>> San Francisco, it's theCUBE, covering Conga Connect West 2018 brought to you by Conga. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are at the Thirsty Bear at Salesforce Dreamforce, 170,000 people, we're in a small side of it put on by Conga, it's called Conga Connect West, think they had 3000 people last year. if you can see behind us the Thirsty Bear is packed to the gills, they're here for three days with free food, free drink, theCUBE and some entertainment. But as you know, we like to get the smartest people we can, get the knowledge from them and we're really excited to have a super smart person from 451, she's Sheryl Kingstone, the VP of Research for Customer Experience and Commerce at 451 Sheryl, great to see you. >> Nice to see you, too and thanks for inviting me. >> Oh absolutely, so you've been coming to this thing you said for a number of years. Every time I come to Dreamforce, it's like oh my goodness, how can it get any bigger? >> So, I can think back to the year 2000 when I did roadshows with Salesforce and we couldn't even get 40 people in the room. >> Oh my goodness. >> And now we have what, 170,000? >> That was kind of the dark, the dark and... >> That was when we were convincing people >> The dark days. >> That SaaS was the way to go and everyone was like wait, what? >> Right. >> Saas? >> When ASP was not Average Selling Price >> Oh god. >> But Application Service Provider. >> Absolutely, absolutely. >> Very good. So let's jump into it. So now it's 2018, time flies. Digital transformation is all the rage and I know you do a lot of work on digital transformation. So where do people get started, what is digital transformation? >> Yeah, yeah >> So how do you help people kind of, you know, I got to do it, the boss wants me to do it, my competitors are doing it. >> Yeah >> Where do they go? >> And here's the thing, you could say digital transformation has been pretty much evolving for two decades, it really is leveraging software. But what's really changed is digital transformation is more than just an IT strategy, right? So digital transformation is a business strategy. It's a culture, it's understanding how to leverage these new, more modern technologies so that we're reducing customer friction points, or empowering employees, or helping our partners sell more. So it's really more of an overarching strategy instead of independent, I'm going to go out and get software A versus software B. >> Right, and there's so many components of it, in not only the technology piece, but as we always see at shows, also the people and the process. The technology by itself is just another tool. >> Yeah, and we've been also talking in decades about people, process and technology, and one of the things I've said for a long time is what's missing in that, is the overlying or underlying data element of it. And that's another thing that's changed, is what are we doing to harness the power of the data that we get through these digital transformation processes that were undertaken? >> Right. >> And data's absolutely critical. >> But data by itself's just data, right? And to turn it in for information you got to have context. >> Yeah. >> You got to have the right data to the right person at the right time make the right decision. >> Yeah, but I've said all along, it's not about he who holds the right data, most data, it's really who has the right data. >> Right. >> So absolutely. >> Right. So as you look at some of the significant kind of glacial shifts in terms of infrastructure, in terms of CPU, in speed of CPUs compared again to 2000, you know, compared to the data that we have, the storage economics, and obviously Cloud. Now, finally, it seems like we're getting to the tipping point, where you've got enough horsepower, you've got enough storage, you Compute, and networking that you can start to implement some of these things that were just a pipe dream when you couldn't get 40 people, >> Yeah, well, >> In a room. >> So Compute has definitely changed and it's one of the things that's changed with respect to machine learning. The storage, because if you really think about intelligence, it's all about making sure you have all of that data. So yes, absolutely, that's changed. But one of the things that we really have to understand, and at 451 we just launched a lot of research around Foresight, right, and it's so about, hindsight is 20/20 and Foresight is 451, right? So it is all about looking more forward. >> Right, right. >> And one of the things that we talk about is just that. What are we doing with invisible infrastructure? Because no one really cares about what the infrastructure it is today, it's what's the intelligence that's coming out of it? So our four themes are around invisible infrastructure, pervasive intelligence, contextual experiences and then the ability to deal with the risk. So those four themes come together to create Foresight, and we actually launched that this week at our own conference, HCTS. >> I used to joke, we used to operate on a sample of historic data, right? Take a little bit of something that already happened. As opposed to now, you actually have the opportunity to get all the data and you have the opportunity to get it in real-time and have that feed your decision making processes. >> Well, what's really changed is we're no longer working from just operational data, we're bringing a lot more of that behavioral data that has to be streamed in real-time, and that's the architectural changes that have shift. >> Right. >> And the other thing you have to do with the infrastructure changes, if you're really making a decision, you have to make that decision on the edge. (announcements in background) >> So I think Marc Benioff is going to start speaking. >> Yeah, that's what we're going to have to adjust, to cut this off. >> So Sheryl, it's great to catch up and we'll see you next time. >> Not a problem, thank you. >> Marc Benioff's coming on. Thanks for watching theCube. (announcements in background) (upbeat music)

(gentle music) >> Hey! Welcome back to theCUBE's coverage of WiDS 2023, the eighth Annual Women In Data Science Conference. I'm your host, Lisa Martin. We are at Stanford University, as you know we are every year, having some wonderful conversations with some very inspiring women and men in data science and technical roles. I'm very pleased to introduce Tracy Zhang, my co-host, who is in the Data Journalism program at Stanford. And Tracy and I are pleased to welcome our next guest, Rhonda Crate, Principal Data Scientist at Boeing. Great to have you on the program, Rhonda. >> Tracy: Welcome. >> Hey, thanks for having me. >> Were you always interested in data science or STEM from the time you were young? >> No, actually. I was always interested in archeology and anthropology. >> That's right, we were talking about that, anthropology. Interesting. >> We saw the anthropology background, not even a bachelor's degree, but also a master's degree in anthropology. >> So you were committed for a while. >> I was, I was. I actually started college as a fine arts major, but I always wanted to be an archeologist. So at the last minute, 11 credits in, left to switch to anthropology. And then when I did my master's, I focused a little bit more on quantitative research methods and then I got my Stat Degree. >> Interesting. Talk about some of the data science projects that you're working on. When I think of Boeing, I always think of aircraft. But you are doing a lot of really cool things in IT, data analytics. Talk about some of those intriguing data science projects that you're working on. >> Yeah. So when I first started at Boeing, I worked in information technology and data analytics. And Boeing, at the time, had cored up data science in there. And so we worked as a function across the enterprise working on anything from shared services to user experience in IT products, to airplane programs. So, it has a wide range. I worked on environment health and safety projects for a long time as well. So looking at ergonomics and how people actually put parts onto airplanes, along with things like scheduling and production line, part failures, software testing. Yeah, there's a wide spectrum of things. >> But I think that's so fantastic. We've been talking, Tracy, today about just what we often see at WiDS, which is this breadth of diversity in people's background. You talked about anthropology, archeology, you're doing data science. But also all of the different opportunities that you've had at Boeing. To see so many facets of that organization. I always think that breadth of thought diversity can be hugely impactful. >> Yeah. So I will say my anthropology degree has actually worked to my benefit. I'm a huge proponent of integrating liberal arts and sciences together. And it actually helps me. I'm in the Technical Fellowship program at Boeing, so we have different career paths. So you can go into management, you can be a regular employee, or you can go into the Fellowship program. So right now I'm an Associate Technical Fellow. And part of how I got into the Fellowship program was that diversity in my background, what made me different, what made me stand out on projects. Even applying a human aspect to things like ergonomics, as silly as that sounds, but how does a person actually interact in the space along with, here are the actual measurements coming off of whatever system it is that you're working on. So, I think there's a lot of opportunities, especially in safety as well, which is a big initiative for Boeing right now, as you can imagine. >> Tracy: Yeah, definitely. >> I can't go into too specifics. >> No, 'cause we were like, I think a theme for today that kind of we brought up in in all of our talk is how data is about people, how data is about how people understand the world and how these data can make impact on people's lives. So yeah, I think it's great that you brought this up, and I'm very happy that your anthropology background can tap into that and help in your day-to-day data work too. >> Yeah. And currently, right now, I actually switched over to Strategic Workforce Planning. So it's more how we understand our workforce, how we work towards retaining the talent, how do we get the right talent in our space, and making sure overall that we offer a culture and work environment that is great for our employees to come to. >> That culture is so important. You know, I was looking at some anitab.org stats from 2022 and you know, we always talk about the number of women in technical roles. For a long time it's been hovering around that 25% range. The data from anitab.org showed from '22, it's now 27.6%. So, a little increase. But one of the biggest challenges still, and Tracy and I and our other co-host, Hannah, have been talking about this, is attrition. Attrition more than doubled last year. What are some of the things that Boeing is doing on the retention side, because that is so important especially as, you know, there's this pipeline leakage of women leaving technical roles. Tell us about what Boeing's, how they're invested. >> Yeah, sure. We actually have a publicly available Global Diversity Report that anybody can go and look at and see our statistics for our organization. Right now, off the top of my head, I think we're hovering at about 24% in the US for women in our company. It has been a male majority company for many years. We've invested heavily in increasing the number of women in roles. One interesting thing about this year that came out is that even though with the great resignation and those types of things, the attrition level between men and women were actually pretty close to being equal, which is like the first time in our history. Usually it tends on more women leaving. >> Lisa: That's a good sign. >> Right. >> Yes, that's a good sign. >> And we've actually focused on hiring and bringing in more women and diversity in our company. >> Yeah, some of the stats too from anitab.org talked about the increase, and I have to scroll back and find my notes, the increase in 51% more women being hired in 2022 than 2021 for technical roles. So the data, pun intended, is showing us. I mean, the data is there to show the impact that having females in executive leadership positions make from a revenue perspective. >> Tracy: Definitely. >> Companies are more profitable when there's women at the head, or at least in senior leadership roles. But we're seeing some positive trends, especially in terms of representation of women technologists. One of the things though that I found interesting, and I'm curious to get your thoughts on this, Rhonda, is that the representation of women technologists is growing in all areas, except interns. >> Rhonda: Hmm. >> So I think, we've got to go downstream. You teach, I have to go back to my notes on you, did my due diligence, R programming classes through Boeings Ed Wells program, this is for WSU College of Arts and Sciences, talk about what you teach and how do you think that intern kind of glut could be solved? >> Yeah. So, they're actually two separate programs. So I teach a data analytics course at Washington State University as an Adjunct Professor. And then the Ed Wells program is a SPEEA, which is an Aerospace Union, focused on bringing up more technology and skills to the actual workforce itself. So it's kind of a couple different audiences. One is more seasoned employees, right? The other one is our undergraduates. I teach a Capstone class, so it's a great way to introduce students to what it's actually like to work on an industry project. We partner with Google and Microsoft and Boeing on those. The idea is also that maybe those companies have openings for the students when they're done. Since it's Senior Capstone, there's not a lot of opportunities for internships. But the opportunities to actually get hired increase a little bit. In regards to Boeing, we've actually invested a lot in hiring more women interns. I think the number was 40%, but you'd have to double check. >> Lisa: That's great, that's fantastic. >> Tracy: That's way above average, I think. >> That's a good point. Yeah, it is above average. >> Double check on that. That's all from my memory. >> Is this your first WiDS, or have you been before? >> I did virtually last year. >> Okay. One of the things that I love, I love covering this event every year. theCUBE's been covering it since it's inception in 2015. But it's just the inspiration, the vibe here at Stanford is so positive. WiDS is a movement. It's not an initiative, an organization. There are going to be, I think annually this year, there will be 200 different events. Obviously today we're live on International Women's Day. 60 plus countries, 100,000 plus people involved. So, this is such a positive environment for women and men, because we need everybody, underrepresented minorities, to be able to understand the implication that data has across our lives. If we think about stripping away titles in industries, everybody is a consumer, not everybody, most of mobile devices. And we have this expectation, I was in Barcelona last week at a Mobile World Congress, we have this expectation that we're going to be connected 24/7. I can get whatever I want wherever I am in the world, and that's all data driven. And the average person that isn't involved in data science wouldn't understand that. At the same time, they have expectations that depend on organizations like Boeing being data driven so that they can get that experience that they expect in their consumer lives in any aspect of their lives. And that's one of the things I find so interesting and inspiring about data science. What are some of the things that keep you motivated to continue pursuing this? >> Yeah I will say along those lines, I think it's great to invest in K-12 programs for Data Literacy. I know one of my mentors and directors of the Data Analytics program, Dr. Nairanjana Dasgupta, we're really familiar with each other. So, she runs a WSU program for K-12 Data Literacy. It's also something that we strive for at Boeing, and we have an internal Data Literacy program because, believe it or not, most people are in business. And there's a lot of disconnect between interpreting and understanding data. For me, what kind of drives me to continue data science is that connection between people and data and how we use it to improve our world, which is partly why I work at Boeing too 'cause I feel that they produce products that people need like satellites and airplanes, >> Absolutely. >> and everything. >> Well, it's tangible, it's relatable. We can understand it. Can you do me a quick favor and define data literacy for anyone that might not understand what that means? >> Yeah, so it's just being able to understand elements of data, whether that's a bar chart or even in a sentence, like how to read a statistic and interpret a statistic in a sentence, for example. >> Very cool. >> Yeah. And sounds like Boeing's doing a great job in these programs, and also trying to hire more women. So yeah, I wanted to ask, do you think there's something that Boeing needs to work on? Or where do you see yourself working on say the next five years? >> Yeah, I think as a company, we always think that there's always room for improvement. >> It never, never stops. >> Tracy: Definitely. (laughs) >> I know workforce strategy is an area that they're currently really heavily investing in, along with safety. How do we build safer products for people? How do we help inform the public about things like Covid transmission in airports? For example, we had the Confident Traveler Initiative which was a big push that we had, and we had to be able to inform people about data models around Covid, right? So yeah, I would say our future is more about an investment in our people and in our culture from my perspective >> That's so important. One of the hardest things to change especially for a legacy organization like Boeing, is culture. You know, when I talk with CEO's or CIO's or COO's about what's your company's vision, what's your strategy? Especially those companies that are on that digital journey that have no choice these days. Everybody expects to have a digital experience, whether you're transacting an an Uber ride, you're buying groceries, or you're traveling by air. That culture sounds like Boeing is really focused on that. And that's impressive because that's one of the hardest things to morph and mold, but it's so essential. You know, as we look around the room here at WiDS it's obviously mostly females, but we're talking about women, underrepresented minorities. We're talking about men as well who are mentors and sponsors to us. I'd love to get your advice to your younger self. What would you tell yourself in terms of where you are now to become a leader in the technology field? >> Yeah, I mean, it's kind of an interesting question because I always try to think, live with no regrets to an extent. >> Lisa: I like that. >> But, there's lots of failures along the way. (Tracy laughing) I don't know if I would tell myself anything different because honestly, if I did, I wouldn't be where I am. >> Lisa: Good for you. >> I started out in fine arts, and I didn't end up there. >> That's good. >> Such a good point, yeah. >> We've been talking about that and I find that a lot at events like WiDS, is women have these zigzaggy patterns. I studied biology, I have a master's in molecular biology, I'm in media and marketing. We talked about transportable skills. There's a case I made many years ago when I got into tech about, well in science you learn the art of interpreting esoteric data and creating a story from it. And that's a transportable skill. But I always say, you mentioned failure, I always say failure is not a bad F word. It allows us to kind of zig and zag and learn along the way. And I think that really fosters thought diversity. And in data science, that is one of the things we absolutely need to have is that diversity and thought. You know, we talk about AI models being biased, we need the data and we need the diverse brains to help ensure that the biases are identified, extracted, and removed. Speaking of AI, I've been geeking out with ChatGPT. So, I'm on it yesterday and I ask it, "What's hot in data science?" And I was like, is it going to get that? What's hot? And it did it, it came back with trends. I think if I ask anything, "What's hot?", I should be to Paris Hilton, but I didn't. And so I was geeking out. One of the things I learned recently that I thought was so super cool is the CTO of OpenAI is a woman, Mira Murati, which I didn't know until over the weekend. Because I always think if I had to name top females in tech, who would they be? And I always default to Sheryl Sandberg, Carly Fiorina, Susan Wojcicki running YouTube. Who are some of the people in your history, in your current, that are really inspiring to you? Men, women, indifferent. >> Sure. I think Boeing is one of the companies where you actually do see a lot of women in leadership roles. I think we're one of the top companies with a number of women executives, actually. Susan Doniz, who's our Chief Information Officer, I believe she's actually slotted to speak at a WiDS event come fall. >> Lisa: Cool. >> So that will be exciting. Susan's actually relatively newer to Boeing in some ways. A Boeing time skill is like three years is still kind of new. (laughs) But she's been around for a while and she's done a lot of inspiring things, I think, for women in the organization. She does a lot with Latino communities and things like that as well. For me personally, you know, when I started at Boeing Ahmad Yaghoobi was one of my mentors and my Technical Lead. He came from Iran during a lot of hard times in the 1980s. His brother actually wrote a memoir, (laughs) which is just a fun, interesting fact. >> Tracy: Oh my God! >> Lisa: Wow! >> And so, I kind of gravitate to people that I can learn from that's not in my sphere, that might make me uncomfortable. >> And you probably don't even think about how many people you're influencing along the way. >> No. >> We just keep going and learning from our mentors and probably lose sight of, "I wonder how many people actually admire me?" And I'm sure there are many that admire you, Rhonda, for what you've done, going from anthropology to archeology. You mentioned before we went live you were really interested in photography. Keep going and really gathering all that breadth 'cause it's only making you more inspiring to people like us. >> Exactly. >> We thank you so much for joining us on the program and sharing a little bit about you and what brought you to WiDS. Thank you so much, Rhonda. >> Yeah, thank you. >> Tracy: Thank you so much for being here. >> Lisa: Yeah. >> Alright. >> For our guests, and for Tracy Zhang, this is Lisa Martin live at Stanford University covering the eighth Annual Women In Data Science Conference. Stick around. Next guest will be here in just a second. (gentle music)

(upbeat music) >> Hey everyone. Welcome back to "The Cube"'s live coverage of "Women in Data Science 2023". As every year we are here live at Stanford University, profiling some amazing women and men in the fields of data science. I have my co-host for this segment is Hannah Freitag. Hannah is from Stanford's Data Journalism program, really interesting, check it out. We're very pleased to welcome our first guest of the day fresh from the keynote stage, Gayatree Ganu, the VP of Data Science at Meta. Gayatree, It's great to have you on the program. >> Likewise, Thank you for having me. >> So you have a PhD in Computer Science. You shared some really cool stuff. Everyone knows Facebook, everyone uses it. I think my mom might be one of the biggest users (Gayatree laughs) and she's probably watching right now. People don't realize there's so much data behind that and data that drives decisions that we engage with. But talk to me a little bit about you first, PhD in Computer Science, were you always, were you like a STEM kid? Little Gayatree, little STEM, >> Yeah, I was a STEM kid. I grew up in Mumbai, India. My parents are actually pharmacists, so they were not like math or stats or anything like that, but I was always a STEM kid. I don't know, I think it, I think I was in sixth grade when we got our first personal computer and I obviously used it as a Pacman playing machine. >> Oh, that's okay. (all laugh) >> But I was so good at, and I, I honestly believe I think being good at games kind of got me more familiar and comfortable with computers. Yeah. I think I always liked computers, I, yeah. >> And so now you lead, I'm looking at my notes here, the Engagement Ecosystem and Monetization Data Science teams at Facebook, Meta. Talk about those, what are the missions of those teams and how does it impact the everyday user? >> Yeah, so the engagement is basically users coming back to our platform more, there's, no better way for users to tell us that they are finding value on the things that we are doing on Facebook, Instagram, WhatsApp, all the other products than coming back to our platform more. So the Engagement Ecosystem team is looking at trends, looking at where there are needs, looking at how users are changing their behaviors, and you know, helping build strategy for the long term, using that data knowledge. Monetization is very different. You know, obviously the top, top apex goal is have a sustainable business so that we can continue building products for our users. And so, but you know, I said this in my keynote today, it's not about making money, our mission statement is not, you know, maximize as much money as you can make. It's about building a meaningful connection between businesses, customers, users, and, you know especially in these last two or three funky, post-pandemic years, it's been such a big, an important thing to do for small businesses all over all, all around the world for users to find like goods and services and products that they care about and that they can connect to. So, you know, there is truly an connection between my engagement world and the monetization world. And you know, it's not very clear always till you go in to, like, you peel the layers. Everything we do in the ads world is also always first with users as our, you know, guiding principle. >> Yeah, you mentioned how you supported especially small businesses also during the pandemic. You touched a bit upon it in the keynote speech. Can you tell our audience what were like special or certain specific programs you implemented to support especially small businesses during these times? >> Yeah, so there are 200 million businesses on our platform. A lot of them small businesses, 10 million of them run ads. So there is a large number of like businesses on our platform who, you know use the power of social media to connect to the customers that matter to them, to like you, you know use the free products that we built. In the post-pandemic years, we built a lot of stuff very quickly when Covid first hit for business to get the word out, right? Like, they had to announce when special shopping hours existed for at-risk populations, or when certain goods and services were available versus not. We had grants, there's $100 million grant that we gave out to small businesses. Users could show sort of, you know show their support with a bunch of campaigns that we ran, and of course we continue running ads. Our ads are very effective, I guess, and, you know getting a very reliable connection with from the customer to the business. And so, you know, we've run all these studies. We support, I talked about two examples today. One of them is the largest black-owned, woman black-owned wine company, and how they needed to move to an online program and, you know, we gave them a grant, and supported them through their ads campaign and, you know, they saw 60% lift in purchases, or something like that. So, a lot of good stories, small stories, you know, on a scale of 200 million, that really sort of made me feel proud about the work we do. And you know, now more than ever before, I think people can connect so directly with businesses. You can WhatsApp them, I come from India, every business is on WhatsApp. And you can, you know, WhatsApp them, you can send them Facebook messages, and you can build this like direct connection with things that matter to you. >> We have this expectation that we can be connected anywhere. I was just at Mobile World Congress for MWC last week, where, obviously talking about connectivity. We want to be able to do any transaction, whether it's post on Facebook or call an Uber, or watch on Netflix if you're on the road, we expect that we're going to be connected. >> Yeah. >> And what we, I think a lot of us don't realize I mean, those of us in tech do, but how much data science is a facilitator of all of those interactions. >> Yeah! >> As we, Gayatree, as we talk about, like, any business, whether it is the black women-owned wine business, >> Yeah. >> great business, or a a grocer or a car dealer, everybody has to become data-driven. >> Yes. >> Because the consumer has the expectation. >> Yes. >> Talk about data science as a facilitator of just pretty much everything we are doing and conducting in our daily lives. >> Yeah, I think that's a great question. I think data science as a field wasn't really defined like maybe 15 years ago, right? So this is all in our lifetimes that we are seeing this. Even in data science today, People come from so many different backgrounds and bring their own expertise here. And I think we, you know, this conference, all of us get to define what that means and how we can bring data to do good in the world. Everything you do, as you said, there is a lot of data. Facebook has a lot of data, Meta has a lot of data, and how do we responsibly use this data? How do we use this data to make sure that we're, you know representing all diversity? You know, minorities? Like machine learning algorithms don't do well with small data, they do well with big data, but the small data matters. And how do you like, you know, bring that into algorithms? Yeah, so everything we do at Meta is very, very data-driven. I feel proud about that, to be honest, because while data gets a bad rap sometimes, having no data and making decisions in the blind is just the absolute worst thing you can do. And so, you know, we, the job as a data scientist at Facebook is to make sure that we use this data, use this responsibly, make sure that we are representing every aspect of the, you know, 3 billion users who come to our platform. Yeah, data serves all the products that we build here. >> The responsibility factor is, is huge. You know, we can't talk about AI without talking about ethics. One of the things that I was talking with Hannah and our other co-host, Tracy, about during our opening is something I just learned over the weekend. And that is that the CTO of ChatGPT is a woman. (Gayatree laughs) I didn't know that. And I thought, why isn't she getting more awareness? There's a lot of conversations with their CEO. >> Yeah. >> Everyone's using it, playing around with it. I actually asked it yesterday, "What's hot in Data Science?" (all laugh) I was like, should I have asked that to let itself in, what's hot? (Gayatree laughs) But it, I thought that was phenomenal, and we need to be talking about this more. >> Yeah. >> This is something that they're likening to the launch of the iPhone, which has transformed our lives. >> I know, it is. >> ChatGPT, and its chief technologist is a female, how great is that? >> And I don't know whether you, I don't know the stats around this, but I think CTO is even less, it's even more rare to have a woman there, like you have women CEOs because I mean, we are building upon years and years of women not choosing technical fields and not choosing STEM, and it's going to take some time, but yeah, yeah, she's a woman. Isn't it amazing? It's wonderful. >> Yes, there was a great, there's a great "Fast Company" article on her that I was looking at yesterday and I just thought, we need to do what we can to help spread, Mira Murati is her name, because what she's doing is, one of the biggest technological breakthroughs we may ever see in our lifetime. It gives me goosebumps just thinking about it. (Gayatree laughs) I also wanted to share some stats, oh, sorry, go ahead, Hannah. >> Yeah, I was going to follow up on the thing that you mentioned that we had many years with like not enough women choosing a career path in STEM and that we have to overcome this trend. What are some, like what is some advice you have like as the Vice-President Data Science? Like what can we do to make this feel more, you know, approachable and >> Yeah. >> accessible for women? >> Yeah, I, there's so much that we have done already and you know, want to continue, keep doing. Of course conferences like these were, you know and I think there are high school students here there are students from my Alma Mater's undergrad year. It's amazing to like get all these women together to get them to see what success could look like. >> Yeah. >> What being a woman leader in this space could look like. So that's, you know, that's one, at Meta I lead recruiting at Meta and we've done a bunch to sort of open up the thinking around data science and technical jobs for women. Simple things like what you write in your job description. I don't know whether you know this, or this is a story you've heard before, when you see, when you have a job description and there are like 10 things that you need to, you know be good at to apply to this job, a woman sees those 10 and says, okay, I don't meet the qualifications of one of them and she doesn't apply. And a man sees one that he meets the qualifications to and he applies. And so, you know, there's small things you can do, and just how you write your job description, what goals you set for diversity and inclusion for your own organization. We have goals, Facebook's always been pretty up there in like, you know, speaking out for diversity and Sheryl Sandberg has been our Chief Business Officer for a very long time and she's been, like, amazing at like pushing from more women. So yeah, every step of the way, I think, we made a lot of progress, to be honest. I do think women choose STEM fields a lot more than they did. When I did my Computer Science I was often one of one or two women in the Computer Science class. It takes some time to, for it to percolate all the way to like having more CTOs and CEOs, >> Yeah. >> but it's going to happen in our lifetime, and you know, three of us know this, women are going to rule the world, and it (laughs) >> Drop the mic, girl! >> And it's going to happen in our lifetime, so I'm excited about it. >> And we have responsibility in helping make that happen. You know, I'm curious, you were in STEM, you talked about Computer Science, being one of the only females. One of the things that the nadb.org data from 2022 showed, some good numbers, the number of women in technical roles is now 27.6%, I believe, so up from 25, it's up in '22, which is good, more hiring of women. >> Yeah. >> One of the biggest challenges is attrition. What keeps you motivated? >> Yeah. >> To stay what, where you are doing what you're doing, managing a family and helping to drive these experiences at Facebook that we all expect are just going to happen? >> Yeah, two things come to mind. It does take a village. You do need people around you. You know, I'm grateful for my husband. You talked about managing a family, I did the very Indian thing and my parents live with us, and they help take care of the kids. >> Right! (laughs) >> (laughs) My kids are young, six and four, and I definitely needed help over the last few years. It takes mentors, it takes other people that you look up to, who've gone through all of those same challenges and can, you know, advise you to sort of continue working in the field. I remember when my kid was born when he was six months old, I was considering quitting. And my husband's like, to be a good role model for your children, you need to continue working. Like, just being a mother is not enough. And so, you know, so that's one. You know, the village that you build around you your supporters, your mentors who keep encouraging you. Sheryl Sandberg said this to me in my second month at Facebook. She said that women drop out of technical fields, they become managers, they become sort of administrative more, in their nature of their work, and her advice was, "Don't do that, Don't stop the technical". And I think that's the other thing I'd say to a lot of women. Technical stuff is hard, but you know, keeping up with that and keeping sort of on top of it actually does help you in the long run. And it's definitely helped me in my career at Facebook. >> I think one of the things, and Hannah and I and Tracy talked about this in the open, and I think you'll agree with us, is the whole saying of you can't be what you can't see, and I like to way, "Well, you can be what you can see". That visibility, the great thing that WiDS did, of having you on the stage as a speaker this morning so people can understand, everyone, like I said, everyone knows Meta, >> Yeah. >> everyone uses Facebook. And so it's important to bring that connection, >> Yeah. >> of how data is driving the experiences, the fact that it's User First, but we need to be able to see women in positions, >> Yes. >> like you, especially with Sheryl stepping down moving on to something else, or people that are like YouTube influencers, that have no idea that the head of YouTube for a very long time, Susan Wojcicki is a woman. >> (laughs) Yes. Who pioneered streaming, and I mean how often do you are you on YouTube every day? >> Yep, every day. >> But we have to be able to see and and raise the profile of these women and learn from them and be inspired, >> Absolutely. >> to keep going and going. I like what I do, I'm making a difference here. >> Yeah, yeah, absolutely. >> And I can be the, the sponsor or the mentor for somebody down the road. >> Absolutely. >> Yeah, and then referring back to what we talked in the beginning, show that data science is so diverse and it doesn't mean if you're like in IT, you're like sitting in your dark room, >> Right. (laughs) >> coding all day, but you know, >> (laughs) Right! >> to show the different facets of this job and >> Right! >> make this appealing to women, >> Yeah. for sure. >> And I said this in my keynote too, you know, one of the things that helped me most is complimenting the data and the techniques and the algorithms with how you work with people, and you know, empathy and alignment building and leadership, strategic thinking. And I think honestly, I think women do a lot of this stuff really well. We know how to work with people and so, you know, I've seen this at Meta for sure, like, you know, all of these skills soft skills, as we call them, go a long way, and like, you know, doing the right things and having a lasting impact. And like I said, women are going to rule the world, you know, in our lifetimes. (laughs) >> Oh, I can't, I can't wait to see that happen. There's some interesting female candidates that are already throwing their hats in the ring for the next presidential election. >> Yes. >> So we'll have to see where that goes. But some of the things that are so interesting to me, here we are in California and Palo Alto, technically Stanford is its own zip code, I believe. And we're in California, we're freaking out because we've gotten so much rain, it's absolutely unprecedented. We need it, we had a massive drought, an extreme drought, technically, for many years. I've got friends that live up in Tahoe, I've been getting pictures this morning of windows that are >> (laughs) that are covered? >> Yes, actually, yes. (Gayatree laughs) That, where windows like second-story windows are covered in snow. >> Yeah. >> Climate change. >> Climate change. >> There's so much that data science is doing to power and power our understanding of climate change whether it's that, or police violence. >> Yeah. (all talk together) >> We had talk today on that it was amazing. >> Yes. So I want more people to know what data science is really facilitating, that impacts all of us, whether you're in a technical role or not. >> And data wins arguments. >> Yes, I love that! >> I said this is my slide today, like, you know, there's always going to be doubters and naysayers and I mean, but there's hard evidence, there's hard data like, yeah. In all of these fields, I mean the data that climate change, the data science that we have done in the environmental and climate change areas and medical, and you know, medicine professions just so much, so much more opportunity, and like, how much we can learn more about the world. >> Yeah. >> Yeah, it's a pretty exciting time to be a data scientist. >> I feel like, we're just scratching the surface. >> Yeah. >> With the potential and the global impact that we can make with data science. Gayatree, it's been so great having you on theCUBE, thank you. >> Right, >> Thank you so much, Gayatree. >> So much, I love, >> Thank you. >> I'm going to take Data WiD's arguments into my personal life. (Gayatree laughs) I was actually just, just a quick anecdote, funny story. I was listening to the radio this morning and there was a commercial from an insurance company and I guess the joke is, it's an argument between two spouses, and the the voiceover comes in and says, "Let's watch a replay". I'm like, if only they, then they got the data that helped the woman win the argument. (laughs) >> (laughs) I will warn you it doesn't always help with arguments I have with my husband. (laughs) >> Okay, I'm going to keep it in the middle of my mind. >> Yes! >> Gayatree, thank you so much. >> Thank you so much, >> for sharing, >> Thank you both for the opportunity. >> And being a great female that we can look up to, we really appreciate your insights >> Oh, likewise. >> and your time. >> Thank you. >> All right, for our guest, for Hannah Freitag, I'm Lisa Martin, live at Stanford University covering "Women in Data Science '23". Stick around, our next guest joins us in just a minute. (upbeat music) I have been in the software and technology industry for over 12 years now, so I've had the opportunity as a marketer to really understand and interact with customers across the entire buyer's journey. Hi, I'm Lisa Martin and I'm a host of theCUBE. (upbeat music) Being a host on theCUBE has been a dream of mine for the last few years. I had the opportunity to meet Jeff and Dave and John at EMC World a few years ago and got the courage up to say, "Hey, I'm really interested in this. I love talking with customers, gimme a shot, let me come into the studio and do an interview and see if we can work together". I think where I really impact theCUBE is being a female in technology. We interview a lot of females in tech, we do a lot of women in technology events and one of the things I.

(upbeat music) >> Morning guys and girls, welcome back to theCUBE's live coverage of Women in Data Science WIDS 2023 live at Stanford University. Lisa Martin here with my co-host for this segment, Tracy Zhang. We're really excited to be talking with a great female rockstar. You're going to learn a lot from her next, Jacqueline Kuo, solutions engineer at Dataiku. Welcome, Jacqueline. Great to have you. >> Thank you so much. >> Thank for being here. >> I'm so excited to be here. >> So one of the things I have to start out with, 'cause my mom Kathy Dahlia is watching, she's a New Yorker. You are a born and raised New Yorker and I learned from my mom and others. If you're born in New York no matter how long you've moved away, you are a New Yorker. There's you guys have like a secret club. (group laughs) >> I am definitely very proud of being born and raised in New York. My family immigrated to New York, New Jersey from Taiwan. So very proud Taiwanese American as well. But I absolutely love New York and I can't imagine living anywhere else. >> Yeah, yeah. >> I love it. >> So you studied, I was doing some research on you you studied mechanical engineering at MIT. >> Yes. >> That's huge. And you discovered your passion for all things data-related. You worked at IBM as an analytics consultant. Talk to us a little bit about your career path. Were you always interested in engineering STEM-related subjects from the time you were a child? >> I feel like my interests were ranging in many different things and I ended up landing in engineering, 'cause I felt like I wanted to gain a toolkit like a toolset to make some sort of change with or use my career to make some sort of change in this world. And I landed on engineering and mechanical engineering specifically, because I felt like I got to, in my undergrad do a lot of hands-on projects, learn every part of the engineering and design process to build products which is super-transferable and transferable skills sort of is like the trend in my career so far. Where after undergrad I wanted to move back to New York and mechanical engineering jobs are kind of few and fall far in between in the city. And I ended up landing at IBM doing analytics consulting, because I wanted to understand how to use data. I knew that data was really powerful and I knew that working with it could allow me to tell better stories to influence people across different industries. And that's also how I kind of landed at Dataiku to my current role, because it really does allow me to work across different industries and work on different problems that are just interesting. >> Yeah, I like the way that, how you mentioned building a toolkit when doing your studies at school. Do you think a lot of skills are still very relevant to your job at Dataiku right now? >> I think that at the core of it is just problem solving and asking questions and continuing to be curious or trying to challenge what is is currently given to you. And I think in an engineering degree you get a lot of that. >> Yeah, I'm sure. >> But I think that we've actually seen that a lot in the panels today already, that you get that through all different types of work and research and that kind of thoughtfulness comes across in all different industries too. >> Talk a little bit about some of the challenges, that data science is solving, because every company these days, whether it's an enterprise in manufacturing or a small business in retail, everybody has to be data-driven, because the end user, the end customer, whoever that is whether it's a person, an individual, a company, a B2B, expects to have a personalized custom experience and that comes from data. But you have to be able to understand that data treated properly, responsibly. Talk about some of the interesting projects that you're doing at Dataiku or maybe some that you've done in the past that are really kind of transformative across things climate change or police violence, some of the things that data science really is impacting these days. >> Yeah, absolutely. I think that what I love about coming to these conferences is that you hear about those really impactful social impact projects that I think everybody who's in data science wants to be working on. And I think at Dataiku what's great is that we do have this program called Ikig.AI where we work with nonprofits and we support them in their data and analytics projects. And so, a project I worked on was with the Clean Water, oh my goodness, the Ocean Cleanup project, Ocean Cleanup organization, which was amazing, because it was sort of outside of my day-to-day and it allowed me to work with them and help them understand better where plastic is being aggregated across the world and where it appears, whether that's on beaches or in lakes and rivers. So using data to help them better understand that. I feel like from a day-to-day though, we, in terms of our customers, they're really looking at very basic problems with data. And I say basic, not to diminish it, but really just to kind of say that it's high impact, but basic problems around how do they forecast sales better? That's a really kind of, sort of basic problem, but it's actually super-complex and really impactful for people, for companies when it comes to forecasting how much headcount they need to have in the next year or how much inventory to have if they're retail. And all of those are going to, especially for smaller companies, make a huge impact on whether they make profit or not. And so, what's great about working at Dataiku is you get to work on these high-impact projects and oftentimes I think from my perspective, I work as a solutions engineer on the commercial team. So it's just, we work generally with smaller customers and sometimes talking to them, me talking to them is like their first introduction to what data science is and what they can do with that data. And sort of using our platform to show them what the possibilities are and help them build a strategy around how they can implement data in their day-to-day. >> What's the difference? You were a data scientist by title and function, now you're a solutions engineer. Talk about the ascendancy into that and also some of the things that you and Tracy will talk about as those transferable, those transportable skills that probably maybe you learned in engineering, you brought data science now you're bringing to solutions engineering. >> Yeah, absolutely. So data science, I love working with data. I love getting in the weeds of things and I love, oftentimes that means debugging things or looking line by line at your code and trying to make it better. I found that on in the data science role, while those things I really loved, sometimes it also meant that I didn't, couldn't see or didn't have visibility into the broader picture of well like, well why are we doing this project? And who is it impacting? And because oftentimes your day-to-day is very much in the weeds. And so, I moved into sales or solutions engineering at Dataiku to get that perspective, because what a sales engineer does is support the sale from a technical perspective. And so, you really truly understand well, what is the customer looking for and what is going to influence them to make a purchase? And how do you tell the story of the impact of data? Because oftentimes they need to quantify well, if I purchase a software like Dataiku then I'm able to build this project and make this X impact on the business. And that is really powerful. That's where the storytelling comes in and that I feel like a lot of what we've been hearing today about connecting data with people who can actually do something with that data. That's really the bridge that we as sales engineers are trying to connect in that sales process. >> It's all about connectivity, isn't it? >> Yeah, definitely. We were talking about this earlier that it's about making impact and it's about people who we are analyzing data is like influencing. And I saw that one of the keywords or one of the biggest thing at Dataiku is everyday AI, so I wanted to just ask, could you please talk more about how does that weave into the problem solving and then day-to-day making an impact process? >> Yes, so I started working on Dataiku around three years ago and I fell in love with the product itself. The product that we have is we allow for people with different backgrounds. If you're coming from a data analyst background, data science, data engineering, maybe you are more of like a business subject matter expert, to all work in one unified central platform, one user interface. And why that's powerful is that when you're working with data, it's not just that data scientist working on their own and their own computer coding. We've heard today that it's all about connecting the data scientists with those business people, with maybe the data engineers and IT people who are actually going to put that model into production or other folks. And so, they all use different languages. Data scientists might use Python and R, your business people are using PowerPoint and Excel, everyone's using different tools. How do we bring them all in one place so that you can have conversations faster? So the business people can understand exactly what you're building with the data and can get their hands on that data and that model prediction faster. So that's what Dataiku does. That's the product that we have. And I completely forgot your question, 'cause I got so invested in talking about this. Oh, everyday AI. Yeah, so the goal of of Dataiku is really to allow for those maybe less technical people with less traditional data science backgrounds. Maybe they're data experts and they understand the data really well and they've been working in SQL for all their career. Maybe they're just subject matter experts and want to get more into working with data. We allow those people to do that through our no and low-code tools within our platform. Platform is very visual as well. And so, I've seen a lot of people learn data science, learn machine learning by working in the tool itself. And that's sort of, that's where everyday AI comes in, 'cause we truly believe that there are a lot of, there's a lot of unutilized expertise out there that we can bring in. And if we did give them access to data, imagine what we could do in the kind of work that they can do and become empowered basically with that. >> Yeah, we're just scratching the surface. I find data science so fascinating, especially when you talk about some of the real world applications, police violence, health inequities, climate change. Here we are in California and I don't know if you know, we're experiencing an atmospheric river again tomorrow. Californians and the rain- >> Storm is coming. >> We are not good... And I'm a native Californian, but we all know about climate change. People probably don't associate all of the data that is helping us understand it, make decisions based on what's coming what's happened in the past. I just find that so fascinating. But I really think we're truly at the beginning of really understanding the impact that being data-driven can actually mean whether you are investigating climate change or police violence or health inequities or your a grocery store that needs to become data-driven, because your consumer is expecting a personalized relevant experience. I want you to offer me up things that I know I was doing online grocery shopping, yesterday, I just got back from Europe and I was so thankful that my grocer is data-driven, because they made the process so easy for me. And but we have that expectation as consumers that it's going to be that easy, it's going to be that personalized. And what a lot of folks don't understand is the data the democratization of data, the AI that's helping make that a possibility that makes our lives easier. >> Yeah, I love that point around data is everywhere and the more we have, the actually the more access we actually are providing. 'cause now compute is cheaper, data is literally everywhere, you can get access to it very easily. And so, I feel like more people are just getting themselves involved and that's, I mean this whole conference around just bringing more women into this industry and more people with different backgrounds from minority groups so that we get their thoughts, their opinions into the work is so important and it's becoming a lot easier with all of the technology and tools just being open source being easier to access, being cheaper. And that I feel really hopeful about in this field. >> That's good. Hope is good, isn't it? >> Yes, that's all we need. But yeah, I'm glad to see that we're working towards that direction. I'm excited to see what lies in the future. >> We've been talking about numbers of women, percentages of women in technical roles for years and we've seen it hover around 25%. I was looking at some, I need to AnitaB.org stats from 2022 was just looking at this yesterday and the numbers are going up. I think the number was 26, 27.6% of women in technical roles. So we're seeing a growth there especially over pre-pandemic levels. Definitely the biggest challenge that still seems to be one of the biggest that remains is attrition. I would love to get your advice on what would you tell your younger self or the previous prior generation in terms of having the confidence and the courage to pursue engineering, pursue data science, pursue a technical role, and also stay in that role so you can be one of those females on stage that we saw today? >> Yeah, that's the goal right there one day. I think it's really about finding other people to lift and mentor and support you. And I talked to a bunch of people today who just found this conference through Googling it, and the fact that organizations like this exist really do help, because those are the people who are going to understand the struggles you're going through as a woman in this industry, which can get tough, but it gets easier when you have a community to share that with and to support you. And I do want to definitely give a plug to the WIDS@Dataiku team. >> Talk to us about that. >> Yeah, I was so fortunate to be a WIDS ambassador last year and again this year with Dataiku and I was here last year as well with Dataiku, but we have grown the WIDS effort so much over the last few years. So the first year we had two events in New York and also in London. Our Dataiku's global. So this year we additionally have one in the west coast out here in SF and another one in Singapore which is incredible to involve that team. But what I love is that everyone is really passionate about just getting more women involved in this industry. But then also what I find fortunate too at Dataiku is that we have a strong female, just a lot of women. >> Good. >> Yeah. >> A lot of women working as data scientists, solutions engineer and sales and all across the company who even if they aren't doing data work in a day-to-day, they are super-involved and excited to get more women in the technical field. And so. that's like our Empower group internally that hosts events and I feel like it's a really nice safe space for all of us to speak about challenges that we encounter and feel like we're not alone in that we have a support system to make it better. So I think from a nutrition standpoint every organization should have a female ERG to just support one another. >> Absolutely. There's so much value in a network in the community. I was talking to somebody who I'm blanking on this may have been in Barcelona last week, talking about a stat that showed that a really high percentage, 78% of people couldn't identify a female role model in technology. Of course, Sheryl Sandberg's been one of our role models and I thought a lot of people know Sheryl who's leaving or has left. And then a whole, YouTube influencers that have no idea that the CEO of YouTube for years has been a woman, who has- >> And she came last year to speak at WIDS. >> Did she? >> Yeah. >> Oh, I missed that. It must have been, we were probably filming. But we need more, we need to be, and it sounds like Dataiku was doing a great job of this. Tracy, we've talked about this earlier today. We need to see what we can be. And it sounds like Dataiku was pioneering that with that ERG program that you talked about. And I completely agree with you. That should be a standard program everywhere and women should feel empowered to raise their hand ask a question, or really embrace, "I'm interested in engineering, I'm interested in data science." Then maybe there's not a lot of women in classes. That's okay. Be the pioneer, be that next Sheryl Sandberg or the CTO of ChatGPT, Mira Murati, who's a female. We need more people that we can see and lean into that and embrace it. I think you're going to be one of them. >> I think so too. Just so that young girls like me like other who's so in school, can see, can look up to you and be like, "She's my role model and I want to be like her. And I know that there's someone to listen to me and to support me if I have any questions in this field." So yeah. >> Yeah, I mean that's how I feel about literally everyone that I'm surrounded by here. I find that you find role models and people to look up to in every conversation whenever I'm speaking with another woman in tech, because there's a journey that has had happen for you to get to that place. So it's incredible, this community. >> It is incredible. WIDS is a movement we're so proud of at theCUBE to have been a part of it since the very beginning, since 2015, I've been covering it since 2017. It's always one of my favorite events. It's so inspiring and it just goes to show the power that data can have, the influence, but also just that we're at the beginning of uncovering so much. Jacqueline's been such a pleasure having you on theCUBE. Thank you. >> Thank you. >> For sharing your story, sharing with us what Dataiku was doing and keep going. More power to you girl. We're going to see you up on that stage one of these years. >> Thank you so much. Thank you guys. >> Our pleasure. >> Our pleasure. >> For our guests and Tracy Zhang, this is Lisa Martin, you're watching theCUBE live at WIDS '23. #EmbraceEquity is this year's International Women's Day theme. Stick around, our next guest joins us in just a minute. (upbeat music)

(ambient music) >> Good morning, everyone. Lisa Martin with theCUBE, live at the eighth Annual Women in Data Science Conference. This is one of my absolute favorite events of the year. We engage with tons of great inspirational speakers, men and women, and what's happening with WiDS is a global movement. I've got two fabulous co-hosts with me today that you're going to be hearing and meeting. Please welcome Tracy Zhang and Hannah Freitag, who are both from the sata journalism program, master's program, at Stanford. So great to have you guys. >> So excited to be here. >> So data journalism's so interesting. Tracy, tell us a little bit about you, what you're interested in, and then Hannah we'll have you do the same thing. >> Yeah >> Yeah, definitely. I definitely think data journalism is very interesting, and in fact, I think, what is data journalism? Is definitely one of the big questions that we ask during the span of one year, which is the length of our program. And yeah, like you said, I'm in this data journalism master program, and I think coming in I just wanted to pivot from my undergrad studies, which is more like a traditional journalism, into data. We're finding stories through data, so that's why I'm also very excited about meeting these speakers for today because they're all, they have different backgrounds, but they all ended up in data science. So I think they'll be very inspirational and I can't wait to talk to them. >> Data in stories, I love that. Hannah, tell us a little bit about you. >> Yeah, so before coming to Stanford, I was a research assistant at Humboldt University in Berlin, so I was in political science research. And I love to work with data sets and data, but I figured that, for me, I don't want this story to end up in a research paper, which is only very limited in terms of the audience. And I figured, okay, data journalism is the perfect way to tell stories and use data to illustrate anecdotes, but to make it comprehensive and accessible for a broader audience. So then I found this program at Stanford and I was like, okay, that's the perfect transition from political science to journalism, and to use data to tell data-driven stories. So I'm excited to be in this program, I'm excited for the conference today and to hear from these amazing women who work in data science. >> You both brought up great points, and we were chatting earlier that there's a lot of diversity in background. >> Tracy: Definitely. >> Not everyone was in STEM as a young kid or studied computer science. Maybe some are engineering, maybe some are are philosophy or economic, it's so interesting. And what I find year after year at WiDS is it brings in so much thought diversity. And that's what being data-driven really demands. It demands that unbiased approach, that diverse, a spectrum of diverse perspectives, and we definitely get that at WiDS. There's about 350 people in person here, but as I mentioned in the opening, hundreds of thousands will engage throughout the year, tens of thousands probably today at local events going on across the globe. And it just underscores the importance of every organization, whether it's a bank or a grocer, has to be data-driven. We have that expectation as consumers in our consumer lives, and even in our business lives, that I'm going to engage with a business, whatever it is, and they're going to know about me, they're going to deliver me a personalized experience that's relevant to me and my history. And all that is powered by data science, which is I think it's fascinating. >> Yeah, and the great way is if you combine data with people. Because after all, large data sets, they oftentimes consist of stories or data that affects people. And to find these stories or advanced research in whatever fields, maybe in the financial business, or in health, as you mentioned, the variety of fields, it's very powerful, powerful tool to use. >> It's a very power, oh, go ahead Tracy. >> No, definitely. I just wanted to build off of that. It's important to put a face on data. So a dataset without a name is just some numbers, but if there's a story, then I think it means something too. And I think Margot was talking about how data science is about knowing or understanding the past, I think that's very interesting. That's a method for us to know who we are. >> Definitely. There's so many opportunities. I wanted to share some of the statistics from AnitaB.org that I was just looking at from 2022. We always talk at events like WiDS, and some of the other women in tech things, theCUBE is very much pro-women in tech, and has been for a very long, since the beginning of theCUBE. But we've seen the numbers of women technologists historically well below 25%, and we see attrition rates are high. And so we often talk about, well, what can we do? And part of that is raising the awareness. And that's one of the great things about WiDS, especially WiDS happening on International Women's Day, today, March 8th, and around event- >> Tracy: A big holiday. >> Exactly. But one of the nice things I was looking at, the AnitaB.org research, is that representation of tech women is on the rise, still below pre-pandemic levels, but it's actually nearly 27% of women in technical roles. And that's an increase, slow increase, but the needle is moving. We're seeing much more gender diversity across a lot of career levels, which is exciting. But some of the challenges remain. I mean, the representation of women technologists is growing, except at the intern level. And I thought that was really poignant. We need to be opening up that pipeline and going younger. And you'll hear a lot of those conversations today about, what are we doing to reach girls in grade school, 10 year olds, 12 year olds, those in high school? How do we help foster them through their undergrad studies- >> And excite them about science and all these fields, for sure. >> What do you think, Hannah, on that note, and I'll ask you the same question, what do you think can be done? The theme of this year's International Women's Day is Embrace Equity. What do you think can be done on that intern problem to help really dial up the volume on getting those younger kids interested, one, earlier, and two, helping them stay interested? >> Yeah. Yeah, that's a great question. I think it's important to start early, as you said, in school. Back in the day when I went to high school, we had this one day per year where we could explore as girls, explore a STEM job and go into the job for one day and see how it's like to work in a, I dunno, in IT or in data science, so that's a great first step. But as you mentioned, it's important to keep girls and women excited about this field and make them actually pursue this path. So I think conferences or networking is very powerful. Also these days with social media and technology, we have more ability and greater ways to connect. And I think we should even empower ourselves even more to pursue this path if we're interested in data science, and not be like, okay, maybe it's not for me, or maybe as a woman I have less chances. So I think it's very important to connect with other women, and this is what WiDS is great about. >> WiDS is so fantastic for that network effect, as you talked about. It's always such, as I was telling you about before we went live, I've covered five or six WiDS for theCUBE, and it's always such a day of positivity, it's a day of of inclusivity, which is exactly what Embrace Equity is really kind of about. Tracy, talk a little bit about some of the things that you see that will help with that hashtag Embrace Equity kind of pulling it, not just to tech. Because we're talking and we saw Meta was a keynote who's going to come to talk with Hannah and me in a little bit, we see Total Energies on the program today, we see Microsoft, Intuit, Boeing Air Company. What are some of the things you think that can be done to help inspire, say, little Tracy back in the day to become interested in STEM or in technology or in data? What do you think companies can and should be doing to dial up the volume for those youngsters? >> Yeah, 'cause I think somebody was talking about, one of the keynote speakers was talking about how there is a notion that girls just can't be data scientists. girls just can't do science. And I think representation definitely matters. If three year old me see on TV that all the scientists are women, I think I would definitely have the notion that, oh, this might be a career choice for me and I can definitely also be a scientist if I want. So yeah, I think representation definitely matters and that's why conference like this will just show us how these women are great in their fields. They're great data scientists that are bringing great insight to the company and even to the social good as well. So yeah, I think that's very important just to make women feel seen in this data science field and to listen to the great woman who's doing amazing work. >> Absolutely. There's a saying, you can't be what you can't see. >> Exactly. >> And I like to say, I like to flip it on its head, 'cause we can talk about some of the negatives, but there's a lot of positives and I want to share some of those in a minute, is that we need to be, that visibility that you talked about, the awareness that you talked about, it needs to be there but it needs to be sustained and maintained. And an organization like WiDS and some of the other women in tech events that happen around the valley here and globally, are all aimed at raising the profile of these women so that the younger, really, all generations can see what they can be. We all, the funny thing is, we all have this expectation whether we're transacting on Uber ride or we are on Netflix or we're buying something on Amazon, we can get it like that. They're going to know who I am, they're going to know what I want, they're going to want to know what I just bought or what I just watched. Don't serve me up something that I've already done that. >> Hannah: Yeah. >> Tracy: Yeah. >> So that expectation that everyone has is all about data, though we don't necessarily think about it like that. >> Hannah: Exactly. >> Tracy: Exactly. >> But it's all about the data that, the past data, the data science, as well as the realtime data because we want to have these experiences that are fresh, in the moment, and super relevant. So whether women recognize it or not, they're data driven too. Whether or not you're in data science, we're all driven by data and we have these expectations that every business is going to meet it. >> Exactly. >> Yeah. And circling back to young women, I think it's crucial and important to have role models. As you said, if you see someone and you're younger and you're like, oh I want to be like her. I want to follow this path, and have inspiration and a role model, someone you look up to and be like, okay, this is possible if I study the math part or do the physics, and you kind of have a goal and a vision in mind, I think that's really important to drive you. >> Having those mentors and sponsors, something that's interesting is, I always, everyone knows what a mentor is, somebody that you look up to, that can guide you, that you admire. I didn't learn what a sponsor was until a Women in Tech event a few years ago that we did on theCUBE. And I was kind of, my eyes were open but I didn't understand the difference between a mentor and a sponsor. And then it got me thinking, who are my sponsors? And I started going through LinkedIn, oh, he's a sponsor, she's a sponsor, people that help really propel you forward, your recommenders, your champions, and it's so important at every level to build that network. And we have, to your point, Hannah, there's so much potential here for data drivenness across the globe, and there's so much potential for women. One of the things I also learned recently , and I wanted to share this with you 'cause I'm not sure if you know this, ChatGPT, exploding, I was on it yesterday looking at- >> Everyone talking about it. >> What's hot in data science? And it was kind of like, and I actually asked it, what was hot in data science in 2023? And it told me that it didn't know anything prior to 2021. >> Tracy: Yes. >> Hannah: Yeah. >> So I said, Oh, I'm so sorry. But everyone's talking about ChatGPT, it is the most advanced AI chatbot ever released to the masses, it's on fire. They're likening it to the launch of the iPhone, 100 million-plus users. But did you know that the CTO of ChatGPT is a woman? >> Tracy: I did not know, but I learned that. >> I learned that a couple days ago, Mira Murati, and of course- >> I love it. >> She's been, I saw this great profile piece on her on Fast Company, but of course everything that we're hearing about with respect to ChatGPT, a lot on the CEO. But I thought we need to help dial up the profile of the CTO because she's only 35, yet she is at the helm of one of the most groundbreaking things in our lifetime we'll probably ever see. Isn't that cool? >> That is, yeah, I completely had no idea. >> I didn't either. I saw it on LinkedIn over the weekend and I thought, I have to talk about that because it's so important when we talk about some of the trends, other trends from AnitaB.org, I talked about some of those positive trends. Overall hiring has rebounded in '22 compared to pre-pandemic levels. And we see also 51% more women being hired in '22 than '21. So the data, it's all about data, is showing us things are progressing quite slowly. But one of the biggest challenges that's still persistent is attrition. So we were talking about, Hannah, what would your advice be? How would you help a woman stay in tech? We saw that attrition last year in '22 according to AnitaB.org, more than doubled. So we're seeing women getting into the field and dropping out for various reasons. And so that's still an extent concern that we have. What do you think would motivate you to stick around if you were in a technical role? Same question for you in a minute. >> Right, you were talking about how we see an increase especially in the intern level for women. And I think if, I don't know, this is a great for a start point for pushing the momentum to start growth, pushing the needle rightwards. But I think if we can see more increase in the upper level, the women representation in the upper level too, maybe that's definitely a big goal and something we should work towards to. >> Lisa: Absolutely. >> But if there's more representation up in the CTO position, like in the managing level, I think that will definitely be a great factor to keep women in data science. >> I was looking at some trends, sorry, Hannah, forgetting what this source was, so forgive me, that was showing that there was a trend in the last few years, I think it was Fast Company, of more women in executive positions, specifically chief operating officer positions. What that hasn't translated to, what they thought it might translate to, is more women going from COO to CEO and we're not seeing that. We think of, if you ask, name a female executive that you'd recognize, everyone would probably say Sheryl Sandberg. But I was shocked to learn the other day at a Women in Tech event I was doing, that there was a survey done by this organization that showed that 78% of people couldn't identify. So to your point, we need more of them in that visible role, in the executive suite. >> Tracy: Exactly. >> And there's data that show that companies that have women, companies across industries that have women in leadership positions, executive positions I should say, are actually more profitable. So it's kind of like, duh, the data is there, it's telling you this. >> Hannah: Exactly. >> Right? >> And I think also a very important point is work culture and the work environment. And as a woman, maybe if you enter and you work two or three years, and then you have to oftentimes choose, okay, do I want family or do I want my job? And I think that's one of the major tasks that companies face to make it possible for women to combine being a mother and being a great data scientist or an executive or CEO. And I think there's still a lot to be done in this regard to make it possible for women to not have to choose for one thing or the other. And I think that's also a reason why we might see more women at the entry level, but not long-term. Because they are punished if they take a couple years off if they want to have kids. >> I think that's a question we need to ask to men too. >> Absolutely. >> How to balance work and life. 'Cause we never ask that. We just ask the woman. >> No, they just get it done, probably because there's a woman on the other end whose making it happen. >> Exactly. So yeah, another thing to think about, another thing to work towards too. >> Yeah, it's a good point you're raising that we have this conversation together and not exclusively only women, but we all have to come together and talk about how we can design companies in a way that it works for everyone. >> Yeah, and no slight to men at all. A lot of my mentors and sponsors are men. They're just people that I greatly admire who saw raw potential in me 15, 18 years ago, and just added a little water to this little weed and it started to grow. In fact, theCUBE- >> Tracy: And look at you now. >> Look at me now. And theCUBE, the guys Dave Vellante and John Furrier are two of those people that are sponsors of mine. But it needs to be diverse. It needs to be diverse and gender, it needs to include non-binary people, anybody, shouldn't matter. We should be able to collectively work together to solve big problems. Like the propaganda problem that was being discussed in the keynote this morning with respect to China, or climate change. Climate change is a huge challenge. Here, we are in California, we're getting an atmospheric river tomorrow. And Californians and rain, we're not so friendly. But we know that there's massive changes going on in the climate. Data science can help really unlock a lot of the challenges and solve some of the problems and help us understand better. So there's so much real-world implication potential that being data-driven can really lead to. And I love the fact that you guys are studying data journalism. You'll have to help me understand that even more. But we're going to going to have great conversations today, I'm so excited to be co-hosting with both of you. You're going to be inspired, you're going to learn, they're going to learn from us as well. So let's just kind of think of this as a community of men, women, everything in between to really help inspire the current generations, the future generations. And to your point, let's help women feel confident to be able to stay and raise their hand for fast-tracking their careers. >> Exactly. >> What are you guys, last minute, what are you looking forward to most for today? >> Just meeting these great women, I can't wait. >> Yeah, learning from each other. Having this conversation about how we can make data science even more equitable and hear from the great ideas that all these women have. >> Excellent, girls, we're going to have a great day. We're so glad that you're here with us on theCUBE, live at Stanford University, Women in Data Science, the eighth annual conference. I'm Lisa Martin, my two co-hosts for the day, Tracy Zhang, Hannah Freitag, you're going to be seeing a lot of us, we appreciate. Stick around, our first guest joins Hannah and me in just a minute. (ambient music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

>>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.

>> Hi, and welcome to data cloud catalyst women in tech round table panel discussion. I am so excited to have three fantastic female executives with me today who have been driving transformation through data throughout their entire career. With me today is Lisa Davis SVP and CIO of Blue Shield of California. We also have Nishita Henry who is the chief innovation officer at Deloitte and Teresa Briggs, who is on a variety of board of directors, including our very own Snowflake. Welcome, ladies. >> Thank you. So I'm just going to dive right in. You all have really amazing careers and resumes behind you. I'm really curious, throughout your career, how have you seen the use of data evolve throughout your career? And Lisa, I'm going to start with you. >> Thank you. Having been in technology my entire career, technology and data has really evolved from being the province of a few in an organization to frankly being critical to everyone's business outcomes. But now every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation probably the last five, seven years. We've all talked about disrupt or be disrupted. At the core of that digital transformation is the use of data, data, and analytics that we derive insights from and actually improve our decision-making by driving a differentiated experience and capability into market. So data has involved as being, I would say, almost tactical in some sense over my technology career to really being a strategic asset of what we leveraged personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. >> Nishita curious your take on, how you've seen data evolve? >> Yeah, I agree with Lisa, it has definitely become the lifeblood of every business, right? It used to be that there were a few companies in the business of technology. Every business is now a technology business. Every business is a data business. It is the way that they go to market, shape the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in healthcare doesn't matter, right? Data is necessary for every business to survive and thrive. And I remember at the beginning of my career, data was always important, but it was about storing data. It was about giving people individual reports. It was about supplying that data to one person or one business unit in silos. And it then evolved right over the course of time and to integrating data and to saying, all right, how does one piece of data correlate to the other? And how can I get insights out of that data? Now let's go on to the point of how do I use that data to predict the future? How do I use that data to automate the future? How do I use that data not just for humans to make decisions but for other machines to make decisions, right? Which is a big leap and a big change in how we use data, how we analyze data and how we use it for insights and evolving our businesses. >> Yeah. It's really changed so tremendously, just in the past five years, it's amazing. So Teresa, we've talked a lot about the data cloud, where do you think we're heading with that? And also how can future leaders really guide their careers in data, especially in those jobs where we don't traditionally think of them in the data science space, curious your thoughts on that. >> Yeah. Well, since I'm on the Snowflake board, I'll talk a little bit about the Snowflake data cloud that we're getting your company's data out of the silos that exist all over your organization. We're bringing third party data in to combine with your own data and we're wrapping a governance structure around it and feeding it out to your employees so that they can get their jobs done. And it's as simple as that, I think we've all seen the pandemic accelerated the digitization of our work. And if you ever doubted that the future of work is here, it is here. And companies are scrambling to catch up by providing the right amount of data, collaboration tools, workflow tools for their workers to get their jobs done. Now it used to be, as prior, people have mentioned that in order to work with data, you had to be a data scientist. But I was an auditor back in the day and we used to work on 16 columns spreadsheet. And now if you're an accounting major coming out of college, joining an auditing firm, you have to be tech and data savvy because you're going to be extracting, manipulating, analyzing, and auditing data. That massive amounts of data that sit in your client's IT systems. I'm on the board of Warby Parker. And you might think that their most valuable asset is their amazing frame collection but it's actually their data. There are 360 degree view of the customer. And so if you're a merchant or you're in strategy or marketing or talent or the co-CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that any anyone who's a knowledge worker has to be able to work with data. >> Now, I think it's just going to be organic to every role going forward in the industry. >> So Lisa curious about your thoughts about data cloud, the future of it, and how people can really leverage it in their jobs from future leaders. >> Yeah, absolutely. Most enterprises today are, I would say, hybrid multi-cloud enterprises. What does that mean? That means that we have data sitting on prem. We have data sitting in public clouds through software, as a service applications. We have a data everywhere. Most enterprises have data everywhere. Certainly those that have owned infrastructure or weren't born on the web. One of the areas that I'd love that data cloud is addressing is the area around data portability and mobility. Because I have data sitting in various locations through my enterprise, how do I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes. And at Blue Shield of California, one of our key initiatives is what we call an experience cube. What does that mean? It means how do I drive transparency of data between providers and members and payers so that not only do I reduce overhead on providers and provide them a better experience or hospital systems or doctors, but ultimately how do we have the member have at their power of their fingertips the value of their data holistically so that we're making better decisions about their healthcare? One of the things Teresa was talking about was the use of this data. And I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists. Yes, we need those data scientists to help us build AI models to really drive and tackle these tougher challenges and business problems that we may have in our environments. But everybody in the company, both on the IT side, both on the business side, really need to understand of how do we become a data insights driven enterprise, put the power of the data into everyone's hands so that we can accelerate capabilities, right? And leverage that data to ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California. >> Yeah. It's really, really exciting time. I want to shift gears a little bit and focus on women in tech. So I think in the past 5 to 10 years there has been a lot of headway in this space but the truth is women are still underrepresented in the tech space. So what can we do to attract more women into technology? Quite honestly. So Nishita curious what your thoughts are on that? >> Great question. And I am so passionate about this for a lot of reasons, not the least of which is I have two daughters of my own and I know how important it is for women and young girls to actually start early in their love for technology and data and all things digital, right? So I think it's one very important to start early, starting early education, building confidence of young girls that they can do this, showing them role models. We at Deloitte just partnered with LOV engineer to actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes in techs solve everyday problems. And so really helping to get people's minds around tech is not just in the back office, coding on a computer, tech is about solving problems together that help us as citizens as customers, right? And as humanity. So I think that's important. I also think we have to expand that definition of tech as we just said, it's not just about database design. It's not just about Java and Python coding. It's about design, it's about the human machine interfaces. It's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say, look we have a absolute imperative to get a diverse population of people, not just women but minorities, those with other types of backgrounds, disabilities, et cetera, involved because this data is being used to drive decision-making, and if we're all involved and how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just 'cause we haven't involved a diverse enough group of people around it. >> Absolutely. Lisa, I'm curious about your thoughts on this. >> Oh, I agree with everything Nishita said. I've been passionate about this area. I think it starts with first, we need more role models. We need more role models as women in these leadership roles throughout various sectors. And it really is, it starts with us and helping to pull other women forward. So I think it certainly it's part of my responsibility. I think all of us as female executives that if you have a seat at the table to leverage that seat at the table to drive change to bring more women forward, more diversity forward into the boardroom and into our executive suites. I also want to touch on a point Nishita made about women. We're the largest consumer group in the company yet we're consumers, but we're not builders. This is why it's so important that we start changing that perception of what tech is. And I agree that it starts with our young girls. We know the data shows that we lose our young girls by middle school, very heavy peer pressure. It's not so cool to be smart or do robotics or be good at math and science. We start losing our girls in middle school. So they're not prepared when they go to high school and they're not taking those classes in order to major in these STEM fields in college. So we have to start the pipeline early with our girls. And then I also think it's a measure of what your boards are doing. What is the executive leadership and your goals around diversity and inclusion? How do we invite more diverse population to the decision-making table? So it's really a combination of efforts. One of the things that certainly is concerning to me is during this pandemic, I think we're losing one in four women in the workforce now because of all the demands that our families are having to navigate through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. >> Yeah, it's really a critical time. And now we're coming to the end of this conversation. I want to ask you Teresa, what would be a call to action to everyone listening, both men and women since it needs to be solved by everyone to address the gender gap in the industry. >> I'd encourage to you to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them in those roles, opening your network, giving very candid feedback. And we need men to participate too. There are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >> Nishita, real quickly, what would be your call to action to everyone? >> I'd say, look around your teams, see who's on them and make deliberate decisions about diversifying those teams, as positions open up, make sure that you have a diverse set of candidates. Make sure that there are women that are part of that team and make sure that you are actually hiring and putting people into positions based on potential, not just experience. >> And real quickly, Lisa, we'll close it out with you. What would your call to action be? >> Well, it's hard to, but Nishita and what Teresa shared, I think were very powerful actions. I think it starts with us taking action at our own table, making sure you're driving diverse panels and hiring, setting goals for the company, having your board engaged and holding us accountable and driving to those goals will help us all see a better outcome with more women at the executive table and diverse populations. >> So I want to talk to you all about a pivotal moment in your career. It could have been a mentorship. It could have been maybe a setback in your career or maybe a time that you really took a risk and it paid off big, something that really helped define your career going forward. Curious what those moments were for you all in your career. Teresa, we'll start with you. >> Sure. I had a great sponsor and he was a white male by the way. He identified some potential in me when I was early in my career about five years in and he really helped pave the way for a number of decisions I made along the way to take different roles in the firm. I was at Deloitte, he's still in my life today. We get together a couple of times a year. And even though we're both retired from Deloitte, we still have that relationship and what that tell me was how to be a great sponsor. And so one of the most satisfying things I did in my career was when I finally got to the place where I was no longer reaching for the next rank of the ladder for myself, I got to turn around and pull through all of these amazing future leaders into roles that were going to help them accelerate their careers. >> What about you, Lisa? >> I think there's been many of those moments. One I'll speak about is having spin 20, 25 years in technology, I had spent my first career in department of defense, moved over to academia and then went to a high-tech firm on their IT side, really in hopes of getting the CIO role having been a CIO, I did not get the CIO role, and really had a decision to make. One of the opportunities that was presented to me was to move to the business side to run a $9 billion P&L on one of the core business units within the company. And of course, I was terrified. It was a very risky decision having never run a P&L before and not starting small going right to the billion dollar mark in terms of (laughs) what that would look like. And frankly decided to seize that opportunity and I've certainly learned in my career that those opportunities that really push you out of your comfort zone that take you down a really completely different path or where the greatest opportunities for growth and learning occur. So I did that role for three and a half years before coming into my current role back to a CIO role at Blue Shield of California in healthcare, and just a tremendous amount of learning, having been on the business side and managing a P&L that I now apply to how I engage with my partners at Blue Shield. >> I couldn't agree more. I think forcing yourself out of that comfort zone is so critical for learning and driving your career for sure. Nishita, what about you? >> Yeah, I agree. Lots of pivotal moments, but I'll talk about one very early in my career, actually was an intern and one of my responsibilities was to help research back then facial recognition technology. And I had to go out there and evaluate vendors and take meetings with vendors and figure out, all right, which ones do we want to actually test? And I remember I was leading a meeting, two of my kind of supervisors were with us. And I know I went through the list of questions and then the meeting kind of ended. And I didn't speak up at that point in time to kind of say here are the next steps or here's what I recommend. I kind of looked at my supervisors to do that. Just assuming they should be wrapping it up and they should be the ones to make a final decision or choice. And after that meeting, he came to me and he's like you know Nishita you did a really nice job in bringing these technologies forward but I wish you would have spoken up because you're the one who've done the most research. And you're the one who has the most background on what we should do next. Next time don't stand by and let someone else be your voice. And it was so powerful for me and I realized, wow, I should have more confidence in myself to be able to actually use my voice and do what I was asked to do versus leave it to someone else because I assumed that I was too junior or I assumed I didn't have enough experience. So that was really pivotal for me early in my career to learn how to use my voice. >> I'm really curious for you, Nishita. What drew you to the industry of data? What was something when you were young that drew you into that space? >> Yeah. So my background is actually in engineering and it's actually funny. It's an electrical engineering and I probably couldn't do another thermal dynamics equation to save my life anymore (laughs). But what drew me to technology was problem solving, right? It was all about how do I take a bunch of data and information and create a new solution, right? Whether it was, how do I create a device? I remember in college, right? Creating a device to go down stadium steps and clean, right? How do I take data for how this machine will interact with the environment in order to create it? So I always viewed it as problem solving and that's what has always attracted me into the field. >> That's great. So, Teresa, I'm curious, at what point did you feel that you really found your voice in your career, in yourself as a part of your professional life? >> Yeah. About 12 years into my career I started working as an M&A partner and I was working with a private equity firm along with their lawyers and other advisors, bankers and so forth. And what I realized in that situation was that I was the expert in what I did. And so, I mean, I found my voice before that in many other ways but that was sort of a moment where I felt like, "I'm here to deliver an expertise to this group of people. And none of them have the expertise that I have. And so I need to just stand firm in my shoes and deliver that expertise with confidence." So that was my example. >> That's great. Well, Lisa, what about you? What was that moment that you felt that you just found your voice kind of in your groove and that confidence kicked in? >> No, I don't know if it was exactly a moment but it was certainly a realization. Right out of college, I was working for the federal government in department of defense and certainly male dominated. And through that realized that to be heard, I had to become very good at what I do. So I built that confidence, frankly, by delivering results and capability and becoming an expert in the work, essentially the services that I provide. And when you become very good at what you do, regardless of what you look like, then people will start to listen. So I think it starts with delivering results. I think you have to build your confidence and through that you find to use your voice so that you are being heard, having worked in department of defense and academia and high tech, I've had to leverage that throughout my entire career ultimately for my voice to be heard, and to be represented within the roles that I was playing. >> That's great. I know one of the things that we've also talked about is just the value, the business value, the importance of having a diverse workforce and a diverse team and the value that that brings to the outcomes. What are some of your strategies to create those types of teams? What, as leaders in your company, you manage a team and what is your advice to them, your strategies to get a diverse pool of candidates and a diverse team. Nishita, what about you? >> I think it's looking beyond what the individual role is, right? So a lot of times we have a role description and you want these certain skills and so (indistinct), or you get a certain set of candidates. I think it's taking a step back and saying, "What are the objectives of my team? What am I trying to accomplish? What types of business acumen do I need on that team? What types of tech acumen, what types of personalities? Do I want people who know how to work with others and therefore bring them together? Do I need people who are also drivers and know how to get things done, right?" It's finding the right chemistry. We have a business chemistry, talk track around. We don't need all different kinds to make a really good team. So I think it's taking a step back and understanding what you need the makeup of your team to be, understanding the hard skills and the soft skills. And then thinking about what are all the sources you could really go to for them and being a little bit non-traditional and saying, "Do I need a full-time person all the time to do this job that's sitting here? Can I be more diverse in finding people from the crowd? Can I have part-time resources? Can I use different pieces and parts of the ecosystem to actually bring together the full team that represents the diversity?" It's just expanding our mind and stop thinking about a role to person, start thinking about it as the makeup of a team, to the outcome you desire. >> It's really about being creative and just thinking in new ways. Teresa, I'm super curious, since you sit on a bunch of different boards, what kind of strategies do you see companies taking to attract different talent? >> So I can address that from the board lens, for sure. And boards are probably one of the least diverse bodies in business right now, but that is changing, and for the better, obviously they were traditionally kind of white male dominated. And then we've had this wave of women joining boards. And now we're starting to see a wave of diverse individuals join boards. And with each person who's diverse that joins a board that I'm on, the dynamic of the discussion changes because they bring a different perspective. They bring a different way of thinking. They came from a different background or a different functional skillset or a different geography or you name, whatever element of diversity you want to see. We just added the head of Apple music to the service in our board. And so you might scratch your head and say, "Wow, the head of Apple music and an enterprise software company that is a B2B software company." But he thinks deeply about how the end user consumes in his case content and in our case software. And so he's able to bring just a completely different perspective to the discussion we have at the board table. And I think at the end of the day, that's what diversity is all about, is improving the outcome of whatever it is. If you're producing something or making important decisions like we do in board rooms. >> That's amazing. Lisa, real quickly, what are some of your strategies? >> Yeah. Well, we know diverse teams actually produce better business results. So there's no reason, there's absolutely no reason why we shouldn't think in that lens. I think it starts with our hiring and the makeup of our teams. I think it requires more than creativity though. You have to be very purposeful. I'm in the process of hiring four leadership positions on my team. And it's really to me, almost like a puzzle piece of diverse perspectives and knowledge and capabilities that come together that ultimately create a high performing team. But I can't tell you how many times I got to go back to HR and say, "I need to see more diverse talent. Are there any more women in the pool?" One of the things we've struggled, we have to get more women into the roles is, and we heard this from Sheryl Sandberg, as women, we feel we need to meet every qualification on an application. Whereas men, "I got a couple I'm good to go." And they throw their name in the hat. They take much more risk than we do as women. So we need to encourage our women to get out of your comfort zone. You don't need to meet every qualification. What Nishita was saying of thinking more broadly about what this role requires and the type of individual that we're looking for, but be purposeful in terms of driving to diversity as our end result. >> That is so true. What you just said. Thank you so much for sharing your insights. It's really interesting to hear all your strategies and thanks for sharing. >> And you're clear.

>>From San Francisco. It's the cube covering PagerDuty summit 2019 brought to you by PagerDuty. >>Okay, welcome back everybody. Jeffrey here with the Q. We're in San Francisco at the Western st Francis historical hotel. It's our third year coming to PagerDuty sound, but I think it's the fourth year of the show. Jennifer tahana just finished the keynote. You can see those places packed with people packed with energy. We're excited to be back and have our first guest of the day. He's Josh Cade and chief evangelists at Cherwell. Josh, great to see you. Great to see you. Thanks for having me today. Absolutely. So have you been to a PagerDuty, sung it before? This is actually my first event with PagerDuty. What do you think yeah, I mean they've really grown. I mean Patriot and he's been a partner of ours for awhile, but they have grown so much so rapidly and I think, you know after the IPO especially, you know, they've, they've really grown pretty crazy. >>A lot of gasoline on the fire with the IP. Exactly right. So let's jump into with the Cherwell for people aren't familiar with Cherwell, what are you guys all about? So Sheryl software is a company that we specialize in it service management and enterprise service management. So we recognize that the world of what we used to know is like help desk management and whatnot has grown. You know, digital transformation means that more people are involved in more revenue bearing activities across the company. And just like PagerDuty recognizes, you're always on, you've got to keep doing all of these things across the company. And so what we do is we act as a system of record to move request to move orchestration across an organization across all teams. So it's not just an it focus and we build a platform basically to enable the building out of all of your processes, automation, orchestration, et cetera. >>We focus in ITSs because the it group is, is the best entry point for this kind of functionality inside of an organization because they have the best broad kind of horizontal view across all departments. Um, but again, we've got customers that use it in a pretty much any kind of way from running public housing development to all kinds of just uses that we never even imagined. Right. Okay. So I think what's confusing to people, certainly the layman certainly me, is you know, there's kind of all these competing system of records, it appears from the outside and we know ITSMs space, we've covered it for a long time. You know, you need to have a single system of record to know what the answer is. And yet, you know, PagerDuty announces all these integrations with all these systems like Cherwell. How do those systems work together to still maintain kind of system of record integrity and yet leverage the capabilities of the different platforms? >>Yeah. You know, it's an interesting thing because we're seeing so much convergence in the industry and we're seeing that, you know, pretty much all of our software has to talk to all of our software, right? And so what we're seeing a lot is system of record doesn't necessarily mean the same thing that it used to. You may have a system of record for your customer data, you may have a system of record for your financial data, you may have a system of record for your request management and workflow data. And the key is really making those things talk to each other. And so, you know, between the, you know, the cloud and all of the growth that we've had there and, and the way that software just works, it's really about being able to handshake and talk to other companies. Software. Okay. And you know, so it's also about companies, one of the problems that happens in a lot of companies is you choose too many systems of record and you know, so you've got this team that all has different data. >>So I think that's part of what we'll see the kind of the future battle of the next few years is either we all got to talk together or somebody has to, you know, become more prevalent and become a bigger system of record if you get what I mean. So what are some of the use cases where the two systems, PagerDuty system, the Cherwell system would interact around a particular type of customer interaction? Yup. So there's a couple of different entry points, but uh, one of them is, so let's say a customer has a request so it's not even an incident for example. So they have a request and you've got SLS where you've got to fulfill a request very quickly. Um, you know, Sharewell is great at getting that request, interacting with the customer, making sure that they know, you know what to expect and whatnot. PagerDuty is great at getting the team together and getting people together to fulfill those things. >>And so there's that kind of transition point where that request goes to PagerDuty and PagerDuty gets to bring the team together, work on fulfilling that thing and get back to the customer, Hey, your thing has been fulfilled. Okay. So another one that happens, a great use case is, you know, we have a lot of links to different event monitoring. You know, just like PagerDuty does. But a lot of times those things will come to our system and turn into, uh, incidents, you know, in our system. So we're able to send that data over to PagerDuty and basically with up the team and get things moving so that we can resolve that event. And we have a upcoming integration to basically share that back and forth. I believe we're actually officially announcing it next week at our conference in Nashville. Um, but so we have an upcoming integration so that we'll be pushing stuff to directional and getting things from pager duty and pushing things back in. >>Great example. That's a great uh, example cause what you're basically doing is breaking the problem down into the pieces that each of the different software takes care of and PagerDuty's really good at figuring out kind of who the team needs to be pulling together the teams and having a relatively low impact, uh, task group to come in and fix that, that the resolution. Well, and you know, while being a system of record for request management and workflow and whatnot, you know, one of the things that we see in the industry is so many of the customers want best of breed. They don't necessarily want one piece of software to come in and try to be everything cause nobody can be everything. Right? And so that key of lets you know, PagerDuty does what they're really good at. We do what we're really good at. Um, our customers really like that. >>So that's how we partner with other companies. Okay. So later today I think you're giving a session on low code. Um, what does low code, I mean I I have an opinion but share would, do you guys think it's low code or why is low code so, so low code is really important for a few reasons, but the first is really, I would say time to value. So when you have to spin up a development team and spend a lot of time to build everything that you want to do in your organization, just a simple business process that can take a lot of time and expense. So the Sharewell platform is built in a low code way. Most of the things that you can do in our software you do through drag and drop interfaces. And a lot of times we'll have people a little skeptical. >>You know, when they first encounter us, no, we need to write Java script or we need to write some language and we bring them into the system and they find, no, not only do not have to, but you can accomplish what you needed to before you got done planning what code you were going to go. Right. You know, forget testing and all that kind of stuff. So most of what you can do in Sharewell is actually no code, but we call it low code because when it comes to integrating, oftentimes you need to speak to other API. So you know, not every piece of software out there is no code. So talking to rest API is talking to other API APIs, you know, integrating things together. That's where a little bit of code comes in. But we also have, you know, basically drag and drop interfaces for even integrating to other things. >>We have something in tune of 80 partnerships right now, partners that we integrate with and that number is growing all the time. Okay. So is the main benefit of low code just the existing developers being able to move faster or we're hearing a lot of conversation about is really kind of democratization and letting people at maybe kid code in the ed are not qualified to do that last integration step, but the start to build absolute lows and processes without having to figure out if I'm doing it in Java or Perl. Yeah, no, it's, it's definitely both of those things. I mean, you know, so you know, the time to value aspect is important for those devs, but often, you know, companies can be utilizing those resources in a much more fruitful manner. And so if you allow the service owners or business analysts to be able to go in and actually affect those processes, just like you're saying, that democratization really helps speed up a business. >>Right? So in terms of engines for your guys' growth, you know, there's a bunch of them that are talked about all the time. There's dev ops, um, which, which is clearly the right bet to make 10 years ago. There's cloud, which has worked out pretty well. Um, and then this whole thing, that digital transformation that everyone is, is, is a, is trying to get done. Yup. No. Which of those three do you think are most important? How do you see those kinds of playing out in your business? So, you know, I think all three are very important. I think digital transformation though is, you know, if you don't transform your business and take advantage of digital transformation right now, you're liking amoeba in the primordial goo. Watching those first fish walk on land and laughing at, that's just a trend. You know, I think all businesses need to transform themselves and take advantage of the digital technologies that they can get ahold of. >>So I think for us, you know, being an accelerator for that being a way that you can bring inputs and outputs into a singular platform and basically, you know, speed up that ability to transform and make it more predictable, uh, utilizing governance and auditability and all those things that don't generally happen in a dev ops or a transformation environment. Right. That's really our key and that's, I think where we're going to see the industry. You know, everybody has to transform to stay competitive and so we're focused on that transformation or I'm distracted. Jen just walked by the star of the show and really make it. Absolutely. All right, Josh, thanks for taking a few minutes. Good luck on your talk. No brag, good luck at your event in Nashville. Awesome. Thank you so much. Thanks for having me, Josh on Jeff here watching the cube words PagerDuty summit at the historic Wetsons de France. Thanks for watching. We'll see you next time.

>> Live from Barcelona, Spain, it's the Cube, covering KubeCon CloudNativeCon Europe 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation, and Ecosystem Partners. >> Welcome back, this is theCube getting towards the end of two days live wall-to-wall coverage here at KubeCon, CloudNativeCon 2019 in Barcelona. I'm Stu Miniman, my co-host for this week has been Corey Quinn and happy to have on one of our hosts for this week from the Cloud Native Computing Foundation, Dee Kumar, the Vice President of Marketing, also helps with developer relations. Dee, welcome back to the program. >> Thanks for having me. >> And thank you for having us. We've been having a great time this week, a lot of buzz, a lot of people and obviously always a lot of enthusiasm at the show here. Thanks so much. Alright, so your team has been super busy. I've talked with a lot of them leading up to the show. >> That's right. >> Anybody that knows any show of this kind of magnitude know we're usually pretty exhausted before we get on planes and change all the time zones. So, you know, thank you for holding strong. Give us a little bit about, you know, when we talk marketing, you have a big annual report that came out recently from 2018. Give us some of the highlights of some of the things you've been seeing. >> Yeah, sure. Like you mentioned, you're seeing all the excitement and buzz here so this is our largest open-source developer conference, when compared to the last year we did in Copenhagen. So we have close to 8,000 attendees so we're really excited about that. And you're absolutely right, with that comes, we're so exhausted, but we really appreciate. I think the reason the conference has been so successful is primarily just because of the community engagement, which I highlight in the annual report. So it's a combination of our community, which is the developers, the contributors, also our end users, and the third significant portion of our ecosystem is our members. So we recently just announced that CNCF has crossed over 400 members, our end user community is growing, I think Sheryl mentioned this morning in the keynote, we have about 81 end users and this is phenomenal because end of the day, end users are companies who are not commercializing Cloud Native, but essentially they're using these products or technologies internally, so they are essentially the guinea pig of Cloud Native technologies and it's really important to learn from them. >> Well Dee, and actually it's interesting, you know, celebrating the five years of Kubernetes here, I happened to talk to a couple of the OG's of the community, Joe Beta, Tim Hawkin and Gabe Monroy. And I made a comment to Joe, and I'm like, "Well Google started it, but they brought in the Ecosync and pulled in a lot of other vendors too, it's people. And Gabe said, he's like "yeah, I started Deis and I was one of the people >> Absolutely. >> that joined in." So, we said this community is, it's people more than it's just the collection of the logos on the slides. >> Absolutely, I completely agree. And the other thing I also want to point out is a neutral home, like CNCF, it definitely increases contributions. And the reason I say that is, having a neutral home helps the community in terms of engaging and what is really interesting again, going back to the annual report is Google had a leadership role and most of the contributors were from Google, and now with having a neutral home, I think Google has done a phenomenal job to make sure that the contributors are not just limited to Google. And we're seeing all the other companies participating. We're also seeing a new little graph of independent contributors, who are essentially not associated with any companies and they've been again, very active with their comments or their engagement with overall, in terms of, not just limiting to Kubernetes, but all the other CNCF projects. >> So, this is sort of a situation of being a victim of your own success to some extent, but I've mentioned a couple of times today with various other guests, that this could almost be called a conference about Kubernetes and friends, where it feels like that single project casts an awfully long shadow, when you talk to someone who's vaguely familiar with the CNCF, it's "Oh you mean the Kubernetes people?" "Cool, we're on the same page." How do you, I guess from a marketing perspective begin to move out from under that shadow and become something that is more than a single project foundation? >> Yeah, that's a great question, and the way we are doing that is, I think, Kubernetes has become an economic powerhouse essentially, and what it has done is, it's allowed for other start-ups and other companies to come in and start creating new projects and technologies built around Kubernetes, so essentially, now, you're no longer talking about one single project. It's no longer limited to containers or orchestration, or just micro-services, which was the conversation 3 years ago at KubeCon, and today, what you will see is, it's about talking about the ecosystem. So, the way, from a marketing perspective, and it's actually the reality as well, is Kubernetes has now led to other growing projects, it's actually helped other developers come onboard, so now we are seeing a lot more co-ord, a lot more contributions, and now, CNCF has actually become a home to 35+ projects. So when it was founded, we had about 4 projects, and now it's just grown significantly and I think Kubernetes was the anchor tannin, but now we're just talking about the ecosystem as a whole. >> Dee, I'm wondering if it might be too early for this, but do you have a way of measuring success if I'm someone that has rolled out Kubernetes and some of the associated projects? When I talked to the early Kubernetes people, it's like, Kubernetes itself is just an enabler, and it's what we can do with it and all the pieces that go with it, so I don't know that there's spectrums of how are we doing on digital transformation, and it's a little early to say that there's a trillion dollars of benefit from this environm... but, do you have any measure today, or thoughts as to how we can measure the success of everything that comes out of the... >> Yeah, so I think there was Redmont, they published a report last year and it looks like they're in the process of updating, but it is just phenomenal to see, just based on their report, over 50% of fortune 100 companies have started to use Kubernetes in production, and then I would say, more than, I think, to be accurate, 71% of fortune 100 companies are using containers, so I think, right there is a big step forward. Also, if you look at it last year, Kubernetes was the first project to graduate, so one of the ways we also measure, in terms of the success of these projects, is the status that we have within CNCF, and that is completely community driven, so we have a project that's very early stage, it comes in as a sandbox, and then just based on the community growth, it moves onto the next stage, which is incubating, and then, it takes a big deal to graduate, and to actually go to graduation, so we often refer to those stages of the projects to Jeffery Moore, in terms of crossing the chasm. We've talked about that a lot. And again, to answer your question, in terms of how exactly you measure success is just not limited to Kubernetes. We had, this year, a few other projects graduates, we have 6 projects that have graduated within CNCF. >> How do you envision this unfolding in the next 5 years, where you continue to accept projects into the foundation? At some point, you wind up with what will only be described as a sarcastic number of logos on a slide for all of the included projects. How do you effectively get there without having the Cheesecake Factory menu problem of... the short answer is just 'yes', rather than being able to list them off coz no one can hold it all in their head anymore? >> Great question, we're still working on it. We do have a trail map that is a representation of 'where do I get started?', so it's definitely not prescriptive, but it kind of talks about the 10 steps, and it not only talks about it from a technology perspective, but it also talks about processes and people, so we do cover the DevOp, CICD cycle or pipeline. The other thing I would say is, again, we are trying to find other creative ways to move past the logos and landscape, and you're absolutely right, it's now becoming a challenge, but, you know, our members with 400+ members within CNCF. The other way to actually look at it is, back to my earlier point on ecosystems. So one of the areas that we are looking at is, 'okay, now, what next after orchestration?', which is all about Kubernetes is, now I think there's a lot of talks around security, so we're going to be looking at use cases, and also Cloud Native storage is becoming another big theme, so I would say we now have to start thinking more about solutions, solution, the terminology has always existed in the enterprise world for a long time, but it's really interesting to see that come alive on the Cloud Native site. So now we are talking about Kubernetes and then a bunch of other projects. And so now, it's like that whole journey from start to finish, what are the things that I need to be looking at and then, I think we are doing our best with CNCF, which is still a part of a playbook that we're looking to write in terms of how these projects work well together, what are some common use cases or challenges that these projects together can solve. >> So, Dee, we're here at the European show, you think back a few years ago it was a public cloud, there was very much adoption in North America, and starting to proliferate throughout the world. Alibaba is doing well in China and everything. CNCF now does 3 shows a year, you do North America, you do Europe and we've got the one coming up in China. We actually did a segment from our studio previewing the OpenStack Summit, and KubeCon show there, so maybe focus a little bit about Europe. Is there anything about this community and this environment that maybe might surprise people from your annual data? >> Yes, so if you look at... we have a tool called DevStart, it's open source, anyone can look at it, it's very simple to use, and based on that, we kind of monitor, what are the other countries that are active or, not just in terms of consuming, but who are actually contributing. So if you look at it, China is number 2, and therefore our strategy is to have a KubeCon in China. And then from a Euro perspective, I think the third leading country in terms of contributions would be Europe, and therefore, we have strategically figured out where do we want to host our KubeCon, and in terms of our overall strategy, we're pretty much anchoring to those 3 regions, which is North America, Europe as well as China. And, the other thing that we are also looking at is, we want to expand our growth in Europe as well, and now we have seen the excitement here at our KubeCon Barcelona, so we are looking to offer some new programs, or, I would say, new event types outside of KubeCon. Kind of you want to look at it as mini KubeCons, and so those would explore more in terms of different cities in Europe, different cities in other emerging markets as well. So that's still in the works. We're really excited to have, I would say 2 new event types that we're exploring, to really get the community to run and drive these events forward as well, outside of their participation in KubeCon because, oftentimes, I hear that a developer would love to be here, but due to other commitments, or, their not able to travel to Europe, so we really want to bring these events local to where they are, so that's essentially a plan for the next 5 years. >> It's fascinating hearing you describe this, because, everything you're saying aligns perfectly with what you'd expect from a typical company looking to wind up, building adoption, building footprints etc., Only, you're a foundation. Your fundamental goal at the end of it is user engagement, of people continuing to participate in the community, it doesn't turn into a 'and now, buy stuff', the only thing you have for sale here that I've noticed is a T-shirt, there's no... Okay, you also have other swag as well, not the important part of the story, I'm curious though, as far as, as you wind up putting all of this together, you have a corporate background yourself, was that a difficult transition to navigate, as far as, getting away from getting people to put money in towards something in the traditional sense, and more towards getting involved in a larger ecosystem and community. >> That was a big transition for me, just having worked on the classic B2B commercial software side, which is my background, and coming in here, I was just blown away with how people are volunteering their time and this is not where they're getting compensated for their time, it's purely based on passion, motivation and, when I've talked to some key community organizers or leaders who have done this for a while, one of the things that has had an impact on me is just the strong core values that the communities exhibit, and I think it's just based on that, the way they take a project and then they form a working group, and then there are special interest groups that get formed, and there is a whole process, actually, under the hood that takes a project from where Kubernetes was a few years ago, and where it is today, and I think it's just amazing to see that it's no longer corporate driven, but it's more how communities have come together, and it's also a great way to be here. Oftentimes... gone are the days where you try to set up a meeting, people look forward to being at KubeCon and this is where we actually get to meet face-to-face, so it's truly becoming a networking event as well, and to build these strong relationships. >> It goes even beyond just users, I mean, calling this a user conference would not... it would be doing it a bit of disservice. You have an expo hall full of companies that are more or less, in some cases, sworn enemies from one another, all coexisting peacefully, I have seen no fist-fights in the 2 days that we've been here, and it's fascinating watching a community effort get corporate decision makers and stakeholders involved in this, and it seems that everyone we've spoken to has been having a good time, everyone has been friendly, there's not that thousand yard stare where people are depressed that you see in so many other events, it's just something I've never experienced before. >> You know, that's a really amazing thing that I'm experiencing as well. And also, when we do these talks, we really make it a point to make sure that it's not a vendor pitch, and I'm not being the cop from CNCF policing everyone, and trying to tell them that, 'hey, you can't have a vendor pitch', but what I'm finding is, even vendors, just did a silverless talk with AWS, and he's a great speaker, and when he and I were working on the content, he in fact was, "you know, you're putting on that hat", and he's like, "I don't want to talk about AWS, I really want to make sure that we talk about the underlying technology, focusing on the projects, and then we can always build on top, the commercial aspect of it, and that's the job for the vendor. So, I think it's really great collaboration to see how even vendors put on the hat of saying, 'I'm not here to represent my products, or my thing', and of course they're here to source leads and stuff, but at the end of the day, the underlying common protocol that's already just established without having explicit guidelines saying, 'this is what you need to be following or doing', it's just like an implicit understanding. Everyone is here to promote the community, to work with the community, and again, I think I really want to emphasize on the point that people are very welcoming to this concept of a neutral home, and that really had helped with this implicit understanding of the communities knowing that it's not about a vendor pitch and you really want to think about a project or a technology and how to really use that project, and what are the use cases. >> It's very clear, that message has resonated well. >> Dee, thank you. We've covered a lot of ground, we want to give you the final word, anything else? We've covered the event, we've covered potential little things and the annual report. Any last words you have for us that you want people to take away? >> Not really, I think, like I said, it's the community that's doing the great work. CNCF has been the enabler to bring these communities together. We're also looking at creating a project journey it terms of how these projects come into CNCF, and how CNCF works with the communities, and how the project kind of goes through different stages. Yeah, so there are a lot of great things to come, and looking forward to it. >> Alright, well, Dee, thank you so much for all of the updates, and a big thank you, actually, to the whole CNCF team for all they've done to put this together. We really appreciate the partnership here. For Corey Quinn, I'm Stu Miniman. Back to wrap 2 days, live coverage, here at KubeCon, Cloud Native Con 2019, Thanks for watching the Cube. >> Thank you.

>> Live, from Mountain View, California, it's theCUBE! Covering DevNet Create 2019, brought to you by Cisco. >> Hey, welcome back to theCUBE, Lisa Martin with John Furrier covering day two of Cisco DevNet Create 2019, and guess who we're here with? Susie Wee SVP and CTO of Cisco DevNet. Susie thank you so much for having theCUBE here and for joining John and me today. >> Oh thank you for being here. >> So this event, there were so many bodies in here yesterday, it was pretty toasty, it's getting toasty now, this is the third DevNet Create, this community John and I have been hearing that and feeling it and seeing it, see it, learn it, code it, kind of all on your theme there the last day and a half. This is a really inspiring, really national sharing community that you guys have built here. >> It is, it's amazing, I mean just the energy here as you bring together folks. Everybody wants to learn, there's so many new technologies out there, but new technologies that can turn into business advantage, and the attendees here they all feel it, and it's a different mixture of people because there's app developers, there's infrastructure and networkers, and just bringing these folks together to see what they can achieve is amazing. So that's the energy that you can really feel here. >> And the thing that's interesting and that I'd like to perspective on where this all started from, is DevNet Create is interesting, you know Amazon's Andy Jassy, the CEO of Amazon Web Services, uses the term builders. So you hear builders, maker culture, create. But creation is a critical part of your ethos here, and with cloud computing, Microsoft's earnings came out they were a trillion dollar market cap now, Amazon crushes their earnings again, you're seeing what cloud is doing that's enabling these creators, a new class of developer, but it's not like a new breed, it's just a new kind of orientation. This is part of your vision to share the story. >> Well and kind of the whole thing is that, you know I'm all about innovation and creation. And I believe that people just want to create. My four year old, she just wants to create. It's just in people's blood, but to now get out there and to do it, you need a catalyst. You can't just sit in a room and then create, and sometimes it's about how you bring new fields together, how you bring new technologies together, how you bring non-technologies together, how you just bring different types of people and perspectives together, and that's really what DevNet Create is all about. So, we started DevNet five years ago, just with the idea that the network is going become programmable. The infrastructure is going to provide more resources, and it's going to be programmable and provide more power to applications, so from then to now, last summer we hit half a million developers, now we're at 590 thousand developser, and we're growing. >> Well we're lucky to be part of it and thank you for including theCUBE in DevNet Create, and bringing something to the DevNet community. It's been fun and inspirational, but to be practical in the industry, you need to have a wind at your back, you need to have a wave to ride on, and creation is also about momentum. And if you look at the marketplace today, there's some big waves happening. Cloud computing is obvious, one everyone looks at, that's already changed the nature of companies, Cisco's multi-cloud looking at a bigger vision there. But new waves are coming, I mean Wifi Six is a game changer, you've got 5G. So you talked about this in the keynote, I want you to take a minute to explain that the big waves that you outlined, because with big waves there's more fun, there's more creation. There's wealth creation, there's economic vitalizations, a new vibe. Share the waves. >> Inside of the whole thing is that we say there's the infrastructure. You get your networking, you get your compute, it evolves to cloud computing and all of that, but on top of that are these applications. And this amazing set of applications, and we know that those are creating entirely new and disruptive businesses and business models, and there's a lot of growth in all of that. Now traditionally what happens is that with every wave of infrastructure advancement, comes a new set of applications and businesses, so going back to our olden days but, there was a time where you started to get a converged IP network, or you put data and voice together on an IP network, and then came voice over IP. Then came cloud computing. And you can do internet search, and you know, we're old enough to remember before then. Then you got 3G, and instead of just having the cell phone, you could do mobile apps on cell phones, so you had mobile apps. And then with 4G, you could do mobile video, and now you just expect it. Now you could think, okay the infrastructure is done, but no there's more, so some of the things that are happening right now that's really exciting is that, is I kind of talked about it in three areas. In networking we a have a couple really big things going on, which is Wifi Six and 5G. And so there's a whole site and we'll talk more about that. In computing there's the fact that actually GPU's are everywhere, and with that you can do AIML everywhere. So AI and machine learning. And then the third one is just an advancement in architecture. We knew that we'd move to mobile, we knew that we moved to compute, but now what becomes real is the edge. Edge computing. And so when you bring these things together you have new capabilities in network with Wifi Six and 5G, you have new capabilities in computing because GPU's are everywhere so you can do AI and ML, and then you actually have a spot at the edge where you can do edge processing, and then all of a sudden there's this whole new world of applications just waiting to be built, and we want to let developers know that. Because you kind of develop and you build from what you know, like oh this is just how good I can do, but there's a whole new capability coming. >> Well first of all, let's unpack those talk chats, because one of the things that I, as an entrepreneur, you know we've always talked about this, the creativity that comes from entrepreneurial thinking, whether your a true entrepreneur starting a company, or within a company doing that inside a company, takes creative juices, you got to have that catalyst as you mentioned, but also you got to imagine new ideas, right. And so by enabling, say Wifi for instance, everyone knows what Wifi is, but when you think about the new advances of Wifi and having connectivity with wireless and wired networks, with new data access, it just opens up this creative outlet. This is going to be the tsunami or the renaissance of applications. And you've been talking about it. >> It is, it is. And so like if we kind of geek out, because I was working on HD TV before it really became HD TV and their doing things like OFDM, and you know, we're so excited, spread spectrum technologies, but right now with Wifi Six, we can really geek out again. So OFDM is moving to OFDMA, OFDM multiple access. That means like, an access point usually talks to one client at a time, but now it can split up and talk to multiple clients at a time. And with that you can actually get much higher capacity, right so you can actually really use your kind of, network more efficiently, and then you can actually now also do scheduling. And then you can actually guarantee that a client is going to be scheduled in and get transmissions. That changes what you can do with Wifi and the way you think about it. And then there's this power savings, because now we can tell a device the time to wake up, so you kind of sleep sleep sleep sleep sleep, here's your target wake up time. Sleep sleep sleep sleep sleep, here's your target wake up time, that extends battery life, so you can have sensors that'll be out there for one year, five years, ten years, doing its thing. And so that takes all those IoT applications you've always wanted to build, but makes them real. Because someone has to go up and install that sensor, and the battery life matters. >> And so the second wave is the GPU anywhere which I like, because when you think of GPUS, Nvidia, you're thinking of graphics, you're thinking of gaming, but it's actually a processor for machine learning, so what are your thoughts on this because if you put GPUs in devices everywhere, and the data that you're now accessing across the network brings more intelligence. What's the impact of this GPU anywhere? Is it just IoT, is it just applications, what's the net net? >> So kind of, the most important thing about it is that before, you kind of needed to have a PhD to do AI and machine learning, right? And we have friends who are experts at that and they're continuing to push the envelope in there. I was just back at MIT and just the advances in AL and ML is amazing. But the other thing that's happening is that this is just getting wrapped up so developers can just use it. So you can actually have a TensorFlow.js library that'll just sit on your mobile device. You can actually just using your browser, you can actually write a web app that uses that and then uses the GPU, which just means right there you can write a little web app, with like five lines of code, you can say, find all the people in this picture. Find the bottles in this picture. Right so just be like, doing that on the fly, and you don't have to have a PhD in machine learning, you can actually, developers can just use this capability. And so that's kind of what unlocks it, is just because it's accessible to everyone and now you'll get that mixed wave of innovation when people can just use it and find the right applications for it. >> So looking at these three big changes that you've talked about, network, compute, architectural, did you leverage these big waves to design this years Create? Because we're hearing all about the three technologies tracks. Tell us a little bit about that. >> It is, well so first of all we have Wifi Six here, live, and people know there's the idea of it, we've done some performance tests around it and we're like it screams. You know, it just, it really does scream, and you're used to not counting on that, right? And so it opened up peoples' eyes and they're thinking differently now about what they can do here. >> What sort of reactions of the geeks at Cisco when they look at the data of Wifi Six, what's some of the anecdotal reactions that they're saying? >> People are surprised, cause everybody's kind of cynical about it. Cause, quite honestly, even getting ready for it, it just like guys we're going to jump on Wifi Six. And they're like eh, yeah, well, whatever. And then one of my guys Oshitosha went off and did the speed test and he started working with it and he came back into my office, his eyes were popped out of his head, (gasp), that's fast. >> And you showed that yesterday, all the cameras came in like, whoa! >> Because you don't have that expectation, but once you know it, it's going to really unleash this whole new set of things. There's actually something else interesting we did with the edge processing with the GPUs which is the idea of edge computing, not a new idea, the reality of it, is still coming into play. Now what happens is Cisco just announced some new products. These industrial routers, it's an industrial gateway, it means that you can like put it up on the telephone pole, you can put it into a manufacturing plant, you know at high temperatures, and it's the gateway that will connect all of your devices and senors, and be the networking conduit to get everything back. So that's an awesome product, the mass product actually hosts applications. And what matters is the deployment of these infrastructures, right? So Cisco's partners will get out there, they're going to sell and kind of install this networking equipment in manufacturing companies, but now it can host applications so developers can actually reach it. And so now that's a place for developers, but we're doing something new here, which is that we have a prototype of taking that product, we have a prototype GPU, a Nvidia Jetson that we've put on top of it, and we're letting developers hack at it. And say, would you use this? Like, tell us some of your best ideas, try it out. Because we still need to figure out the market and what's there, and we're doing it with developers. >> And where do they go with the creativity there? Because obviously one's a gateway so they're used to gateways, and they understand edge devices. What are some of the ideas that are going to come out of hacking a GPU? Is it running data analytics on the edge? Is it hosting an application and managing edge devices themselves? What are some of the cool things? >> I mean things like video sensing. So now like at your edge you have lots of cameras and because you can do GPU processing, you can actually take these multi-camera inputs, do video sensing algorithms, you know things that you kind of dreamed about before, but now just doing that for real. You know, finding construction workers, finding the hard hats, in the images to make sure that you can actually have people be safe. One thing that we know about AI and machine learning, is like a lot of times people say, okay I'm going to hire a data scientist, a data scientist comes in, and they can't really get the data. Like they don't have anything to work on until there's a good data set to work on. Well actually as you connect up these environments, that's one data set coming in. So you connect up like transportation systems, like SCADA, like utilities protocols, you're actually talking to manufacturing equipment. >> Real time data from traffic, Teslas. >> Exactly. And so that stuff comes in, but then you need to kind of munch on that data to know, when should I be looking, how can I get it into a form that I can do some AI and machine learning on it. >> So new use cases, you expect new use cases to emerge? >> They are, and it's really cool because there was a time when there was all of this stuff you could do on the web, and in the cloud, and with our applications, but it's coming back to the physical world. >> And that's what you mean by the edge, is then this architectural thing, that's really the edge. The new architecture of having these kinds of capabilities is going to create sets of applications that we've never seen before. New startups, new applications. >> It is and really the kind of thing with DevNet Create is bringing in the community of people who do install infrastructure, knowing that this infrastructure is becoming programmable, and having that able to host the applications and the innovations that are coming from the developers, it's like, it just unlocks entirely new business models. And I think here these two communities are meeting and mixing, and I think that's the energy that we're seeing out here. Because they didn't expect to talk to each other. When we started DevNet Create, we knew that it was coming, we didn't know how the people would mix, and this has evolved to where people are mixing in entirely new ways and making connections, and someone who's written an app is like, oh, you're a partner, you can deploy this in all different countries, that's a new kind of deployment model for my app. >> We talked a little bit about that yesterday, with our guest as well as Mandy, and you've got these kind of different worlds colliding, but one of the things that John pointed out, is that this is not a marketing driven event, this is not for lead generation, this is a truly collaborative event, and you're getting clearly developers and infrastructure guys and girls from clearly, very probably, computing companies who are sharing. So I can imagine the cultural change that this can bring to, born in the cloud, traditional enterprise, maybe something that wasn't originally planned, but I can just imagine these worlds colliding and seeing how much better they can work together. >> And that is something that with DevNet, if you even go to the world of networking and IT and you know, just enterprises, there's a new model. So things become programmable, people's biggest problem is automation, doing things at scale, like how do I go ahead and deploy my networks across all these sites around the world? You can automate that. How do I take machinery and get business insights from that so I can actually use it for more, you know, you want to do that in software. And so you have to change your mindset cause then it is about collaboration, it's about sharing software and everyone knows that they can get there faster by sharing code and ending up with a code repository, we have code exchange, that we've created in DevNet, we've just opened it up last year, we now have over 400 repos, we just crossed over 400 on there. >> You guys are changing the way people are doing work within your own community, both DevNet and DevNet Create, bringing those worlds together. And it's working, it's magical so congratulations on all the success you've had. I got to ask you about your journey because we've talked years before you even joined Cisco and we've been following and talking to you since you've been here, and I was saying on our opening yesterday, Cisco as a company is like a big aircraft carrier, it's making the big move right, and you're seeing Chuck Robinson, the CEO, cloud, everything has APIs on, every portfolio project got APIs, so he's the pulling company into telemove, which is let's get cloudified, let's figure out our role in cloud computing and beyond, and you're mentioning some of those things, as you continue to show progress in the growth of DevNet and the community, it's changing Cisco. And we're seeing as we cover with theCUBE, and Chuck's called you out publicly and said Susie, great job, so this is a recognition that DevNet and the work that you and your team are doing is changing the face of Cisco internally and externally. How is that going, as the battleship starts to move, and by the way, data center is still more important than ever before with fibrated multicloud, things are lining up for Cisco, and you're a big part of it. What's going on in the company, and what's Chuck Robinson saying to you in your meetings with him, like hey, good job, or let's double down. >> Yeah, no Chuck is an amazing leader. And Chuck completely understands the vision, and that's why he's been supporting DevNet. So he's been supporting DevNet, not just because oh, he likes Susie or anything like that, it's because he understands the importance of programmability he understands what it means for starting new businesses and creating new business models. What it means for the ecosystem to grow into it, what that opportunity is. So he's always understood it, and I'm super lucky because he's been supporting these efforts. But now what's happening is of course he wants more. And I just presented to Chuck and his executive leadership team last week, about the plans that we have going forward. We've actually just kind of, what I would say is that, we've done the MVP of DevNet, so I know that you know, we've got the half a million members, actually almost 600 thousand >> Product market fit, it's all there >> We know have like, real assets, we have a real community, we have companies that are changing how they work, using our assets and really forming in this community, and now to get it to the next level, he's actually really kind of, sponsoring and working with us to develop it to the next level. And really the team is all coming together. The engineering team, the customer experience teams, sales and marketing, and then how we work externally with all of our communities. And so we're really growing into the next level. >> And you've got a great team, you know we've worked with all of you team, a lot of your team, but one of things that I like about what you've done here, is that, and you said it yesterday on stage at closing keynote, you feel like a star, you used the word MVP, minimum viable product. That's a startup word. So you have this startup culture, and you're in a big company so it's working. Is it contagious, are people, are there antibodies coming at you, are there people joining you, what's going on because how do you keep that startup vibe going. >> Yeah, I think that I'm just very fortunate because my team all has that attitude, they're very externally driven, so they're like, how do I help our developers, how do we help our community, how do bring them along, and we totally drive ourselves by that. And then we're constantly asking them how can we help you more, what do you want from us, and they say if we're doing something that's not useful to you, tell us now so we can stop, so we can build something else. And so we continue to evolve. And so we actually listen and then we really figure out how to go to that next level. Now what's really fun is that also though, we work with all of the other organizations, right, so you know I'm not going to replicate the sales force, we work with them, I'm not going to replicate the SEs that are out on the field. They're using DevNet, and they're running their own DevNet express events in their countries for their partners and customers. So we've really built out, really collaboratively and we've gotten so much support. And the first days, everyone was like, hey, guys you have a software strategy, you need to look at developers, you need APIs, and they're like nice job Susie, yes. Keep on going. >> You're bringing the Dev Ops ethos to the culture. DevNet's an API to all the other organizations. >> Well and now that we are where we are, it's just, it's the partnerships like our product teams are investing and improving their APIs. We advocate for the developers viewpoint into those, and it's a collaboration. Like so I don't make the products, our product teams make the products. I don't sell the products, our sales team sells the products. Right, so we've really brought together the forces and we're fortunate because everyone is joining in. >> Well it sounds to me like what DevNet is doing, is really driving this organic cultural evolution within Cisco. Is it, would you say, and maybe I'm making a leap here, it sounds to me, like what I've seen, and this is my first DevNet as well, is that DevNet seems to be an accelerator of Cisco's evolution. >> I would it's an accelerator, and you know, what I want to say is that we have great efforts going on across the company, and people are trying to figure it out. So I can't say I'm the one driving it, that would just be too much to say. But we are trying to accelerate each other's efforts and now that we've grown a community, we've provided a platform. Like, we do get more than a million eyeballs a month onto our site. And we use that as a channel, so we really working to accelerate and kind of catalyze each other's efforts. >> And if you step out and zoom out, you can see how it all hangs together. You've got APIs in all the products, so that's an enabler. You have developer onboarding of new kinds of customers and existing ones melting together, kind of in the same melting pot of developers, and you got the cloud wave behind you, and Ad Gen AI. And then you can see Cisco becoming multicloud, it's almost like it's feeding and turning in the right spot, where, I mean you don't have a cloud, but I mean you have connectivity, you have data, you have Dev Ops, Net Dev, so it seems like a nice positioning for the future. But you have all this other revenue and customers, so it's going to take some time. >> We have great products. Our products five years ago, we had handful of products with APIs. Now, our whole portfolio is programmable. So that's not my efforts, those are the product teams building great products, and entering this world of programmability. We're bringing in the community and giving them the tools so they can use them, right? So otherwise you can't just make a product and have it sit there, you need to help it come along. >> Okay, what was your presentation to Chuck? What's the vision? Where do you go next? You've got some great momentum, congratulations on the success, we love being a part of this, a lot of action. It's very inspiring and intoxicating at the same time, what's next, what's the vision? >> Yeah, so really if we, and I love the way that we've built up DevNet, is because we started with our developers, and the communities that needed to become developers, or power users of software. So, we've done the technical enablement, like we have documented APIs, we have learning labs, we have sandboxes so people can just code. So we've really been focusing on enabling them and providing all that technical enablement. And now what happens is people are asking us, how do I make this real, how do I spread this across my organization, how do I bring these solutions to my customers and then to the world? And in order to do that I need to change how I do manufacturing, in order to do this, I need to change how we build solutions, and so help us with that fuller solution, so we're really stepping up to go beyond the technical enablement, to just bringing it to reality, and to real solutions that are in operational environments, and so it's just really exciting to be working together on all that. And then we'll have a bunch more new stuff coming that we'll talk about at Cisco Live. >> And you have a great party at Cisco Live, you also have those social club event, you got to keep that going, right? >> Of course, we'll keep the social club going and we'll have a bunch of new things to announce at Cisco Live as well. >> It's starting in just a few weeks from now, so last question, your takeaway from this, some of the anecdotes that you've heard the last day and a half of DevNet Create 3. >> Yeah, so you know, kind of the vision that we had set forward. And it's one that we've been thinking about it, it's just that the infrastructure really enables a new set of applications and business models. And we had the idea of it, but again with these advances that we talked about, with Wifi Six and 5G, with GPUs enabling AI and machine learning, and with edge computing, is that people get it. And people know that it's not like some day you will have this, and some day you will have that, which I've been in research, I know that view. But it's actually like right here and right now. >> Making it real. >> Making it real, and it's available for people to use, like this next one to two years is going to be super exciting for the industry, cause it's not just theoretical, it's not just what it could do, but there's real goals that are right out there for people to develop exciting new things. >> I wish I was younger, I wish I was in my 20s, I mean like. >> It's okay, we take old people and young people all together, diversity, yes. >> More inclusion, young and old. It's so exciting because it's such an enablement, and knowing what's the megatrends that are the real waves, it's actually real, it's happening. >> And I actually want to, while we do talk about diversity and inclusion and enablement, what's really exciting is I just brought us that, we have some of our partners who are transforming themselves, and we actually have some women in tech initiatives that have started out. >> I love that, tell us about it. >> Okay so, Presidio, Verizon, they've invested in helping the women in their organizations, well they're helping everybody evolve to embrace programmability and automation to understand the application, you know the opportunities there. So they are fully, kind of, taking this paradigm and transforming their workforces to embrace it. But in addition we've partnered to also provide extra support, and call out for the women who are making the journey, and who have to, you know, face maybe some additional challenges, or just ensuring that they have the opportunity and they get the visibility, and they've both sponsored, so Presidio, Verizon, have both sponsored bringing some of their women to DevNet Create. >> I loved how you brought them on stage this morning, without telling them. They endeavor you, and you just had this genuinely enormous smile of pride. >> I'm so proud of them. >> And you should be. But that's amazing that Cisco and DevNet is also making that investment in women in technology. >> And we're doing it together with them and I'm just proud of what their doing, and this is the workforce. You saw the women up on stage if you guys watched the keynote, you'll see that it's out there. These are the people you want to hire, and why would you not use that workforce. >> Exactly, why would you not? >> And get them all young too, like you mentioned your daughter, when she starts putting the Meraki switch at home, you know you've made it. She's almost ready. >> Yes she's handling a computer for me already, she's like mommy you have two, how come I don't have one? >> She says mommy why are you using command line? >> That's next! Susie, you're an inspiration, an inspirational female in technology, we all often gravitate towards Sheryl Sandberg. I think we should start including Susie Wee in that. Thank you so much, >> No thank you very much. For having us at DevNet, it's been a pleasure to meet you, and have the chance to interview you, and we can't wait to see where do you go from here. >> We will continue to change the world together, thank you. >> I love it. Awesome. For John Furrier, I'm Lisa Martin. You're watching theCUBE live, from Cisco DevNet Create 2019. Thanks for watching. (upbeat music)

>> Announcer: From the heart of Silicon Valley, it's theCUBE. Covering Cloud-Now's Seventh Annual Top Women Entrepreneurs in Cloud Innovation Awards. (upbeat music) >> Hi, Lisa Martin with theCUBE, on the ground, at Facebook headquarters. We're here for the seventh annual Cloud-Now Top Women Entrepreneurs in Cloud Innovation Awards. Excited to welcome, from the AtScale team, to theCUBE for the first time, Sarah Gerwck co-founder and chief architect and award winner. Sarah it's so great to have you on the program. >> Thanks so much, it's great to be here. >> So I mention you join a number of your peers at AtScale who have been on theCUBE, so we're glad to have you on. So co-founder of a tech company, we're here celebrating women who have not only founded companies, technical entrepreneurs, venture bad companies, really hard things to achieve. Give us a little bit of the backstory about the co-founding opportunity that you and your co-founders had about what, 5 or so years ago at AtScale. >> Yeah so a number of the founding team came out of Yahoo where in the analytics group, we were seeing that the scale of data that companies were operating with was changing. And the operational environment was changing with both public and private clouds. And even at Yahoo as a technology company, we found we were struggling both internally to develop the tools that we needed and also to find tools on the market that served the needs of our business users, and our executives, and our accounts and sales people. So we realized that this was just a sort of pivotal moment in the change of the way business was being done in the Valley. That there was this great opportunity to really help companies connect to their data wherever that data might be and whatever types of data they might have. So about 5 years so ago from your perspective, you are a STEM kid. You've got background in what is it, math and physics. >> That's right. >> So you knew from the time you were a kid, I love this, this is what I want to do. What were some of the things the inspired you as being... And many industries are challenging, but tech is as well. That inspired you to not only continue doing what you love, but to actually step out of, maybe you'd say a comfort zone of a large company like a Yahoo with your co-founders and start something brand new? >> Sure, I think it's the... The key thing to me is you have to sort of just believe in yourself and be your own champion because really everybody out there who accomplishes these things takes these steps and says this is going to be my moment, this is going to be my thing. And I think whether you're a woman, or a minority, or a man, or anybody, you just have to be confident in yourself. Look for the things that you really enjoy. For me that was math and science and technology. And just sort of find, here's my niche, here's something I can be really good at. And become an expert in that area. And that's sort of something you walk into over time, and sort of develop that confidence to sort of strike out and do some amazing things in your life. >> How do you find that for those next generation, or even those that are in tech now, to go I don't feel confident enough, or they might feel some pressure. What's your recommendation on lending themselves with a mentor, whether it be male, female whatever to help them just kind of take stock of what's really important to them? >> Yeah, I think finding people who have been through it and talking to them, whether it could be a boss or a coworker whose done interesting things in their lives, or an old teacher, or a present teacher, I think finding somebody who can sort of give you that story of like here's how I felt because you have to have confidence in yourself but really nobody feels confident all the time. Everybody gets anxious or fearful before doing something new. That's part of it and sort of learning to look back and say well, I've been successful in the past, and I've overcome these obstacles and I'm ready for another one. >> I always think something that's so interesting is the concept of imposter syndrome. And how many people suffer from it, and I didn't even know it existed until a few years ago. And it level set, Okay, I'm not the only one. And so I think that's something that some people are kind of born with that like regardless, you love math and physics and you're going to keep going. But for those, I think even sometimes acknowledging, oh, this is something that a lot of people that have confidence now didn't have back in the day. I can overcome this as well. >> Right, I think everybody has a little bit of imposter syndrome at times. I just think that the world can seem like such a big and challenging place, but really it's all made of people and they all have the same sort of interests and desires. Not necessarily all the same skills, but deep down we're all people. >> Exactly, so tonight though, in the last minute or so, you have the opportunity to present in front of one of the most influential females of our time in technology, Sheryl Sandberg. Can you think back to yourself in college, and if you'd known this opportunity was going to happen, would have just said, yeah, that's about right? >> I would've been a surprise. I think with work and sort of following your passion, I think anything's possible. >> I love that. Well, Sarah, congratulations on the award and for all of your success at AtScale. We congratulate you, and we thank you for stopping by theCUBE. >> Thank you. >> Have a great night as well. >> Thanks. >> We want to thank you for watching theCUBE. I am Lisa Martin on the ground at Facebook headquarters. We'll see you next time. (upbeat music)

>> Narrator: From the heart of Silicon Valley, it's theCube. Covering CloudNOW's seventh annual top women entrepreneurs in cloud innovation awards. >> Hi, Lisa Martin with theCube on the ground at Facebook headquarters. We are here for the 7th annual Cloud Now top women in cloud innovation awards. Excited to be welcoming to theCube for the first time, one of tonight's winners, Catherine Krow, the founder and CEO of Digitory Legal. Catherine, welcome. >> Thank you so much, it's a pleasure to be here. >> So one of the things I love about your story, Catherine, is you were a practicing attorney for 17 years. >> Yes. >> You're one of the assistant DA's in San Francisco. And you are now the founder of a SAS based software company. >> I am, and I was a partner at major law firm named Orrick for many many years before doing that. >> So, I can imagine, back in school when you were in law school, didn't envision you would actually be a female entrepreneur in technology. >> Oh heavens no. When I graduated from law school 20 years ago, this was probably dead last on the things that I thought I would be doing. But, when I was practicing, it became clear that there was an enormous change in the market, and a huge need for better and more powerful tools, particularly around the area of cost management and cost prediction. >> So tell us a little bit about Digitory Legal, and exactly what the software enables legal departments and companies to do. >> Well, the short answer is, we are bringing data driven cost prediction to law. And we're doing it to really help law firms and corporate legal departments succeed in a changing legal market. Now, for most of the time that I was practicing law, when clients would ask that "how much" question, the answer, which was perfectly acceptable, was, it depends. And that is no longer acceptable. So, in order for legal departments to do their job and for law firms to really succeed, we have to, as an industry, dig into our data and do better. And that's what we do. >> So when you had the idea, tell us about the process and the phases that you went through to carry it forward and get the angel funding that you're currently receiving. >> Well, the starting point was a lot of market research. Because I knew as a lawyer what my pain point was. I knew how hard it was to answer that "how much "question in complicated cases, and communicate with clients when things would change. But I didn't know if everybody else was feeling that pain, and I didn't know if there were markets out there, software tools out there that I just didn't know about. So I dug in and I dug in deep on what was out there, what were the pain points, and it took several months to realize that the problem really is a data problem, and it's been an industry wide problem for a long time. So to solve cost prediction, we needed to tackle the data problem, and then it was about pulling on my networking, finding the best Silicon Valley talent to help me do that. >> And speaking of network, here we are at CloudNOW, which is the network of women. And your background, and actually digging in there and being an attorney, looking at, these are the challenges I'm having, how much of an advantage has that been in the networking conversations that you've had, demonstrating to potential funders and those that are funding you, this is a huge gap in the market that isn't solvable, we have an idea, help us actually start this so we can start enabling organizations to leverage that data as you're saying, it's really the only option now. >> The industry expertise, the deep experience and my background, has really helped because I walked away from a big law firm partnership to solve this problem, it was so pressing. And there are very clear trigger points if you understand the industry very well, that are, make it easy to explain why now, and why us, and the market has changed and the whole approach of corporate law has changed, and we can explain that because I've lived it and breathed it. >> So a big part of this is digital transformation, which is a theme we hear at every tech event that we go to, but it's not just transforming a tech company. I was talking this morning to a ski resort company that digitized their entire process from paper to electronic, so everybody understands we are digital, we are mobile, we need to have that. I'm curious, do your conversations with maybe traditional law firms, maybe such as the ones that you've worked at, how easy is it to get them on board with being data driven, is the only way for you as a law form to continue to succeed and to compete with the next generation that understands data has to drive the business, revenue opportunities, etc. >> There's fortunately there's been enough publicity and enough of a market shift, and requirements on the client side that law is starting to understand that data driven decision making is the way of the future, and if they are not early, they are late. So in order to compete in what has become an incredibly difficult market for law firms, they must be able to help their clients make data driven decisions, and be different than the rest of the pack. So fortunately, the market has shifted, and that shift is very very clear to even the most traditional law firms. >> So even in customer conversations, they're getting it. >> They're getting it, and they know that I experience their pain. So it's working. >> Excellent. Well kind of to wrap things up, and to bring us back to the event that we're at tonight, you have the opportunity not only to present to about 300 attendees today, this event was sold out not even advertised, it was selling like hotcakes with just networking and word of mouth, but there's also some pretty big notable keynotes that are here tonight. Sheryl Sandberg being one of them, and kind of one of the beacons that us females in technology look to. You have the opportunity as a lawyer turned technology entrepreneur to present in front of someone who's pretty well known and inspirational. Thoughts on that? >> It's an honor. It's an honor and a privilege. I really can't thank CloudNOW enough for putting together this event and giving female entrepreneurs like myself the opportunity to stand up and say what we do to an audience like this. >> Lisa: It's pretty exciting. >> Yeah. >> Last question there, about your company, are you guys hiring, what types of rock stars are you looking for? Are you looking for people with legal background? With tech background? >> Um AI, because the core of what we do is artificial intelligence, natural language processing, so rock stars in artificial intelligence, send me your resume, I would love to talk to you. >> Excellent. Catherine, congratulations on the award. Thank you so much for stopping by. Lawyer turned tech entrepreneur. I love that, it's a great headline. >> Thank you so much, I really appreciate the time. >> Our pleasure. We want to thank you for watching theCube. I'm Lisa Martin on the ground at Facebook headquarters. We'll see you next time. (Techno music)

>> Announcer: From the heart of Silicon Valley, it's theCUBE. Covering CloudNOW's seventh annual Top Women Entrepreneurs in Cloud Innovation Awards. (upbeat music) >> Hi, Lisa Martin with theCUBE, on the ground at Facebook Headquarters. We're here for the seventh annual CloudNOW Top Women Entrepreneurs in Cloud Innovation Awards. Welcoming one of the award winners and a CUBE alumni to the program, we have Tongtong Gong. You are co-founder and COO of Amberdata, Tongtong. Welcome back to theCUBE, and congrats on the award. >> Thank you, thanks for having me Lisa. >> Our pleasure. So, you've been on theCUBE before. We'll talk about Amberdata in a second. And I love the name, so I want you to tell us a little bit about that. Health and intelligence for blockchain, but one of the really interesting things about you is you are a technical female co-founder of a venture-funded company. A lot of words there, huge accomplishment. >> Tongtong: Thank you. >> Tell us about the inspiration. What was the opportunity? Was it your idea? Was it your co-founder's idea? How did this opportunity for the technology come to fruition? Then how did you, as a female, go and lead and get funding for this technology? >> Wow, how much time do I have? I can talk all day on this subject. So, it all started last 2017, summer. I was just very intrigued with blockchain technology and the potential of how blockchain can change our life and take our identity, assets, have full control, remove intermediaries. I had a full-time job at that time, leading engineering for a startup company, and I just don't have enough time in the day to learn about this new technology and what's the better way to do it, and then jump right in, start own company, and start from blockchain data. So, my background is in data analytics and computing, and when I start learning blockchain, I realized blockchain data, it's stored, it's immutable, but it's really hard to access. It's really hard to analyze. It's really hard to process without all the tools that we all know and comfortable with. So, me and my co-founder at that point were going back and forth with this new technology and the opportunities. I think it's his idea. Let's do something with the data that's stored on blockchain. Amberdata, the company's name, it's because Nick Szabo did a podcast with Tim Ferriss and Naval about blockchain is a fly trapped in amber. Upon layers and layers of amber solidified and the bubbles and the fly, you can still see it but it's immutable. You can't change it anymore. So, we're like, what brilliant name is that, right? >> Lisa: Absolutely. >> Amberdata. Without a tool, a platform like us, you can't possibly count all the bubbles in the amber. We help you extract the bubbles from the amber, the flies from the amber, and analyzing it. And that's what we do. >> Wow, that's a great analogy, a great name. Health and intelligence for blockchain. Blockchain is a very hot technology topic. Every company out there, whether they're a startup born in the cloud or legacy enterprise, wants to be doing something in blockchain. As a female co-founder, was that an advantage for you when you went in to venture capitalists looking to get funding? What do you think some of those advantages were? >> Honestly, I always consider being female is an attribute of me. It's not the definition of me. My gender doesn't define me. It doesn't constrain me. It's just who I am and I'm also engineer. I'm also incredibly curious all the time. I'm also bubbly. I'm also a wife. I'm also a daughter. So, there's just many attributes of me. When we start a company, we went into lots of friends and VCs and Meetups and we'd talk to anyone about our idea. Looking for advice, looking for validation. That's really what led us to get the funding. >> I love that. One day I hope we'll be to a place where gender doesn't define us but we know the numbers in females in technical roles. But it sounds like one of the things that you leveraged, maybe, were some of those softer skills. You're very personable. You had a great idea. You clearly have passion for it. Building your own groundswell with Meetups and a network seems like one of the key initiators of your success. >> Now you put it that way, I think so. I never thought about it that way. Yeah, 'cause in the beginning, you really try to define and refine the idea and the product. Are you solving a problem? What is the problem that you are solving? You really can't get answers unless you talk to lots of people and I think, perhaps, being a female, it really helps me just to talk to people all day long. >> It's good that you can do that. Genetically, I think we both have that in common. Tonight, as we wrap up here, you're presenting in front of Sheryl Sandberg, who is probably one of the beacons that women have globally. Not just in technology, she's obviously written some incredibly inspiring books about a number of different life situations. You must be pretty excited to have the opportunity to not only be a co-founder but to be recognized by this award and have somebody as prestigious and inspirational as Sheryl in the audience. >> Absolutely. I have both her books, Lean In and Option B. I actually bough both books in Chinese version for my mom, as well. So, I have four copies. I'm a huge fan of Sheryl. I think she's very inspirational about leaning in and take a seat at the table. One of my friend, Jamie Moy, once said, "Girl, let's forget about taking a seat. Let's create a table. Let's create a seat for other people." >> "Girl, let's create a seat." I love that. Tongtong, thank you so much for stopping by. Congratulations again on the award. >> Thank you. >> And we look forward to having you back on theCUBE again, talking more about what you're doing with Amberdata. >> Thank you for having me. >> We want to thank you. You're watching theCUBE. I'm Lisa Martin from Facebook headquarters. Thanks for watching. (upbeat music)

>> From the heart of Silicon Valley, it's the Cube Covering CloudNow 7th Annual Top Women Entrepreneurs in Cloud Innovation Awards. >> Lisa Martin on the ground with the Cube at Facebook Headquarters. We are here for the 7th Annual CloudNow Top Women Entrepreneurs in Cloud Innovation Awards. Welcoming to the Cube for the first time, one of tonight's winners, we have Charu Sharma, the Founder and CEO of Nextplay.ai. Charu, it's great to have you on the Cube. >> Thanks Lisa, I'm really excited to be talking to you. >> And congratulations on your award. Your pedigree, when I looked you up on LinkedIn, I thought wow, where do I even start, the things you've accomplished in such a short time period are pretty impressive. I want to share a few with our guests. You've built, in college, in your spare time, two award-winning start-up companies out of your dorm room before you got napped up by LinkedIn to grow their talent solutions revenue. You've won awards by Grace Hopper. We mention tonight you're here with CloudNow, one of the top women entrepreneurs in cloud innovation. Tell us about, I'd love to get your story of what inspired you to go off and found Nextplay.ai, the inspiration, also the chutzpah to say, "You know what I want to do this, "and I need to go get funding" which is really challenging for women in technical roles to do. Tell us about that. >> Yeah, so tonight I'll be giving a talk next to Sheryl Sandberg and that's nothing short of a miracle for me because I grew up in a family in India where women were not allowed to work, and so growing up it was important for me to have access to economic opportunities and that's how I came to the US for a scholarship, and I'm here today because a lot of mentors serendipitously came in my life and opened doors for me. So, to pay it forward, when I worked at LinkedIn before, I built a mentoring program for women at LinkedIn specifically cuz I think in the workplace especially women, minorities, and introverts suffer in finding a sponsor in helping open doors for you and mentors at your company can specially help you navigate the political landscape and help you grow your career at the company which helps the companies with retention as well. Exactly two years ago I started Nextplay.ai to be able to do this at scale, so today we work with companies from Coca Cola to Lyft to Splunk, and we not only connect their employees internally for mentorship, we also have robust analytics to show the ROI on retention. >> I was looking at some of your stats, I was telling you before we went live, I geek out on stats, that really show that your technology can make significant business impact for, you mention Coca Cola, Lyft, Splunk, etcetera but you obviously saw a gap a few years ago when you got into tech yourself saying not only do we know the numbers and the stats of women in technical roles as being quite low, but one of the things that you saw is one of the things we need to do to help increase those numbers is start internally and mentoring these women. To your point, of not just helping them establish confidence to stay but navigate that political landscape. I think that's a really unique opportunity, when you pitched this idea to these Cs, what was their response? >> Yeah, so mentorship is not an established product category, and on top of that, I inserted gender, race, accent, age, etcetera, and so frankly I got mixed opinions, but I chose to focus on the people who saw the big vision and who cared about the story and the impact something like this could have, so LinkedIn's executives, 500 Start-ups, TechCrunch's former CEO, who's a woman, they're some of the earliest investors who put their bets on us. Today we have shown success stories at every scale, so after six months of working with us employees are 25% more likely to recommend working at their company which actually when you do the math, it's huge. It saves millions of dollars for companies. There was a woman at a company who became the first woman at her company to get promoted while away on mat leave, that's huge. >> Wow, that is huge. >> A new product manager was able to, because of us, connect with somebody who they otherwise wouldn't know, and they were able to help identify a multi-million dollar market opportunity for the company, so there are definitely these case studies which is now creating a movement and now we have over 300 companies who want to work with us. They're on a waiting list. >> A waiting list? >> Mmhhm So we're definitely creating this momentum. >> And we talk about groundswell and momentum, especially at an event like tonight where there's over 300 attendees, 1o winners, one of them being yourself, and there was no advertising to buy tickets because the groundswell is growing so much. The trajectory that Nextplay.ai is on, in two years is pretty steep, you got some exciting things coming up in March, tell us about that. >> Yes, thank you, so when ai play and we sell to enterprise companies to do their mentoring and sponsorship programs internally for talent retention, that said, we started the company to help level the playing field so now that we're relatively stable and are a strong robust team with decent traction, this March we want to give a give back, so we're launching a social impact campaign where around the world we're going to help 100,000 women get mentored. So, if you want to host events at your company, if you want to get involved as a mentor or a mentee, please e-mail me at charu@nextplay.ai. >> And people can also go to the website to find out more information about that? >> Not about that campaign specifically yet, but they'll find my contact information, so it's nextplay.ai. >> And even at your Twitter handle which is probably in the lower third here. >> Yes >> Excellent, so congratulations on the award. The amount of work that you have done in such a short period of time is incredible. I can see it in your attitude and your smile and your energy, congratulations on getting to present to Sheryl Sandberg tonight and for seeing this opportunity in the market to help with that retention from within. What a great opportunity and thanks again. >> Thank you Lisa. >> We want to thank you for watching the Cube. I am Lisa Martin on the ground at Facebook headquarters, thanks for watching. (light electronic music)

>> From the heart of Silicon Valley, it's the Cube, covering CloudNOW's seventh annual Top Women Entrepreneurs in Cloud Innovation Awards. (upbeat music) >> Lisa Martin on the ground with the Cube at Facebook headquarters. We are at the seventh annual CloudNOW Top Women Entrepreneurs in Cloud Innovations Awards event. Joined by one of the 2016 winners welcoming you back to the Cube Syamala Bandla you are now at Facebook, a Director of Production Engineering. Welcome back to the Cube. >> Thank you Lisa. >> So we are at Facebook Headquarters, and we were talking with Jocelyn DeGance Graham a little bit ago who is the founder of CloudNOW. Their 7th annual event, first time at Facebook, and you a past winner are largely responsible for getting Facebook to say yes. Tell us a little bit about how you are paying it forward as a winner and enabling this years awards to have such a boost up. >> So I attended the CloudNOW event at the Google campus in 2016, and when I walked out of the event just not being the award recipient, but just meeting the other award winners, as well as the speakers, I was completely pumped up and charged. When I joined Facebook last year I saw how much deeply Facebook actually cares about diversity and inclusion. And I know that cloud computing and conversion technologies as an area where women are under represented. So when I pitched to my leadership team that when we care so much about, we should be hosting this years event and they jumped on board immediately. >> So it was an easy sell, but something also that's pretty remarkable that you should know about is that this year one of the keynote speakers is the COO of Facebook Sheryl Sandberg, and again Syamala you were instrumental in securing Sheryl who has a crazy busy schedule. That's huge for everybody here, and the ground swell of women in technology. Tell us a little bit about that coup. >> So when we decided finally to host it and as we were planning and all the line up of, great line up of speakers and the winners. We couldn't have thought about anybody else to do the opening remarks than Sheryl Sandberg. I know we had, she had, a very very tough schedule but my leadership team and I, we were persistent, and it's an honor to have her here to do the opening remarks. >> Absolutely yes. So talk to us a little bit about your tenure here at Facebook, you mentioned joining about eight or nine months or so ago and being a culture that fosters diversity, gender diversity, thought diversity. Tell us a little bit about your team in production engineering and how that culture, how are you helping to grow that? >> That's a great question. So definitely I'll be very honest, we have a lot more to do. Production engineering predominately in the industry is male-dominated. But just this year, just in the teams around me, we have hired quite a bit of female managers as well as individual contributors. And the support we get from our peers, the open thoughts, the collaboration, it's just great to be in an environment where we can foster that culture. >> And one of the things too, tell me about your background. Is your education background in a STEM field? Your engineering background? >> Yes. >> Yes, so talk to us about one of the things that's also challenging that we're all very familiar with, with women in technical roles, is the under representation, but it's also being able to retain women. You are establishing a great tech career yourself, what's your advice for inspiring your generation, and then the younger generation that you're helping to hire here at Facebook, to stay in technology. >> So cloud computing or technology, I mean we all have to pay it forward. I think we as women who are in influential positions and can make an impact on the younger generation I think need to absolutely do a lot more to pay it forward. It is not only with awareness but also wherever, whenever you get opportunities try to mentor students. Early on in their career encourage them to believe in themselves, to reach out for mentors and sponsors, do networking, which I think in general girls and women they shy away from it. I would say networking, meeting with people in the industry, they would be learning a lot more early on in their career. >> Great advice. One of the things that's also fantastic, and a first for this 7th annual CloudNOW event, is its, not only is it sold out, they're expecting over 300 attendees here tonight, both men and women, but also there was no advertising for the selling of tickets, so this was all word of mouth from the sponsors, Facebook, Google, Intel, past winners like yourself. So Jocelyn talked about that ground swell, that momentum that we're all feeling, what are your expectations for the event tonight? >> First of all we are super thrilled and excited. Like when I look at the list of the guest list, when I look at the speakers, when I look at the winners. I mean it was just the word of mouth as we started telling who will be the speakers and we will have a VC panel, and the winners. I think the word of mouth really paid it forward and we're super thrilled to have about close to 300 people attending the evening tonight. >> And there's a really nice diverse set of winners you mentioned. I was chatting with Jocelyn earlier and this is the first year that they've been able to recognize female, technical founders who are venture backed. And there's a variety of technologies, we're going to be speaking with all the winners tonight from the smart homes, the smart apartments technology, to blockchain, intelligence on blockchain, so the diversity there, and also not just the technologies but also the background of some of these entrepreneurs who, one of them is a lawyer who was a practicing attorney for 17 years founding Digitory Legal. Just really interesting backgrounds, what are your thoughts on that? >> So I think when we looked we had more than 100 nominees. It was very very hard, and I was also part of the committee as we were going through the winner, choosing the winners. It was very hard. But one of the things we really wanted to make sure was that we had a diverse set of winners. Not only from their backgrounds, but also the technology domain they were representing, which is very very important. And as we were going through the planning deck, and looking at the presentations, I can't wait to hear what they have to present. It is so thrilling to see the accomplishments and what they have achieved in their respective fields. >> And we're excited as well. Syamala thanks for taking time to stop by and join us on the program tonight, and it was good to see you again. >> Thank you so much Lisa, it's been a pleasure being here. Thank You >> Excellent. We want to thank you for watching Lisa Martin on the ground at Facebook for the Cube. Thanks for watching. (upbeat music)

[Narrator] From the heart of Silicon Valley, it's the Cube. Covering Cloud Now seventh annual Top Women Entrepreneurs in Cloud Innovation Awards. (techno music) >> Hi, Lisa Martin on the ground with the Cube at Facebook headquarters at the seventh annual Cloud Now Top Women in Cloud Innovation Awards. We are here for our third time with the founder of Cloud Now, Jocelyn Degance Graham. Jocelyn, it is great to have you back. Great to be back here for your seventh annual Cloud Now. >> We are just so delighted to be here with you Lisa and the Cube and all of the support and wonderful help that you've given us through the years for this event. >> So you have a lot of firsts that I wanted to cover and I know we've just got a few minutes of your time. Seventh annual, as I mentioned. >> Jocelyn: That's right. >> Your Cloud Now community now boasts over 1500 members. There's over 300 attendees here tonight. >> Jocelyn: That's right. >> And tell us what was really unique about how easy it was to attract this audience. >> Well this, we've never had such a great response for this event Lisa. And some of that could just be the timing. It is finally an idea who's time has come, right? And so there just seems to be such a groundswell of understanding the importance of inclusion and diversity. And beyond that actually creating belonging, right? So more and more, I feel like there's such an actual enthusiasm that we hadn't seen before. So this year, we didn't actually publish tickets or let people know that tickets were available. Everything was essentially sold through word of mouth. And so, we never even published any tickets. And we sold out of the event. And that was definitely a first for us. >> Another first is being here. >> Yeah. >> Not only being here at Facebook headquarters in Menlo Park California, but also having Sheryl Sandberg as one of the keynote speakers this evening. >> It is such an honor. You know she is one of the women who has just been so important in terms of the Seminole movement of women in tech. Like many women, I read her book, Lean In, years ago. And the fact that she's here with us tonight at the event, after having inspired an entire movement, is really significant and we're just thrilled. >> Another thing that's really interesting and a unique first for Cloud Now this year is you're recognizing 10 female tech entrepreneurs who are technical founders. >> Jocelyn: Technical founder, venture backed. >> Of venture backed businesses. >> Jocelyn: That's absolutely right. >> Tell us about how you've been able to achieve that because their backgrounds are diverse and the technologies that they're designing and driving are really incredible. >> This is one of the most, I think, exciting firsts about the event this year is in past events, we were recognizing women that had made major contributions in a technical field. And we were recognizing women regardless of the level or role or responsibility in the organization. Now we had largely done that because there were so few female founders of venture funded startups. This year was an absolute breakthrough year for many different reasons. There are organizations now like Allraise.org that are supported by women VC's. And there just seems to be an entire groundswell of female founders and we were able to, this year for the first time, align the criteria around female technical founders. And I'm really hoping that moving forward we'll be able to continue with that as more and more women realize that they should be starting businesses and they can get venture backing. >> And we're excited to talk to those winners tonight and ask how did you go about doing that? What were your inspirations and how do you kind of combat those fears and just the history of the challenge of getting funding there? Another thing that I noticed on the Cloud Now website is one of your taglines is together we can make a difference. In, you know, just the last minute or so give me some examples of how you're helping to make a difference that really resonate with you and that give you inspiration for your 2019 goals. >> That's such a great question. So for me, really one of the most heartening things about the organization is that the work we're doing together and through our scholarship program. So we're identifying the next generation of both female and minority leaders in tech and we're investing in them through our stem scholarship fund. This year, we have funders. Our funders include Google, Intel and Facebook. And we're really hoping to be able to expand that scope next year, Lisa, to increase the number of students we're helping. This year we're also, in addition to women, we are helping minority students as well. And for next year, we're wanting to expand those categories even further and being able to support people with disabilities. So we're really hoping that to create this kind of very strong fabric of the community coming together and really giving each other support. >> Jocelyn, thank you so much for having the Cube back for the third year in a row and congratulations on the groundswell that you're capitalizing on and that you're helping to create. We congratulate you and we appreciate your time. >> Lisa, it's always a pleasure. I love speaking with you. Thanks so much for coming. >> Likewise, we want to thank you for watching the Cube. Lisa Martin on the ground at Facebook headquarters at the Cloud Now Top Women Entrepreneurs in Cloud Innovation Awards. Thanks for watching. (techno music)