCUBE Conversation. (soft upbeat music)

>> Narrator: From theCUBE Studios in Palo Alto, in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in our Palo Alto Studios today, talking about a pretty interesting topic. You probably haven't heard of it, but you're going to know a lot of the attributes and it's going to sound very familiar. And that's BizOps, the concept of BizOps. We've heard about DevOps and DevSecOps and a whole bunch of ops, but BizOps is really a new twist and a new way to think about this. And we're excited to have the woman who actually wrote the book on the topic. She's Laureen Knudsen. She's a Chief Transformation Officer from Broadcom. She's also the co-author of the "Modern Business Management: Creating a Built-to-Change Organization", and a founding member of the BizOps Coalition. Laureen, great to see you. >> Great to be here. Thanks so much for having me. >> Absolutely. For people that aren't familiar with BizOps, give us kind of the quick high level. What is BizOps? >> BizOps is a new way of doing business. Just like Agile changed engineering and DevOps changed how we put things into production, BizOps is changing from soup to nuts. So from concept to cash or strategy to execution, right. There's a lot of... This has been talked about for a few years now, but this is formalizing that structure. So what do you need to do to truly have your strategy linked to your customer base? And so it's creating that umbrella over all of these other ops processes that brings it all together to tie the top to the bottom. >> Right. So, DevOps, right, fundamentally changed, the way the software gets developed. There used to be waterfall, it used to be data market's development document and then a product requirements document, then you put together a plan and you code it for six months or nine months, threw it over the Wall operations, and then hopefully they delivered. That doesn't happen anymore. And that was really set forth about 20 years ago when this kind of revolution happened on the software side. So what's been happening on the business side, and why now do they need their own ops to be pulled into this process? >> Well, sort of in the same way that things happened in the late 1990s, where certain organizations started to realize that that wasn't the most efficient way to create software and came together and created the Agile Manifesto. We've realized that there's certain things in doing business that make us much more effective and efficient. Things like bringing a data stream from the top to the bottom so every level of the organization has the data they need to run their business. Having that trust run throughout the organization, having that communication and that transparency from the strategy to the execution. You know, the global economy is just in dire straits right now, and the world is moving faster than ever. And so being able to respond to that change is vital at all levels of the organization. >> So you wrote the book years ago, I'm sure you've speaking to ton of business leaders, you know, as an author of the book, what were the biggest inhibitors to kind of the adoption of these ops and there must have been something, because why then did you found this coalition? What was the, you know, kind of the founding principle behind the coalition? >> Well, a bunch of industry leaders have come together to realize that in the same way that development needed to change in the early 2000s, really business needs to change today. And to your point, we've been talking about this for a while. Different companies are doing it better than others. And the ones that are doing this well are really heads and tails succeeding above the others. So, it's not easy though. It's not easy to change an entire organization and to change the way you do business. So, the coalition is bringing together some principles and values. We've come together to talk about how we're doing business differently and what actually works. And the main things you need to focus on in order to ensure success. >> Right. But you did it loud and proud with this declarative manifesto and then an event, actually, later this month that you're going to have to really unveil the manifesto, October 15th. I think it's 9:00, or excuse me, >> 11: 00 AM Eastern, 8:00 AM Pacific. Manifesto, right? Just the word manifesto, elicits all types of, kind of emotional response and really strong declarative statement of purpose and mission. So, why the manifesto and what's really the key pieces of the manifesto? >> You know, you need the principles that go along to help you change people, process and technology. And a lot of folks are focusing only on the technology and the data that comes from that technology and all that is key and vital to the way that you run your business differently. It's not the only piece. And so we need to focus on how do we get to bring the people along with us, how do we change our processes to be more efficient and effective. And the four values and the principles that we've created as this coalition, really help companies to do that more easily and to know they're on the right track, in the same way that the Agile principles and the values that brought out in the Agile Manifesto did. >> Right. So, I have a preview version here of the values. And I think it is really important for people to stay kind of fundamental values. 'Cause then everything builds from that and if there's ever a question, you can go back to the values as of a reference point. But just to read a few of, you know, business outcomes over individual projects, trust and collaboration over siloed teams and organizations, data-driven decisions over opinions and judgment calls, and finally, learn responded pivot over following a documented plan. And that seems so, right, so simple and so foundational and so fundamental to the way business works today. But the fact that you have to put this coalition together, and the fact that you're publishing this manifesto, tells me that the adoption really isn't where it should be. And this is really a new way to try to drive the adoption of these values. >> Absolutely. I mean, everybody seems to understand that they need to focus on their customers and that they need to focus on outcomes, but you can't just take something, you know, once you have work in progress and say, well, what's the value of this one piece of work. You have to have started at the beginning to come with the right outcome you're trying to meet, and then ensure that you're doing that all along the path to creating that and to bringing that to your customer base. It's focusing on your customers and creating the trust with your customers as well as through your organization. The data is really vital. Being able to run our businesses on real data and know the reality of the situation rather than at status reports that were created by people saying, yeah, I'm done, but there's no definition of done, right? It's fundamentally changing how we do business, which sounds easy. But as we know because of the Agile transformations that we've done and DevOps transformations that we've done, it's not as easy as it sounds. >> Right. So, why not just try to include more of the business people in the DevOps process? Why the strategy to have BizOps as kind of a standalone activity and again, to have the coalition and manifesto, that means it's super important. Can't the business people participate in the DevOps, or why has that not really been effective? >> It's really a different part of the business. And BizOps is a framework that pulls together all of these other operational pieces. So, security, operations, you know, how do you get something from engineering out to your customers, really were DevOps focuses, right? So, that's great. But running your business includes a lot more than your IT organization or your engineering teams. So this really expands out and brings in all of the rest of the business for how you sell software, how you plan, how you fund your teams, how you look at the work from that high strategic level and ensuring that you create that solid pipeline of data so that you truly know the status of any strategy in your organization. I was working with one group who had really good strategies and they had really good execution and they found that they spent over $100 million annually rolling up that data to try and understand the true status of their strategies. So companies are spending and are being very inefficient in, you know, they're spending millions of dollars on trying to do this link where if you just fundamentally change the way you do business a little bit, day to day, you can have that as a natural outcome of your processes. >> Right. 'Cause you've talked about on some of this stuff about using it as a way to do prioritization and to make sure you're not spending money places that you shouldn't. Another thing that strikes me as I go through the principles are, again, things that in 2020 should not be new information, you know, frequent changes, which was not part of the old paradigm. Trust and transparency. And I think you even tied it back into one of the articles I saw, tying trust and transparency really back to employee engagement, which then drives profitability and productivity. So I wonder if you can talk about the role of trust and in your conversations with people, as you've been kind of developing this idea over the years since the book, getting leaders to, you know, to trust their people, to do what that needs to be done rather than managing tasks, you know, manage the outcome, not manage tasks. >> Right. This is really important. Having trust in your organizations, especially today when everyone's remote, right? And in almost every company in the globe right now, most of their employees are working from their houses. You can't really do command and control well when no one is sitting in your building with you. So being able to have that trust to truly trust in your employees, you know, we spend a lot of money on all of these technical folks that we hire, and then we put people in place to try and direct them what to do on a daily basis. And so having... Building that trust within your organization, and it goes both ways, right? Employees need to trust the leadership, leadership needs to trust the employees, but it's not just from the top level to the end level, right? To the team level. It's actually every level in the middle. So this is truly pulling the pieces of work that we've done over the past few years through the entire organization. It's getting rid of what we call that frozen middle, of middle management and making sure that trust is aligned in there as well. And that the communication and transparency is working through that part of the organization. >> Right. Another principle I want to highlight is talking about the role of machine learning and artificial intelligence. Clearly, we all know, right, data's exploding, et cetera, et cetera, and we want to get the data driven decisions. But what this really calls out is that there's probably more data, both in terms of frequency and complexity, than people can really sift through, in terms of finding what they should be working on and what's important and what's not, you know, the classic separating the signal from the noise. I wonder if you can speak to a little bit about the role of machine learning and artificial intelligence, as an enhancer to productivity in this BizOps world versus a threat to people's jobs. >> Absolutely. I mean, like I said already that there's some companies spending $100 million rolling up data on things that computers can do today, even without machine learning and an AI. But when we put that into place, it really doesn't replace people any more than DevOps removed people from the organization. We automated a lot in testing yet we still have test organizations. It's just a different focus and a way of doing business. And this is no different. I'm seeing a lot of companies though start to try and throw all of their data together. And I've recently started saying that they're creating data land fields when they're attempting to create data lakes. And so you really need to understand your data that you're collecting and why you're collecting it and what outcomes you're trying to get from that data so that you can understand your business and you're not just creating, to your point, more noise. >> Right. So let's shift gears a little bit and talk about the event that's coming up on the 15th, about, you know, kind of, what is the role of the coalition? How should people get involved, what's membership all about, and then what can they expect to happen on the 15th? >> We have 10 industry leaders that have come together to author the BizOps Manifesto. And it's everyone from influencers, transformation experts, CEOs of a lot of companies or of organizations. We have people like Evan Leybourn of the Business Agility Institute and Sally Elatta from AgilityHealth, who have come to help author this and are really transformational leaders across the globe. And to get involved, you can go to bizopsmanifesto.org. and you can sign the manifesto. You can align to that if, you know, if you want to bring this into your own organization, we're happy to help work with that as well. So it's a group of industry leaders who are here to help the globe get more efficient and effective in how they do business. >> It's really interesting, right. It's not really an open source project, but it is kind of a co-opetition in terms of, you know, you're reaching out to lots of different companies and lots of different leaders to participate. They may or may not be competitive, but really this is more kind of an industry, kind of productivity thing, if you will, to bring all these people together at the coalition. Would that be accurate? >> It is accurate, but we're also looking to have competitors. I mean, we've... Competitors is an interesting thing today because there's no company just uses one company software, for example, to automate all of their pieces, right? There's all of these products that have to come together and share data today in the same way that we needed to share, you know, access to software. In the past, integrations were really difficult and now, you know, everyone's got open APIs. It's a very similar thing with data today. And so we are working with our competitors and we're working with, you know, like you said, industry leaders. We have Mik Kersten from Tasktop as part of this as well. We're looking at how we can benefit the companies of the world today, much more efficiently and effectively than we have in the past. So it is a group of people who compete with each other, maybe on a daily basis, but also have the same customers and have the need to help companies today, especially in this economy with the pandemic, right. There's a lot of companies in dire straits right now and we all need to come together as business leaders to help those companies get through this time. And anything that we can do to do that is going to benefit us all in the long run. >> Right. You know, it is really interesting co-opetition, is like you say, most companies have everybody's, you know, a lot of different products and people compete as well as having API connections and having all kinds of interesting relationships. So the lines are not so clean, like they used to be. And as we've seen with DevOps, you know, significant delta in the productivity and the responsiveness and the way software is delivered. So, sounds super exciting. We'll look forward to the event on the 15th. I give you the last word. What are you looking most forward to for the big launch in a couple of weeks? >> I'm really excited for people to give us their feedback on what they think and how this benefits them. And I'm excited to help our customers and help the, you know, the big companies of the world get through these next 18 months. I think we're all in for a bit more of a struggled time, you know, at a difficult time, and anything that we can all do to work together. So I'm looking forward to working with other industry leaders on this as well, and to the benefit of, you know, the global economy. >> Right. Well, great. Well, Laureen, thank you for giving us the one on one on BizOps. Really appreciate it. And best of luck to you and good luck to you and the team on the 15th. >> Thanks so much. >> Alrighty. Thank you. All right, she's Laureen, I'm Jeff. You're watching theCUBE. Thanks for watching. We'll see you next time. (upbeat music begins)

>>from around the globe. It's the Cube covering HP Discover Virtual experience Brought to you by HP >>Hi, welcome to the Cube's coverage of HP Discover 2020 Virtual experience. I'm Lisa Martin, and I'm pleased to welcome from scale any one of our long Time Cube alumni. We have, all specially the chief product officer at agility. Hey, Paul, welcome back to the Cube. >>Hi, Lisa. It's been a long time, and it's just wonderful to be back. Thank you. >>This is our new virtual cube that appear where everybody is very socially distant but socially connected. So since it's been a while since we've had you on and your peers from stability tell us a little bit about scale and then we'll dive into what you're doing with HP, >>Okay? Absolutely. Let me give you kind of a pop down recap of where we're at. So interestingly, we're now it 10 year old company. We actually celebrated our never anniversary last year. Um, we still have our flagship product, the Ring, which we launched originally in 2000 and 10 that is distributed file and object storage software. But about three years ago, we added a second product called Zenko, which is for multi cloud data management. We do continue to invest in the ring a lot, both on the file side and the object side. The current release now is Ring eight. The target market for this is pretty broad, but we really focus on financial services institutions. That's a big base for us. We have something like half of the world's banks, about 60% of the world service providers, a lot of government institutions. But what's been fastest growing for us now is healthcare. We have a lot of growth there in medical imaging and genomics research. And then I guess the last thing I'll add is that partners are just super important to us. We continue to certify and test with SDI Solutions. I think we have 80 of them now deployed and ready to go. But there's a real focus here now on partners like Said Era and with a Iot and Splunk VM HP East or one. So those partners are critical to our business and we just love to partner with them. >>Do you been partners with HP for quite a while? Tell me about the evolution of the partnership as you've evolved your technology. >>Yeah, absolutely. It's interesting, cause I just noted this Ah, a couple of weeks ago. The company is 10 years old. We've been partners with HP for over half of that. It's about 5.5 years. The way to think about this is that we have a worldwide OM relationship with HP for the Apollo 4000 server line. The official name for our product is HP Apollo 4000 systems with scale itty ring scalable storage. Also quite a mouthful, but very descriptive. Ah, and then we work very closely with the HP storage and big data teams. I'm very tied into the product side, talking to the product managers, but also the marketing side and very much so. On the sales side, we've had super success with them in Europe, also here in the US, and there's growing business, but also in a P J in Japan. Specifically, >>you mentioned that one of the doctors right now that's really urging a healthcare and given the fact that we are three months into a global pandemic, anything that's interesting that you want to share in terms of how skeleton is helping some of your health care customers rapidly pivot in this very unprecedented time. >>Yeah, I would say that there's a couple of very notable trends here. The 1st 1 started a few years ago. We really, honestly didn't focus so much on health care until about 2000 and 17 18. But since that time, we now have something like 40 hospital hospital systems globally using our product and notably on H P E servers. Uh, and that's to retain medical images for long term retention. These are things like digital diagnostic images. MRI's CAT scans CT scans. These hospitals are mandated to keep them for a long term right, sometimes for five years, 10 years or even page patient Lifetime. I would say the newer thing that we're seeing now just in the last year or so is genomics research. There's so much concentration now on pharmaceutical and biotechnology around genomics. That data tends to be very voluminous, you know, it can go from hundreds of terabytes and petabytes, and moreover, they need to run simulations on that to do you know, fast iteration on different drug research. We've now been applied to that problem, and a lot of times we do it with a partner or something like a fast tier one file system and then us as the archive here. But we're seeing that the popularity of that just wrote tremendously within hospitals, hospital groups and also just dedicated research for biotechnology. >>The vault. You talked about volumes there, and the volumes are growing and growing each year as his retention periods, depending on the type of data, the type of of ah, imagery, for example. But from a use case perspective, what is it that you're helping your health care customers achieve? Is it is it backup targets? Is it disaster? Recovery is speed of access All the above. >>Yeah, so where we focus in health care is really on the unstructured data. This is all the file content that they deal with, you know, in a hospital. Think about all the different medical image studies that they have, things like digital files for CAT scans and MRI's. These are becoming huge files, you know. One multi slice X ray or digital scan, for example, can be gigabytes in size and profile, and that's per patient. Now think about the number of patients and the right attention of all of that. It's a perfect use case for what we do, which is capacity optimized storage for long term retention. But we can also be used for other things. For example, backups of the electronic patient records. Those are typically stored in databases, but they need to be backed up. What we found is that we're an ideal long term backup target. So the way hospitals look at us is that they can consolidate multiple use cases, undo our ring system on HP. They can grow it over time. They could just keep adding servers, and typically what they do is they start with a single use case, what they think of as a single modality, perhaps an imaging. And then they grow over time to encompass more and more and eventually think about a comprehensive image management system within a hospital. But those are popular today. Hospitals are also starting to look at other use cases. Obviously, we mentioned genomics, but hybrid cloud is coming at them as well. >>Talk to me about that as we see growing volumes of data, different types of modalities, lots of urgent need to you, said backup data, So data protection is critical. But as as healthcare organizations move to multi cloud, how considerate Ian HP help facilitate that migration? >>Yeah, So what we've noticed is, you know, there's both a feeling that they're fast and they're slow to embrace the public clouds. But one of the things that's obvious is that from a sass perspective, software as a service, they've really embraced it. Most of the big EMR systems, the electronic medical records, are already SAS based, so they are there, and in fact they're probably already multi cloud. But on the data management side, that's where we focus. And we hear a lot of use cases that would involve taking older data from on Prem and perhaps archiving it long term in a HIPAA compliant cloud in the US, for example, for long term retention. But there are other things. For example, they may want to push some data that they've generated on Prem to a public cloud like Amazon or azure, and do some kind of computing against it. Perhaps an analytic service, some kind of image recognition or, you know, image pattern detection. Um, the 3rd 1 that we see now in hybrid cloud is their interest in having second copies of the data so that they can continue operations. Right? I think we all know that hospitals have an absolute uptime need. They need to be running 24 by seven. One of the things that's starting to happen is rather than a second physical data center. They established a second site in a public cloud on and then they stage their applications and we can help with HP. Move the data from on Prem to the public cloud to have this sort of cloud disaster recovery solution. >>So cloud here interesting topic. Do you see there that in healthcare in particular, that hospitals and healthcare organizations are getting less concerned about cloud from a security perspective and more open to it as an enabler of scale? >>I think what they've seen is that the cloud vendors have really matured in terms of providing all of the hardening that you want in terms of data, privacy and data security. You know, 10 years ago, if you looked at the cloud, you would have been extremely nervous about putting your data up there. But now all of the right principles are there in terms of multi tenancy. Ah, secure authentication based on very strong keys. Encryption of the data. One of the first healthcare customers we worked with was completely ready to do this. But then, of course, they said, the images that we store in the cloud must be infected. So we were able to work in collaboration with them, to develop encryption and actually use their own management service for encrypting those images so that our system or the HP servers don't store the keys for encryption. So I would say yes, It's a combination of the cloud's becoming super mature. Some of them are now certified and compliant for this use case on, the customers are just sort of. They passed the first step of trying it on there really to sort of go into these use cases a little bit more broadly. >>And so with that maturity of the technologies and the more the willingness on the part of the customer to try and tell me how to HP and scale a go to market together. >>Yeah, so what we do is we've really focused on specific market verticals, healthcare being one of them, but there are others. Financial services is where we've had other success with them. The way we do it is that we first start by building very specific swim lanes. In HP parlance, that helps aimed the Salesforce on where we can provide a great solution not only with Ring but perhaps with complementary software. Like I mentioned H p e store once for data protection backup. They have other partner solutions that we just love to work with. Vendors like Wicca. Iot has a wonderful fast file system that is now useful in biotech. Um, and they use a system like the ring for storing the data from their file system and the snapshots in that. But the way it's been organized is really by vertical and to go and have specialized kind of teams that understand how to sell that message. We jointly sell with them, so their teams and our teams Goto calls together. It's obviously been very virtual, but we've usually collaborated very extensively in the field working kind of air cover at the marketing level, and now one of the newer things with obviously the new way of working is lots of virtual events were not only doing a discover virtual experience, but we started doing more and more webinars, especially with HP and these other joint part >>and carries in this new virtual era where everything like, he said, This is how we're communicating now. And thankfully, we have the technology. Couple questions on that related to sales and engagement. One. What are some of the things that the sales team but the joint sales teams are hearing now from customers that might be changing requirements given the Koven situation? First >>question. Yeah, I think what one of the things we've certainly seen is that almost nothing has slowed down in these industries. I mean, we're focused on industries that seem to kind of think long term, right? I obviously healthcare. They're dealing with the current crisis as much as they can. But what we've seen is that there still planning, right, so they want to build their I T infrastructure. They're certainly thinking about how to leverage hybrid cloud. I think that's it becomes very clear that they see that as not only a way to offer new services in the future, but also to save money today. They're very interested in that right. How can they save on capital expenses and human talent is an example. I think those have been the themes for us. You know, we do have some exposure to industries that might have a little bit more, you know, sensitivity to the current climate, things like travel related services. But honestly, it's been minor. And what we're finding is that even those companies are still investing in this kind of technology, really to think about the 2 to 3 and you're being horizon and beyond. >>Have you done any any messaging, your positioning changes? I know you also in product marketing or corporate marketing that relate to customers. You know, everybody prepares for different types of disruptions or natural disasters. But now we have this invisible disruptor. Any change in your messaging, your positioning either at stability or with the partnership with HP that will help customers understand if you're not on this journey yet, why they need to be >>so, Yeah, we have looked at how we message the technology and the solution, especially in the light of the pandemic. You know, we stayed true to kind of a top level hybrid cloud data management message, but underneath the covers, what do customers care about? They care about a solution that you provide, but they also care about what they pay for it. Let's let's be honest. One of the things we've done very historically is to have a very simplified pricing model. It's based on usable protected capacity. So the user says I have a petabytes of data. That's the license fee. It's not based on how much disk they have or how many copies they want to create or how many sites they want to spread it across. So one of the things we want to do is make that a little bit more clear. Eso that's come out a bit more in our messaging in recent months. The second is that what we feel is that customers really want to know us as a company. They want to feel assured that were here, that will support them in all cases and that were available at all times. And what that's translated into is a more of a customer community focus. We are very much carrying about, you know, our customers. We see them invest in our systems today, but they also continue to expand. So we're doing things like new community portals where they can engage us in discourse. They can ask questions live. We're online. We have a lot of tips and knowledge available for them. So I would say that those are the two changes that we put in our messaging, both on pricing and on a community involved >>and where community involvement is concerned. It's even more critical now because we can't get together face to face and have conversations or meetings or conferences as chief product officer. Imagine that was a lot of what you were doing before. Tell me what it is from your perspective to engage with the community, to engage with sales and your partners during this TBD timeframe of we don't know when we're going to get back together. What do you find? It works really well for continuing continuing that engagement. >>Yeah, I think the keyword for me has just been transparency. You know, customers have always bonded to know, really, what's what's going on behind the scenes. How does the tech work? Right? What's the architecture? And I think now what we're seeing is there sort of a ramp up on that. For example, what's very important for community is for people to know what's coming right? They want to know the roadmaps. They want to be alerted to new things that are not only the next quarter, but in the next year. Right? So I think that's our focus here is to make this community a place where people can learn absolutely everything so that they can plan not only for the next year, but like we said there, they're thinking three years and beyond. So we're going to do our best to be totally transparent and be expressed as we can possibly be >>transparent entrusted. Paul, those are two great words to end on. We Thank you so much for joining us on the Cube, sharing what's new at stability and with the HP partnership. >>It's been a pleasure. Lisa. Thank you for your time. >>Likewise. For my guest, Paul Scott. Sally, I am Lisa Martin. You're watching the Cube's coverage of HP Discover 2020. The virtual experience. Yeah, yeah, yeah, yeah

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi buddy welcome to this special noob digital event where we're focusing in on data ops data ops in Acton with generous support from friends at IBM let me set up the situation here there's a real problem going on in the industry and that's that people are not getting the most out of their data data is plentiful but insights perhaps aren't what's the reason for that well it's really a pretty complicated situation for a lot of organizations there's data silos there's challenges with skill sets and lack of skills there's tons of tools out there sort of a tools brief the data pipeline is not automated the business lines oftentimes don't feel as though they own the data so that creates some real concerns around data quality and a lot of finger-point quality the opportunity here is to really operationalize the data pipeline and infuse AI into that equation and really attack their cost-cutting and revenue generation opportunities that are there in front of you think about this virtually every application this decade is going to be infused with AI if it's not it's not going to be competitive and so we have organized a panel of great practitioners to really dig in to these issues first I want to introduce Victoria Stassi with who's an industry expert in a top at Northwestern you two'll very great to see you again thanks for coming on excellent nice to see you as well and Caitlin Alfre is the director of AI a vai accelerator and also part of the peak data officers organization at IBM who has actually eaten some of it his own practice what a creep let me say it that way Caitlin great to see you again and Steve Lewis good to see you again see vice president director of management associated a bank and Thompson thanks for coming on thanks Dave make speaker alright guys so you heard my authority with in terms of operationalizing getting the most insight hey data is wonderful insights aren't but getting insight in real time is critical in this decade each of you is a sense as to where you are on that journey or Victoria your taste because you're brand new to Northwestern Mutual but you have a lot of deep expertise in in health care and manufacturing financial services but where you see just the general industry climate and we'll talk about the journeys that you are on both personally and professionally so it's all fair sure I think right now right again just me going is you need to have speech insight right so as I experienced going through many organizations are all facing the same challenges today and a lot of those pounds is hard where do my to live is my data trust meaning has a bank curated has been Clinton's visit qualified has a big a lot of that is ready what we see often happen is businesses right they know their KPIs they know their business metrics but they can't find where that data Linda Barragan asked there's abundant data disparity all over the place but it is replicated because it's not well managed it's a lot of what governance in the platform of pools that governance to speak right offer fact it organizations pay is just that piece of it I can tell you where data is I can tell you what's trusted that when you can quickly access information and bring back answers to business questions that is one answer not many answers leaving the business to question what's the right path right which is the correct answer which which way do I go at the executive level that's the biggest challenge where we want the industry to go moving forward right is one breaking that down along that information to be published quickly and to an emailing data virtualization a lot of what you see today is most businesses right it takes time to build out large warehouses at an enterprise level we need to pivot quicker so a lot of what businesses are doing is we're leaning them towards taking advantage of data virtualization allowing them to connect to these data sources right to bring that information back quickly so they don't have to replicate that information across different systems or different applications right and then to be able to provide that those answers back quickly also allowing for seamless access to from the analysts that are running running full speed right try and find the answers as quickly as they find great okay and I want to get into that sort of how news Steve let me go to you one of the things that we talked about earlier was just infusing this this mindset of a data cult and thinking about data as a service so talk a little bit about how you got started what was the starting NICUs through that sure I think the biggest thing for us there is to change that mindset from data being just for reporting or things that have happened in the past to do some insights on us and some data that already existed well we've tried to shift the mentality there is to start to use data and use that into our actual applications so that we're providing those insight in real time through the applications as they're consumed helping with customer experience helping with our personalization and an optimization of our application the way we've started down that path or kind of the journey that we're still on was to get the foundation laid birch so part of that has been making sure we have access to all that data whether it's through virtualization like vic talked about or whether it's through having more of the the data selected in a data like that that where we have all of that foundational data available as opposed to waiting for people to ask for it that's been the biggest culture shift for us is having that availability of data to be ready to be able to provide those insights as opposed to having to make the businesses or the application or asked for that day Oh Kailyn when I first met into pulp andari the idea wobble he paid up there yeah I was asking him okay where does a what's the role of that at CBO and and he mentioned a number of things but two of the things that stood out is you got to understand how data affect the monetization of your company that doesn't mean you know selling the data what role does it play and help cut cost or ink revenue or productivity or no customer service etc the other thing he said was you've got a align with the lines of piss a little sounded good and this is several years ago and IBM took it upon itself Greek its own champagne I was gonna say you know dogfooding whatever but it's not easy just flip a switch and an infuse a I and automate the data pipeline you guys had to go you know some real of pain to get there and you did you were early on you took some arrows and now you're helping your customers better on thin debt but talk about some of the use cases that where you guys have applied this obviously the biggest organization you know one of the biggest in the world the real challenge is they're sure I'm happy today you know we've been on this journey for about four years now so we stood up our first book to get office 2016 and you're right it was all about getting what data strategy offered and executed internally and we want to be very transparent because as you've mentioned you know a lot of challenges possible think differently about the value and so as we wrote that data strategy at that time about coming to enterprise and then we quickly of pivoted to see the real opportunity and value of infusing AI across all of our needs were close to your question on a couple of specific use cases I'd say you know we invested that time getting that platform built and implemented and then we were able to take advantage of that one particular example that I've been really excited about I have a practitioner on my team who's a supply chain expert and a couple of years ago he started building out supply chain solution so that we can better mitigate our risk in the event of a natural disaster like the earthquake hurricane anywhere around the world and be cuz we invest at the time and getting the date of pipelines right getting that all of that were created and cleaned and the quality of it we were able to recently in recent weeks add the really critical Kovach 19 data and deliver that out to our employees internally for their preparation purposes make that available to our nonprofit partners and now we're starting to see our first customers take advantage too with the health and well-being of their employees mine so that's you know an example I think where and I'm seeing a lot of you know my clients I work with they invest in the data and AI readiness and then they're able to take advantage of all of that work work very quickly in an agile fashion just spin up those out well I think one of the keys there who Kaelin is that you know we can talk about that in a covet 19 contact but it's that's gonna carry through that that notion of of business resiliency is it's gonna live on you know in this post pivot world isn't it absolutely I think for all of us the importance of investing in the business continuity and resiliency type work so that we know what to do in the event of either natural disaster or something beyond you know it'll be grounded in that and I think it'll only become more important for us to be able to act quickly and so the investment in those platforms and approach that we're taking and you know I see many of us taking will really be grounded in that resiliency so Vic and Steve I want to dig into this a little bit because you know we use this concept of data op we're stealing from DevOps and there are similarities but there are also differences now let's talk about the data pipeline if you think about the data pipeline as a sort of quasi linear process where you're investing data and you might be using you know tools but whether it's Kafka or you know we have a favorite who will you have and then you're transforming that that data and then you got a you know discovery you got to do some some exploration you got to figure out your metadata catalog and then you're trying to analyze that data to get some insights and then you ultimately you want to operationalize it so you know and and you could come up with your own data pipeline but generally that sort of concept is is I think well accepted there's different roles and unlike DevOps where it might be the same developer who's actually implementing security policies picking it the operations in in data ops there might be different roles and fact very often are there's data science there's may be an IT role there's data engineering there's analysts etc so Vic I wonder if you could you could talk about the challenges in in managing and automating that data pipeline applying data ops and how practitioners can overcome them yeah I would say a perfect example would be a client that I was just recently working for where we actually took a team and we built up a team using agile methodologies that framework right we're rapidly ingesting data and then proving out data's fit for purpose right so often now we talk a lot about big data and that is really where a lot of industries are going they're trying to add an enrichment to their own data sources so what they're doing is they're purchasing these third-party data sets so in doing so right you make that initial purchase but what many companies are doing today is they have no real way to vet that so they'll purchase the information they aren't going to vet it upfront they're going to bring it into an environment there it's going to take them time to understand if the data is of quality or not and by the time they do typically the sales gone and done and they're not going to ask for anything back but we were able to do it the most recent claim was use an instructure data source right bring that and ingest that with modelers using this agile team right and within two weeks we were able to bring the data in from the third-party vendor what we considered rapid prototyping right be able to profile the data understand if the data is of quality or not and then quickly figure out that you know what the data's not so in doing that we were able to then contact the vendor back tell them you know it sorry the data set up to snuff we'd like our money back we're not gonna go forward with it that's enabling businesses to be smarter with what they're doing with 30 new purchases today as many businesses right now um as much as they want to rely on their own data right they actually want to rely on cross the data from third-party sources and that's really what data Ops is allowing us to do it's allowing us to think at a broader a higher level right what to bring the information what structures can we store them in that they don't necessarily have to be modeled because a modeler is great right but if we have to take time to model all the information before we even know we want to use it that's gonna slow the process now and that's slowing the business down the business is looking for us to speed up all of our processes a lot of what we heard in the past raised that IP tends to slow us down and that's where we're trying to change that perception in the industry is no we're actually here to speed you up we have all the tools and technologies to do so and they're only getting better I would say also on data scientists right that's another piece of the pie for us if we can bring the information in and we can quickly catalog it in a metadata and burn it bring in the information in the backend data data assets right and then supply that information back to scientists gone are the days where scientists are going and asking for connections to all these different data sources waiting days for access requests to be approved just to find out that once they figure out how it with them the relationship diagram right the design looks like in that back-end database how to get to it write the code to get to it and then figure out this is not the information I need that Sally next to me right fold me the wrong information that's where the catalog comes in that's where due to absent data governance having that catalog that metadata management platform available to you they can go into a catalog without having to request access to anything quickly and within five minutes they can see the structures what if the tables look like what did the fields look like are these are these the metrics I need to bring back answers to the business that's data apps it's allowing us to speed up all of that information you know taking stuff that took months now down two weeks down two days down two hours so Steve I wonder if you could pick up on that and just help us understand what data means you we talked about earlier in our previous conversation I mentioned it upfront is this notion of you know the demand for for data access is it was through the roof and and you've gone from that to sort of more of a self-service environment where it's not IT owning the data it's really the businesses owning the data but what what is what is all this data op stuff meaning in your world sure I think it's very similar it's it's how do we enable and get access to that clicker showing the right controls showing the right processes and and building that scalability and agility and into all of it so that we're we're doing this at scale it's much more rapidly available we can discover new data separately determine if it's right or or more importantly if it's wrong similar to what what Vic described it's it's how do we enable the business to make those right decisions on whether or not they're going down the right path whether they're not the catalog is a big part of that we've also introduced a lot of frameworks around scale so just the ability to rapidly ingest data and make that available has been a key for us we've also focused on a prototyping environment so that sandbox mentality of how do we rapidly stand those up for users and and still provide some controls but have provide that ability for people to do that that exploration what we're finding is that by providing the platform and and the foundational layers that were we're getting the use cases to sort of evolve and come out of that as opposed to having the use cases prior to then go build things from we're shifting the mentality within the organization to say we don't know what we need yet let's let's start to explore that's kind of that data scientist mentality and culture it more of a way of thinking as opposed to you know an actual project or implement well I think that that cultural aspect is important of course Caitlin you guys are an AI company or at least that you know part of what you do but you know you've you for four decades maybe centuries you've been organized around different things by factoring plant but sales channel or whatever it is but-but-but-but how has the chief data officer organization within IBM been able to transform itself and and really infuse a data culture across the entire company one of the approaches you know we've taken and we talk about sort of the blueprint to drive AI transformation so that we can achieve and deliver these really high value use cases we talked about the data the technology which we've just pressed on with organizational piece of it duration are so important the change management enabling and equipping our data stewards I'll give one a civic example that I've been really excited about when we were building our platform and starting to pull districting structured unstructured pull it in our ADA stewards are spending a lot of time manually tagging and creating business metadata about that data and we identified that that was a real pain point costing us a lot of money valuable resources so we started to automate the metadata and doing that in partnership with our deep learning practitioners and some of the models that they were able to build that capability we pushed out into our contacts our product last year and one of the really exciting things for me to see is our data stewards who be so value exporters and the skills that they bring have reported that you know it's really changed the way they're able to work it's really sped up their process it's enabled them to then move on to higher value to abilities and and business benefits so they're very happy from an organizational you know completion point of view so I think there's ways to identify those use cases particularly for taste you know we drove some significant productivity savings we also really empowered and hold our data stewards we really value to make their job you know easier more efficient and and help them move on to things that they are more you know excited about doing so I think that's that you know another example of approaching taken yes so the cultural piece the people piece is key we talked a little bit about the process I want to get into a little bit into the tech Steve I wonder if you could tell us you know what's it what's the tech we have this bevy of tools I mentioned a number of them upfront you've got different data stores you've got open source pooling you've got IBM tooling what are the critical components of the technology that people should be thinking about tapping in architecture from ingestion perspective we're trying to do a lot of and a Python framework and scaleable ingestion pipe frameworks on the catalog side I think what we've done is gone with IBM PAC which provides a platform for a lot of these tools to stay integrated together so things from the discovery of data sources the cataloging the documentation of those data sources and then all the way through the actual advanced analytics and Python models and our our models and the open source ID combined with the ability to do some data prep and refinery work having that all in an integrated platform was a key to us for us that the rollout and of more of these tools in bulk as opposed to having the point solutions so that's been a big focus area for us and then on the analytic side and the web versus IDE there's a lot of different components you can go into whether it's meal soft whether it's AWS and some of the native functionalities out there you mentioned before Kafka and Anissa streams and different streaming technologies those are all the ones that are kind of in our Ketil box that we're starting to look at so and one of the keys here is we're trying to make decisions in as close to real time as possible as opposed to the business having to wait you know weeks or months and then by the time they get insights it's late and really rearview mirror so Vic your focus you know in your career has been a lot on data data quality governance master data management data from a data quality standpoint as well what are some of the key tools that you're familiar with that you've used that really have enabled you operationalize that data pipeline you know I would say I'm definitely the IBM tools I have the most experience with that also informatica though as well those are to me the two top players IBM definitely has come to the table with a suite right like Steve said cloud pack for data is really a one-stop shop so that's allowing that quick seamless access for business user versus them having to go into some of the previous versions that IBM had rolled out where you're going into different user interfaces right to find your information and that can become clunky it can add the process it can also create almost like a bad taste and if in most people's mouths because they don't want to navigate from system to system to system just to get their information so cloud pack to me definitely brings everything to the table in one in a one-stop shop type of environment in for me also though is working on the same thing and I would tell you that they haven't come up with a solution that really comes close to what IBM is done with cloud pack for data I'd be interested to see if they can bring that on the horizon but really IBM suite of tools allows for profiling follow the analytics write metadata management access to db2 warehouse on cloud those are the tools that I've worked in my past to implement as well as cloud object store to bring all that together to provide that one stop that at Northwestern right we're working right now with belieber I think calibra is a great set it pool are great garments catalog right but that's really what it's truly made for is it's a governance catalog you have to bring some other pieces to the table in order for it to serve up all the cloud pack does today which is the advanced profiling the data virtualization that cloud pack enables today the machine learning at the level where you can actually work with our and Python code and you put our notebooks inside of pack that's some of this the pieces right that are missing in some of the under vent other vendor schools today so one of the things that you're hearing here is the theme of openness others addition we've talked about a lot of tools and not IBM tools all IBM tools there there are many but but people want to use what they want to use so Kaitlin from an IBM perspective what's your commitment the openness number one but also to you know we talked a lot about cloud packs but to simplify the experience for your client well and I thank Stephen Victoria for you know speaking to their experience I really appreciate feedback and part of our approach has been to really take one the challenges that we've had I mentioned some of the capabilities that we brought forward in our cloud platform data product one being you know automating metadata generation and that was something we had to solve for our own data challenges in need so we will continue to source you know our use cases from and grounded from a practitioner perspective of what we're trying to do and solve and build and the approach we've really been taking is co-creation line and that we roll these capability about the product and work with our customers like Stephen light victorious you really solicit feedback to product route our dev teams push that out and just be very open and transparent I mean we want to deliver a seamless experience we want to do it in partnership and continue to solicit feedback and improve and roll out so no I think that will that has been our approach will continue to be and really appreciate the partnerships that we've been able to foster so we don't have a ton of time but I want to go to practitioners on the panel and ask you about key key performance indicators when I think about DevOps one of the things that we're measuring is the elapsed time the deploy applications start finished where we're measuring the amount of rework that has to be done the the quality of the deliverable what are the KPIs Victoria that are indicators of success in operationalizing date the data pipeline well I would definitely say your ability to deliver quickly right so how fast can you deliver is that is that quicker than what you've been able to do in the past right what is the user experience like right so have you been able to measure what what the amount of time was right that users are spending to bring information to the table in the past versus have you been able to reduce that time to delivery right of information business answers to business questions those are the key performance indicators to me that tell you that the suite that we've put in place today right it's providing information quickly I can get my business answers quickly but quicker than I could before and the information is accurate so being able to measure is it quality that I've been giving that I've given back or is this not is it the wrong information and yet I've got to go back to the table and find where I need to gather that from from somewhere else that to me tells us okay you know what the tools we've put in place today my teams are working quicker they're answering the questions they need to accurately that is when we know we're on the right path Steve anything you add to that I think she covered a lot of the people components the around the data quality scoring right for all the different data attributes coming up with a metric around how to measure that and and then showing that trend over time to show that it's getting better the other one that we're doing is just around overall date availability how how much data are we providing to our users and and showing that trend so when I first started you know we had somewhere in the neighborhood of 500 files that had been brought into the warehouse and and had been published and available in the neighborhood of a couple thousand fields we've grown that into weave we have thousands of cables now available so it's it's been you know hundreds of percent in scale as far as just the availability of that data how much is out there how much is is ready and available for for people to just dig in and put into their their analytics and their models and get those back into the other application so that's another key metric that we're starting to track as well so last question so I said at the top that every application is gonna need to be infused with AI this decade otherwise that application not going to be as competitive as it could be and so for those that are maybe stuck in their journey don't really know where to get started I'll start with with Caitlin and go to Victoria and then and then even bring us home what advice would you give the people that need to get going on this my advice is I think you pull the folks that are either producing or accessing your data and figure out what the rate is between I mentioned some of the data management challenges we were seeing this these processes were taking weeks and prone to error highly manual so part was ripe for AI project so identifying those use cases I think that are really causing you know the most free work and and manual effort you can move really quickly and as you build this platform out you're able to spin those up on an accelerated fashion I think identifying that and figuring out the business impact are able to drive very early on you can get going and start really seeing the value great yeah I would actually say kids I hit it on the head but I would probably add to that right is the first and foremost in my opinion right the importance around this is data governance you need to implement a data governance at an enterprise level many organizations will do it but they'll have silos of governance you really need an interface I did a government's platform that consists of a true framework of an operational model model charters right you have data domain owners data domain stewards data custodians all that needs to be defined and while that may take some work in in the beginning right the payoff down the line is that much more it's it it's allowing your business to truly own the data once they own the data and they take part in classifying the data assets for technologists and for analysts right you can start to eliminate some of the technical debt that most organizations have acquired today they can start to look at what are some of the systems that we can turn off what are some of the systems that we see valium truly build out a capability matrix we can start mapping systems right to capabilities and start to say where do we have wares or redundancy right what can we get rid of that's the first piece of it and then the second piece of it is really leveraging the tools that are out there today the IBM tools some of the other tools out there as well that enable some of the newer next-generation capabilities like unit nai right for example allowing automation for automation which right for all of us means that a lot of the analysts that are in place today they can access the information quicker they can deliver the information accurately like we've been talking about because it's been classified that pre works being done it's never too late to start but once you start that it just really acts as a domino effect to everything else where you start to see everything else fall into place all right thank you and Steve bring us on but advice for your your peers that want to get started sure I think the key for me too is like like those guys have talked about I think all everything they said is valid and accurate thing I would add is is from a starting perspective if you haven't started start right don't don't try to overthink that over plan it it started just do something and and and start the show that progress and value the use cases will come even if you think you're not there yet it's amazing once you have the national components there how some of these things start to come out of the woodwork so so it started it going may have it have that iterative approach to this and an open mindset it's encourage exploration and enablement look your organization in the eye to say why are their silos why do these things like this what are our problem what are the things getting in our way and and focus and tackle those those areas as opposed to trying to put up more rails and more boundaries and kind of encourage that silo mentality really really look at how do you how do you focus on that enablement and then the last comment would just be on scale everything should be focused on scale what you think is a one-time process today you're gonna do it again we've all been there you're gonna do it a thousand times again so prepare for that prepare forever that you're gonna do everything a thousand times and and start to instill that culture within your organization a great advice guys data bringing machine intelligence an AI to really drive insights and scaling with a cloud operating model no matter where that data live it's really great to have have three such knowledgeable practitioners Caitlyn Toria and Steve thanks so much for coming on the cube and helping support this panel all right and thank you for watching everybody now remember this panel was part of the raw material that went into a crowd chat that we hosted on May 27th Crouch at net slash data ops so go check that out this is Dave Volante for the cube thanks for watching [Music]

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hi everybody this is Dave Volante and welcome to this special digital cube presentation sponsored by IBM we're going to focus in on data op data ops in action a lot of practitioners tell us that they really have challenges operationalizing in infusing AI into the data pipeline we're going to talk to some practitioners and really understand how they're solving this problem and really pleased to bring Victoria stayshia vich who's the Global Information Systems Manager for information management at harley-davidson Vik thanks for coming to the cube great to see you wish we were face to face but really appreciate your coming on in this manner that's okay that's why technology's great right so you you are steeped in a data role at harley-davidson can you describe a little bit about what you're doing and what that role is like definitely so obviously a manager of information management >> governance at harley-davidson and what my team is charged with is building out data governance at an enterprise level as well as supporting the AI and machine learning technologies within my function right so I have a portfolio that portfolio really includes DNA I and governance and also our master data and reference data and data quality function if you're familiar with the dama wheel of course what I can tell you is that my team did an excellent job within this last year in 2019 standing up the infrastructure so those technologies right specific to governance as well as their newer more modern warehouse on cloud technologies and cloud objects tour which also included Watson Studio and Watson Explorer so many of the IBM errs of the world might hear about obviously IBM ISEE or work on it directly we stood that up in the cloud as well as db2 warehouse and cloud like I said in cloud object store we spent about the first five months of last year standing that infrastructure up working on the workflow ensuring that access security management was all set up and can within the platform and what we did the last half of the year right was really start to collect that metadata as well as the data itself and bring the metadata into our metadata repository which is rx metadata base without a tie FCE and then also bring that into our db2 warehouse on cloud environment so we were able to start with what we would consider our dealer domain for harley-davidson and bring those dimensions within to db2 warehouse on cloud which was never done before a lot of the information that we were collecting and bringing together for the analytics team lived in disparate data sources throughout the enterprise so the goal right was to stop with redundant data across the enterprise eliminate some of those disparity to source data resources right and bring it into a centralized repository for reporting okay Wow we got a lot to unpack here Victoria so but let me start with sort of the macro picture I mean years ago you see the data was this thing that had to be managed and it still does but it was a cost was largely a liability you know governance was sort of front and center sometimes you know it was the tail that wagged the value dog and then the whole Big Data movement comes in and everybody wants to be data-driven and so you saw some pretty big changes in just the way in which people looked at data they wanted to you know mine that data and make it an asset versus just a straight liability so what what are the changes that you discerned in in data and in your organization over the last let's say half a decade we to tell you the truth we started looking at access management and the ability to allow some of our users to do some rapid prototyping that they could never do before so what more and more we're seeing as far as data citizens or data scientists right or even analysts throughout most enterprises is it well they want access to the information they want it now they want speed to insight at this moment using pretty much minimal Viable Product they may not need the entire data set and they don't want to have to go through leaps and bounds right to just get access to that information or to bring that information into necessarily a centralized location so while I talk about our db2 warehouse on cloud and that's an excellent example of one we actually need to model data we know that this is data that we trust right that's going to be called upon many many times from many many analysts right there's other information out there that people are collecting because there's so much big data right there's so many ways to enrich your data within your organization for your customer reporting the people are really trying to tap into those third-party datasets so what my team has done what we're seeing right change throughout the industry is that a lot of teams and a lot of enterprises are looking at s technologists how can we enable our scientists and our analysts right the ability to access data virtually so instead of repeating right recuperating redundant data sources we're actually ambling data virtualization at harley-davidson and we've been doing that first working with our db2 warehouse on cloud and connecting to some of our other trusted versions of data warehouses that we have throughout the enterprise that being our dealer warehouse as well to enable obviously analysts to do some quick reporting without having to bring all that data together that is a big change I see the fact that we were able to tackle that that's allowed technology to get back ahead because most backup Furnish say most organizations right have given IT the bad rap wrap up it takes too long to get what we need my technologists cannot give me my data at my fingertips in a timely manner to not allow for speed to insight and answers the business questions at point of time of delivery most and we've supplied data to our analysts right they're able to calculate aggregate brief the reporting metrics to get those answers back to the business but they're a week two weeks too late the information is no longer relevant so data virtualization through data Ops is one of the ways and we've been able to speed that up and act as a catalyst for data delivery but we've also done though and I see this quite a bit is well that's excellent we still need to start classifying our information and labeling that at the system level we've seen most most enterprises right I worked at Blue Cross as well with IBM tool had the same struggle they were trying to eliminate their technology debt reduce their spend reduce the time it takes for resources working on technologies to maintain technologies they want to reduce their their IT portfolio of assets and capabilities that they license today so what do they do to do that it's time to start taking a look at what systems should be classified as essential systems versus those systems that are disparate and could be eliminated and that starts with data governance right so okay so your your main focus is on governance and you talked about real people want answers now they don't want to have to wait they don't want to go big waterfall process so what was what would you say was sort of some of the top challenges in terms of just operationalizing your data pipelining getting to the point that you are today you know I have to be quite honest um standing up the governance framework the methodology behind it right to get it data owners data stewards at a catalog established that was not necessarily the heavy lifting the heavy lifting really came with I'm setting up a brand new infrastructure in the cloud for us to be quite honest um we with IBM partnered and said you know what we're going to the cloud and these tools had never been implemented in the cloud before we were kind of the first do it so some of the struggles that we aren't they or took on and we're actually um standing up the infrastructure security and access management network pipeline access right VPN issues things of that nature I would say is some of the initial roadblocks we went through but after we overcame those challenges with the help of IBM and the patience of both the Harley and IBM team it became quite easy to roll out these technologies to other users the nice thing is right we at harley-davidson have been taking the time to educate our users today up for example we had what we call the data bytes a Lunch and Learn and so in that Lunch and Learn what we did is we took our entire GIS team our global information services team which is all of IT through these new technologies it was a form of over 250 people with our CIO and CTO on and taking them through how do we use these tools what are the purpose of schools why do we need governance to maintain these pools why is metadata management important to the organization that piece of it seems to be much easier than just our initial scanning it up so it's good enough to start letting users in well sounds like you had real sponsorship from from leadership and input from leadership and they were kind of leaning into the whole process first of all is that true and how important is that for success oh it's essential we often said when we were first standing up the tools to be quite honest is our CIO really understand what it is that were for standing up as our CIO really understand governance because we didn't have the time to really get that face-to-face interaction with our leadership so I myself made it a mandate having done this previously at Blue Cross to get in front of my CIO and my CTO and educate them on what it is we are exactly standing up and once we did that it was very easy to get at an executive steering committee as well as an executive membership Council right I'm boarded with our governance council and now they're the champions of that it's never easy that was selling governance to leadership and the ROI is never easy because it's not something that you can easily calculate it's something that has to show its return on investment over time and that means that you're bringing dashboards you're educating your CIO and CTO and how you're bringing people together how groups are now talking about solutions and technologies in a domain like environment right where you have people from at an international level we have people from Asia from Europe from China that join calls every Thursday to talk about the data quality issue specific to dealer for example what systems were using what solutions on there are on the horizon to solve them so that now instead of having people from other countries that work for Harley as well as just even within the US right creating one-off solutions that are answering the same business questions using the same data but creating multiple solutions right to solve the same problem we're now bringing them together and we're solving together and we're prioritizing those as well so that return on investment necessarily down the line you can show that is you know what instead of this printing into five projects we've now turned this into one and instead of implementing four systems we've now implemented one and guess what we have the business rules and we have the classification I to this system so that you CIO or CTO right you now go in and reference this information a glossary a user interface something that a c-level can read interpret understand quickly write dissect the information for their own need without having to take the long lengthy time to talk to a technologist about what does this information mean and how do i how do I use it you know what's interesting is take away based on what you just said is you know harley-davidson is an iconic brand cool company with fuckin motorcycles right and but you came out of an insurance background which is a regulated industry where you know governance is sort of de rigueur right I mean it's it's a table steak so how are you able that arleigh to balance the sort of tension between governance and the sort of business flexibility so there's different there's different lovers I would call them right obviously within healthcare in insurance the importance becomes compliance and risk and regulatory right they're big pushes gosh I don't want to pay millions of dollars for fines start classifying this information enabling security reducing risk all that good stuff right for Harley Davidson it was much different it was more or less we have a mission right we want to invest in our technologies yet we want to save money how do we cut down the technologies that we have today reduce our technology spend yet and able our users have access to more information in a timely manner that's not an easy that's not an easy pass right um so what we did is I took that my married governance part-time model and our time model is specific worried they're gonna tolerate an application we're going to invest in an application we're gonna migrate an application or we're gonna eliminate that so I'm talking to my CIO said you know we can use governance the classifier system help act as a catalyst when we start to implement what it is we're doing with our technologies which technologies are we going to eliminate tomorrow we as IG cannot do that unless we discuss some sort of business impact unless you look at a system and say how many users are using us what reports are essential the business teams do they need this system is this something that's critical for users today to eat is this duplicate 'iv right we have many systems that are solving the same capability that is how I sold that off my CIO and it made it important to the rest of the organization they knew we had a mandate in front of us we had to reduce technology spend and that really for me made it quite easy and talking to other technologists as well as business users on why if governance is important why it's going to help harley-davidson and their mission to save money going forward I will tell you though that the businesses of biggest value right is the fact that they now owns the data they're more likely right to use your master data management systems like I said I'm the owner of our MDM services today as well as our customer knowledge center today they're more likely to access and reference those systems if they feel that they built the rule and they own the rules in those systems so that's another big value add to write as many business users will say ok you know you think I need access to this system I don't know I'm not sure I don't know what the data looks like within it is it easily accessible is it gonna give me the reporting metrics that I need that's where governance will help them for example like our state a scientist beam using a catalog right you can browse your metadata you can look at your server your database your tables your fields understand what those mean understand the classifications the formulas within them right they're all documented in a glossary versus having to go and ask for access to six different systems throughout the enterprise hoping right that's Sally next few that told you you needed access to these systems was right just to find out that you don't need the access and hence it took you three days to get the access anyway that's why a glossary is really a catalyst a lot of that well it's really interesting what you just said about you went through essentially an application rationalization exercise which which saved your organization money that's not always easy because you know businesses even though the you know IIT may be spending money on these systems businesses don't want to give them up but you were able to use it sounds like you're able to use data to actually inform which applications you should invest in versus you know sunset as well you'd sounds like you were giving the business a real incentive to go through this exercise because they ended up as you said owning the data well then what's great right who wants pepper what's using the old power and driving a new car if they can buy the I'm sorry bull owning the old car right driving the old park if they can truly own a new car for a cheaper price nobody wants to do that I've even looked at Tesla's right I can buy a Tesla for the same prices I can buy a minivan these days I think I might buy the Tesla but what I will say is that we also use that we built out a capabilities model with our enterprise architecture team and building that capabilities model we started to bucket our technologies within those capabilities models right like AI machine learning warehouse on cloud technologies are even warehousing technologies governance technologies you know those types of classifications today integrations technologies reporting technologies by kind of grouping all those into a capabilities matrix right and was Eve it was easy for us to then start identifying alright we're the system owners for these when it comes to technologies who are the business users for these based on that right let's go talk to this team the dealer management team about access to this new profiling capability with an IBM or this new catalog with an IBM right that they can use stay versus this sharepoint excel spreadsheets they were using for their metadata management right or the profiling tools that were old you know ten years old some of our sa peoples that they were using before right let's sell them on the noodles and start migrating them that becomes pretty easy because I mean unless you're buying some really old technology when you give people a purview into those new tools and those new capabilities especially with some of the IBM's new tools we have today there the buy-in is pretty quick it's pretty easy to sell somebody on something shiny and it's much easier to use than some of the older technologies let's talk about the business impact in my understanding is you were trying to increase the improve the effectiveness of the dealers not not just go out and brute force sign up more dealers were you able to achieve that outcome and what does it meant for your business yes actually we were so right now what we did is we slipped something called a CDR and that's our consumer dealer and development repository right that's where a lot of our dealer information resides today it's actually argue ler warehouse we had some other systems that we're collecting that information Kalinin like speed for example we were able to bring all that reporting man to one location sunset some of those other technologies but then also enable for that centralized reporting layer which we've also used data virtualization to start to marry submit information to db2 warehouse on cloud for users so we're allowing basically those that want to access CDR and our db2 warehouse and called dealer information to do that within one reporting layer um in doing so we were able to create something called a dealer harmonized ID really which is our version of we have so many dealers today right and some of those dealers actually sell bytes some of those dealers sell just apparel material some of those dealers just sell parts of those dealers right can we have certain you IDs kind of a golden record mastered information if you will right bought back in reporting so that we can accurately assess the dealer performance up to two years ago right it was really hard to do that we had information spread out all over it was really hard to get a good handle on what dealers were performing and what dealers weren't because was it was tough right for our analysts to wrangle that information and bring it together it took time many times we you would get multiple answers to one business question which is never good right one one question should have one answer if it's accurate um that is what we worked on within us last year and that's where really our CEO so the value at is now we can start to act on what dealers are performing at an optimal level versus what dealers are struggling and that's allowed even our account reps or field steel fields that right to go work with those struggling dealers and start to share with them the information of you know these are what some of our stronger dealer performing dealers are doing today that is making them more affecting it inside sorry effective is selling bikes you know these are some of the best practices you can implement that's where we make right our field staff smarter and our dealers smarter we're not looking to shut down dealers we just want to educate them on how to do better well and to your point about a single version of the truth if you will the the lines of business kind of owning their own data that's critical because you're not spending all your time you know pointing at fingers trying to understand the data if the if the users own it then they own it I and so how does self-service fit in were you able to achieve you know some level of self-service how far could you and you go there we were we did use some other tools I'll be quite honest aside from just the IBM tools today that's enabled some of that self-service analytics si PSAC was one of them Alteryx is another big one that we like to that our analyst team likes to use today to wrangle and bring that data together but that really allowed for our analysts spread in our reporting teams to start to build their own derivations their transformations for reporting themselves because they're more user interface space versus going in the backend systems and having to write straight pull right sequel queries things of that nature it usually takes time then requires a deeper level of knowledge then what we'd like to allow for our analysts right to have today I can say the same thing with the data scientist scheme you know they use a lot of the R and Python coding today what we've tried to do is make sure that the tools are available so that they can do everything they need to do without us really having to touch anything and I will be quite honest we have not had to touch much of anything we have a very skilled data scientist team so I will tell you that the tools that we put in place today Watson explore some of the other tools as well they haven't that has enabled the data scientists to really quickly move do what they need to do for reporting and even in cases where maybe Watson or Explorer may not be the optimal technology right for them to use we've also allowed for them to use some of our other resources are open source resources to build some of the models that they're that they were looking to build well I'm glad you brought that up Victoria because IBM makes a big deal out of you know being open and so you're kind of confirming that you can use third-party tools and and if you like you know tool vendor ABC you can use them as part of this framework yeah it's really about TCO right so take a look at what you have today if it's giving you at least 80% of what you need for the business or for your data scientists or reporting analysts right to do what they need to do it's to me it's good enough right it's giving you what you need it's pretty hard to find anything that's exactly 100 percent it's about being open though to when you're scientists or your analysts find another reporting tool right that requires minimal maintenance or let's just say did a scientist flow that requires minimal maintenance it's free right because it's open source IBM can integrate with that and we can enable that to be a quicker way for them to do what they need to do versus telling them no right you can't use the other technologies or the other open source information out there for you today you've got to use just these spools that's pretty tough to do and I think that would shut most IT shops down pretty quick within larger enterprises because it would really act as a roadblock to allow most of our teams right to do what they need to do reporting well last question so a big part of this the data ops you know borrowing from DevOps is this continuous integration continuous improvement you know kind of ongoing MOOC raising the bar if you will what do you see going from here oh I definitely see I see a world I see a world of where we're allowing for that rapid prototyping like I was talking about earlier I see a very big change in the data industry you said it yourself right we are in the brink of big data and it's only gonna get bigger there are organizations right right now that have literally understood how much of an asset their data really is today but they're starting to sell their data ah to other of their similar people are smaller industries right similar vendors within the industry similar spaces right so they can make money off of it because data truly is an asset now the key to it that was obviously making sure that it's curated that it's cleanse that it's rusted so that when you are selling that back you can't really make money off of it but we've seen though and what I really see on the horizon is the ability to vet that data right is in the past what have you been doing the past decade or just buying big data sets we're trusting that it's you know good information we're not doing a lot of profiling at most organizations arts you're gonna pay this big top dollar you're gonna receive this third-party data set and you're not gonna be able to use it the way you need to what I see on the horizon is us being able to do that you know we're building data Lake houses if you will right we're building um really those Hadoop link environments those data lakes right where we can land information we can quickly access it we can quickly profile it with tools that it would take hours for an ALICE write a bunch of queries do to understand what the profile of that data look like we did that recently at harley-davidson we bought and some third-party data evaluated it quickly through our agile scrum team right within a week we determined that the data was not as good as it as the vendor selling it right pretty much sold it to be and so we told the vendor we want our money back the data is not what we thought it would be please take the data sets back now that's just one use case right but to me that was golden it's a way to save money and start betting the data that we're buying otherwise what I would see in the past or what I've seen in the past is many organizations are just buying up big third-party data sets and just saying okay now it's good enough we think that you know just because it comes from the motorcycle and council right for motorcycles and operation Council then it's good enough it may not be it's up to us to start vetting that and that's where technology is going to change data is going to change analytics is going to change is a great example you're really in the cutting edge of this whole data op trend really appreciate you coming on the cube and sharing your insights and there's more in the crowd chatter crowd chatter off the Thank You Victoria for coming on the cube well thank you Dave nice to meet you it was a pleasure speaking with you yeah really a pleasure was all ours and thank you for watching everybody as I say crowd chatting at flash data op or more detail more Q&A this is Dave Volante for the cube keep it right there but right back right after this short break [Music]

>>  Welcome back to theCUBE everybody. This is a special digital presentation sponsored by Oracle Consulting. We go out to the events, we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of Oracle Consulting. Stephanie Trunzo is here. She is the head of transformation and offerings at Oracle consulting North America. Stephanie, good to see you. >> Yeah, good to see you. >> Okay so we talked about sort of the mission of Oracle Consulting, now let's get into it and talk about some of what the customers are seeing. There's this theme in the industry that Gartner brought up about Bimodal IT and you guys are talking about Trimodal IT, so what is that all about? >> Well, two wasn't good enough so we had to add a third. (laughs) So Bimodal IT, two speed IT, the idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that have to be sources of truth. They're often slow to change. There's a lot of rigger around transforming those systems of record. And then on the second side, on the Bimodal side, there are the systems of interaction or systems of engagement, they're sometimes called. And those systems are things like the applications where there's users, customers at the other end. And they need to move at the speed of business. And so the idea of Bimodal IT and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time? There's complications in the processes, the tools, and certainly in the budget. And at the same time, there's kind of looming out there, this threat almost, that if you aren't in the AI NML data driven world yet, you're going to fall behind. And so our clients are struggling with the fact that they have not yet successfully addressed Bimodal IT, but still have to figure out how to get into this AI space. So our third system, hence Trimodal IT is the systems of intelligence. And that's what we've added. >> So, to make sure I've got the Bimodal right, >> Yeah sure. >> Is that, You've got people who are handling the systems of record you said. And so they have knowledge, they've got tribal knowledge, deep expertise, which may not be widespread. Kids coming out of school don't necessarily have that same expertise. And then there's sort of the systems of engagement kind of the new fun stuff. Did customers in your sense, buy into that? Or did they try to sort of cross-pollinate, as practitioners? >> Yeah they do buy into it. But they're really still struggling with the idea of Bimodal IT without even getting into the third system yet. So they are buying into it. The challenge, it's not even really about buying into it. It's addressing the challenge, because they have to overcome this legacy stuff, that they have in their system in order to address the speed of business. >> So the third piece, obviously relates to machine intelligence, AI, NML. It seems like that type of capability would apply to both systems of record and systems of engagement. Is that how you're looking at it? >> Yes, and so the Trimodal IT concept is kind of three different systems and how they interlock and relate to one another. If you think about systems of record, the currency, so to speak, for system of record are processes. If you think about the currency for systems of interaction it's the people, it's the users, it's the humans. And the currency for the system of intelligence is data, to your point. So when you're talking about systems of intelligence, collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward. >> And that's the common thread between all three. And it just seems to me, that is ultimately the underpinning of modernization. I wonder what your customers, how do they view, and how do you view modernization? >> So the awesome thing about being at Oracle is data is our DNA. That's where Oracle started from, that's where we still are today is data underpins everything we do, all of the technology that we build is built on the understanding that it must be data-driven. And so when we're looking at all three of those systems and you're looking at it from an Oracle perspective, data is at the heart of even systems of record. Even systems of interaction, not only the systems of intelligence. When our clients are looking at modernization, they are trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they are getting intelligence and insights out of their data. They're not just unlocking it. They're not just moving workloads in a lift and shift kind of model. They're doing it, because they want to serve the ultimate outcome that they get smarter as a business. >> So data is kind of like raw material, the AI or machine intelligence allows you to take data and create insights, if you will. And then cloud gives you scale and agility and all of those things. So Cloud's again another fundamental piece of, just from an infrastructure standpoint, and I think you guys define Cloud as sort of an experience, not a place. So it includes the on prime workloads, of course. So, talk about Cloud. Customers want to go from where they are today, to some outcome, some end point. And they don't want to spend a zillion dollars. And they don't want to disrupt their business. They are going to have to make investments, clearly. How do they get from point A to point B on that Cloud journey? >> So we've built something called a Cloud evolution framework. That Cloud evolution framework has several different phases and stages. And it's intended to be a skeleton to have that conversation with clients. Are you thinking about all of the things that you need to consider to make a healthy decision that has a real road map behind it. To your point on budget, and this is part of the Trimodal IT conversation is. They're struggling, I've talked to so many CIOs who are struggling to figure out. I right now am spending, 90% of my spend is on maintenance of systems versus on innovation. So how do I shift that spending story to something that is actually going to move the needle on getting the business ahead. That's going to serve my stakeholders, who are the lines of business, in a way that is not additive to my budget. But actually a shift of the budget. So we're looking at it from a Cloud perspective, helping our clients make that monetary shift. Make the shift of the budget where they're self-financing their own innovation by getting smarter and faster on moving their workloads to the Cloud. >> That's interesting, I want to come back to that self-financing. It reminds me of Y2K where you had all these activities going on, and the boom times. And then people wanted to go through an application rationalization exercise so they could self-fund really the innovation. >> Stephanie: Right. >> And when you're in the tenth year of a boom cycle, here. I wonder if there are similar things going on. Is that where the self-funding comes in? >> That's exactly it. So, I kind of use this example as a way of helping people consume and understand this. Marie Kondo, KonMari method is a popular, she wrote a best-selling book. She's on Netflix. The premise of her concept is helping to declutter your life. And her premise is you should hold each object in your hand and say, "Does it bring me joy?" And if it does, I'm going to keep it. And if it doesn't, I'm going to thank it for it's service, and get rid of it. And so we're talking to our clients about something very similar. You said, rationalization exercise and it's precisely the same thing. We're kind of using the KonMari method, if you will, to help our clients make those determinations. What are the things that they still need? What are the things that they can de-commission? What are the things that can stay where they are? And you don't have to do anything with, because they are serving the purpose just fine. >> Yeah, we're kind of hoarders by nature, and creatures of habit, so you have all these applications that nobody's using, but you're still spending maintenance and-- >> Stephanie: Correct. >> Keeping them up and it may not be delivering, and many aren't delivering value to the organization. So you want to double down on those that do. You guys use this concept and other do as well, of the autonomous enterprise. You have the autonomous database, I wonder if we could drill into that. Get passed the buzz words. What is the autonomous enterprise and what is Oracle's fit there? >> Yeah, I think one of the big misconceptions when people here autonomous, is that they think it means without people. And that's not right. (laughs) So, autonomous means that you're helping elevate all the parts of the system to their highest value. Which means, you don't need to worry about security patches. You don't need to worry about repairing things on the database. Those kinds of autonomous things is the technology helping heal and serve itself. That doesn't mean you don't need people anymore. What it means is two things. You need the experts that can help make sure that you're optimizing the value you get out of the autonomous tooling, but it also means that the humans are now freed up to do different kinds of high value work. So, an autonomous enterprise would be one where they're really sort of self-actualized. In the sense that their technology is feeding itself. It's getting smarter, and they're getting insights out of that, so that the people in their business are as valuable as they can be, leveraging the insights from the technology. >> So I can see how that trickles into IT. No questions about it. Can the autonomous IT organization trickle into the autonomous enterprise? And I mean I know it's sort of early days, but how do you see that shaping up? >> So, these kind of transformations, I believe are fundamentally across the whole company. And this is true at Oracle as well. We have something called Oracle@Oracle. And it's about drinking our own champagne and applying our own technology in house. So it's not just in an IT organization capacity. It's across HR, Procurement, Legal, every supporting function you can imagine. So that cultural change bleeds out across the entire body of the company. And I believe fully that if you're going after something like an AI mission or an autonomous enterprise state, which is an evolution that you need to involve everyone in the company in different roles. >> So what's that future state look like? >> I think the future state looks like a place where you're not just getting incremental gains on business processes or tasks that already exist. You're fundamentally seeing shifts in the way the business runs itself, as a result of the technology learning and getting smarter. And the people who are benefiting from that technology changing the way they operate in the company as well. >> So you mentioned the sort of decluttering example before, which I love, I'm getting that book. And are there other examples that inspire you? >> There are. So there was an anecdote, a client told me this story, which is a fantastic story, kind of triggered a thought for me. Told a story about a guy who was retiring. And at his retirement dinner, he told a story that 30 years ago when he started at the company. He remembers his dad teaching him, how to use the application that he then spent his entire career building and maintaining. As I heard that story, and they jokingly said at this point, our only solution is to get him out of retirement or find his son. (laughs) I thought about that, and I thought about 23 and me. You know 23 and me? >> Yes. >> So it's a DNA testing, tells you your heritage, lineage. And we're kind of at a state now, where a lot of our enterprise clients legitimately have these systems of record applications that are generations old, human generations old. So getting into the weeds on what that looks like, I've been telling clients pretty often lately. Institutional knowledge is the enemy, right? It's the enemy of the autonomous enterprise. If you have a challenge where you keep referring to the same name (laughs). If Bob leaves, we're in big trouble. If Sally isn't here anymore, that's a trigger for you to know that that's something you need to pay attention to. Because that institutional knowledge is not getting built into your technology. >> So what do you guys do? Do you put some kind of abstraction layer around that system of record, so that it can be automated? Is that part of what you do? >> Sure. So we're looking at, there's a couple different ways you can go about it. So you can look at the systems of record as a partial move that you do over time to the Cloud. And so you have to be pretty smart about the pattern and how you do that. Moving the workloads, kind of whole, will give you a little bit of that self-financing ability to dig in deeper and start transforming them. >> Okay, Trimodal IT. We'll be watching. (laughs) All right, Stephanie, thanks so much. It was great to see you. >> Absolutely, thanks. >> And thank you for watching. You're watching theCUBE at the special digital presentation. We'll be right back after this short break. (upbeat electronic music)

from Chicago it's the cube covering Oracle transformation day 2020 not to you by Oracle consulting welcome back to the queue of everybody this is a special digital presentation sponsored by Oracle consulting we go out to the events we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of or consulting Stephanie trunzo is here she's the head of transformation and offerings at or consulting North America Stephanie good to see you yeah good to see you okay so we talked about sort of the mission of Oracle consulting now let's get into it and talk about what some of the customers are seeing there's this you know theme in the industry the Gartner brought up about bimodal lights yeah you guys are talking about trimodal eyes yeah so what is that all about well ii wasn't good enough so we had a third so bimodal IT two-speed IT the idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that are have to be sources of truth they're often slow to change there's a lot of rigor around transforming those systems of record and then on the the second side on the bimodal side there are the systems of interaction or systems of engagement they're sometimes called and those systems are things like the applications where there's users customers at the other end and they need to move at the speed of business and so the idea of bimodal IT and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time there's complications in the processes the tools and certainly in the budget and at the same time there's kind of looming out there this you know threat almost that if you aren't in the a IML data-driven world yet you're going to fall behind and so our clients are struggling with the fact that they have not yet successfully addressed by modal IT but still have to figure out how to get into this AI space so our third system hence trimodal IT as the systems of intelligence and that's what we've added so should I get the bimodal right yes that you know people that are handling the the systems of record you said hmm and so they have knowledge they got you know tribal knowledge yes DJ BIA which may not be you know widespread it's not kids kids coming out of school don't necessarily have that that same expertise and then there's sort of the systems of engagement kind of the new fun stuff did customers in your sense buy into that or did they try to sort of cross pollinate as practitioners yeah they they do buy into it but they're really alright they're still struggling with the idea of bimodal IT without even getting into the third system yet and so they are buying into it the challenge I don't it's not even really about buying into it it's addressing the challenge because they have to overcome this legacy stuff that they have in their system in order to address the speed of business so the third piece obviously relates to machine intelligence AI nml it seems like that type of capability would apply to both systems of record and systems of engagement is that is that how you're looking at yes and so the trimodal IT concept is kind of three different systems and how they interlock and relate to one another if you think about systems of record the currency so to speak for systems of record or processes if you think about the currency for systems of interaction it's the people it's the users it's the humans and this is the currency for the system of intelligence is data to your point so when you're talking about systems of intelligence collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward and that's the common thread between you know all three and it just seems to me that is ultimately the underpinning of modernization I wonder what do your customers how do they view and how do you view modernization so the awesome thing about being at Oracle is data is our DNA that's where Oracle started from that's where we still are today is data underpins everything we do all of the technology that we build is built on the understanding that it must be data driven and so when we're looking at all three of those systems and you're looking at it from an Oracle perspective data is at the heart of even system a record of even systems of interaction not only the systems of intelligence when our clients are looking at modernization they're trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they're getting intelligence and insights out of their data they're not just unlocking it they're not just moving workloads and a lift and shift kind of model they're doing it because they want to serve the ultimate outcome that they get smarter as a business so data is kind of like raw material the AI or machine intelligence provides it allows you to take data and create insights if you will and then cloud gives you scale and agility and all those things so so clouds again another fundamental piece of just from an infrastructure standpoint and I think you guys define cloud as sort of an experience not a place so includes the on-prem workloads of course so talk about cloud customers want to go from where they are today to somehow become some ending point and they don't want to spend a zillion dollars and they don't want to disrupt their business they're gonna have to make investments clearly how do they get from point A to point B on that cloud journey so we've built something called a cloud evolution framework that cloud evolution framework has several different phases and stages and it's intended to be kind of a skeleton to have that conversation with clients are you thinking about all of the things you need to consider to make a healthy decision that has a real roadmap behind it to your point on budget and this is part of the trimodal IT conversation is there struggling I've talked to so many CIOs who are struggling to figure out I right now I'm spending you know 90% of my spend is on maintenance of systems versus on innovation so how do I shift that spending story to something that's actually going to move the needle on getting the business ahead that's gonna serve my stakeholders who are the lines of business in a way that is not additive to my budget but actually a shift of the budget and so we're looking at from a cloud perspective helping our clients make that monetary shift make the shift of the budget where they're self financing their own innovation by getting smarter and faster on moving their workloads to the cloud it's a - I want to come back to that self financing via y2k where you had all these activities going on in the boom times and then people wanted to go through an application rationalization exercise yes it could self fund really the innovation right and we're in a tenth year of a boom cycle here I wonder are there similar things going on is that where the self funding comes in that's exactly it so you know I kind of used this example as a way of helping people consume and understand this Marie Kondo konmari method is a popular she wrote a best-selling book she's on Netflix the premise of her concept is helping to declutter your life and her premises you should hold each object in your hand and say does it bring me joy and if it does I'm going to keep it and if it doesn't I'm gonna thank it for its service and get rid of it and so we're talking to our clients about something very similar you said rationalization exercise and it's precisely the same thing we're kind of using the konmari method if you will to help our clients make those determinations what are the things that they still need what are the things that they can decommission what are the things that can stay where they are and you don't have to do anything with because they're serving the purpose just fine yeah we're kind of hoarders by nature in creature habit so you have all these applications that nobody's using but you're still spending maintenance and correct keeping them up and and they may not be delivering and in problem any aren't delivering value for the organization so you want to double down on those that do you guys use this concept and others do as well of the autonomous enterprise you have autonomous database I wonder if we could you know drill into that get past the buzz words what is the autonomous enterprise and and what's Oracle's fit there yeah I think one of the big misconceptions when people hear autonomous is that they think it means without people and that's not right so autonomous means that you're helping elevate all the parts of the system to their highest value which means you don't need to worry about security patches you don't need to worry about repairing things on the the database those kinds of autonomous things is is the technology helping heal and serve itself that doesn't mean you don't need people anymore what it means is two things you need the experts that can help make sure that you're optimizing the value you get out of autonomous tooling but it also means that the humans are now freed up to do different kinds of high-value work so an autonomous enterprise would be one where they're really sort of self actualized in the sense that their technology is feeding itself it's getting smarter and they're getting insights out of that so that the people in their business are as valuable as they can be leveraging the insights from the technology so I can see how that trickles into IT no question about it can can the autonomous IT organization trickle into the autonomous enterprise and I mean I know it's early days but how do you see that you know shaping up so the these kinds of transformations I believe are fundamentally across the whole company and and this is true at Oracle as well we have we have something called Oracle at Oracle and it's about drinking our own champagne and applying our own technology in-house so it's not just in an IT organization capacity its across you know HR procurement legal every supporting function that you can imagine so that cultural change bleeds out across the entire body of the company and I believe fully that if you're going after something like an AI mission or an autonomous enterprise you know state which is an evolution that you need to involve everyone in the company in different roles so what's that future state look like I think the future state looks like a place where you're not just getting incremental gains on business processes or tasks that already exist you're fundamentally seeing shifts and the way the business runs itself as a result of the technology learning and getting smarter and the people who are benefiting from that technology changing the way they operate in the company as well so you mentioned the hood decluttering example yeah which I love are there other examples that inspire you there are so I there was an anecdote a client told me this story which is a fantastic story kind of triggered a thought for me a told a story about a guy who was retiring at his retirement dinner he told a story that thirty years ago when he'd started at the company he remembers his dad teaching him how to use the application that he then spent his entire career building and maintaining as I heard that story and they jokingly said at this point our only solution is to get him out of retirement or find his son I thought about that and I thought about 23andme have you know yes so it's a you know kind of DNA testing tells you your heritage lineage and we're kind of at a state now where a lot of our enterprise clients legitimately have these systems of record applications that are generations old human generations old so getting into the weeds on what that looks like I've been telling clients pretty often lately institutional knowledge is the enemy right if and it's the enemy of the autonomous enterprise if you have if you have a challenge where you keep referring to the same name you know if Bob leaves we're in big trouble if Sally isn't here anymore that's a trigger for you to know that that's something you need to pay attention to because that institutional knowledge is not getting built into your your technology so what do you guys do you put some kind of abstraction layer around that system of Records so that it can be automated does that part of sure so so we are looking at there's a couple different ways you can go about it so you can look at the systems of record as a partial move that you do over time to the cloud and so you have to be pretty smart about the pattern and how you do that moving think the workloads kind of whole will give you a little bit of that self financing ability to dig in deeper and start transforming them ok trimodal IT will be watching hey Stephanie thanks so much it's great yeah absolutely Thanks thank you for watching you watching the queue at this special digital presentation we'll be right back right after this short break

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Good afternoon everyone and welcome back to the cubes live coverage of Microsoft ignite 26,000 people here at this conference at the orange County convention center. I'm your host, Rebecca Knight, alongside my cohost Stu Miniman. We are joined by Seth Juarez. He is the cloud developer advocate at Microsoft. Thank you so much for coming on the show. >>Glad to be here. You have such a lovely sad and you're lovely people. We just met up. You don't know any better? No. Well maybe after after the end of the 15 minutes we'll have another discussion. >>You're starting off on the right foot, so tell us a little bit about what you do. You're also a host on channel nine tell us about your role as a, as a cloud developer. >>So a cloud advocate's job is primarily to help developers be successful on Azure. My particular expertise lies in AI and machine learning and so my job is to help developers be successful with AI in the cloud, whether it be developers, data scientists, machine learning engineers or whatever it is that people call it nowadays. Because you know how the titles change a lot, but my job is to help them be successful and sometimes what's interesting is that sometimes our customers can't find success in the cloud. That's actually a win for me too because then I have a deep integration with the product group and my job is to help them understand from a customer perspective what it is they need and why. So I'm like the ombudsman so to speak because the product groups are the product groups. I don't report up to them. So I usually go in there and I'm like, Hey, I don't report to any of you, but this is what the customers are saying. >>We are very keen on being customer centered and that's why I do what I do. >> Seth, I have to imagine when you're dealing with customers, some of that skills gap and learning is something that they need to deal with. You know, we've been hearing for a long time, you know, there's not enough data scientists, you know, we need to learn these environments. Satya Nadella spent a lot of time talking about the citizen developers out there. So you know H bring us inside the customers you're talking to, you know, kind of, where do you usually start and you know, how do they pull the right people in there or are they bringing in outside people a little bit? Great organization, great question. It turns out that for us at Microsoft we have our product groups and then right outside we have our advocates that are very closely aligned to the product groups. >>And so anytime we do have an interaction with a customer, it's for the benefit of all the other customers. And so I meet with a lot of customers and I don't, I'm to get to talk about them too much. But the thing is I go in there, I see what they're doing. For example, one time I went to the touring Institute in the UK. I went in there and because I'm not there to sell, I'm there to figure out like what are you trying to do and does this actually match up? It's a very different kind of conversation and they'd tell me about what they're working on. I tell them about how we can help them and then they tell me where the gaps are or where they're very excited and I take both of those pieces of feedback to the, to the product group and they, they just love being able to have someone on the ground to talk to people because sometimes you know, when work on stuff you get a little siloed and it's good to have an ombudsman so to speak, to make sure that we're doing the right thing for our customers. >>As somebody that works on AI. You must've been geeking out working, working with the Turing Institute though. Oh yeah. Those people are absolutely wonderful and it was like as I was walking in, a little giddy, but the problems that they're facing in AI are very similar. The problems that people at the other people doing and that are in big organizations, other organizations are trying to onboard to AI and try to figure out, everyone says I need to be using this hammer and they're trying to hammer some screws in with the hammer. So it's good to figure out when it's appropriate to use AI and when it isn't. And I also have customers with that >>and I'm sure the answer is it depends in terms of when it's appropriate, but do you have any sort of broad brush advice for helping an organization determine is is this a job for AI? Absolutely. >>That's uh, it's a question I get often and developers, we have this thing called the smell that tells us if a code smell, we have a code smell tells us, maybe we should refactor, maybe we should. For me, there's this AI smell where if you can't precisely figure out the series of steps to execute an algorithm and you're having a hard time writing code, or for example, if every week you need to change your if L statements or if you're changing numbers from 0.5 to 0.7 and now it works, that's the smell that you should think about using AI or machine learning, right? There's also a set of a class of algorithms that, for example, AI, it's not that we've solved, solved them, but they're pretty much solved. Like for example, detecting what's in an image, understanding sentiment and text, right? Those kinds of problems we have solutions for that are just done. >>But if you have a code smell where you have a lot of data and you don't want to write an algorithm to solve that problem, machine learning and AI might be the solution. Alright, a lot of announcements this week. Uh, any of the highlights for from your area. We last year, AI was mentioned specifically many times now with you know, autonomous systems and you know it feels like AI is in there not necessarily just you know, rubbing AI on everything. >> I think it's because we have such a good solution for people building custom machine learning that now it's time to talk about the things you can do with it. So we're talking about autonomous systems. It's because it's based upon the foundation of the AI that we've already built. We released something called Azure machine learning, a set of tools called in a studio where you can do end and machine learning. >>Because what what's happening is most data scientists nowadays, and I'm guilty of this myself, we put stuff in things called Jupiter notebooks. We release models, we email them to each other, we're emailing Python files and that's kinda like how programming was in 1995 and now we're doing is we're building a set of tools to allow machine learning developers to go end to end, be able to see how data scientists are working and et cetera. For example, let's just say you're a data scientist. Bill. Did an awesome job, but then he goes somewhere else and Sally who was absolutely amazing, comes in and now she's the data scientist. Usually Sally starts from zero and all of the stuff that bill did is lost with Azure machine learning. You're able to see all of your experiments, see what bill tried, see what he learned and Sally can pick right up and go on. And that's just doing the experiments. Now if you want to get machine learning models into production, we also have the ability to take these models, version them, put them into a CIC, D similar process with Azure dev ops and machine learning. So you can go from data all the way to machine learning in production very easily, very quickly and in a team environment, you know? And that's what I'm excited about mostly. >>So at a time when AI and big and technology companies in general are under fire and not, Oh considered to not always have their users best interests at heart. I'd like you to talk about the Microsoft approach to ethical AI and responsible AI. >>Yeah, I was a part of the keynote. Scott Hanselman is a very famous dab and he did a keynote and I got to form part of it and one of the things that we're very careful even on a dumb demo or where he was like doing rock paper, scissors. I said, and Scott, we were watching you with your permission to see like what sequence of throws you were doing. We believe that through and through all the way we will never use our customers' data to enhance any of our models. In fact, there was a time when we were doing like a machine learning model for NLP and I saw the email thread and it's like we don't have language food. I don't remember what it was. We don't have enough language food. Let's pay some people to ethically source this particular language data. We will never use any of our customer's data and I've had this question asked a lot. >>Like for example, our cognitive services which have built in AI, we will never use any of our customer's data to build that neither. For example, if we have, for example, we have a custom vision where you upload your own pictures, those are your pictures. We're never going to use them for anything. And anything that we do, there's always consent and we want to make sure that everyone understands that AI is a powerful tool, but it also needs to be used ethically. And that's just on how we use data for people that are our customers. We also have tools inside of Azure machine learning to get them to use AI. Ethically. We have tools to explain models. So for example, if you very gender does the model changes prediction or if you've very class or race, is your model being a little iffy? We allow, we have those tools and Azure machine learning, so our customers can also be ethical with the AI they build on our platform. So we have ethics built into how we build our models and we have ethics build into how our customers can build their models too, which is to me very. >>And is that a selling point? Are customers gravitating? I mean we've talked a lot about it on the show. About the, the trust that customers have in Microsoft and the image that Microsoft has in the industry right now. But the idea that it is also trying to perpetuate this idea of making everyone else more ethical. Do you think that that is one of the reasons customers are gravitate? >>I hope so. And as far as a selling point, I absolutely think it's a selling point, but we've just released it and so I'm going to go out there and evangelize the fact that not only are we as tickle with what we do in AI, but we want our customers to be ethical as well. Because you know, trust pays, as Satya said in his keynote, tra trust the enhancer in the exponent that allows tech intensity to actually be tech intensity. And we believe that through and through not only do believe it for ourselves, but we want our customers to also believe it and see the benefits of having trust with our customers. One of the things we, we talked to Scott Hanselman a little bit yesterday about that demo is the Microsoft of today isn't just use all the Microsoft products, right? To allow you to use, you know, any tool, any platform, you know, your own environment, uh, to tell us how that, that, that plays into your world. >>It's, you know, like in my opinion, and I don't know if it's the official opinion, but we are in the business of renting computer cycles. We don't care how you use them, just come into our house and use them. You wanna use Java. We've recently announced a tons of things with spraying. We're become an open JDK contributor. You know, one of my colleagues, we're very hard on that. I work primarily in Python because it's machine learning. I have a friend might call a friend and colleague, David Smith who works in our, I have other colleagues that work in a number of different languages. We don't care. What we are doing is we're trying to empower every organization and every person on the planet to achieve more where they are, how they are, and hopefully bring a little bit of of it to our cloud. >>What are you doing that, that's really exciting to you right now? I know you're doing a new.net library. Any other projects that are sparking your end? >>Yeah, so next week I'm going to France and this is before anyone's going to see this and there is a, there is a company, I think it's called surf, I'll have to look it up and we'll put it in the notes, but they are basically trying to use AI to be more environmentally conscious and they're taking pictures of trash and rivers and they're using AI to figure out where it's coming from so they can clean up environment. I get to go over there and see what they're doing, see how I can help them improvement and promote this kind of ethical way of doing AI. We also do stuff with snow leopards. I was watching some Netflix thing with my kids and we were watching snow leopards and there was like two of them. Like this is impressive because as I'm watching this with my kids, I'm like, Hey we are at Microsoft, we're helping this population, you know, perpetuate with AI. >>And so those are the things it's actually a had had I've seen on TV is, you know, rather than spending thousands of hours of people out there, the AI can identify the shape, um, you know, through the cameras. So they're on a, I love that powerful story to explain some of those pieces as opposed to it. It's tough to get the nuance of what's happening here. Absolutely. With this technology, these models are incredibly easy to build on our platform. And, and I and I st fairly easy to build with what you have. We love people use TensorFlow, use TensorFlow, people use pie torch. That's great cafe on it. Whatever you want to use. We are happy to let you use a rent out our computer cycles because we want you to be successful. Maybe speak a little bit of that when you talk about, you know, the, the cloud, one of the things is to democratize, uh, availability of this. >>There's usually free tiers out there, especially in the emerging areas. Uh, you know, how, how is Microsoft helping to get that, that compute and that world technology to people that might not have had it in the past? I was in, I was in Peru a number of years ago and I and I had a discussion with someone on the channel nine show and it was absolutely imp. Like I under suddenly understood the value of this. He said, Seth, if I wanted to do a startup here in Peru, right, and it was a capital Peru, like a very industrialized city, I would have to buy a server. It would come from California on a boat. It would take a couple of months to get here and then it would be in a warehouse for another month as it goes through customs. And then I would have to put it into a building that has a C and then I could start now sat with a click of a button. >>I can provision an entire cluster of machines on Azure and start right now. That's what, that's what the cloud is doing in places like Peru and places that maybe don't have a lot of infrastructure. Now infrastructure is for everyone and maybe someone even in the United States, you know, in a rural area that doesn't, they can start up their own business right now anywhere. And it's not just because it's Peru, it's not just because it's some other place that's becoming industrialized. It's everywhere. Because any kid with a dream can spin up an app service and have a website done in like five minutes. >>So what does this mean? I mean, as you said, any, any kid, any person or rural area, any developing country, what does this mean in five or 10 years from now in terms of the future of commerce and work and business? >>Honestly, some people feel like computers are art, stealing, you know, human engineering. I think they are really augmenting it. Like for example, I don't have to, if I want to know something for her. Back when, when I was a kid, I had to, if I want to know something, sometimes I had to go without knowing where like I guess we'll never know. Right? And then five years later we're like, okay, we found out it was that a character on that show, you know? And now we just look at our phone. It's like, Oh, you were wrong. And I like not knowing that I'm wrong for a lot longer, you know what I'm saying? But nowadays with our, with our phones and with other devices, we have information readily available so that we can make appropriate response, appropriate answers to questions that we have. AI is going to help us with that by augmenting human ingenuity, by looking at the underlying structure. >>We can't, for example, if you look at, if you look at an Excel spreadsheet, if it's like five rows and maybe five columns, you and I as humans can look at and see a trend. But what if it's 10 million rows and 5,000 columns? Our ingenuity has been stretched too far, but with computers now we can aggregate, we can do some machine learning models, and then we can see the patterns that the computer found aggregated, and now we can make the decisions we could make with five columns, five rows, but it's not taking our jobs. It's augmenting our capacity to do the right thing. >>Excellent. We'll assess that. Thank you so much for coming on the Cuba. Really fun conversation. >>Glad to be here. Thanks for having me. >>Alright, I'm Rebecca Knight for Stu minimun. Stay tuned for more of the cubes live coverage of Microsoft ignite.

>> Is and who we are today as as a country, as a universe. >> Narrator: Congratulations Reggie Jackson, (inspirational music) you are a CUBE alumni. (upbeat music) >> Announcer: Live from Las Vegas it's theCUBE covering Splunk.Conf19. Brought to you by Splunk. >> Okay, welcome back everyone it's theCUBE's live coverage here in Las Vegas for Splunk.Conf19. I am John Furrier host of theCUBE. It's the 10th Anniversary of Splunk's .Conf user conference. Our 7th year covering it. It's been quite a ride, what a wave. Splunk keeps getting stronger and better, adding more features, and has really become a powerhouse from a third party security standpoint. We got a C-SO in theCUBE on theCUBE today. Chief Information Security, John Frushour Deputy Chief (mumbles) New York-Presbyterian The Award Winner from the Data to Everywhere Award winner, welcome by theCube. >> Thank you, thank you. >> So first of all, what is the award that you won? I missed the keynotes, I was working on a story this morning. >> Frushour: Sure, sure. >> What's the award? >> Yeah, the Data Everything award is really celebrating using Splunk kind of outside its traditional use case, you know I'm a security professional. We use Splunk. We're a Splunk Enterprise Security customer. That's kind of our daily duty. That's our primary use case for Splunk, but you know, New York Presbyterian developed the system to track narcotic diversion. We call it our medication analytics platform and we're using Splunk to track opioid diversion, slash narcotic diversions, same term, across our enterprise. So, looking for improper prescription usage, over prescription, under prescription, prescribing for deceased patients, prescribing for patients that you've never seen before, superman problems like taking one pill out of the drawer every time for the last thirty times to build up a stash. You know, not resupplying a cabinet when you should have thirty pills and you only see fifteen. What happened there? Everything's data. It's data everything. And so we use this data to try to solve this problem. >> So that's (mumbles) that's great usage we'll find the drugs, I'm going to work hard for it. But that's just an insider threat kind of concept. >> Frushour: Absolutely. >> As a C-SO, you know, security's obviously paramount. What's changed the most? 'Cause look at, I mean, just looking at Splunk over the past seven years, log files, now you got cloud native tracing, all the KPI's, >> Frushour: Sure. >> You now have massive volumes of data coming in. You got core business operations with IOT things all instrumental. >> Sure, sure. >> As a security offer, that's a pretty big surface area. >> Yeah. >> How do you look at that? What's your philosophy on that? >> You know, a lot of what we do, and my boss, the C-SO (mumbles) we look at is endpoint protection and really driving down to that smaller element of what we complete and control. I mean, ten, fifteen years ago information security was all about perimeter control, so you've got firewalls, defense and depth models. I have a firewall, I have a proxy, I have an endpoint solution, I have an AV, I have some type of data redaction capability, data masking, data labeling capability, and I think we've seen.. I don't think security's changed. I hear a lot of people say, "Oh, well, information security's so much different nowadays." No, you know, I'm a military guy. I don't think anything's changed, I think the target changed. And I think the target moved from the perimeter to the endpoint. And so we're very focused on user behavior. We're very focused on endpoint agents and what people are doing on their individual machines that could cause a risk. We're entitling and providing privilege to end users today that twenty years ago we would've never granted. You know, there was a few people with the keys to the kingdom, and inside the castle keep. Nowadays everybody's got an admin account and everybody's got some level of privilege. And it's the endpoint, it's the individual that we're most focused on, making sure that they're safe and they can operate effectively in hospitals. >> Interviewer: What are some of the tactical things that have changed? Obviously, the endpoint obviously shifted, so some tactics have to change probably again. Operationally, you still got to solve the same problem: attacks, insider threats, etc. >> Frushour: Yeah. >> What are the tactics? What new tactics have emerged that are critical to you guys? >> Yeah, that's a tough question, I mean has really anything changed? Is the game really the game? Is the con really the same con? You look at, you know, titans of security and think about guys like Kevin Mitnick that pioneered, you know, social engineering and this sort of stuff, and really... It's really just convincing a human to do something that they shouldn't do, right? >> Interviewer: Yeah. >> I mean you can read all these books about phone freaking and going in and convincing the administrative assistant that you're just late for meeting and you need to get in through that special door to get in that special room, and bingo. Then you're in a Telco closet, and you know, you've got access. Nowadays, you don't have to walk into that same administrative assistant's desk and convince 'em that you're just late for the meeting. You can send a phishing email. So the tactics, I think, have changed to be more personal and more direct. The phishing emails, the spear phishing emails, I mean, we're a large healthcare institution. We get hit with those types of target attacks every day. They come via mobile device, They come via the phishing emails. Look at the Google Play store. Just, I think, in the last month has had two apps that have had some type of backdoor or malicious content in them that got through the app store and got onto people's phones. We had to pull that off people's phones, which wasn't pretty. >> Interviewer: Yeah. >> But I think it's the same game. It's the same kind to convince humans to do stuff that they're not supposed to do. But the delivery mechanism, the tactical delivery's changed. >> Interviewer: How is Splunk involved? Cause I've always been a big fan of Splunk. People who know me know that I've pretty much been a fan boy. The way they handle large amounts of data, log files, (mumbles) >> Frushour: Sure. >> and then expand out into other areas. People love to use Splunk to bring in their data, and to bring it into, I hate to use the word data leg but I mean, Just getting... >> Yeah >> the control of the data. How is data used now in your world? Because you got a lot of things going on. You got healthcare, IOT, people. >> Frushour: Sure, sure. >> I mean lives are on the line. >> Frushour: Lives are on the line, yeah. >> And there's things you got to be aware of and data's key. What is your approach? >> Well first I'm going to shamelessly plug a quote I heard from (mumbles) this week, who leads the security practice. She said that data is the oxygen of AI, and I just, I love that quote. I think that's just a fantastic line. Data's the oxygen of AI. I wish I'd come up with it myself, but now I owe her a royalty fee. I think you could probably extend that and say data is the lifeline of Splunk. So, if you think about a use case like our medication analytics platform, we're bringing in data sources from our time clock system, our multi-factor authentication system, our remote access desktop system. Logs from our electronic medical records system, Logs from the cabinets that hold the narcotics that every time you open the door, you know, a log then is created. So, we're bringing in kind of everything that you would need to see. Aside from doing something with actual video cameras and tracking people in some augmented reality matrix whatever, we've got all the data sources to really pin down all the data that we need to pin down, "Okay, Nurse Sally, you know, you opened that cabinet on that day on your shift after you authenticated and pulled out this much Oxy and distributed it to this patient." I mean, we have a full picture and chain of everything. >> Full supply chain of everything. >> We can see everything that happens and with every new data source that's out there, the beauty of Splunk is you just add it to Splunk. I mean, the Splunk handles structured and unstructured data. Splunk handles cis log fees and JSON fees, and there's, I mean there's just, it doesn't matter You can just add that stream to Splunk, enrich those events that were reported today. We have another solution which we call the privacy platform. Really built for our privacy team. And in that scenario, kind of the same data sets. We're looking at time cards, we're looking at authentication, we're looking at access and you visited this website via this proxy on this day, but the information from the EMR is very critical because we're watching for people that open patient records when they're not supposed to. We're the number five hospital in the country. We're the number one hospital in the state of New York. We have a large (mumbles) of very important people that are our patients and people want to see those records. And so the privacy platform is designed to get audit trails for looking at all that stuff and saying, "Hey, Nurse Sally, we just saw that you looked at patient Billy's record. That's not good. Let's investigate." We have about thirty use cases for privacy. >> Interviewer: So it's not in context of what she's doing, that's where the data come in? >> That's where the data come in, I mean, it's advanced. Nurse Sally opens up the EMR and looks at patient Billy's record, maybe patient Billy wasn't on the chart, or patient Billy is a VIP, or patient Billy is, for whatever reason, not supposed to be on that docket for that nurse, on that schedule for that nurse, we're going to get an alarm. The privacy team's going to go, "Oh, well, were they supposed to look at that record?" I'm just giving you, kind of, like two or three uses cases, but there's about thirty of them. >> Yeah, sure, I mean, celebrities whether it's Donald Trump who probably went there at some point. Everyone wants to get his taxes and records to just general patient care. >> Just general patient care. Yeah, exactly, and the privacy of our patients is paramount. I mean, especially in this digital age where, like we talked about earlier, everyone's going after making a human do something silly, right? We want to ensure that our humans, our nurses, our best in class patient care professionals are not doing something with your record that they're not supposed to. >> Interviewer: Well John, I want to hear your thoughts on this story I did a couple weeks ago called the Industrial IOT Apocalypse: Now or Later? And the provocative story was simply trying to raise awareness that malware and spear phishing is just tactics for that. Endpoint is critical, obviously. >> Sure. >> You pointed that out, everyone kind of knows that . >> Sure. >> But until someone dies, until there's a catastrophe where you can take over physical equipment, whether it's a self-driving bus, >> Frushour: Yeah. >> Or go into a hospital and not just do ransom ware, >> Frushour: Absolutely. >> Actually using industrial equipment to kill people. >> Sure. >> Interviewer: To cause a lot of harm. >> Right. >> This is an industrial, kind of the hacking kind of mindset. There's a lot of conversations going on, not enough mainstream conversations, but some of the top people are talking about this. This is kind of a concern. What's your view on this? Is it something that needs to be talked about more of? Is it just BS? Should it be... Is there any signal there that's worth talking about around protecting the physical things that are attached to them? >> Oh, absolutely, I mean this is a huge, huge area of interest for us. Medical device security at New York Presbyterian, we have anywhere from about eighty to ninety thousand endpoints across the enterprise. Every ICU room in our organization has about seven to ten connected devices in the ICU room. From infusion pumps to intubation machines to heart rate monitors and SPO2 monitors, all this stuff. >> Interviewer: All IP and connected. >> All connected, right. The policy or the medium in which they're connected changes. Some are ZP and Bluetooth and hard line and WiFi, and we've got all these different protocols that they use to connect. We buy biomedical devices at volume, right? And biomedical devices have a long path towards FDA certification, so a lot of the time they're designed years before they're fielded. And when they're fielded, they come out and the device manufacturer says, "Alright, we've got this new widget. It's going to, you know, save lives, it's a great widget. It uses this protocol called TLS 1.0." And as a security professional I'm sitting there going, "Really?" Like, I'm not buying that but that's kind of the only game, that's the only widget that I can buy because that's the only widget that does that particular function and, you know, it was made. So, this is a huge problem for us is endpoint device security, ensuring there's no vulnerabilities, ensuring we're not increasing our risk profile by adding these devices to our network and endangering our patients. So it's a huge area. >> And also compatible to what you guys are thinking. Like I could imagine, like, why would you want a multi-threaded processor on a light bulb? >> Frushour: Yeah. >> I mean, scope it down, turn it on, turn it off. >> Frushour: Scope it down for its intended purpose, yeah, I mean, FDA certification is all about if the device performs its intended function. But, so we've, you know, we really leaned forward, our CSO has really leaned forward with initiatives like the S bomb. He's working closely with the FDA to develop kind of a set of baseline standards. Ports and protocols, software and services. It uses these libraries, It talks to these servers in this country. And then we have this portfolio that a security professional would say, "Okay, I accept that risk. That's okay, I'll put that on my network moving on." But this is absolutely a huge area of concern for us, and as we get more connected we are very, very leaning forward on telehealth and delivering a great patient experience from a mobile device, a phone, a tablet. That type of delivery mechanism spawns all kinds of privacy concerns, and inter-operability concerns with protocol. >> What's protected. >> Exactly. >> That's good, I love to follow up with you on that. Something we can double down on. But while we're here this morning I want to get back to data. >> Frushour: Sure. >> Thank you, by the way, for sharing that insight. Something I think's really important, industrial IOT protection. Diverse data is really feeds a lot of great machine learning. You're only as good as your next blind spot, right? And when you're doing pattern recognition by using data. >> Frushour: Absolutely. >> So data is data, right? You know, telecraft, other data. Mixing data could actually be a good thing. >> Frushour: Sure, sure. >> Most professionals would agree to that. How do you look at diverse data? Because in healthcare there's two schools of thought. There's the old, HIPAA. "We don't share anything." That client privacy, you mentioned that, to full sharing to get the maximum out of the AI or machine learning. >> Sure. >> How are you guys looking at that data, diverse data, the sharing? Cause in security sharing's good too, right? >> Sure, sure, sure. >> What's your thoughts on sharing data? >> I mean sharing data across our institutions, which we have great relationships with, in New York is very fluid at New York Presbyterian. We're a large healthcare conglomerate with a lot of disparate hospitals that came as a result of partnership and acquisition. They don't all use the same electronic health record system. I think right now we have seven in play and we're converging down to one. But that's a lot of data sharing that we have to focus on between seven different HR's. A patient could move from one institution to the next for a specialty procedure, and you got to make sure that their data goes with them. >> Yeah. >> So I think we're pretty, we're pretty decent at sharing the data when it needs to be shared. It's the other part of your question about artificial intelligence, really I go back to like dedication analytics. A large part of the medication analytics platform that we designed does a lot of anomaly detections, anomaly detection on diversion. So if we see that, let's say you're, you know, a physician and you do knee surgeries. I'm just making this up. I am not a clinician, so we're going to hear a lot of stupidity here, but bare with me. So you do knee surgeries, and you do knee surgeries once a day, every day, Monday through Friday, right? And after that knee surgery, which you do every day in cyclical form, you prescribe two thousand milligrams of Vicodin. That's your standard. And doctors, you know, they're humans. Humans are built on patterns. That's your pattern. Two thousand milligrams. That's worked for you; that's what you prescribe. But all of the sudden on Saturday, a day that you've never done a knee surgery in your life for the last twenty years, you all of a sudden perform a very invasive knee surgery procedure that apparently had a lot of complications because the duration of the procedure was way outside the bounds of all the other procedures. And if you're kind of a math geek right now you're probably thinking, "I see where he's going with this." >> Interviewer: Yeah. >> Because you just become an anomaly. And then maybe you prescribe ten thousand milligrams of Vicodin on that day. A procedure outside of your schedule with a prescription history that we've never seen before, that's the beauty of funneling this data into Splunk's ML Toolkit. And then visualizing that. I love the 3D visualization, right? Because anybody can see like, "Okay, all this stuff, the school of phish here is safe, but these I've got to focus on." >> Interviewer: Yeah. >> Right? And so we put that into the ML Toolkit and then we can see, "Okay, Dr. X.." We have ten thousand, a little over ten thousand physicians across New York Presbyterian. Doctor X right over here, that does not look like a normal prescriptive scenario as the rest of their baseline. And we can tweak this and we can change precision and we can change accuracy. We can move all this stuff around and say, "Well, let's just look on medical record number, Let's just focus on procedure type, Let's focus on campus location. What did they prescribe from a different campus?" That's anomalous. So that is huge for us, using the ML Toolkit to look at those anomalies and then drive the privacy team, the risk teams, the pharmacy analytics teams to say, "Oh, I need to go investigate." >> So, that's a lot of heavy lifting for ya? Let you guys look at data that you need to look at. >> Absolutely. >> Give ya a (mumbles). Final question, Splunk, in general, you're happy with these guys? Obviously, they do a big part of your data. What should people know about Splunk 2019, this year? And are you happy with them? >> Oh, I mean Splunk has been a great partner to New York Presbyterian. We've done so much incredible development work with them, and really, what I like to talk about is Splunk for healthcare. You know, we've created, we saw some really important problems in our space, in this article. But, we're looking, we're leaning really far forward into things like risk based analysis, peri-op services. We've got a microbial stewardship program, that we're looking at developing into Splunk, so we can watch that. That's a huge, I wouldn't say as big of a crisis as the opioid epidemic, but an equally important crisis to medical professionals across this country. And, these are all solvable problems, this is just data. Right? These are just events that happen in different systems. If we can get that into Splunk, we can cease the archaic practice of looking at spreadsheets, and look up tables and people spending days to find one thing to investigate. Splunk's been a great partner to us. The tool it has been fantastic in helping us in our journey to provide best in-class patient care. >> Well, congratulations, John Frushour, Deputy Chief Information Security Officer, New York Presbyterian. Thanks for that insight. >> You're welcome. >> Great (mumbles) healthcare and your challenge and your opportunity. >> Congratulations for the award winner Data to Everything award winner, got to get that slogan. Get used to that, it's two everything. Getting things done, he's a doer. I'm John Furrier, here on theCube doing the Cube action all day for three days. We're on day two, we'll be back with more coverage, after this short break. (upbeat music)

>> live from Washington, D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Welcome back, everyone to the cubes Live coverage of a ws public sector Here in our nation's capital Washington D. C. I'm your host Rebecca. Night hosting alongside of John Farrier. Always a pleasure being with you. >> So good to see you again. >> And we're joined by first time Cube guest Brett MacMillan. He is the GM ground station. Eight of us. Thanks so much for coming on >> the road to be here. Thank you. >> So why don't you start by telling our viewers a little bit about ground station? What? It is one of us. >> You're first of all really excited to be here at this conference yesterday we had our second annual Earth Science Day. Last year was really successful, and we're finding a huge amount of interest around a space and space primarily tto help save the earth. And so >> eight of >> us came out with the solution, and we made it generally available last month called Ground Station. And if you think back about 15 years ago, before the commercial cloud came out, uh, you had to do for a data center. You Hey, either had to buy the data center. You had to do a long term lease. And then >> we >> came out with the commercial cloud. And from that point forward, there was a tremendous number of innovations. That movie came out of that. I don't think any of us back then could have predicted things like Pin arrests O R. Spotify Or or that Netflix would have gone from shipping your DVDs to be in the online streaming company and all those innovations happening, we think that we're at the beginning of that stage of satellite industry. So what ground station is is It's a service that you can use like any other cloud service. Just pay for what you used on demand. You can scale up you, Khun scale down. And we think that we're in the early stages of opening up innovations in this >> industry >> and its satellite specific. So it's a satellite services of connectivity. How how's it work? What's that >> s what happened to you. You would have a you just go into the eight of us counsel on you schedule a contact. And most of these early use cases there for our low earth orbit. Satellites are medium earth orbit satellites, and we have deployed these satellite antennas. And what's really important about this is we put them right next to our data centers or availability zones. So now you're getting the entire power of the cloud. And so what happens is you would schedule contact and either up Linker downlink your data during that contact period. And we just charge per per minute. And >> so it's like the two was servers and still has three. With storage and thie used. Case wasn't solved. The provisioning problem. So you guys are doing it for up Lincoln down Lincoln to satellite usage and data over satellite. Pretty >> direct. Correct. And so And the other thing that's really nice about it is just like the cloud would announce enable people to go global and minutes ground station allowed you to go global also. So, traditionally, what would happen if you would buy a satellite antenna or you'd Lisa Sal? I'd intended somewhere in the world and you're only catching so many passes of those satellites. We are deploying these at our data centers through out the world, and so you're able to at a very low cost. Now touch these passes of the sound lights. >> You know, Brett, Rebekah and I were talking on the intro around the role of technology. How it's causing a lot of change. You mentioned that window of 10 years where, before YouTube, after YouTube, all these new services came on. Think about it. Those didn't exist around before. Two thousand four time frame. Roughly two thousand 10 2 4 2 4 to 5. Then the mobile revolution hit. Similar wave is coming into government and seeing it. Amazon Webster Public Sector Summit is our fourth year. It gets bigger. The inclusion of space is a tell sign of commercialization of some of the tech coming in infiltrating process, change within government and use cases. So I would agree with you that that's relevant. >> Yeah, And >> next level is what? What was that window? What's gonna happen that 10 year? >> You don't change? It is hard to predict, but we know from our past experience on what we've done in the cloud. We know that when you remove the undifferentiated heavy lifting like buying servers are doing networks and things like that. It frees people up to do innovations on DH And when you look at what's happening in the satellite industry, virtually every industry, every person can benefit from a better understanding of this earth and from satellite imagery and satellite sensing. And so, if you start moving forward with that and you ask what can happen, we've got governments throughout the world that are very concerned about deforestation. And so, for example, today they find out 54 station after the trees are gone. And what if you could instead, for a very low cost, download pictures of satellite images and get it in more of a really time type basis? Or get it in that same hour that, uh, sound like took the picture. Now what you could do is catch the deforestation when the boulders air show up, not after the trees went down, so >> get in front of it. Used the data is a data business just about other use cases, because again, early adopters are easily the developers that are hungry for the resource. We saw that with cloud to industry, I mentioned now those service thousands and thousands of new services a year from a baby s jazz. He loves to talk about that at reinvent, and it's pretty impressive. But the early days was developers. They were the ones who have the value. They were thirsty for the resource. What are the sum of that resource? Is what's the low hanging fruit coming in for ground station that you could share that tell sign for >> where it's going? Interest not only for the his new developers in these new things, but large, established sound like companies are very interested in that, because when I was talking about earlier, you can cover areas with our service in ways that were very expensive to do. Like until you Ground Station would have been a little hard for us to roll out, had we not first on eight of us if you didn't first have things like Ace two and three and your ways of of storing your data or our petabytes scale worldwide network. And so when you look at that, you're able to get multiple different organizations doing some really cool things. We're in partnership with Cal Poly, Cal Poly and Cal Poly's been in the space industry for a long time. Back in 1999 they were one of the inventors of original Cube sat, and today what they're doing is they have this STDs, Sally Data Solutions service on. It's an initiative that they're doing and they did a hackathon. And when you look at all the areas that could benefit from from space and satellite tourists, all kinds of things pop up. So, for example, if your cattle rancher and you have a very large area, sometimes cat cat will get stuck in an area like a canyon or something. You don't find out about it. It's too. It's too late. So Cal Poly did this hackathon on DH. What they came up with is, it's very inexpensive now to put a I ot device on it on the cows on with the ground station. You can now download that information you can communicate to a satellite, and now we can find out how where those cows are and get them if they're in a dangerous situation. I >> think the eye OT impact is going to be huge. Rebecca, think about what we talked about around Coyote. I ot is the edge of the network, but there's no networks, not flat. It's in space. The earth is round right, so You know, it's kind of like a Christopher Columbus moment where if you have the data, all you need power and connectivity. So battery power is getting stronger every day. Long life batteries. But the connectivity with ground station literally makes a new eye ot surface area of the earth. Absolutely. I mean, that's pretty groundbreaking. >> This is a really exciting time to be in the space industry. A couple things are driving it. One is that the capabilities that were able to put up in space for the same amount of weight and the same amount of payload is increasing dramatically. The only thing that's happening is that the cost for lift the cost to put satellites and and orbit is dropping dramatically. And so what's happening with those two things is were able to get a lot more organisations putting satellites up there. And what's turning out is that there's a tremendous number of images and sensing capabilities. It's coming down actually more than the humans are able to analyze. And that's where the cloud comes in is that you take and you download this information and then you start using things like machine learning and artificial intelligence and you can see anomalies and point them out to the humans and say, for example, these balls are just showed up. Maybe we should go take a look at that. >> You know, imagery has always been a hot satellite thing. You see Google Earth map three D mapping is getting better. How is that playing into it? Is that a use case for you guys? I mean, you talk about the impact. Is that something we all relate to >> you and I would submit that we are in the early stages of that. It's amazing what we can do with their damaging today. And everybody on their phones get Google maps and all the other things that are out there. But we're in early stages of what we could do with that. So some areas that we're looking at very closely. So, for example, during the California wildfires last year, NASA worked on something to help out the people on the ground. You know, with ground station, what you'll be able to do is do more downloads and get more information than a more real time basis, and you'll actually be able to look at this and say the wildfires are happening in these areas and help the citizens with escape routes and help them understand things that were actually hard to determine from the ground. And so we're looking at this for natural disasters as well as just Data Day solutions. >> It's such an exciting time, and you and your pointing at so many different use cases that have a lot of potential to really be game changers. What keeps you up at night about this, though? I mean, I think that they're as we know, there's a lot of unintended consequences that comes with these new technologies and particularly explosion of these new technologies. What are what are your worries? What what is the future perils that you see? >> So So we definitely are working with these agencies of the federal government and commercial things on making sure that you can sit. You're the data. But again, that was one of the benefits of starting with a ws. We started with security being a primary of part of what we did. And so when when you have ground station, you do a satellite uplink for downlink, and then you immediately tell it where in the world you want the data to be stored. So, for example, we could download, Let's say, in another part of the world, and then you can bring it back to the nine states and store it in your we call a virtual private cloud. It's a way for our customers to be able to control their environment securely. And so we spent a lot of time explain to people how they could do that and how they could do it securely. And so, uh, well, it doesn't keep me awake at night, But we spend a tremendous amount of time working with these organisations, making sure that they are using best practices when they're using our solution. Right? >> Talk about the challenges you mentioned, storing the securely role of policy. We're living in a world now where the confluence of policy science tech people are all kind of exploding and studio innovation but also meet challenges. What are some of the things that you guys are doing? Obeys the bar improving? I mean, I'll say there's early days, so you're seeing areas to improve. What if some of the areas that you're improving on that are being worked on now on impact >> So you mentioned policy side of it. What I'd like Teo say is any time there's a new technology that comes out way. Have to do some catching up from, You know, the policy, the regulator point in front of you right now because the satellite industry is moving so fast. Um, there's a scale issues on. So governments throughout the world are looking at the number of satellites they're going up in, the number of communications are happening, and they're working with that scale on Andi. I I'm very proud to say that they're reacting. They were acting fairly quickly on DH. That's one of the areas that I think we're going to see more on is as this industry evolves, having things like having antennas insert and antennas and satellite certified quickly is one of the things that we need to talk. >> Some base infrastructure challenges mean Consider space kind of infrastructure. At this point, it plenty of room up there currently, but can envision a day with satellites, zillion satellites up there at some point. But that gets set up first. You're saying the posture. The government is pro innovation in this area. >> Oh, you're wasting a lot of interest in that way. We launched ground station governments both here in this country as well as throughout the world, very interested in this on DH. They see the potential on being able to make the satellite's on satellite imagery and detection available. And it's not just for those largest organizations like the governments. But it's also when you commercialize this and what we've made it so that small, medium sized businesses now, Khun, get into this business and do innovative things. >> Question. I want to ask. You know, we're tight on time, Rebecca, but we'll get this out. In your opinion. What? What do you think the modernization of public policy governments means? Because the paint on your definition, what modernization is This seems to be the focus of this conference here, a ws re public sector summit. This is the conversation we're having in other agencies. They want to modernize. >> What does that mean to you? It takes on many things. Many perspectives. What? What I find a lot is modernizations is making helping your workers be more productive. And so we do this with a number of different ways. So when you look at ground station. Really? Benefit of it isn't. Can I get the image? Can I get the data? But how can I do something with it? And so when you start applying machine learning artificial intelligence now you can put a point toe anomalies that are happening. And now you can have the people really focus on the anomalies and not look at a lot of pictures. They're exactly the same. So when you look at a modernization, I think it's some economists with How do we make the workforce that's in place more productive >> and find those missing cows? It's Fred McMillan. Thank you so much for coming on the Q. Thank >> you. It was a pleasure. We've >> got a lot of great mark. We got many more gas. Got Teresa Carlson. Jay Carney? >> Yeah. Yeah. General Keith Alexander, About how date is being used in the military. We got ground station connectivity. I really think this is a great opportunity for io. T wait to see how it progresses. >> Excellent. Thank you. >> Becca. Knight for John Furrier. Stay tuned to the Cube.

>> Live from Las Vegas. It's theCUBE. Covering Informatica World 2019, brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World. I am your host, Rebecca Knight, along with co-host, John Furrier. We have two guests for this segment. We have Abhiman Matlapudi. He is the Product Master at Deloitte. Welcome. >> Thanks for having us. >> And we have Kubalahm Rajeev Krishnan, Specialist Leader at Deloitte. Thank you both so much for coming on theCUBE. >> Thanks Rebecca, John. It's always good to be back on theCUBE. >> Love the new logos here, what's the pins? What's the new take on those? >> It looks like a honeycomb! >> Yeah, so interesting that you ask, so this is our joined Deloitte- Informatica label pin. You can see the Deloitte green colors, >> Nice! They're beautiful. >> And the Informatica colors. This shows the collaboration, the great collaboration that we've had over, you know, the past few years and plans, for the future as well. Well that's what we're here to talk about. So why don't you start the conversation by telling us a little bit about the history of the collaboration, and what you're planning ahead for the future. Yeah. So, you know, if we go like you know, ten years back the collaboration between Deloitte and Informatica has not always been that, that strong and specifically because Deloitte is a huge place to navigate, and you know, in order to have those meaningful collaborations. But over the past few years, we've... built solid relationships with Informatica and vise versa. I think we seek great value. The clear leaders in the Data Management Space. It's easy for us to kind of advise clients in terms of different facets of data management. You know, because no other company actually pulls together you know, the whole ecosystem this well. >> Well you're being polite. In reality, you know where it's weak and where it's real. I mean, the reality is there's a lot of fun out there, a lot of noise, and so, I got to ask you, cause this is the real question, because there's no one environment that's the same. Customers want to get to the truth faster, like, where's the deal? What's the real deal with data? What's gettable? What's attainable? What's aspirational? Because you could say "Hey, well I make data, data-driven organization, Sass apps everywhere." >> Yeah. Yeah absolutely. I mean every, every company wants to be more agile. Business agility is what's driving companies to kind of move all of their business apps to the Cloud. The uh, problem with that is that, is that people don't realize that you also need to have your data management governance house in order, right, so according to a recent Gartner study, they say by next year, 75% of companies who have moved their business apps to the Cloud, is going to, you know, unless they have their data management and data assets under control, they have some kind of information governance, that has, you know, context, or purview over all of these business apps, 50% of their data assets are going to erode in value. So, absolutely the need of the hour. So we've seen that great demand from our clients as well, and that's what we've been advising them as well. >> What's a modern MDM approach? Because this is really the heart of the conversation, we're here at Informatica World. What's- What does it look like? What is it? >> So I mean, there are different facets or functionalities within MDM that actually make up what is the holistic modern MDM, right. In the past, we've seen companies doing MDM to get to that 360-degree view. Somewhere along the line, the ball gets dropped. That 360 view doesn't get combined with your data warehouse and all of the transaction information, right, and, you know, your business uses don't get the value that they were looking for while they invested in that MDM platform. So in today's world, MDM needs to provide front office users with the agility that they need. It's not about someone at the back office doing some data stewardship. It's all about empowering the front office users as well. There's an aspect of AIML from a data stewardship perspective. I mean everyone wants cost take out, right, I mean there's fewer resources and more data coming in. So how how do you manage all of the data? Absolutely you need to have AIML. So Informatica's CLAIRE product helps with suggestions and recommendations for algorithms, matching those algorithms. Deloitte has our own MDM elevate solution that embeds AIML for data stewardship. So it learns from human data inputs, and you know, cuts through the mass of data records that have to be managed. >> You know Rajeev, it was interesting, last year we were talking, the big conversation was moving data around is really hard. Now there's solutions for that. Move the data integrity on premise, on Cloud. Give us an update on what's going on there, because there seems to be a lot of movement, positive movement, around that. In terms of, you know, quality, end to end. We heard Google up here earlier saying "Look, we can go into end to end all you want". This has been a big thing. How are you guys handling this? >> Yeah absolutely, so in today's key note you heard Anil Chakravarthy and Thomas Green up on the stage and Anil announced MDM on GCP, so that's an offering that Deloitte is hosting and managing. So it's going to be an absolutely white-glove service that gives you everything from advice to implement to operate, all hosted on GCP. So it's a three-way ecosystem offering between Deloitte, Informatica, and GCP. >> Well just something about GCP, just as a side note before you get there, is that they are really clever. They're using Sequel as a way to abstract all the under the hood kind of configuration stuff. Smart move, because there's a ton of Sequel people out there! >> Exactly. >> I mean, it's not structured query language for structured data. It's lingua franca for data. They've been changing the game on that. >> Exactly, it should be part of their Cloud journey. So organizations, when they start thinking about Cloud, first of all, what they need to do is they have to understand where all the data assets are and they read the data feeds coming in, where are the data lakes, and once they understand where their datas are, it's not always wise, or necessary to move all their data to the Cloud. So, Deloitte's approach or recommendation is to have a hybrid approach. So that they can keep some of their legacy datas, data assets, in the on premise and some in the Cloud applications. So, Informatica, MDM, and GCP, powered by Deloitte, so it acts as an MDM nimble hub. In respect of where your data assets are, it can give you the quick access to the data and it can enrich the data, it can do the master data, and also it can protect your data. And it's all done by Informatica. >> Describe what a nimble hub is real quick. What does a nimble hub mean? What does that mean? >> So it means that, in respect of wherever your data is coming in and going out, so it gives you a very light feeling that the client wouldn't know. All we- Informatica, MDM, on GCP powered by Deloitte, what we are saying is we are asking clients to just give the data. And everything, as Rajeev said, it's a white-glove approach. It's that from engagement, to the operation, they will just feel a seamless support from Deloitte. >> Yeah, and just to address the nimbleness factor right, so we see clients that suddenly need to get into new market, or they want to say, introduce a new product, so they need the nimbleness from a business perspective. Which means that, well suddenly you've got to like scale up and down your data workloads as well, right? And that's not just transactional data, but master data as well. And that's where the Cloud approach, you know, gives them a positive advantage. >> I want to get back to something Abhiman said about how it's not always wise or necessary to move to the Cloud. And this is a debate about where do you keep stuff. Should it be on on prem, and you said that Deloitte recommends a hybrid approach and I'm sure that's a data-driven recommendation. I'm wondering what evidence you have and what- why that recommendation? >> So, especially when it depends on the applications you're putting on for MDM, and the sources and data is what you are trying to get, for the Informatica MDM to work. So, it's not- some of your social systems are already tied up with so many other applications within your on premise, and they don't want to give every other data. And some might have concerns of sending this data to the Cloud. So that's when you want to keep those old world legacy systems, who doesn't want to get upgrades, to your on premise, and who are all Cloud-savy and they can all starting new. So they can think of what, and which, need a lot of compute power, and storage. And so those are the systems we want to recommend to the Cloud. So that's why we say, think where you want to move your data bases. >> And some of it is also driven by regulation, right, like GDPR, and where, you know, which providers offer in what countries. And there's also companies that want to say "Oh well my product strategy and my pricing around products, I don't want to give that away to someone." Especially in the high tech field, right. Your provider is going to be a confidere. >> Rajeev, one of the things I'm seeing here in this show, is clearly that the importance of the Cloud should not be understated. You see, and you guys, you mentioned you get the servers at Google. This is changing not just the customers opportunity, but your ability to service them. You got a white-glove service, I'm sure there's a ton more head room. Where do you guys see the Cloud going next? Obviously it's not going away, and the on premise isn't going away. But certainly, the importance of the Cloud should not be understated. That's what I'm hearing clearly. You see Amazon, Azure, Google, all big names with Informatica. But with respect to you guys, as you guys go out and do your services. This is good for business. For you guys, helping customers. >> Yeah absolutely, I think there's value for us, there's value for our clients. You know, it's not just the apps that are kind of going to the Cloud, right? I mean you see all data platforms that are going to the Cloud. For example, Cloudera. They just launched CDP. Being GA by July- August. You know, Snowflake's on the Cloud doing great, getting good traction in the market. So eventually what were seeing is, whether it's business applications or data platforms, they're all moving to the Cloud. Now the key things to look out for in the future is, how do we help our clients navigate a multi Cloud environment, for example, because sooner or later, they wouldn't want to have all of their eggs invested in one basket, right? So, how do we help navigate that? How do we make that seamless to the business user? Those are the challenges that we're thinking about. >> What's interesting about Databricks and Snowflake, you mentioned them, is that it really is a tell sign that start-ups can break through and crack the enterprise with Cloud and the ecosystem. And you're starting to see companies that have a Sass-like mindset with technology. Coming into an enterprise marketed with these ecosystems, it's a tough crowd believe me, you know the enterprise. It's not easy to break into the enterprise, so for Databricks and Snowflake, that's a huge tell sign. What's your reaction to that because it's great for Informatica because it's validation for them, but also the start-ups are now growing very fast. I mean, I wouldn't call Snowflake 3 billion dollar start-up their unicorn but, times three. But it's a tell sign. It's just something new we haven't seen. We've seen Cloudera break in. They kind of ramped their way in there with a lot of raise and they had a big field sales force. But Data Bear and Snowflake, they don't have a huge set in the sales force. >> Yeah, I think it's all about clients and understanding, what is the true value that someone provides. Is it someone that we can rely on to keep our data safe? Do they have the capacity to scale? If you can crack those things, then you'll be in the market. >> Who are you attracting to the MDM on Google Cloud? What's the early data look like? You don't have to name names, but whats some of the huge cases that get the white glove service from Deloitte on the Google Cloud? Tell us about that. Give us more data on that. >> So we've just announced that, here at Informatica World, we've got about three to four mid to large enterprises. One large enterprise and about three mid-size companies that are interested in it. So we've been in talks with them in terms of- and that how we want to do it. We don't want to open the flood gates. We'd like to make sure it's all stable, you know, clients are happy and there's word of mouth around. >> I'm sure the end to end management piece of it, that's probably attractive. The end to end... >> Exactly. I mean, Deloitte's clearly the leader in the data analytics space, according to Gartner Reports. Informatica is the leader in their space. GCP has great growth plans, so the three of them coming together is going to be a winner. >> One of the most pressing challenges facing the technology industry is the skills gap and the difficulty in finding talent. Surveys show that I.T. managers can't find qualified candidates for open Cloud roles. What are Deloitte's thought on this and also, what are you doing as a company to address it? >> I mean, this is absolutely a good problem to have, for us. Right, which means that there is a demand. But unless we beat that demand, it's a problem. So we've been taking some creative ways, in terms of addressing that. An example would be our analytics foundry offering, where we provide a pod of people that go from data engineers you know, with Python and Sparks skills, to, you know, Java associates, to front end developers. So a whole stack of developers, a full stack, we provide that full pod so that they can go and address a particular business analytics problem or some kind of visualization issues, in terms of what they want to get from the data. So, we teach Leverate that pod, across multiple clients, I think that's been helping us. >> If you could get an automated, full time employee, that would be great. >> Yeah, and this digital FD concept is something that we'd be looking at, as well. >> I would like to add on that, as well. So, earlier- with the data disruption, Informatica's so busy and Informatica's so busy that Deloitte is so busy. Now, earlier we used plain Informatica folks and then, later on because of the Cloud disruption, so we are training them on the Cloud concepts. Now what the organizations have to think, or the universities to think is that having the curriculum, the Cloud concepts in their universities and their curriculum so that they get all their Cloud skills and after, once they have their Cloud skills, we can train them on the Informatica skills. And Informatica has full training on that. >> I think it's a great opportunity for you guys. We were talking with Sally Jenkins to the team earlier, and the CEO. I was saying that it reminds me of early days of VMware, with virtualization you saw the shift. Certainly the economics. You replaced servers, do a virtual change to the economics. With the data, although not directly, it's a similar concept where there's new operational opportunities, whether it's using leverage in Google Cloud for say, high-end, modern data warehousing to whatever. The community is going to respond. That's going to be a great ecosystem money making opportunity. The ability to add new services, give you guys more capabilities with customers to really move the needle on creating value. >> Yeah, and it's interesting you mention VMware because I actually helped, as VMware stood up there, VMCA, AW's and NSA's offerings on the Cloud. We actually helped them get ready for that GA and their data strategy, in terms of support, both for data and analytics friendliness. So we see a lot of such tech companies who are moving to a flexible consumption service. I mean, the challenges are different and we've got a whole practice around that flex consumption. >> I'm sure Informatica would love the VMware valuation. Maybe not worry for Dell technology. >> We all would love that. >> Rajeem, Abhiman, thank you so much for joining us on theCube today. >> Thank you very much. Good talking to you. >> I'm Rebecca Knight for John Furrier. We will have more from Informatica World tomorrow.