(gentle upbeat music) >> Hey, friends of theCUBE. It's Lisa Martin live at Stanford University covering the Eighth Annual Women In Data Science. But you've been a Cube fan for a long time. So you know that we've been here since the beginning of WiDS, which is 2015. We always loved to come and cover this event. We learned great things about data science, about women leaders, underrepresented minorities. And this year we have a special component. We've got two grad students from Stanford's Master's program and Data Journalism joining. One of my them is here with me, Hannah Freitag, my co-host. Great to have you. And we are pleased to welcome from Intuit for the first time, Shir Meir Lador Group Manager at Data Science. Shir, it's great to have you. Thank you for joining us. >> Thank you for having me. >> And I was just secrets girl talking with my boss of theCUBE who informed me that you're in great company. Intuit's Chief Technology Officer, Marianna Tessel is an alumni of theCUBE. She was on at our Supercloud event in January. So welcome back into it. >> Thank you very much. We're happy to be with you. >> Tell us a little bit about what you're doing. You're a data science group manager as I mentioned, but also you've had you've done some cool things I want to share with the audience. You're the co-founder of the PyData Tel Aviv Meetups the co-host of the unsupervised podcast about data science in Israel. You give talks, about machine learning, about data science. Tell us a little bit about your background. Were you always interested in STEM studies from the time you were small? >> So I was always interested in mathematics when I was small, I went to this special program for youth going to university. So I did my test in mathematics earlier and studied in university some courses. And that's when I understood I want to do something in that field. And then when I got to go to university, I went to electrical engineering when I found out about algorithms and how interested it is to be able to find solutions to problems, to difficult problems with math. And this is how I found my way into machine learning. >> Very cool. There's so much, we love talking about machine learning and AI on theCUBE. There's so much potential. Of course, we have to have data. One of the things that I love about WiDS and Hannah and I and our co-host Tracy, have been talking about this all day is the impact of data in everyone's life. If you break it down, I was at Mobile World Congress last week, all about connectivity telecom, and of course we have these expectation that we're going to be connected 24/7 from wherever we are in the world and we can do whatever we want. I can do an Uber transaction, I can watch Netflix, I can do a bank transaction. It all is powered by data. And data science is, some of the great applications of it is what it's being applied to. Things like climate change or police violence or health inequities. Talk about some of the data science projects that you're working on at Intuit. I'm an intuit user myself, but talk to me about some of those things. Give the audience really a feel for what you're doing. >> So if you are a Intuit product user, you probably use TurboTax. >> I do >> In the past. So for those who are not familiar, TurboTax help customers submit their taxes. Basically my group is in charge of getting all the information automatically from your documents, the documents that you upload to TurboTax. We extract that information to accelerate your tax submission to make it less work for our customers. So- >> Thank you. >> Yeah, and this is why I'm so proud to be working at this team because our focus is really to help our customers to simplify all the you know, financial heavy lifting with taxes and also with small businesses. We also do a lot of work in extracting information from small business documents like bill, receipts, different bank statements. Yeah, so this is really exciting for me, the opportunity to work to apply data science and machine learning to solution that actually help people. Yeah >> Yeah, in the past years there have been more and more digital products emerging that needs some sort of data security. And how did your team, or has your team developed in the past years with more and more products or companies offering digital services? >> Yeah, so can you clarify the question again? Sorry. >> Yeah, have you seen that you have more customers? Like has your team expanded in the past years with more digital companies starting that need kind of data security? >> Well, definitely. I think, you know, since I joined Intuit, I joined like five and a half years ago back when I was in Tel Aviv. I recently moved to the Bay Area. So when I joined, there were like a dozens of data scientists and machine learning engineers on Intuit. And now there are a few hundreds. So we've definitely grown with the year and there are so many new places we can apply machine learning to help our customers. So this is amazing, so much we can do with machine learning to get more money in the pocket of our customers and make them do less work. >> I like both of those. More money in my pocket and less work. That's awesome. >> Exactly. >> So keep going Intuit. But one of the things that is so cool is just the the abstraction of the complexity that Intuit's doing. I upload documents or it scans my receipts. I was just in Barcelona last week all these receipts and conversion euros to dollars and it takes that complexity away from the end user who doesn't know all that's going on in the background, but you're making people's lives simpler. Unfortunately, we all have to pay taxes, most of us should. And of course we're in tax season right now. And so it's really cool what you're doing with ML and data science to make fundamental processes to people's lives easier and just a little bit less complicated. >> Definitely. And I think that's what's also really amazing about Intuit it, is how it combines human in the loop as well as AI. Because in some of the tax situation it's very complicated maybe to do it yourself. And then there's an option to work with an expert online that goes on a video with you and helps you do your taxes. And the expert's work is also accelerated by AI because we build tools for those experts to do the work more efficiently. >> And that's what it's all about is you know, using data to be more efficient, to be faster, to be smarter, but also to make complicated processes in our daily lives, in our business lives just a little bit easier. One of the things I've been geeking out about recently is ChatGPT. I was using it yesterday. I was telling everyone I was asking it what's hot in data science and I didn't know would it know what hot is and it did, it gave me trends. But one of the things that I was so, and Hannah knows I've been telling this all day, I was so excited to learn over the weekend that the the CTO of OpenAI is a female. I didn't know that. And I thought why are we not putting her on a pedestal? Because people are likening ChatGPT to like the launch of the iPhone. I mean revolutionary. And here we have what I think is exciting for all of us females, whether you're in tech or not, is another role model. Because really ultimately what WiDS is great at doing is showcasing women in technical roles. Because I always say you can't be what you can't see. We need to be able to see more role models, female role role models, underrepresented minorities of course men, because a lot of my sponsors and mentors are men, but we need more women that we can look up to and see ah, she's doing this, why can't I? Talk to me about how you stay the course in data science. What excites you about the potential, the opportunities based on what you've already accomplished what inspires you to continue and be one of those females that we say oh my God, I could be like Shir. >> I think that what inspires me the most is the endless opportunities that we have. I think we haven't even started tapping into everything that we can do with generative AI, for example. There's so much that can be done to further help you know, people make more money and do less work because there's still so much work that we do that we don't need to. You know, this is with Intuit, but also there are so many other use cases like I heard today you know, with the talk about the police. So that was really exciting how you can apply machine learning and data to actually help people, to help people that been through wrongful things. So I was really moved by that. And I'm also really excited about all the medical applications that we can have with data. >> Yeah, yeah. It's true that data science is so diverse in terms of what fields it can cover but it's equally important to have diverse teams and have like equity and inclusion in your teams. Where is Intuit at promoting women, non-binary minorities in your teams to progress data science? >> Yeah, so I have so much to say on this. >> Good. >> But in my work in Tel Aviv, I had the opportunity to start with Intuit women in data science branch in Tel Aviv. So that's why I'm super excited to be here today for that because basically this is the original conference, but as you know, there are branches all over the world and I got the opportunity to lead the Tel Aviv branch with Israel since 2018. And we've been through already this year it's going to be it's next week, it's going to be the sixth conference. And every year our number of submission to make talk in the conference doubled itself. >> Nice. >> We started with 20 submission, then 50, then 100. This year we have over 200 submissions of females to give talk at the conference. >> Ah, that's fantastic. >> And beyond the fact that there's so much traction, I also feel the great impact it has on the community in Israel because one of the reason we started WiDS was that when I was going to conferences I was seeing so little women on stage in all the technical conferences. You know, kind of the reason why I guess you know, Margaret and team started the WiDS conference. So I saw the same thing in Israel and I was always frustrated. I was organizing PyData Meetups as you mentioned and I was always having such a hard time to get female speakers to talk. I was trying to role model, but that's not enough, you know. We need more. So once we started WiDS and people saw you know, so many examples on the stage and also you know females got opportunity to talk in a place for that. Then it also started spreading and you can see more and more female speakers across other conferences, which are not women in data science. So I think just the fact that Intuits started this conference back in Israel and also in Bangalore and also the support Intuit does for WiDS in Stanford here, it shows how much WiDS values are aligned with our values. Yeah, and I think that to chauffeur that I think we have over 35% females in the data science and machine learning engineering roles, which is pretty amazing I think compared to the industry. >> Way above average. Yeah, absolutely. I was just, we've been talking about some of the AnitaB.org stats from 2022 showing that 'cause usually if we look at the industry to you point, over the last, I don't know, probably five, 10 years we're seeing the number of female technologists around like a quarter, 25% or so. 2022 data from AnitaB.org showed that that number is now 27.6%. So it's very slowly- >> It's very slowly increasing. >> Going in the right direction. >> Too slow. >> And that representation of women technologists increase at every level, except intern, which I thought was really interesting. And I wonder is there a covid relation there? >> I don't know. >> What do we need to do to start opening up the the top of the pipeline, the funnel to go downstream to find kids like you when you were younger and always interested in engineering and things like that. But the good news is that the hiring we've seen improvements, but it sounds like Intuit is way ahead of the curve there with 35% women in data science or technical roles. And what's always nice and refreshing that we've talked, Hannah about this too is seeing companies actually put action into initiatives. It's one thing for a company to say we're going to have you know, 50% females in our organization by 2030. It's a whole other ball game to actually create a strategy, execute on it, and share progress. So kudos to Intuit for what it's doing because that is more companies need to adopt that same sort of philosophy. And that's really cultural. >> Yeah. >> At an organization and culture can be hard to change, but it sounds like you guys kind of have it dialed in. >> I think we definitely do. That's why I really like working and Intuit. And I think that a lot of it is with the role modeling, diversity and inclusion, and by having women leaders. When you see a woman in leadership position, as a woman it makes you want to come work at this place. And as an evidence, when I build the team I started in Israel at Intuit, I have over 50% women in my team. >> Nice. >> Yeah, because when you have a woman in the interviewers panel, it's much easier, it's more inclusive. That's why we always try to have at least you know, one woman and also other minorities represented in our interviews panel. Yeah, and I think that in general it's very important as a leader to kind of know your own biases and trying to have defined standard and rubrics in how you evaluate people to avoid for those biases. So all of that inclusiveness and leadership really helps to get more diversity in your teams. >> It's critical. That thought diversity is so critical, especially if we talk about AI and we're almost out of time, I just wanted to bring up, you brought up a great point about the diversity and equity. With respect to data science and AI, we know in AI there's biases in data. We need to have more inclusivity, more representation to help start shifting that so the biases start to be dialed down and I think a conference like WiDS and it sounds like someone like you and what you've already done so far in the work that you're doing having so many females raise their hands to want to do talks at events is a good situation. It's a good scenario and hopefully it will continue to move the needle on the percentage of females in technical roles. So we thank you Shir for your time sharing with us your story, what you're doing, how Intuit and WiDS are working together. It sounds like there's great alignment there and I think we're at the tip of the iceberg with what we can do with data science and inclusion and equity. So we appreciate all of your insights and your time. >> Thank you very much. >> All right. >> I enjoyed very, very much >> Good. We hope, we aim to please. Thank you for our guests and for Hannah Freitag. This is Lisa Martin coming to you live from Stanford University. This is our coverage of the eighth Annual Women in Data Science Conference. Stick around, next guest will be here in just a minute.

>>Welcome everyone to the cubes coverage of women in data science conference width 2022. Live from Stanford at the Arriaga alumni center. I'm Lisa Martin. My next guest is joined me. Sharon Hutchins is here the VP and chief of AI plus data operations at Intuit Sharon. Welcome. Thank you. >>Excited to >>Be here. This is your first woods, very first but into it in words. >>That's right. Intuitively it's goes way back. I'm relatively new to the organization, but Intuit has been a long time sponsor of woods, and we love this organization. We have a great alignment with our goals, which has a passion and commitment to advancing women in technology and data science. And we have the same goal added to it. We are at 30% women in technology with the goal of hitting 37% by 2024. And I know that widths has a great goal of 30 by 30, so that's awesome. >>30 by 30. And here we are around, I think it's still less than 25% of stem positions are filled by women. But obviously you're ahead of that on Intuit congratulate. >>I think we're ahead of that. And I think part of the reason why we're ahead of that is because we've got great programs at Intuit to support women. One of our key programs is tech women at Intuit. And so it's an internal initiative where we focus on attracting, retaining and advancing women. So it's a great way for women across technology to support one another. Sure. You've heard of the term there's power in the pack, and we believe that when we connect women, we can help elevate their voices, which elevates our business and elevates our products. >>It does. In fact, there's some stats I was looking at recently that just showed if there was even 30% females at the executive level, how much more profitable organizations can be in how much higher performance they can have. So the data is there that suggests this is a really smart business decision to be making. >>Absolutely absolutely the data is, is no lie. I see it firsthand in my own business. And in fact, at Intuit, we've got a broader initiative around diversity and inclusion. It's led from the top. We have set goals across the company and we hold ourselves accountable because we know that if there are more women at the table and more diversity at the table, all around, we make better business decisions. And if you look at our product suite, which is a terrible tax, QuickBooks, mint, credit, karma, and MailChimp, we've got a diverse customer base of a hundred thousand, sorry, a hundred million customers. And so it's a lot of diversity in our customer base and we want a lot of diversity in the company. >>Fantastic. That there's such a dedicated effort to it. You just came in here from the career panel. Talk to me about that. What were some of the key things that were discussed? Yeah, >>I have my notebook open here because there were so many great takeaways from actually just from the day in general. I'm just so at, at the types of issues that women are tackling across different industries, they're tackling bias. And we know that bias is corrected when women are at the table, but from a career perspective, some of the things that were mentioned from the panel is the fact that women need to own their own careers and they need to actively manage their careers. And there's only so much your manager can do and should do. You've got to be in the driver's seat, driving your own career. One of the things that we've done at Intuit as we've implemented sort of a self promoting process. So twice a year during our promotion period, either your manager can nominate you for a promotion or you can self promote. So it's all about you creating a portfolio of all of your great work. And of course, you know, managers are very supportive of the process and support, you know, women and, and all technologists in crafting their portfolios for a fair chance at promotion. And so we just believe that if you take bias out of a career progression, you can close that fair and equitable gap that we see sometimes across industries with compensation. >>This is, that would be great if we can ever get there. One of the things that's nice about woods, I think it was last year or the year before they opened it up to high school students. So it was so nice walking in this morning, seeing the young, fresh faces, the mature faces, but you bring up a great point of women need to be their own mini to create their own personal board of directors and really be able to, to be at the helm of their career. Do you, did you find that the audience is receptive to that? Do they have the confidence to be able to do that? >>Yeah, absolutely. And, and that was a point that was raised a couple of times this morning, there were women who talked about having great mentors, but it is more important to have a board of your personal board of directors than one mentor, because you've got to make sure that you sort of tackle all aspects of your career life. And you know, it's not all about the technology, a good portion of how you spend your time and where you spend your time is collaborating and negotiating and communicating across the company. And so that's very important. And so that was a key message that folks shared this morning. >>That's good. That's incredibly important. I wish we had more time. You've got to run to the airport. Sharon, it's been a pleasure to have you on the program. Thank you for sharing what Intuit and woods are doing together, your involvement and some of the great messages, inspiring messages from the career panel. >>Exactly. And for all of the young expiring high school students. Yes. We want them to check out into it. www.intuit.com, careers, >>Intuit.com. Is it slash careers slash careers slash careers perfectly. I'm an Intuit customer. I will say. Awesome. It's been a pleasure talking to you. Thank you, Sharon. Bye-bye for Sharon Hutchins. I'm Lisa Martin. You're watching the cubes coverage of women in data science, 2022.

>>live from Stanford University. It's the queue covering Stanford women in data science 2020. Brought to you by Silicon Angle Media. Yeah. >>Hi. And welcome to the Cube. I'm your host Sonia Category. And we're live at Stanford University for the fifth annual Woods Women in Data Science Conference. Joining us today is none. Ho, the director of data Science at Intuit None. Welcome to the Cube. >>Thank you for having me here, so yeah, >>so tell us a little bit about your role at Intuit. So I leave the >>applied Machine Learning teams for our QuickBooks product lines and also for our customer success organization within my team. We do applied machine learning. So what? We specialize in building machine learning products and delivering them into our products for >>our users. Great. Today. Today you're giving a talk. You talked about how organizations want to achieve greater flexibility, speed and cost efficiencies on. And you're giving it a technical vision. Talk today about data science in the cloud world. So what should data scientists know about data science in a cloud world? >>Well, I'll just give you a little bit of a preview into my talk later because I don't want to spoil anything. Yeah, but I think one of the most important things being a data scientist in a cloud world is that you have to fundamentally change the way you work a lot of a start on our laptops or a server and do our work. But when you move to the cloud, it's like all bets are off. All the limiters are off. And so how do you fully take advantage of that? How do you change your workflow? What are some of the things that are available to you that you may not know about? And in addition to that, some some things that you have to rewire in your brain to operate in this new environment. And I'm going to share some experiences that I learned firsthand and also from my team in into its cloud migration over the past six years. >>That's great. Excited to hear that on DSO you were getting into it into it has sponsored Woods for many years now. Last year we spoke with could be the San Juan from Intuit. So tell us about this Intuit's sponsorship. Yeah, >>so into it. We are a champion of gender diversity and also all sorts of diversity. And when we first learned about which we said, We need to be a champion of the women in data science conference because for me personally, often times when I'm in a room, um, going over technical details I'm often the only woman and not just I'm often the only woman executive and so part of the sponsorship is to create this community of women, very technical women in this field, to share our work together to build this community and also to show the great diversity of work that's going on across the field of data science. >>And so Intuit has always been really great for embracing diversity. Tell us a little bit about about bad experience, about being part of Intuit and also about the tech women part. Yeah, >>so one of the things that into it that I really appreciate is we have employees groups around specific interests, and one of those employees groups is tech women at Intuit and Tech women at Intuit. The goal is to create a community of women who can provide coaching, mentorship, technical development, leadership development and I think one of the unique things about it is that it's not just focused on the technical development side, but on helping women develop into leadership positions. For me, When I first started out, there were very few women in executive positions in our field and data science is a brand new field, and so it takes time to get there. Now that I'm on the other side, one of the things that I want to do is be able to give back and coach the next generation. And so the tech women at Intuit Group allows me to do that through a very strong mentorship program that matches me and early career mentees across multiple different fields so that I can provide that coaching in that leadership development >>and speaking about like diversity. In the opening address, we heard that diversity creates perspectives, and it also takes away bias. So why gender diversity is so important into it, and how does it help take away that bias? Yeah, >>so one of the important things that I think a lot of people don't realize is when you go and you build your products, you bring in a lot of biases and how you build the product and ultimately the people who use your products are the general population for us. We serve consumer, small businesses and self employed. And if you take a look at the diversity of our customers, it mirrors the general population. And so when you think about building products, you need to bring in those diverse perspectives so you could build the best products possible because of people who are using those products come from a diverse background as well, >>right? And so now at Intuit like instead of going from a desktop based application, we're at a cloud based application, which is a big part of your talk. How do you use data Teoh for a B testing and why is it important? >>Yeah, a B testing That is a personal passion of mine, actually, because as a scientist, what we like to do is run a lot of experiments and say, Okay, what is the best thing out there so that ultimately, when you ship a new product or feature, you send the best thing possible that's verified by data, and you know exactly how users are going to react to it. When we were on desktop, they made it incredibly difficult because those were back in the days. And I don't know if you remember those put back in the days when you had a floppy disk, right or even a CD ROM's. That's how we shipped our products. And so all the changes that you wanted to make had to be contained. In the end, you really only ship it once per year. So if there's any type of testing that we did, we're bringing our users and have them use our products a little bit and then say Okay, we know exactly what we need to dio ship that out. So you only get one chance now that we're in the cloud. What that allows us to do is to test continuously via a B, testing every new feature that comes out. We have a champion Challenger model, and we can say Okay, the new version that we're shipping out is this much better than the previous one. We know it performs in this way, and then we got to make the decision. Is this the best thing to do for a customer? And so you turn what was once a one time process, a one time change management process. So one that's distributed throughout the entire year and at any one time we're running hundreds of tests to make sure that we're shipping exactly the best things for our customers. >>That's awesome. Um, so, um, what advice would you give to the next generation of women who are interested in stem but maybe feel like, Oh, I might be the only woman. I don't know if I should do this. Yeah, I think that the biggest >>thing for me was finding men's ownership, and initially, when I was very early career and even when I was doing my graduate studies for me, a mentor with someone who was in my field. But when I first joined into it, an executive in another group who is a female, said, Hey, I'd like to take your side, provide you some feedback, and this is some coaching I want to give you, And that was when I realized you don't actually need to have that person be in your field to actually guide you through to the next up. And so, for women who are going through their journey and early on, I recommend finding a mentor who is at a stage where you want to go, regardless of which field there in, because everybody has diverse perspectives and things that they can teach you as you go along. >>And how do you think Woods is helping women feel like they can do data science and be a part of the community? Yeah, I think >>what you'll see in the program today is a huge diversity of our speakers, our Panelists through all different stages of their career and all different fields. And so what we get to see is not only the time baseline of women who are in their PhDs all the way to very, very well established women. The provost of Stanford University was here today, which is amazing to see someone at the very top of the career who's been around the block. But the other thing is also the diversity and fields. When you think about data science, a lot of us think about just the tech industry. But you see it in healthcare. You see it in academia and there's a scene that wide diversity of where data science and where women who are practicing data science come from. I think it's really empowering because you can see yourself in the representation does matter quite a bit. >>Absolutely. And where do you see data science going forward? >>Oh, that is a, uh, tough and interesting question, actually. And I think that in the current environment today, we could talk about where it could go wrong or where it could actually open the doors. And for me, I'm an eternal optimist on one of the things that I think is really, really exciting for the future is we're getting to a stage where we're building models, not just for the general population. We have enough data and we have enough compute where we can build a model. Taylor just for you, for all of your life's on for me. I think that that is really, really powerful because we can build exactly the right solution to help our customers and our users succeed. Specifically, me working in the personal friend, Small business finance lease. That means I can hope that cupcake shop owner actually manage her cash flow and help her succeed to me that I think that's really powerful. And that's where data science is headed. >>None. Thank you so much for being on the Cube and thank you for your insight. Thank you so much. I'm so sorry. Thanks for watching the Cube. Stay tuned for more. Yeah, Yeah, yeah, yeah, yeah, yeah.

>> Live from Barcelona, Spain it's theCUBE. Covering KubeCon + CloudNativeCon Europe 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation and ecosystem partners. >> Welcome back to theCUBE here in Barcelona, Spain at the Fira, it's KubeCon + CloudNativeCon 2019. I'm Stu Miniman and my co-hosts for two days of live wall-to-wall coverage is Corey Quinn. Joining us back, we have two CUBE alums, Liz Rice, right to my right here who is a Technology Evangelist with Aqua security. Liz, thank you so much welcome back. >> Pleasure to be here. >> And Jeff Brewer, Vice President and Chief Architect, Small Business & Self-Employed Group, of Intuit. A CUBE alum since a few hours ago this morning. >> Yes, yes, thank you. >> Jeff, welcome back. >> Thank you. >> So, we've got you back with a different hat. Everybody in our industry can definitely recognize we wear lots of different hats we have lots of jobs thrown at us. Both of you are in the Technical Oversight Committee and Liz is not only a member but also the Chairperson, President. (people laughing) >> President is definitely a promotion. But, yeah, I'm Chair of the committee. >> Maybe, as it's known, the TOC. Liz, before we get there, your shirt says +1 binding. You have to explain for us and did not get a preview before the interview, so we'll see where this goes. >> It's one of the perks of being on the TOC. When we have something that comes to a vote we want to get input from the community so we ask anyone in the community to vote. But unless you're a member of the TOC your vote is non-binding. As a member of the committee, we have binding votes. And the traditional thing you write on the voting email is +1 binding. So, it's a nice surprise to get a t-shirt when I joined the TOC. >> Very nice. Can you just give us, our audience, that might not be familiar with the TOC, give us some of the key things about it. >> It's the Technical Oversight Committee for the CNCF. We are, really, the technical curation of the projects that come in to the CNCF. Which projects will get support and at what level because we have the sandbox experimentation stage then incubation and then finally graduation for the really established and kind of, de-risked projects. So, we're really evaluating the projects and kind of making a decision collaboratively on which ones we want the CNCF to support. >> All right. So Jeff, we had a great conversation with you about Intuit's cloud journey. Tell us how you got involved in the TOC. We always love the end users, not just using but participating in and helping to give some governance over what the community is doing. >> Yeah, so, about a year and a half ago we made a decision to acquire a small company called Applatix. Who was, actually, already in the end user community. And also contributors as well. Through that acquisition, I was part of that acquisition, I led that acquisition from the Intuit side and really got excited about the Kubernetes and the KubeCon story overall. Through the Kubernetes experts, I met them at a KubeCon and they introduced me to a whole lot more of the community. Just through some overall partnerships with AWS and also spending a lot of time with end-users that's how I really got to know the community a little bit. And then, was voted onto the CNCF as an end user representative in January. >> Wonderful. As far as you're concerned, as you go through this, do you find it challenging at times to separate your roles professionally from working for a large company, to whom many things matter incredibly. Again, as mentioned earlier, I am one of your customers. I care very much about technical excellence, coming out of Intuit, versus your involvement with the larger project. >> Yeah, so like most people in technology companies I'm extremely busy and I would love to spend, I would love to clone myself and spend more (laughing) more time. >> Everybody wants to submit a client project to the TOC we will prioritize that one. >> Exactly, exactly. >> The way I really balance it is that I make an explicit time carve out for those two activities. And most importantly, I attend the meetings. The TOC meetings that we have, those are extremely important. We get a lot of project reviews in those meetings. Liz chairs those meetings. That's where I always make sure that my schedule is cleared for that. >> Taking it, I guess, one step further. Do you find it challenging at all to separate out, in fact, when you're making decisions and making votes, for example, that are presumably binding, +1 binding as we've learned now, is the terminology. Do you find that you are often pulled between trying to advocate for your company and advocating for the community or are they invariably aligned in your mind? >> I mean, my job's the easiest because I come from an end user. So what I use and what I consume is likely what the community at large. There might be some niches and stuff like that. But I usually don't have that conflict. I don't know, as more of a vendor, you might have more of a conflict. >> It's something that I have be conscious of. I just try to mentally separate. I have a role with a company that pays my salary but when I'm doing open-source things if I feel conflicted about. This hasn't really come up yet, but if I do feel that there's some kind of conflict of interest I will always recuse myself. Actually, in my previous role, as the Co-Chair for the Program Committee for the KubeCon and CloudNativeCon Conference, on a couple of occasions we had competitors submit, and I would always just step back from those. Because it's the right thing to do. >> All right. So Liz, there's quite a few projects now, under the umbrella of CNCF. If I've go it right, it was like, 38 different ones. When Brian went on the stage this morning, 16 in the sandbox, 16 incubating and six have graduated now. How do you manage that? You know, there's some in the community they're like, oh my gosh, reminds us of like, big tent, from some initiatives. Some other things here, how much is too much? How do you balance that and what's the input of the TOC? >> Yeah, so one of the things that we're doing with the TOC is we've just established a thing called the SIGs, the special interest groups. Very much following the same model of Kubernetes SIGs. But the idea here is that we can, kind of formalize getting experts in the community to help us with particular kind of areas. So, we've already got a storage and security SIG set up. We expect there will be probably four to six more coming on board during the year. And that helps us with things like the project reviews and the due diligence to just be able to say, we would really appreciate some help. Those groups are also really enthusiastic about kind of sharing knowledge in the form of things like white papers. I think it will be really important for end-users to be able to navigate their way around these projects. Quite often there is more than one solution for a particular thing. And being able to, in a non-vendor way, in a neutral way, express why project X is good in one circumstance and project Y would be better in a different environment. There's work to be done there and I'm hoping to see that come out. >> This is one of my passions as the end user representative, is that trail map or that road map. That's one of the reasons why we really have invested at Intuit, in the Kubernetes technology and the Cloud Native technology. We didn't just roll them out as is. We actually curate them and create, really, a paved road for our developers to navigate that space. >> Yeah, and as we heard from your story it's not always, well, if there's some overlap you use SDO and Hellman. >> Yeah. >> That there's a fit for both of those in your environment, right. >> Yeah. >> From a, I guess, an end user perspective is there a waiting difference between someone like Intuit and someone like Twitter for pets, where there's a slight revenue scale, a slight revenue difference, like scale difference, like everything difference. >> Yes. >> Certainly, there is. I think that, but that's one of the beautiful things about the Cloud Native technologies. You can consume what you need and what you want, right. It's not one size fits all. A lot of people talk about, oh, there's a paradox of choice, there's so many projects, right. Actually, that's a benefit. Really, all you need is that road map to navigate your way through that, rather than just adopting a paved road that might not work for everybody. >> It almost feels, to some extent, almost like the AWS Service Catalog. Whenever you wind up looking at all the things they offer. It feels like going out to eat at the Cheesecake Factory. Where there is 80 pages of menu to flip through with some advertisements, great. And reminding yourself, at time, that they are not Pokemon, you do not need to catch them all. It's, sometimes, a necessary step, as you start to contextualize this. >> That's one of the great things about having over 80 members in the end user is. You can find a buddy, you can find a company like you. Talk to them, get connected with them and figure out what they're doing and learn from them. The community is broad enough to be able to do that. >> All right, so Liz, let's talk about security. >> Okay. (people laughing) >> You said there's a SIG that started up. Where are we, how are things going and you can you share about where we're going in the near future? >> The SIG came together from a group of people who really wanted to make it easier for end-users to roll out their Cloud Native stacks in a secure fashion. We don't always, as a community, speak the same language about security, we don't always have the most secure settings by default. They really came together around this common interest of just making it easier for people to secure. I think a big part of that will be looking at how the different projects, are they applying best practices from a security perspective? Is there more they should do to document how to operate their particular project more securely? I think that whole initiative and that group of people who've come together for SIG security, I'm so impressed and so pleased that they have come together with that enthusiasm to help on that front. >> Any commentary on what you're seeing in this space? >> Yeah, so as an almost, a fintech company, with a lot of fintech and, you know, we're not quite a bank, but we have a lot of the same security and compliance things. That SIG is so, so important to us. And having a roadmap. I found a education is really, really a big part of it of the security experts, right. Because this is somewhat newer technology. Even though it's been in use at Google for a long time the regulator's, the compliance people, don't totally understand it, right. So you have to have a way to explain to them what's going on. So things like, open policy agent, something that we've adopted, helps us explain what's going on in our system. Once they get it, they're like, this is awesome and our end users can now, really, our end users, meaning the people that use QuickBooks and TurboTax can really trust that we have those guardrails in place. >> At Aqua, it's a huge concern from a lot of our customers. Many of whom, coming from that kind of finance industry. That they're coming to us and saying, well, how can I be PCI compliant or GDPR. How do I manage these requirements with my container based stack, with my Cloud Native stack. That's why there is this huge ecosystem quite a lot of effort around security, compliance, policy. >> It feels very much like it's two problems rolled into one. First, how do you make sure that data is secure in these things? Secondly, how do you effectively and responsibly communicate that to a regulator, who expects to be taken on a tour of a data center when they show up on site? (people laughing) I checked, they won't let you. >> There are definitely two sets of security people in my experience. There are a set of people who care about how will I get attacked. How will breaches happen. And there are other people who go, I have a checklist and I need to check the boxes in the checklist, tell me how. Sometimes those two things overlap, but not always. >> All right, Liz, lot of updates, as always. Jeff, I really appreciate your commentary there. Well, there's the paradox of choice but we have a lot of customers out there and therefore we do. (people chuckling) Any highlights you want to share with our audience? >> I think one thing that happens every year is we see more. Well, we saw Kubernetes graduate, I think, early last year, end of the previous year. Now we've got six projects into graduation. From my perspective, that says something about how mature this whole set of projects, this whole platform is becoming. Because graduation is a pretty high bar. Not least in terms of the number of end users that have to be using it in production. This is solid technology. >> Yeah, any highlights from you? >> I think, like we might have touched on a little bit this morning. But I think that usually the technologies that where you're facing the big problems is pretty obvious which one to use, right. Like serverless, you're going to go look at something like Knative or whatnot. Functions as a service. There's some open fast projects, whatnot, like that. SDO services mesh is another one where it's getting mature and it's getting to the point where you can have these ubiquitous service meshes throughout it. So, those are the areas that we're most looking at right now. >> Great, all right. Well, Liz and Jeff, thank you so much for joining us. Thanks for all the work you do on the Oversight Committee and appreciate you sharing the updates with our community. >> Thank you for having us. >> Thank you. >> For Cory Quinn, I'm Stu Miniman. We'll be back more, with theCUBE here at KubeCon + CloudNativeCon 2019. Thanks for watching. (upbeat music)

>> Live from Barcelona, Spain, it's theCUBE, covering KubeCon CloudNativeCon Europe 2019. Brought to you by Red Hat, the Cloud Native Computing Foundation, and ecosystem partners. >> Hi and welcome back, I'm Stu Miniman with my co-host Corey Quinn, and you're watching theCUBE, the worldwide leader in live tech coverage of KubeCon CloudNativeCon 2019. Happy to welcome to the program a first-time guest, Jeff Brewer, who's the Vice President and Chief Architect of Small Business and Self-Employed Group at Intuit. He's going to talk about your cloud journey. Jeff, thanks so much for joining us. >> You're welcome, I'm glad to be here. >> All right, so, Jeff, the easy part of this is, I think, most of our audience has probably heard of Intuit, but maybe give us that first setting of, you know, the part of the group you're in, and your role, and then we want to get into that journey. >> Yeah, yeah, no, it's great. So, yeah, first of all, thanks for having me here and I'm what's called the Chief Architect of the Small Business and Self-Employed Group. Intuit is about powering prosperity around the world. That's our fairly new mission. And helping both taxpayers with TurboTax and QuickBooks is our other big project. So, think of me as the Chief Architect for the QuickBooks group. And so, mostly for small businesses, helping small businesses survive through their first year, survive and prosper continuing on, so. >> And your charter there, is that the infrastructure there, you're not trying to help the world rid those malicious attacks of like, oh no, I got the new TurboTax and it didn't work well because, disclaimer, you know, I'm not paid, I've used it for many years and it's super easy for me. >> Yeah so, as a Chief Architect, I set the technical direction of the overall QuickBooks franchise both the desktop version which is our older version that, you know, has been around for 20, 25 years, and our QuickBooks Online version, which is about, only about 15 years old and is our SAS offering. And so, I do things like choose technologies that we adopt. I do things like set what are the most important technology priorities whether it's breaking things up into microservices, our cloud strategy, Kubernetes, going to cloud native, all that kind of stuff. >> Okay, so, you are a member of the Technical Oversight Committee, but we're actually going to bring you back a little bit later to talk about that, so, we'll put a pin in that. But give us a little bit as to kind of what led to this journey towards cloud and, you know, all of those pieces that you were just talking about. >> Yes, so, like many other companies with, you know, lots of legacy and lots of code that we've developed over about 35 years of existence, we actually started out in the early 2000's with building our own data centers, right. And it's very expensive, very ambitious, but at the time, there really wasn't a public cloud. But we realized that, you know, putting servers under our desks and stuff like that, you know, we really needed to grow to a more robust data center. And, you know, as we progressed in that journey, we figured out we're not the experts at maintaining and developing all the complicated networking you have to do, reliability, resiliency. We had some outages, this is 10 years ago or so, where a truck drove into a light post outside one of our data centers and took us down for a day. And that's just not acceptable for our customers. The public cloud was just starting out, AWS was a big partner out there, and our CIO, and CEO, met with the AWS executives and really decided that we needed a great partner in public cloud that really was their technical expertise. And so, we began this journey, mostly I would describe it as lift and shift, of technologies and services that we already had. We had to rewrite a few of them to make them actually work with the cloud. But by and large, most of our code is written in Java and that ports pretty well. So, we started on that journey and really right now, we are mostly running in the public cloud. We have a few legacy systems that are still running in our private data centers, but we're planning on decommissioning those. And with the public cloud, a journey we really have seen quite a, improvement in our reliability, our downtime, we can fail over between availability zones, it's just been fantastic from our overall availability, recoverability standpoint. But what we realized during that journey was that the, that the AWS native experience for our developers, while AWS is just an amazing, amazing partner, it wasn't quite the developer experience we wanted. >> It had some sharp edges. >> Yeah, we worked with them on that, and that's why we started looking at cloud-native technologies, things already developed by the community. AWS is part of the community, as well, and so they were extremely supportive in our journey to want to, from the developer experience standpoint, really start to press on these cloud-native technologies. >> Wonderful. As you went down that entire path, whenever a company goes public and they put in their S1 that they're doing some committed level of giant deal with AWS, people immediately chime in with, oh, they could save so much money by building and running their own data centers. How do you stand on that particular perspective? >> So, what's really interesting about our, our public cloud journey, right, it's not necessarily about saving a lot of money, right? And we realized that, you know, Intuit, as a mature company, you know, we're not a start-up looking to shave every little penny off of every little server. What we really want is reliability for our customers, we want awesome operations, and so, the public cloud journey actually hasn't been a huge, huge cost savings, but it has been a huge improvement in all these other levels, so it does amazing things for our customers. And we're looking to cloud native as just another, you know, bump up in that overall thing, where we get immediate mean time to recovery, where things go down, things go wrong, and we get those pods and those services right back up and running. >> Can you elaborate a little bit about the application that you're talking about, like when I first heard you say, you know, we just lifted and shifted there, it's like, oh wait, you know, a lot of times that is when we kind of claw things back because it's costs more than I thought or it didn't run as well as I thought. >> It turns out the mainframe's hard to move because they didn't build an AWS 400 yet, something doesn't happen. >> So, the challenges there, and then, you know, connect the dots with that to what you're calling the cloud native piece of this, as to what your application development looks like. >> So, I'll use QuickBooks Online as an example. Massive property, over four million customers. >> I'm one of them. >> And it started out as a, as kind of our first really big foray into SAS, right? And luckily, at the time we wrote it, mostly in Java. But it was written as this huge, monolithic piece of code, right. And so, millions of lines of code, you can imagine, large memory footprints, all that kind of stuff. And so, during our first, for public cloud, we just looked at, well, we're not going to rewrite these millions and millions of lines of code, but we want to get into public cloud. Lucky for us, EC2 instances, things like that, can run those large memory footprints. But once there, we really started examining, okay, what does this look like as microservices? Because when you have over 400 engineers working on a single code base, imagine what doing a release, a release is a ceremony, right? It's like this huge thing, you have-- >> It takes a many page calendar in order to do those things. >> Exactly, and so, what we really wanted to do is press into the microservices journey and say, okay, what if instead of having this huge oil tanker, you know, driving down the, you know, sailing down the ocean, what if we could be a bunch of speedboats, right, and use that analogy. And that's where cloud native comes in, because that's really what it's meant to do, right? A bunch of independent teams doing dev ops, you build it, you run it, right? You write the code, you run the code. And so, it plays right into to this, this ability to be very agile, give each team, you can imagine at a scale of 4000 engineers, you want little pizza team, you know, to be independent and do their own releases, and not have to coordinate all with each other. >> So, Jeff, which of the, you know, CNTF pieces are you using at Intuit, and I would like you to go in a little bit, you know, Kubernetes, a lot of people, it's like, oh well, I want portability, and it sounds like you're all in, primarily, on one public cloud, so that's probably not the first thing on your list, so, help us understand the landscape from your eyes. >> So, really it's about, it's about developer productivity. So yes, we do have this very good, strong partnership with AWS, and that is our public cloud provider. And so, the cloud-native technology, using, obviously, Kubernetes, obviously, you know, we're running Docker in the background for running the containers and all that infrastructure. We have our own open source called Argo, which we're using for deployments in the community, so we're contributing a little bit back to community, as well. We're using Istio and Envoy as a service match to really secure the interservice communications and support all the routing and whatnot. And we're also leaning very heavily now into serverless technologies, and so, we write our app, QBO or QuickBooks Online, as a stateful application, but we're realizing the power of having these really stateless small functions, and so we want to do that, as well. And the way we look at it as, Lambda is a fantastic technology for something like that, but the developer experience, we want the same developer experience for our containers that we do from our functions, right? And if you really think about it, it's just about deploying, it's how you deploy. Do I deploy into containers and then a pod structure, like in Kubernetes? Or do I deploy to a functions as a service? It should run on the infrastructure, and so, from a developer standpoint, from the end developer that's actually developing the applications and services that our customers are using, we want the declarative infrastructure of Kubernetes, we want the ease of deployment and of operations. You can just imagine a development team not having to learn the huge depth that's behind that Kubernetes, that developer experience is just unbelievable and second to none. And you can imagine these teams sitting around, you know, at lunch time, doing their release, something goes wrong, they're on the call, they're solving the problems for their customers, in fact, doing another release, if there's any problems. And so, that's where we really, really lean in heavily to these cloud technologies, the cloud-native technologies, so we can get even faster at the developers. >> Do you find that making it more accessible and having a consistent developer experience has, I guess, broadened the ability of your developers to iterate more rapidly, or is more about ensuring consistency across the board? In other words, is it a speed value for you or is it more about just consistency, so you can wind-up up-to-point to multiple architectures? >> It's really about both. We see, you know, agility is often confused with speed and velocity, but we see that enabling a developer to release code to production in just a few minutes is extremely, extremely powerful to the overall velocity because what they're more likely to do is they're more likely to experiment, be bold, try new things, and then get immediate feedback for the customer. There's this experimentation loop that you want it to move as fast as possible. And so, not only that, but to your second part about the consistency, for a company like Intuit with 4000 developers, you want mobility in your organizations, and so, you want someone to feel very natural going from one small pizza team to another, and have the same tools, the same deployment architecture, and the same thing, right? So, you're not retraining them on a ton of different technologies. >> Alright, so, Jeff, you know, what could the ecosystem, you know, the partners you're working with, the various ecosystem, what could they do to make your life easier? I mean, the one that comes to mind for me is, you know, today, serverless, you know, Lambda, specifically, and Kubernetes. There are some ways to get them, you know, work at little bit, but, you know, is that top of your mind or are there other things? >> That is actually really top of my mind. We have a lot of teams experimenting with Lambda. We're running huge workloads in Lambda, but we're very much worried about this. If there's teams working on that and it's very, it's very fragmented. Some teams are deploying Lambdas off their laptops, other teams are, you know, using CICD processes. And so, we want that experience to be consistent, secure and everything. And so, as it moves to more production workloads, right, we would really like the Kubernetes and the CNCF Foundation to really have a story about serverless itself. I think it's probably more aptly called functions as a service or running functions. And I think a lot of thing happens is that it's treated as a versus. It's like, oh, I'm going to skip over that containers to Kubernetes thing and go to serverless, because it's versus, right? It's not versus, it's a choice for the developer about what to I want to deploy in functions, in short-running functions, or do I want to deploy in containers? Everything else up to that point is the same. And so, I'd really like to see, and that, as my role on the Technical Oversight Committee, that's something I'm really focused on for the end users 'cause I see that a lot in the end user's communities. They're dealing with the same things that we are on that functions as a service. >> Alright, so, Jeff, before I let you go, Intuit's an award winner, so, congratulations on that. >> Thank you. >> I want final word from you. Talk a little bit about the award and two, talk your peers that might be, you know, they've heard about Kubernetes, but, you know, we're into the, we've crossed the chasm in the majority, but that means there's a lot of people that are still relatively early. What do you recommend to them, what tips would you give them, and start with the award though. >> Yeah, so, we're extremely honored to be the CNCF end user award winner. Our cloud journey has been a really interesting one that came really out of a, also, out of an acquisition that we did of some fantastic Kubernetes experts about 14 of them, a little company called Applatix that had this Argo project. And their mission was to make Kubernetes accessible to the overall community. And by acquiring them, we left their mission the same, but they're really helping Intuit, and we're not selling their, they're helping the community for free, when they were charging before as enterprise customers. And that's something I'd overall recommend for the peers and the companies thinking about going on a cloud native journey is it's about those people that you can find here at the conference, right, about those experts that you can hire, just a few of them, have them come into your company, explain these things, and it turns the entire company around. We now have hundreds and hundreds of teams going through and onboarding, we call it modern SAS, internally, onboarding onto this technology because they started out with that nugget or that kernel. >> Alright, well, Jeff, modern SAS, love the story, thank you so much and thanks for joining us and we will see you later to talk about the TOC. >> Glad to be here, thank you very much. >> Thank you very much. >> For Corey Quinn, I'm Stu Miniman, and that was Jeff Brewer from Intuit, we'll be back with lots more coverage and thank you for watching theCUBE. (dynamic digital music)

[Announcer] Live from Stanford University, it's The Cube! Covering global women in Data Science Conference. Brought to you by SiliconeANGLE Media. >> Welcome back to The Cube. I'm Lisa Martin, live at Stanford University for the fourth annual Women in Date Science Conference, hashtag WiDS2019. We are here with Kavita Sangwan, the Director of Technical Programs, Artificial Intelligence and Machine Learning at Intuit. Kavita, it's wonderful to have you on the program. >> Thank you, pleasure is all mine. >> So Intuit is a global and visionary sponsor of WiDs, and has been for a couple of years. Talk to us a little bit about Intuit's sponsorship of this WiDs movement. >> Sure, well, Tech Women at Intuit has been important part of our culture. It was founded sometime a couple of years back from our previous CTO Taylor Stansbury. He was the founder and sponsor for it, and it has been getting the continuous support and sponsorship from our current CTO, Marianna Tessel. We highly believe that diversity in inclusion, and diversity in talks, and diversity in employees, is an important aspect for our company because that kind of helps us to deliver awesome product experiences and seamless experiences to our customers. This is our second year at WiDs, and we are proud to be part of this event today. >> It's growing tremendously, you know I mentioned it as a movement, and in three and a half years, this is the fourth annual, as I mentioned, and Margot Gerritsen, one of the co founders, chatted with me a couple hours ago and said they're expecting 20,000 people to be engaging today alone. The live stream at the event here at Stanford, but also the impact that they're making. There's a 150 plus regional events going on around this event in 50 plus countries. >> So it's the... You and I were chatting before we went live that you feel this, this palpable energy when you walk in. Tell me a little bit about your role at Intuit, and how you're able to really kind of grow your career in this organization that really seems to support diversity. >> Sure, I head the Technical Program Management for Intuit Data Science Organization, so it's all about data, data science, AI Machine Learning. We apply and imbed AI Machine Learning across all of our product suites. And also try to apply AI Machine Learning in different other aspects as well. Some of the focus areas where we applying AI Machine Learning is making our products smart, security risk and fraud space, where we are all several steps ahead of the fraudsters. Also, in customer success space, and also within the organization, the products and services our work employees use to make their experiences amazing. I have been with Intuit for almost three years now, and it has been an amazing journey. Intuit is such a... It embraces diversity, and it's because of its diverse, durable, innovative culture, I think Intuit has been in Silicone Valley as a strong force for over 35 years. >> So when we think about Data Science, often we think about the technical skills that a data scientist would need to have, right? It's the computational mathematics and engineering, being able to analyze data, but there's this whole other side that seems to be, based on some of the conversations that we've had, as important but maybe lagging behind, and that is skills on being a team player, being collaborative, communication skills, empathy skills. Tell me about, from your perspective, how do you use those skills in your daily job, and how does Intuit maybe foster some of those communication negotiation skills as equal importance as the actual data itself? >> It's very important for us, as we hire our top talent in our organization to empower and grow that top talent as well. We do that by providing them opportunities to learn from different sessions we host around executive presence, negotiation skills, public speaking skills. In addition to advancing them in their technological space. As you rightly said, it's very important for us to operate in a team setting. You know, a data scientist has to interact with a product manager, and a data engineer, a business person, a legal person, because there is questions about security and privacy. So there are so much interactions happening across functional space, it is very important for us to be a team player, and having the ability to have those conversations in the right way. So, Intuit invests heavily, not just in the technology space to advance women, but also in all the other ancillary spaces, which are equally important to be successful as you advance in your career. >> So, as our viewers understand Intuit, I'm a user of it as well for my business, who understand it to a degree. What do you think would surprise our viewers about how Intuit is applying Data Science? >> So, it's important to know that we operate with a customer's mindset. Everything we do starts with our customers, and it's very important for us to build a culture which reflects the values, and the talent, and the skills of our customers. And that is why I said it's very important for us to have diversity in our teams. Our most opportunistic areas for investment in the AI machine learning is the smart products space where we are heavily investing to make our products intelligent, customize it according to the needs of our customers, and giving them great insights for our customers to save them money, make them do less work, and build more confidence in our product suites. >> Confidence, that word kind of reminds me of another word that we hear used a lot around data, and I'm making it very general, but it's trust. That's something that is critical for any business to establish with the customer, but if we look at how much data we're all generating just as people, and how every company has a trail of us with what we eat, what we buy, what we watch, what we download. Where does trust come into play, if you're really designing these things for the customer in mind, how are you delivering on that promise of trust? >> It's very rightly said, just to add to that sentiment, it has been shared in some articles that we have accumulated so much data in the last two years which is more than what we have accumulated in the last five thousand years of humanity. It is really important to have trust with your customers because we are using their data for their own benefits. Intuit operates with the principle and the mindset that this our customer's data, and we are their stewards. We make sure that we are one of the best stewards for their data, and that's what we reflect in our products, how we serve them, build intelligent products for them, and that's how we start to gain trust from our customers. >> And I imagine being quite transparent in the process. >> That's true, yes. >> So in terms of your career, I was doing some research on you, and I know that you love to give back to the community by being a champion for women in technology, encouraging young girls in STEM towards building that community. Tell me a little bit about your career as we are here at WiDS at Stanford there's a lot of involvement in the student community. Tell me a little about your background and what some of your favorite things are about giving back to the next generation. >> Sure, I actually, when I graduated from engineering, I was one of the four women students out of the, maybe, a class of around 50 students. So I think it struck me right there that there is a disparity in the industry, in the education system, and then in the industry. I felt the same thing in my different companies where I worked, and that always led me to a point that I actually, rather than just being observing this from afar, why can't I be the one who moved the needle on this? That led me to a point where I started collaborating within the companies, started forming teams, and started working with the teams who were already there to move the needle in technical women's space. I think, if I reflect back in my journey, a couple of things that stand out for me is passion for what you do, and I am really passionate about what my goal is and I try to line up my work according to that and that's why this women in tech, something which is close to my heart and I'm passionate about, always comes forward whenever I do something. The second important aspect is, I've always thrown myself into situations which I've never done before. For example we were offline talking about hackathon, which is DevelopHer. I had never done any hackathons before because I was so passionate about doing it, I just threw myself in and I ran that hackathon. And then the third thing is being persistent about what you do. I mean, you can't just do one thing and then drop it and then come back after a few weeks and then do it again. You have to have that consistency of doing it, only then do you start moving the needle. I think when I reflect and look back, these three things stand out for me and that has applied in my own personal career, as well as everything I do in my life. >> How do you give, and the last question, it seems like you sort of have that natural passion, I love this, this is what I want to do, you were persistent with it, how do you advise younger girls who might not have that natural passion to really develop that within themselves? >> I think experiment and explore. When you try to do different things, only then you find out where your passion lies. Just don't be scared of throwing yourself into a situation which you have never dealt before. Always try to find new things and throw yourself in an uncomfortable situation, and try to get out of it. It helps you become super bold, and gives you confidence, and that's the way to find what you're naturally passionate about. >> I like that, I like to say get comfortably uncomfortable. Last question in the last few seconds, I just want you to have the opportunity to tell our viewers where they can go to learn more about Intuit and their Data Science jobs. >> Yes, you can always go to intuit.com, and intuitcareers.com, and learn about the great opportunities we have for Intuit and Data Science. >> Excellent, well Kavita, it's been a pleasure to have you on The Cube this afternoon. Thank you for stopping by, and also for sharing what Intuit is doing to support WiDS. >> Thank you, it was my pleasure, thank you so much. >> We want to thank you for watching The Cube, I'm Lisa Martin live from the WiDS fourth annual WiDS global conference at Stanford. Stick around, I'll be right back with our next guest.

>> Narrator: Live from Orlando, Florida. It's theCube. Covering Grace Hopper's Celebration of Women In Computing. Brought to you by, SiliconANGLE Media. >> Welcome back to theCube's coverage of the Grace Hopper conference here in Orlando, Florida. I'm your host, Rebecca Knight. We are joined by Raji Arasu, she is the CTO of Development at Intuit. And also, by Marianna Tessel. She is the Chief Product Officer at Intuit. So thank you both for joining us. >> I think you got the title wrong. >> Oh no! (laughter) Please correct me! >> It's SVP. >> SVP. >> SVP of our organization is called CTO Dev, and I manage the platform and infrastructure services for our... >> Great. >> So now we've got that under control. >> Wonderful. >> So tell a little bit about your background. We'll start with you Raji, how you got into this business. >> I have been about 27 years in the consumer and retail space. And a ton of background on ecommerce and payments. This actually my first job sort of focusing on platform and core services for the company. A huge responsibility, my job is not just to provide and you know, delightful services for both my internal and external customers. But to really make sure that we are really thinking about the future and the capabilities that we're building for the future. So, super excited about my role at Intuit. >> How about you, Marianna? >> First of all, thanks for having me here. >> Yes. >> And I have to confess, this is my first time at the Grace Hopper Conference. >> That's wonderful! That's, that's great! >> And I'm completely blown away from the wonderful people here and the representation and the energy. So, I'm now a fan. So, anyway, just wanted to say that. You know, my background has always been engineering, I've done multiple engineering roles. I actually, before this, I spent a lot of time in systems and infrastructure and I really get a kick right now out of using some of the products I built. And actually using them in other products. And seeing how customers are using it. So, that's an interesting kind of journey, and interesting to see kind of full picture, of kind of the industry. >> Both of you, and we are here at Grace Hopper, which is the celebration of women in computing. And both of you are passionate about creating a more inclusive engineering culture. Can you talk about why, why this is a passion project of yours. And then also, what you're doing to make, to help that happen. Raji? >> I think, I mean, Grace Hopper. This is my seventh year in the conference and I love it. >> So you're a veteran. She's a virgin, you're a veteran. >> I'm definitely a veteran, absolutely. (laughter) >> And I think it's such a joy because it not only, I have started to recognize some familiar faces. It's a fantastic opportunity for us to network, with women in technology, and talk about actually, what's cool, is not just the issue around fixing the numbers, but actually, we talk about capabilities and building, you know, what's really important for our craft. And so I'm actually excited about that. The more and more I see, you know we have about 112 people attending from Intuit. And you know, a ton of men as well, participating in that but a lot of people are going to be talking about things that are very core to us. Like, data engineering, data science, architecture, services-oriented journey, and all of that which is awesome. Because I think, that's what people want to hear, the work that we do. And they want to understand, what it would be like to work at Intuit. So, there's a ton of opportunity for companies and for individuals who work there to really show what they do everyday. And really connect in a very authentic way. And show off their work. More than actually be, you know, really talking about the Uber problem that many of us do care about that as well. But I see, down here, especially where we are sitting, everybody's connecting on where they work, what is the work that I'm going to do, or what is the stuff that actually interests me. Which I think is pretty cool. >> During the keynote, Melinda Gates had a very quotable quote and she said, "Not every idea is wrapped in a hoodie," not every good idea is wrapped in a hoodie. And this is really bemoaning the brogrammer culture. Is that message getting through, do you think, to young women? In the sense of, this is not all the sea of white dudes. >> You know, I, I think it is but there's still like work to do. Both for like, women that enter the field, as well as women that been here for, for awhile. And, you know, there's still plenty of opportunity. So, you know, the culture is definitely, at least, I'll have to tell you that, again, being a bit in the industry now, and gaining a bit of a perspective, just the fact that it's being talked about and the fact that there's more energy towards solving it is already, you know, a great win. And, you know, to your question before, if I can jump on that as well. >> Knight: Yes! Absolutely. >> You know, this whole idea of diversity in the work place, there is nothing, I don't know if there's much to say there beyond what's already said about how it's good for businesses, how the customers at many of the of, I know definitely for us, in the small businesses, a lot of our customers are diverse. And we want to have diverse people build product for our customers, right? You know, so all of these are true, it makes sense for the business. But now I can tell you from my own lens, and my own kind of perspective and experience, you know, women are just awesome. And they make like, outstanding engineers, outstanding leaders, and every time I have a group of, you know, that has all sorts of people, again all kinds of diversity it's just a stronger group. So, some of it, you know, I love to have a diverse team selfishly, because it's an awesome team and that's kind of what I think we should all be pursuing. Just, be awesome, not just diverse. >> So you're passionate about getting more women into this industry, keeping them, retaining them in the industry. But, tell me a little bit about the tech. I mean, because that is, that was obviously your first love and that's why you do what you do. So tell me about what you're working on that's really exciting to you at Intuit. >> I think, you know, as I look at my past, one of the things that always excited me is to work on complex stuff that actually makes a difference in the world. And it started fairly early on in my career where I started to, when I worked at eBay it was about actually connecting to our customers and sellers and having that sort of a social impact. Moving on to StubHub it was a lot about actually entertainment and how do you really get people to the game and that perfect evening they were looking for. And then moving on to Intuit, it's about making that financial freedom possible for many of our customers. And I think when I look at that, for Intuit, there's a huge opportunity. Which we are actively working on is, to start looking at our data and be able to create some delightful customer experiences for our people. And to, to really give them more time and more money at the end of the day. And I think, and that sort of confidence in our own products, about the decisions we make for them and the expertise that we provide, and so as part of that, a lot of that can only come alive with technology. So, when we start to look at that, you know, there's a huge focus within the company on building great tools for developers so they can move faster. There's a huge focus on trying to do AI and machine learning on our data and looking at what we can do to personalize our experiences for our customers and reduce friction in the flow. There's a ton of work that's being done there. And I also think that we, we're very excited about our journey to the cloud. And having gone through the whole services-oriented architecture, re-architecture that we are being embarked on for many years. So, I think really, really there's a ton of good work that's happening inside with all towards the focus of servicing the customer. So there's a ton of conversations that we have around customer empathy. And then all of the technology towards making the lives of our customers better from a financial perspective. >> And giving them back time and money as you said, yes. Yes, absolutely. >> If I can add, to that, like our mission as a company is to power prosperity around the world and you know, and that's like a great mission. But, as Raji was saying, it's even awesome when you get to connect technology to a mission that is really inspiring like this. >> Knight: Yes. >> And is really something we put in practice. You know, I'll talk specifically in one of my products, Quick Books Online, QBO. You know, we have, a lot of the problems that, a lot of the challenges, we shouldn't call them problems. Challenges that many of the SAS companies are facing in terms of scale, in terms of velocity, how are we doing DEV ops in the most modern way? What's our CICD pipeline look like? How do we use, we have all this great data, how do we use the right data? Because, obviously we want to respect privacy. How do we use the right data to giving even more value to our, getting more value to our customers? How do we apply machine learning and AI? And, you know et cetera, to make it even more interesting because we have some touch with financial data. There's a lot of view on security and what we do there. So, lots of problems to solve that are deep technical problems. Lots of modern technology. Some that other, that you know, we have to look at but you know, really interesting set of challenges. From all the way to, in close to the infrastructure, all the way to the UI and some really cool things that we're doing there. >> I think that's a really great point, and the fact that, you know, as you're women technologists so you face issues of biases and sexism in the industry. But as technologists, as human technologists, you face questions about, am I looking at the right data, is this data secure, am I doing enough around privacy? Do you think that this conference does enough to acknowledge both sides of this coin in the sense that you are technical leaders in your field and you are here, at a tech conference, but then you're also here to rally around this issue of getting more women and retaining more women in the industry? What do you think? >> I think, I think that I am in this, in these booths here, I sense it. I sense that we're talking about the real problems around technology. The conversations around the specialties that are required in data science or maybe architecture, maybe engineering. I mean any parts of that, we do have those conversations. I think at the keynotes and maybe at the higher level, it's a lot more about developing women and addressing the problem and probably building leadership. So, there's probably two flavors that you find in this conference. Which I think cater to different sets of women and some about staying in the field and not sort of, you know, dealing with the problems that we have. So I think it does. But I think it'd be awesome to have a panel where we have very different points of view on a technology, and having a really good debate about that. Which would be really cool I think, if we had something like that. I don't know if it's in our curriculum. I'm definitely not aware of everything in our curriculum but it would be cool to have a panel like that. >> I want to wrap up here but I want to ask, what is your best advice for aspiring women in this field? And it could be someone who is just starting her computer science journey in college, or it could be someone who maybe is feeling as though, do I stay in this field, I don't know if this is for me. What would you say to that young woman? >> You know, again, maybe something that she heard before, but I would say, you know, go for it, stick with it, be ready to fall down. And come back up and be ready, be open-minded, know that you can learn anything. And, you know, but stick with it. >> Just stay, stick with it. (laughter) >> Yes, through hard and through easy. >> I love that. I mean, I want to definitely second Marianna saying don't be afraid of failures. Take it on, and use that as an opportunity to convert that into success in the next opportunity that you have. I think the part that I would also say, is protect being a leader in tech and staying true to it. You got to have a learning mindset. Every single day you come in, you got to learn new skills, you have to open to change, and constant change. And if you learn, and every one of us has different ways to learn. You know, some of us learn through conversation, some of us learn through reading papers, whatever that might be. But if you do that, you will stay as a credible and relevant leader for the longer run. >> Knight: The growth mindset. >> Absolutely. >> Well Raji, Marianna, thank you so much for joining us. It's been a lot of fun. >> Thank you. >> Thanks for having us. >> I'm Rebecca Knight, here at the Grace Hopper Conference, we will have more, just after this. (electronic music)

>> Narrator: Live from San Jose, California. In the heart of Silicon Valley. It's theCUBE. Covering QuickBooks Connect 2016. Now here're your hosts. Jeff Frick and John Walls. (upbeat music) >> Welcome back here in San Jose, we're live at the Convention Center for the second day of QuickBooks Connect 2016. A thriving community, 5000 plus attendees here enjoying where there have been some fascinating keynotes and breakout sessions. And it's our pleasure to bring you some of the brightest and best minds in the QuickBooks community. And we have that with us today in the form of Jim McGinnis, who's the Vice President of Product Management at ProConnect. Jim, thanks for being with us. >> Thanks for having me. I'm excited to be here. >> I got to tell you, I wasn't aware of your stature until Jeff informed me of last year when the two of you met. He said, "I could barley have a conversation with him because the man's a rock star". People kept coming up, they wanted to take selfies with him and it was nonstop. So apparently, your cache goes well beyond theCUBE. >> It's very kind, but the truth is, the rock stars are our 150,000 plus pro-advisors from around the world. These guys are making a huge difference in the small businesses' lives. They come here, they connect with small businesses, with each other, et cetera. Sometimes it feels a little silly, but I'm just honored to get to spend time with them. >> But they wanted the selfie so good for you. They're not asking for Jeff and John. They're asking for Jim. >> In the near future I'm sure. >> Give me an idea, first off, your feelings about the vibe. You heard us talking about, a little bit ago but your thoughts about what you're seeing here and the growth of this show over the last three years. >> I was having a conversation, you know this started on the back of a notebook three years ago where we said, "We're getting big enough that we believe we need to have a show to bring folks together". But we want to be different. We want to be about making connections. So the name QB Connect was born. We wanted to be the place where developers, small businesses, and accountants come together and meet. The vibe is phenomenal. The vibe it starts early Monday morning when we do the accountant kickoff. They go into training. A lot of them get certified in QuickBooks online and advance certifications as well. It continues the next day, yesterday, with these fabulous keynote speakers. Last night with a great band, Third Eye Blind. Sometimes these bands say, "Am I seriously playing for a bunch of accountants"? But they always come away and say, "That is one of the best "shows we've ever done because the enthusiasm, the excitement". Everybody loves to be here. And then today continued. We had fabulous speakers on the stage again. People like Tony Hawk and Simone Biles. >> Yeah, so what do you want when people leave here, and we're going to get into accounting and what's going on certainly in your world. But I'm just curious. The takeaway that you want people to have as they go back to all corners of the globe, frankly. What do you want them to do, and how do you want them to feel about QuickBooks when they go back and do their 12-hour day jobs? >> Absolutely. You know, I want them to feel empowered to really make a difference in their clients' lives, which is super fun. There was a quote yesterday from America who said, "You are modeling possibilities for someone else and you may not even realize it". And boy, our pro-advisors from around the world really model possibilities. They save small businesses all the time. In fact, 89% of small businesses say they're more successful because they work with and accountant. How do I want them to feel about QuickBooks and Intuit? I really want them to feel like we're their partners. Scott Cook founded this company believing that we're here to make a difference. To change our customer's financial lives so profoundly they can't imagine going back. When I talked to accountants last night, today, that's what they tell me. They want to change their small businesses' financial lives so profoundly, they can't imagine not working with an accountant. We're perfect partners. That's what I'd like them to take back. >> It's so funny right? The dirty little secret everyone thinks an accounting show. It's not an accounting show. >> No. >> It's a small business show. It's really a building businesses and partnerships, and really creating that foundation for other people to build from to be more successful in really pursuing their passions. I think that's why the energy is so strong. >> You said it well. It's all about possibilities and it's all about connections. >> Excellent. So lets talk about some big global trends that are not only impacting QuickBooks and Intuit, and your customers, and the accountants but everyone all over the place. The two big ones that have recently just overtaken everything, mobile and cloud. Huge impact on what you can build, how you can deliver it, how people consume it. How have those really changed what you guys have built and delivered at QuickBooks? >> That's great. I'll start with the cloud side because I think that's where it all starts. All those desktops, they're coffins. The data is buried underneath your desk and it's unusable in so many ways. When the data moves up into the cloud, now you can make connections between industries. You can do industry benchmarking. Now the data can just flow seamlessly from one application, like QuickBooks online, through trial balance to another application, like our ProConnect Tax online. We're able to connect up all these fabulous developers who are building solutions that we would never be able to build the creativity that we see and all plug in this online ecosystem. It changes everything. On the mobile side, boy isn't it fun to see all the tweets going by? Our reputations are being built for us. The best we can do is curate them at this stage. The other is it's anytime, anywhere isn't it? This idea that you can make an appointment with your accountant and he or you would drive across town to get some bit of information. It's just too slow in today's world. Mobile enables us to collaborate constantly with our accounting professionals and the accounting professionals to collaborate with their clients. >> And really in a different kind of form and function because mobile is quick. I got two minutes standing in line at the grocery store at Safeway. I got a couple of minutes while I'm filling up my car full of gas. I'm waiting for the kids to come out of the coach's meeting after the soccer games. So it's a lot more frequent little bits of connecting in the way that we use mobile apps to interact with our world. >> Absolutely. Think about all the productivity that's unlocked with mobile. Usually it's a simple question. I need something now. Make an appointment, drive across town, it's miserable. Instead you can ask a question and all that's successful because the data's in the cloud. >> Jeff: Right. >> So what do you do then in terms of, at least with a client base that has a reputation for being a bit slow to move. And there's not an enormous number of early adopters, it's almost like show me. But yet when you have these new possibilities like moving to the cloud, migration there, people are going to get left behind if they don't. How do you convey that sense of urgency and get them to convert and get them to adopt and take advantage of these great products and services that you're developing for people? >> I'm going to answer that by saying I say it ain't so. I think accountants and accounting professionals are some of the most forward people that I've known. Now, they have to be responsible. They have to look out for their clients. And they're under a lot time pressure. I think that if there's been some slowness in moving it's because we haven't gone fast enough to create applications that really save them the time. Software's a tough business, folks. Because before in my previous life I was in Proctor & Gamble. You knew the benefit up front. Software comes with immediate pain and uncertainty about whether it's really going to deliver the promise, the benefit that's there. What we have to do is we have to help show accountants that the possibilities are there and give them immediate satisfaction that the time savings that they seek is there. When we do that, we've already seen it. They move quickly. >> So you're kind of talking about, in a way I think, this firm of the future concept, right? That as far as where we're going in this 21st century. So talk a little more about that and what it means, brass tax terms. When the rubber hits the road here, in terms of the products that you're providing people and the changes you think the customer's going to have to make in order to really fulfill this vision of the firm of the future. >> That's exactly right. Sometimes our accounting professionals or pro-advisors come to us and say, "Can't you make it simpler? "Can't you break it down into a few steps "so I can follow a roadmap step-by-step "and get there?" And we've done that a little bit with our concept of firm of the future. The first step is the importance of getting online. That first client, that's a little scary. Put your next client online, see what its like, enjoy the benefits, learn the new operating systems, learn the new workflows. And then the benefits start to unlock. You can manage them all in QuickBooks online account. You can start tying in the different applications. You can see all of your clients there. And as you get your second and your third, you start to enjoy that. The second part of our pilar I would say, the firm of the future, is we do believe that the billable hour it's not scalable. Of all of the time savings that's coming by moving to an online platform, gosh, you'd have to have a lot more clients in order to make as much money as you're making today. We believe accounting professionals deserve to get paid for the value they create. And that means moving to fixed fee pricing, it means offering a range of services, that means going beyond just typing in data and compliance to actually creating more value through advisory services. And then that's the third pilar right there. Once you're online, and you're making money by creating value through advisory services, you need to get your name out there. Become a specialist in a certain vertical. Help people around the country, even around the globe, know the value that you can create. And they'll flock to you. We've seen little companies start up with two people, this one in Canada, has gone up to I think more than 500 clients in less than three years because they followed the firm of the future approach. >> That's really interesting. It was apart of the keynote too where a lot of the entrepreneurs said they started with their family accountant or family friend who didn't really have a specialization in the industries that they decided to build. Then at some point they had to flip because the value of accounting is not data entry. And it's kind of old school that automation should help you get rid of the redundant low value activity to free you up on the higher value activity which is asset planning, and tax planning, and future planning, and inventory planning, and the things where the accountant can bring much more value to the relationship that aren't tied to how many hours did it take to prepare your return. >> That's absolutely right. We say that the most important feature we can add into QuickBooks is an accountant. Sometimes there's some fear of technology, I have to share what I read recently in the Wall Street Journal which is, machines have been able to beat humans at chess. But there's a concept called centaur chess, which is half machine half human. When a chess expert is combined with a computer can beat any computer. And that's where we are in the accounting profession too. All this technology is fabulous, but where it really starts to sing is when it's combined with an accounting professional who understands it and leverages to give advice only a human being can give. >> Alright so a couple more trends now that are coming, get your reaction. Machine learning, big one, big data obviously it's been around awhile but the machine learning and the augmented intelligence, AI. Some people say artificial intelligence other people say there's nothing artificial about it. >> That's right. >> It should be augmented intelligence. The impacts of those on your software and your customers? >> Great question. Let's be specific. Things like chart of accounts. We can do a pretty good job of estimating what a chart of accounts should be for a given vertical. But they always get modified by the accountants because they know better than we do. When a few of them start to modify it and few more, pretty soon we can leverage the wisdom of the accounting profession crowd to get the very best chart of accounts for any given vertical. What a great opportunity. And then you think about benchmarks. I was talking to somebody before about when all of the plumbing industry is on QBO. And accountants can go in and say this is what accounts receivable should look like for plumbing, for a plumber. Think of the power of that. But one thing we know is every small business says the same thing, but I'm different. No problem, tell me how you're different? And in fact, we'll find 10,000 others who're different, just like you. >> Just like you, right. (all laughing) So, just going forward, you've go tax pros on one side, you've got accountants on the other, never the twain shall meet. Now you're bringing them together. And the importance of that, the value of that in terms of making sure there's an integration, there's a collaboration for small firms? >> In my new role as product manager for the ProConnect group, that's the part I'm really really excited about. Last year we launched QuickBooks online trial balance so that the data flows into the trial balance and from the trial balance mappings can be done and it flows directly into the tax software with a little modification, a click of the button, you can file right from the tax software. But our accountants told us, I don't understand. I don't want to run two different client lists when somethings going on in the tax side of it. I want to know about it where I do my work, in QuickBooks online accountants. So this year we've integrated the tax software right into QuickBooks online accountant. And now we're dreaming a little bit. Where as we talk about moving to advisory services, when it's a separate business impacts in my books, impacts in the decisions I make here, then get handed over the tax side of the shop. Now when it's all one application, those insights come back from tax and say, I wouldn't do it that way. I'd lease that. I wouldn't buy it because you're going to be in a much better position from a tax standpoint. And gosh, your business has really taken off. You need to think differently about your quarterly estimates. Because otherwise you're going to find yourself in a cash flow situation come October. >> So you're getting ahead. You're not looking after the fact and reacting. >> It's advisory service. It moves tax from being a once a year event to being an ongoing relationship. That's exciting. >> Well Jim, it's that kind of vision that I think, makes you a rock star. And if you got time for a quick selfie. (all laughing) If we all just kind of, you know... >> I'm all in. >> Jim McGinnis, Glad you could join us here. I look forward to seeing you down the road too. >> Thank you very much. >> Jeff: Best of luck to you. >> Jim: I've certainly enjoyed it. >> It's a little blurry, we'll have to do another one here. Back with more here from San Jose right after this. You're watching theCUBE. (upbeat music)

>> Narrator: Live from San Jose, California in the heart of silicon valley, it's theCUBE! Covering QuickBooks Connect 2016. Sponsored by Intuit QuickBooks. Now here are your hosts Jeff Frick and John Walls. >> Welcome back to San Jose, California. We continue here on theCUBE our coverage of QuickBooks Connect 2016. Of course theCube is the flagship broadcast here on SiliconANGLE TV where we extract the signal from the noise and I tell you what, with our next guest, we have a lot of signal to bring you. Scott Cook, the founder and the chairman of the executive committee at Intuit. Scott, thank you for being with us. We really appreciate the time and have been looking forward to this for quite some time once we knew you were going to be on theCube. It's good to have you. >> Good to be here. >> Let's talk about just first off, look at where you are now, right? 30-some odd years. It's been quite a ride I would assume for you. >> Yeah, it started, you know Tom and I got together and then there were two of us and then we eventually had seven of us in a basement. Well they called it the garden level. But the only part of the garden you could see would be the roots and the gophers. (laughter) And then we hit bad times and the things ... We just couldn't get money. We couldn't get sales so we shrunk down to four people. Couldn't pay salaries. It was pretty ugly. And from that, to look at 5,000 people here today. 8,000 employees in the company. When I started the biggest PC software company was 160 employees, and they were huge! Oh these giants! (laughter) >> How do I manage all this? >> Yeah, yeah. >> Well a quote that we've heard a couple of times today. We heard on the keynote stage. About the corporate philosophy of we fall in love with your problems, not our solutions. And is that the driving force you think? I mean, why you've made it through 33 years? >> I think yeah. Yeah, I actually think that's pretty important not just to the success of Intuit and QuickBooks and Mint and TurboTax, but to business in general. My theory is what great entrepreneurs do is they find the intersection of two circles. So think of a Venn diagram and the intersection. One circle is what are people's biggest, most important unsolved problems? Not the problems that are already solved by someone else. Find the ones that aren't solved yet. And then look for the ones that we can solve. Cause you can't solve everything. But look where we can apply the best technologies in the world. What's in that intersection? And focus there. >> And in some of the research to get ready for this. You've talked about really focusing on the important stuff. You gave a great example in that Khan Academy talk about there's really only 1 1/2 things that you should really be focusing on to really move the ship forward. And that was a very great insight. >> Yeah, you know all of of us have the desire to do too many things. You get groups. You've got 10 people in a room, they each have their ideas and it's tempting to shoot at too many targets. And those 10 targets are not of equal importance. You got to go through and kind of rigorously and be disciplined and say what's the 1 1/2 most important? And stay relentlessly focused on that. >> And then how is your role changed? As time has passed and you're no longer the CEO. Now you're chairman head of the executive board. How have you kind of learned to still keep your hands on it but in kind of a little bit more of a distant role? >> Well, first of all, thank goodness for leaders like Brad Smith, Sasan Goodarzi who heads up our small business group, that's really the host of this show. Thank goodness for great leaders like that. So my role's changed a ton. I work really on two areas now which is strategy and coaching our entrepreneurs. So strategy over to Brad and our other leaders. I'm trying to help our leaders see the future and make the big strategic calls. What's really most important? How do we know? And then work with our entrepreneurs. We're a collection of entrepreneurs basically. We've got a couple hundred entrepreneurial projects going on inside the company at any one time. And each one of those is like a little startup. I mean, they've got a customer in mind. They've got a problem they're trying to solve to improve people's lives so fundamentally. And there are challenges. So helping grow our entrepreneurs and then grow the culture around them to allow great entrepreneurs to invent things to change the world and do that from within Intuit with a huge reach to be able to get the inventions out in the hands of millions. And change the lives of tens of millions of people. >> So, over the course of the run of the company, they haven't all been home runs. >> Scott: Oh yeah. >> Right. So how have you learned from those swings and misses? And applied them to the small businesses that you're serving? Who are swinging and missing on a regular basis and you're trying to narrow that margin, right? Trying to make them more successful. >> Scott: Yeah. >> So what did you learn you think maybe through your attempts about that culture of trying basically. >> I think maybe the most important thing really dovetails with what you just said. Early on, when the company was, before we even had our first product out, we'd build a version of it and then we would bring in test audiences of it and have them test it to see if they could figure it out without us saying anything. And they couldn't. So then we'd redesign it and then we'd test again. And then we'd redesign it and test again. Over time kind of lost some of that dedication to running experiments. And it became whose opinion? And you'd build, and it was the loudest opinion in the room. Or the boss' opinion. And that produced a number of failures. Things that just didn't work. Customers didn't buy it. Or they bought it and it didn't it didn't produce the desired effect when they bought it. So the thing I've learned about life and companies is to set up a culture where you make decisions based on fast cheap experiments. That very thing you were talking about. If you got an idea, figure out, okay, what's a leap of faith assumption, let's go try it. And don't debate it. Try it. And then we learned from trying. Oh, a bunch of those don't work. And then we learned from the things. Why didn't it work? And that teaches us something we didn't know before. That maybe the fulcrum, the pivot, to a new idea. And some of those do work or most of it worked. But other pieces didn't. And we learned by doing. Not by debating in a conference room. So to set up your company so that people throughout the company can take their idea and run the experiment. That produces great entrepreneurs and great learning. A continuous stream of learning. I guess the learning begins when you first get real people trying your idea for real. >> Let me follow up. Cause the other thing you talk about is that often comes from the youngest and the newest employees. Which is completely antithesis to a kind of hierarchical structure. Where these are the people that you should be listening and giving them the opportunity within this comfortable framework to do these experiments. >> Absolutely. Sometimes the very freshest ideas come from the people farthest from the boss. Newest in the company. Closest to the customer. But typically in a hierarchy, whose got the least clout? Whose ideas are the least listened to? It'd be the new person, the young person. >> Jeff: Right. >> And so part of the genius of running a company of decision by experiment is that everyone's ideas can be run as an experiment. The boss' idea. The CEO's idea. And the person that's new. We should be testing each of those. Except in a crisis where you got to make snap decisions. And hopefully those aren't very often. You should run the company so that each good idea can be tested, regardless of where it comes from. And then the great thing is, then you get the best ideas from all your folks and they learn from doing. If their idea doesn't work, now they learn from that. Ooh, okay. I thought it was going to do X, it did Y. Why? What didn't I know? That's where learning comes from. Learning doesn't tend to come from the successes, learning comes from the things that didn't work. >> So, I think we've all seen good executives. How they operate. They hire good people, right? That's ... You have a vision and then you hire people who surround that and amplify that vision. So when you're looking for people or when you've been looking for people to work with you. What's that common thread? Or what are the traits that you've looked for the most to think that's a good fit? Or this is the person that I want on my team. In order to carry on this vision to where it's expanded to where it is today. >> Let me break that into two buckets. There are a set of things which are unique to particular career paths. So certain things from engineers might be different than certain things from a salesperson or a marketer or a finance person. So let's set that aside. Let's cover the commonalities. I think there's a few things. When you think about the people you've most loved working with or for. There are people who are great creative problem solvers. Instead of seeing a problem or barrier and giving up or being unglued by it. Can figure out okay, how're we going to solve that problem? And then there's people who are there to serve. Where it's not all about them. I've got a thing that I tell our folks that others won't care how much you know until they first know how much you care. So if one of our speakers today said it. If your first job is to serve yourself you're not going to go very far. Because who wants to work with someone who's self serving? Who wants to buy from a company that's only looking after its own front P&L? Job one is you got to serve who you're serving. The customer or the person of the company who you serve. So we look for people who are really motivated by the outside to try to do right by the customer. I think you look for people who are achievement oriented. Who get stuff done. Who make things happen. Do you want to work with somebody who always needs to be dragged along? No. You want to work with somebody who's pulling you along. Who's getting a lot done. So you go, wow, that person gets a lot done. So I think those are pretty core. Solve the creative problems. Have the passion and energy to serve, do what's right for the customer. And then get a lot done. >> And then you've talked about the curse of success. And avoiding the curse of success. And you guys have done that, obviously. So what are the kind of the lessons to say fresh? This started as a checkbook register and now the future of payments and mobile and the options are just tremendous. Bitcoin, who knows where that's going. So, as the future keeps evolving, how do you stay fresh? How do you keep the team fresh? How do you not rest on your laurels even though you have 5,000 fans walking around San Jose convention center today? >> This is a real challenge for companies. Because success turns organizations. It makes them dumb and slow. It's tempting, the thing I would avoid is it's tempting to look at your achievements. To look through the rear view mirror. And look at boy, how much we've achieved. But that only makes you self satisfied. In fact, with an organization you need to do the opposite. Look to where we want to be. Look to where we should be. And we're here. And then say, well shoot we are not very far. So for example, and I define these in customer terms. For example, we started our first product helped somebody manage a checkbook and pay bills. If you look at it really, the problem of paying bills has gotten worse. It used to be all bills came in the mail. So you had a little physical reminder. Some come in the mail, some you get by e-mail with invoices from some people. Some you go online and find a website. You pay some at a bank website. Maybe you go to the biller, you pay some. You write checks for some. It's much harder now. We have not actually got to the point. When our nirvana is you never worry about a bill. And you're never late. And you're never overdraft. The overdraft rate in the country is around 30% of households have a late payment during the year from which they get fees. And the overdraft rates, the overdraft charges can be $30, $35. We have not solved that yet. We got to look and say with all that we've done, that's what we should have done. So we've got a team working on that right now. Because we got re-focused on it. So we'll be coming out in December with stuff in there. Look at tax. Tax many people would say is one of our best businesses. And it is. Look at all we've achieved. But, look at the reality. People are still spending a lot of time on tax. Who wants to be spending time typing stuff into tax software? Does anybody? (laughter) No. There's not an accountant, there's not a consumer. We haven't solved that yet guys. There are still a hundred million people in the country typing stuff in to systems to do taxes every February, March and April. That's where we want to be. Is ultimately there is no typing in. All that information you have that goes in your tax return goes in automatically. And if you're an accountant, it all goes in for your clients automatically. So that you can focus on the high level stuff and not the drudgery. So, viewed from the lens of really what life should be. What's our aspiration? Our ideal? Keep people focused on that. And it sure has helped motivate us. I mean, we should be finding a lot of money for small businesses. And we're launching, announcing today ways that we help small businesses find more money. We should be eliminating the drudgery of running a small business. Nobody wants to do the book work. Instead, they want to do what they love to do in business. It could be working with clients. It could be the craft of doing the business. It could be selling new business. Every business person has something they love to do. And it's not doing the books. And that yet, people still have to do it. We want to have it on your phone so you don't have to do the books. It's done automatically. And you got a question, boop boop, there's the answer. >> So you mentioned the phone. Is that the next big growth opportunity? Mobile this is top priority with so many different sectors right now. >> Yeah, yeah. It's the growth today. In fact, every new feature and new benefit that Sasan Goodarzi showed today in his keynote address. Every one of 'em, he showed it on a mobile phone. Every one. It's the fastest growing. TurboTax the great consumer business. It's the fastest growing platform by far. So yeah, if you can take stuff off a desktop and put it so automatically that you can just get on your phone, say, okay, yep, do it. >> Right, right. >> Yeah, so that's where we're aiming a lot of our innovation. And these are amazing platforms. A simple example, the fastest growing form of employment in the United States and in fact, in the world is self employed. Where you think of an Uber driver or someone like that. People who work as consultants, contractors, they work for themselves. They've got to keep track of all their business expenses. Or they lose that money on their tax returns. Money out of their pocket. They got to keep track of every individual business expense which of course, they co-mingle with their personal checking, personal credit card. And they got to keep track of every mile they drive for business. And keep it separate with contemporaneous records that the IRS requires with the starting odometer reading, the ending odometer reading, and the destination and what it was for. Well you can imagine that's such a pain in the butt. So many independent business people, freelancers fail. Or they do some but not others. And that's money right out of their pocket. Thousands of dollars they don't get. They should get that they deserve. So we've devised and a team really creative work, QuickBooks Self Employed. It sits on your phone in your pocket. It reads what's coming from your bank and your credit cards and anytime you're stopped at a stop light or you've got two minutes before a meeting starts. You can go through and say oh, that was a business expense, business, business. That was personal, personal. It's that fast. And then you get complete records for your taxes. Oh then mileage. There's lots of software out there that'll track your mileage but it does by pinging the GPS. GPS takes battery. You ping the GPS all day long, what happens? Zhoom. >> Goodbye phone. >> Bye bye phone. So it's worthless. Our guys we launched that. Quickly found out that people stopped using it because it drained their battery just like everyone else. So, three clever engineers. Together with a couple others came up with a really clever idea which we've patented now. And it tracks your location without pinging your GPS all day long. So it doesn't drain your battery. So now you had complete records. It can detect when you're driving and where you started, where you finished. How many miles. Keeps perfect record, just as the IRS requires. And then you just have to tell it which are business, which are personal. And then it learns. Which one are business trips. So that over time, it knows when you're driving on business and you don't have to do anything. You get complete tax records. We've got businesses using it who get on average $7,000 of tax deductions. $7,000 of tax deductions. Because of the way it tracks. >> And you're taking advantage of the platform. You're taking advantage of the accelerometer. >> Yes. >> More importantly I think. The thing about mobile that most people don't maybe consciously think of is the way we interact with it as you said is little bits of time here, there, and everywhere. >> Scott: Yes. >> It's not the sit down thing. But I think what I think is most exciting about this show is it's a lot of talk about technology. But at the end of the day, it's really more about business. And small business. And small medium size business. And getting business done. >> Scott: Yes. >> And letting people do those dreams like the gal that was on the keynote. >> Scott: Yes. >> Letting her build her company and her franchise. And not have to worry about am I getting all the right deductions. >> That's right. I think the technology is the enabler. But it's all to enable what? What are we trying to deliver? And you saw it, in the kind of lead of slides. We're trying to fuel the success of small business. This is all about success. The technology's an enabler but that's not the center, the star of the show. The star of the show are small businesses and how they succeed. And how the suite of things that hundreds of developers and hundreds of software entrepreneurs who all build for the QuickBooks ecosystem. The new methods, and new ways to drive small business success. And at the end of the day, we don't measure ourselves with software. We measure ourselves with how much more money did we make small businesses? How much time did we save them so they could do what they love? How did we help them grow their business? Running a small business is a, and I know from starting Intuit, it absorbs who you are. You identify with that business. It is your representation to the world. To your spouse, to your in-laws. And if that business is successful, it's something about you that's irreplaceably positive. If that business is struggling, it strikes to the core. I mean, you feel bad. You look bad. So helping businesses succeed. And move them from mediocrity to success is such a home run for the psychology of this growing part of our economy. For each individual, it's your report card on yourself. And we can help make those report cards much better. That's our mission. That's how we're going to change the world so, so dramatically. People can't imagine going back. >> I'd say that you've already changed it dramatically. And it is exciting to hear about the next steps but this whole blend of strategy and execution and culture you're being commended for. It's just a great example of all those factors coming together and make great things happen for a lot of people around the globe so congratulations for that and thank you for being with us Scott. We appreciate the time here on theCube. >> Jeff, John thank you very much. This was a pleasure. >> Jeff: Thank you. >> You bet. Back with more from San Jose in just a bit. You're watching theCube here on SiliconANGLE TV. (techno music)

(upbeat pop music) >> Announcer: Live from San Jose, California. In the heart of Silicon Valley. It's theCUBE, covering QuickBooks Connect 2016! Sponsored by Intuit QuickBooks. (upbeat pop music) Now, here are your hosts, Jeff Frick and John Walls. >> Welcome back here on theCUBE. Along with Jeff Frick, I'm John Walls. As we continue our coverage here at QuickBooks Connect 2016. Gathering here in San Jose at the Convention Center. Third annual gathering with a record crowd of more than 5,000 attendees. (crowd noise) So the show continues to show explosive growth. Which is, I guess you can say a lot about what Intuit's doing, in terms of how it's growing its portfolio, in terms of how it serves the business ... The small business and the medium-size business communities. With us now is Sasan Goodarzi, who is the EVP of the small business group at Intuit. Sasan, good to have you with us-- >> Thank you. >> We appreciate the time. >> Thank you for having me. >> What are the keynote stars today? You were talking about some key things, big things about the company about how we're going to help save time. How we're going to have more accessibility to money. And ultimately what we could do to deliver a better proposition to small business. So talk about that, if you would, a little about that theme on the keynote stage, and how that applies to what you're doing in general with QuickBooks. >> Sure, sure. Well one of the things that our customers have taught us is, that there are three things that are important to them. One is time, so they can actually spend running their business and the product that they're passionate about; versus all the tedious, drudgery things that it takes to run your business. The second is money. It's mind boggling the effort that goes into earning money. But how hard is it for them to actually get access to their money. And then last, but not least, is ways to help them grow their business. They're experts in their industry, but where they need help is ways in which that they can drive growth. And so everything that we do is centered around those three things. And it's what inspires us when we show up to work every single day. So a lot of, obviously, what we talked about today on stage, was just very quick, we call ESPN highlight reels of here's the innovation that's coming your way to either save you time, put more money into your pocket, or help you grow your business, or your practice. >> Sure, okay. >> What's amazing is as I say, as much as they've worked to finally get that sale, a lot of times it seems all the collection side-- >> That's right. >> For small business. A huge issue, getting paid. To do all that work, sell it, have a happy customer and then, don't necessarily get their receivables in line. >> That's right. I know we threw a lot of stats out there this morning. But first of all, 80% of small businesses have some sort of a cash flow issue. And in that context about 65% of them have invoices that are 60 days overdue. And in fact, they live and die by getting paid on time. And so, obviously, the innovations that we talked about on stage today, were how do you get access to those funds right away. >> Jeff: Right, right. >> That's one element of it. The other element is we have all the data of small businesses. And so we know what they're good for. And so we can deliver loans to them on the spot. If they have payables and they want to borrow on the payable to make payroll for the week, or they want to go buy more inventory to grow their business, we can actually fund them very quickly. Literally within minutes. And so those are examples of what we showed on stage today all in service of helping them thrive and achieve their dreams. >> I love to ding into that a little bit, because growth actually exacerbates your cash flow problem if you're not managing it well. And now suddenly you're selling more and you got to buy to fulfill those obligations. But the fact that you almost have a secondary market now for people to be able to borrow money without pulling all their paper together, and trekking down to the bank and hoping they can get it, because you actually have the real data. It's updated (chuckles)-- >> That's right. >> All the time. And it's a different set of data ... Potentially more complete set of data for a lender to actually make that decision, than the stack of paper that they bring down-- >> That's right. >> to the local bank. >> That's right. Well, you know it's interesting. You just said something that triggered a thought. When you think about startups that go out and get VC money ... There's a reason why they have board of directors, 'cause the board of directors what they're looking for is one, do you have a growth plan, but then how do you manage that growth? How do you make sure you have enough money? How much money are you burning per week? And are you going to be able to maintain that growth? Small businesses don't have that. They don't have the board of directors that are actually helping them with some of those decisions. They may not be surrounded by a CFO or a finance expert in the office. And so part of what we're trying to do is just digitize and automate everything so they don't have to worry about that. And secondarily I think to the point you made, helping them with access to money at the point in which they need it. But I think even before we get to that stage, what we're trying to do is help them by being that board of directors without having to have one. Which is to helping them manage their cash flow, their inventory. Because as they're on that growth curve ... One of the main reasons why they go out of business is 'cause they're growing fast, but they're not managing their funds, and they do not have enough money sometimes to make payroll. >> Right. Well we've heard the stat from a couple of different sources but 50% of all small businesses fail in the first five years-- >> That's right. >> of operation. And the use of accounting and accountant, what that could do to increase your odds of being in business for the long term. So certainly you could see where all that is coming in play. You mentioned payments, so we're thinking about Apply Pay. That was one of the announcements-- >> Yes. >> You had. Google Calendar, talking about time. >> Sasan: Yes. >> And then AMEX with the loans. So the power of these partnerships, I'd like to hear from you on that, because, you know, big names, right (chuckles) >> Sasan: Yes, yes. >> That I ... If Jeff or I or anybody watching ran a little mom and pop operation in Morgantown, WV, I've got Apple, and I've got Google, and I've got Intuit on my side. Talk about leveraging that power for small businesses? >> Yes, actually listening to you inspires me around what Intuit is doing for these small businesses. And it starts with our vision of having an open platform. It's less about what we innovate on that platform, but our goal is to bring all of the innovation; whether it's our engineers or engineers outside of our four walls. Bring all of that innovation on our platform, so that in fact we can digitize and automate everything with Google Calendar. So we can go in and we know all of where you spent your time, and help you easily, with one click, invoice your customers. Or, as an example you used, be able to use Apple Pay Touch where you can immediately get paid. But that's because our goal is to have an open platform where we bring all the innovation of the best companies out there to you. So that you can run your business on any device, and you don't have to worry about which application it is, but that we do it all for you. >> I just love the Google Calendar example, because so many great innovations today are basically reassembling stuff that's already out there; leveraging APIs and presenting it in a different way. And so the fact that you're taking advantage of Google Calendar, which so so many people ... You probably know the numbers use ... And then have that drive your billing, have that drive your time management, and then just take advantage of the data that's there, or as Scott said, "Take advantage of the data that's in your phone." >> Sasan: That's right. >> It knows exactly how far you went on that drive to the client. It knows when you left and when you arrived-- >> That's right. >> and when you got home. So the leverage of Cloud platform with APIs, to pull that data in and drive in a seamless integration, it makes (chuckles) it makes too much sense, right? (Sasan laughs) It does, and when you think about someone like Google, where there's a billion people that use Gmail ... >> A billion. >> And most of them are using ... There's a billion people that have Gmail accounts. >> Jeff: Wow. >> And over 60% of our customers use Google Calendar to run their business. And so, it's only intuitive to figure out a way well, how do we automate all of that-- >> Jeff: Right. >> so that the customer doesn't have to use cookbooks for taxes and accounting, then go to Google Calendar to see where they spent their time so they can figure out how to invoice? >> And they type it in, right. >> Just integrate it all together so it's all in one place, yeah. >> How do you all keep focused when your market, your potential market's so big? You've got, I don't know ... I've read, was it 800 million possible businesses, right? Small businesses. >> Sasan: That's right. >> So how do you ... If you look at what would be reasonable growth trajectory and expansion, your plans ... How do you keep your eyes on the target, and how do you determine that target? >> Yeah, that's a great question. Let me start with where you just ended, which is there are 800 million self-employed and small businesses worldwide. And 97 to 8% of 'em actually are not using the Cloud to run their business, or their time. And the way we prioritize is think about the countries that are the biggest opportunity to create virility by those that are using the platform. And so we've prioritized which countries that we're going after, and really doubling down in those countries. And that's where we really are able to focus our efforts in time. 'Cause once we create this, what we call the network effect, the more small businesses and self-employed we get to use the platform, the more we get accountants to be able to see the power of the platform. The more they tell their friends. The more accountants are recommending it, you in essence create this flywheel effect of more and more going to the Cloud. And once we get that flywheel effect going, we'll think about what's that next country that we want to go into. We're not that serial about it, but our biggest focus comes from being clear which countries we're going to play in today, and which countries, for now, we're going to wait 'til we get this network effect going. >> And now you've got this whole new way to work. People that are giving up part of their house or apartment for Airbnb rentals. Or people that are driving in Uber for four hours a couple of days a week. Again, those are all based on systems that are driving that engagement. Do you see that it's just a whole new opportunity, do you see a lot of growth in ... I always forget the technical term for-- >> Sasan: The digamy ... The giga-- >> The gig. >> Sasan: The gig economy. >> The gig economy. >> That's right-- >> Which is a whole new and swelling thing. >> It is. >> And for a lot of those people, they are even less sophisticated on keeping track of their tax withdrawals than the small mom and pop store (chuckles)-- >> Sasan: That's right. >> that's at least been paying their social security for a number of years. >> Sasan: That's right. >> So another huge opportunity for you. >> It absolute is. One of the myths is most self-employed are actually not part of the gig economy. There's the photographer that you may call on to come take pictures of your family, or the landscaper that's a one-person shop. That's 90% of self-employment. About less than 10% is the Airbnbs, the Lyft, and the Ubers of the world. But that number's only going to grow over time. In fact, our view is in this day and age people will work at a company for three to four years at a time. We believe in ten years, people will work for three to four companies in a day. 'Cause they're workers, and they're outsourcing their time to different companies. >> Jeff: Three or four companies-- >> A day. >> Jeff: A day? >> A day. Because in essence, they're self-employed. Now I may work for you and do a job. I may work for you and do a job. That's actually starting to happen today. Except it's a small part of the economy. We believe ten years from now it'll be a huge part of the economy. And that creates a huge opportunity for us, 'cause they're all self-employed. >> Right. >> Before you head out, again, one of the big trend topics, artificial intelligence, machine learning. How do those come into play in your vision for the company's vision, and the products and services that you think you could develop that can be put to use? >> Yeah, in fact we think there are two core competencies that we must have. One is an open platform where we integrate all applications into the platform, whether it's ours or somebody else's. The second is being amazing at leveraging the data, whether it's data from a PayPal app, a Square app our own app. And leveraging artificial intelligence and machine learning, so we can do the work for our customers. So we believe when it comes to data and artificial intelligence, that is actually one of two or three primary core competencies that we are building as a company. And it's something we're not new at. We've been doing this for years. In fact, last year in TurboTax we've reduced the amount of time it took to do your taxes by 40%, by using machine learning. And we're now applying that within QuickBooks. >> I'd like you to reduce my tax liability by about 40%. (Jeff laughs) If we can (chuckles) take care of that and I'm yours. >> Or at least-- >> Well, listen-- >> Or at least get you to the July deadline. (John laughs) >> If you just make less income-- (Jeff laughing) >> That's right. >> I'm sure that's doable. (Sasan laughs) >> If you don't make it, you don't pay it. >> Sasan: That's right (chuckles). >> You mentioned ESPN earlier about the stage and all that. You made top plays today, no doubt about it with the keynotes address. >> Sasan: Oh, thank you-- >> Job very well done. >> Thank you very much. >> Jeff: Cute Kim's (mumbles) coming. >> Sasan: Thank you. >> And thank you (Jeff laughs) for joining us here on theCUBE. We appreciate the time-- >> Thank you, thank you for having me. >> John: You bet. Back with more-- >> Alright, thanks. QuickBooks Connect 2016 here in San Jose. You're watching theCUBE. (upbeat pop music)

(energetic music) >> Everyone, welcome back to theCUBE's coverage of WiDS 2023. This is the eighth annual Women in Data Science Conference. As you know, WiDS is not just a conference or an event, it's a movement. This is going to include over 100,000 people in the next year WiDS 2023 in 200-plus countries. It is such a powerful movement. If you've had a chance to be part of the Livestream or even be here in person with us at Stanford University, you know what I'm talking about. This is Lisa Martin. I have had the pleasure all day of working with two fantastic graduate students in Stanford's Data Journalism Master's Program. Hannah Freitag has been here. Tracy Zhang, ladies, it's been such a pleasure working with you today. >> Same wise. >> I want to ask you both what are, as we wrap the day, I'm so inspired, I feel like I could go build an airplane. >> Exactly. >> Probably can't. But WiDS is just the inspiration that comes from this event. When you walk in the front door, you can feel it. >> Mm-hmm. >> Tracy, talk a little bit about what some of the things are that you heard today that really inspired you. >> I think one of the keyword that's like in my mind right now is like finding a mentor. >> Yeah. >> And I think, like if I leave this conference if I leave the talks, the conversations with one thing is that I'm very positive that if I want to switch, say someday, from Journalism to being a Data Analyst, to being like in Data Science, I'm sure that there are great role models for me to look up to, and I'm sure there are like mentors who can guide me through the way. So, like that, I feel reassured for some reason. >> It's a good feeling, isn't it? What do you, Hannah, what about you? What's your takeaway so far of the day? >> Yeah, one of my key takeaways is that anything's possible. >> Mm-hmm. >> So, if you have your vision, you have the role model, someone you look up to, and even if you have like a different background, not in Data Science, Data Engineering, or Computer Science but you're like, "Wow, this is really inspiring. I would love to do that." As long as you love it, you're passionate about it, and you are willing to, you know, take this path even though it won't be easy. >> Yeah. >> Then you can achieve it, and as you said, Tracy, it's important to have mentors on the way there. >> Exactly. >> But as long as you speak up, you know, you raise your voice, you ask questions, and you're curious, you can make it. >> Yeah. >> And I think that's one of my key takeaways, and I was just so inspiring to hear like all these women speaking on stage, and also here in our conversations and learning about their, you know, career path and what they learned on their way. >> Yeah, you bring up curiosity, and I think that is such an important skill. >> Mm-hmm. >> You know, you could think of Data Science and think about all the hard skills that you need. >> Mm, like coding. >> But as some of our guests said today, you don't have to be a statistician or an engineer, or a developer to get into this. Data Science applies to every facet of every part of the world. >> Mm-hmm. >> Finances, marketing, retail, manufacturing, healthcare, you name it, Data Science has the power and the potential to unlock massive achievements. >> Exactly. >> It's like we're scratching the surface. >> Yeah. >> But that curiosity, I think, is a great skill to bring to anything that you do. >> Mm-hmm. >> And I think we... For the female leaders that we're on stage, and that we had a chance to talk to on theCUBE today, I think they all probably had that I think as a common denominator. >> Exactly. >> That curious mindset, and also something that I think as hard is the courage to raise your hand. I like this, I'm interested in this. I don't see anybody that looks like me. >> But that doesn't mean I shouldn't do it. >> Exactly. >> Exactly, in addition to the curiosity that all the women, you know, bring to the table is that, in addition to that, being optimistic, and even though we don't see gender equality or like general equality in companies yet, we make progress and we're optimistic about it, and we're not like negative and complaining the whole time. But you know, this positive attitude towards a trend that is going in the right direction, and even though there's still a lot to be done- >> Exactly. >> We're moving it that way. >> Right. >> Being optimistic about this. >> Yeah, exactly, like even if it means that it's hard. Even if it means you need to be your own role model it's still like worth a try. And I think they, like all of the great women speakers, all the female leaders, they all have that in them, like they have the courage to like raise their hand and be like, "I want to do this, and I'm going to make it." And they're role models right now, so- >> Absolutely, they have drive. >> They do. >> Right. They have that ambition to take something that's challenging and complicated, and help abstract end users from that. Like we were talking to Intuit. I use Intuit in my small business for financial management, and she was talking about how they can from a machine learning standpoint, pull all this data off of documents that you upload and make that, abstract that, all that complexity from the end user, make something that's painful taxes. >> Mm-hmm. >> Maybe slightly less painful. It's still painful when you have to go, "Do I have to write you a check again?" >> Yeah. (laughs) >> Okay. >> But talking about just all the different applications of Data Science in the world, I found that to be very inspiring and really eye-opening. >> Definitely. >> I hadn't thought about, you know, we talk about climate change all the time, especially here in California, but I never thought about Data Science as a facilitator of the experts being able to make sense of what's going on historically and in real-time, or the application of Data Science in police violence. We see far too many cases of police violence on the news. It's an epidemic that's a horrible problem. Data Science can be applied to that to help us learn from that, and hopefully, start moving the needle in the right direction. >> Absolutely. >> Exactly. >> And especially like one sentence from Guitry from the very beginnings I still have in my mind is then when she said that arguments, no, that data beats arguments. >> Yes. >> In a conversation that if you be like, okay, I have this data set and it can actually show you this or that, it's much more powerful than just like being, okay, this is my position or opinion on this. And I think in a world where increasing like misinformation, and sometimes, censorship as we heard in one of the talks, it's so important to have like data, reliable data, but also acknowledge, and we talked about it with one of our interviewees that there's spices in data and we also need to be aware of this, and how to, you know, move this forward and use Data Science for social good. >> Mm-hmm. >> Yeah, for social good. >> Yeah, definitely, I think they like data, and the question about, or like the problem-solving part about like the social issues, or like some just questions, they definitely go hand-in-hand. Like either of them standing alone won't be anything that's going to be having an impact, but combining them together, you have a data set that illustrate a point or like solves the problem. I think, yeah, that's definitely like where Data Set Science is headed to, and I'm glad to see all these great women like making their impact and combining those two aspects together. >> It was interesting in the keynote this morning. We were all there when Margot Gerritsen who's one of the founders of WiDS, and Margot's been on the program before and she's a huge supporter of what we do and vice versa. She asked the non-women in the room, "Those who don't identify as women, stand up," and there was a handful of men, and she said, "That's what it's like to be a female in technology." >> Oh, my God. >> And I thought that vision give me goosebumps. >> Powerful. (laughs) >> Very powerful. But she's right, and one of the things I think that thematically another common denominator that I think we heard, I want to get your opinions as well from our conversations today, is the importance of community. >> Mm-hmm. >> You know, I was mentioning this stuff from AnitaB.org that showed that in 2022, the percentage of females and technical roles is 27.6%. It's a little bit of an increase. It's been hovering around 25% for a while. But one of the things that's still a problem is attrition. It doubled last year. >> Right. >> And I was asking some of the guests, and we've all done that today, "How would you advise companies to start moving the needle down on attrition?" >> Mm-hmm. >> And I think the common theme was network, community. >> Exactly. >> It takes a village like this. >> Mm-hmm. >> So you can see what you can be to help start moving that needle and that's, I think, what underscores the value of what WiDS delivers, and what we're able to showcase on theCUBE. >> Yeah, absolutely. >> I think it's very important to like if you're like a woman in tech to be able to know that there's someone for you, that there's a whole community you can rely on, and that like you are, you have the same mindset, you're working towards the same goal. And it's just reassuring and like it feels very nice and warm to have all these women for you. >> Lisa: It's definitely a warm fuzzy, isn't it? >> Yeah, and both the community within the workplace but also outside, like a network of family and friends who support you to- >> Yes. >> To pursue your career goals. I think that was also a common theme we heard that it's, yeah, necessary to both have, you know your community within your company or organization you're working but also outside. >> Definitely, I think that's also like how, why, the reason why we feel like this in like at WiDS, like I think we all feel very positive right now. So, yeah, I think that's like the power of the connection and the community, yeah. >> And the nice thing is this is like I said, WiDS is a movement. >> Yes. >> This is global. >> Mm-hmm. >> We've had some WiDS ambassadors on the program who started WiDS and Tel Aviv, for example, in their small communities. Or in Singapore and Mumbai that are bringing it here and becoming more of a visible part of the community. >> Tracy: Right. >> I loved seeing all the young faces when we walked in the keynote this morning. You know, we come here from a journalistic perspective. You guys are Journalism students. But seeing all the potential in the faces in that room just seeing, and hearing stories, and starting to make tangible connections between Facebook and data, and the end user and the perspectives, and the privacy and the responsibility of AI is all... They're all positive messages that need to be reinforced, and we need to have more platforms like this to be able to not just raise awareness, but sustain it. >> Exactly. >> Right. It's about the long-term, it's about how do we dial down that attrition, what can we do? What can we do? How can we help? >> Mm-hmm. >> Both awareness, but also giving women like a place where they can connect, you know, also outside of conferences. Okay, how do we make this like a long-term thing? So, I think WiDS is a great way to, you know, encourage this connectivity and these women teaming up. >> Yeah, (chuckles) girls help girls. >> Yeah. (laughs) >> It's true. There's a lot of organizations out there, girls who Code, Girls Inc., et cetera, that are all aimed at helping women kind of find their, I think, find their voice. >> Exactly. >> And find that curiosity. >> Yeah. Unlock that somewhere back there. Get some courage- >> Mm-hmm. >> To raise your hand and say, "I think I want to do this," or "I have a question. You explained something and I didn't understand it." Like, that's the advice I would always give to my younger self is never be afraid to raise your hand in a meeting. >> Mm-hmm. >> I guarantee you half the people weren't listening or, and the other half may not have understood what was being talked about. >> Exactly. >> So, raise your hand, there goes Margot Gerritsen, the founder of WiDS, hey, Margot. >> Hi. >> Keep alumni as you know, raise your hand, ask the question, there's no question that's stupid. >> Mm-hmm. >> And I promise you, if you just take that chance once it will open up so many doors, you won't even know which door to go in because there's so many that are opening. >> And if you have a question, there's at least one more person in the room who has the exact same question. >> Exact same question. >> Yeah, we'll definitely keep that in mind as students- >> Well, I'm curious how Data Journalism, what you heard today, Tracy, we'll start with you, and then, Hannah, to you. >> Mm-hmm. How has it influenced how you approach data-driven, and storytelling? Has it inspired you? I imagine it has, or has it given you any new ideas for, as you round out your Master's Program in the next few months? >> I think like one keyword that I found really helpful from like all the conversations today, was problem-solving. >> Yeah. >> Because I think, like we talked a lot about in our program about how to put a face on data sets. How to put a face, put a name on a story that's like coming from like big data, a lot of numbers but you need to like narrow it down to like one person or one anecdote that represents a bigger problem. And I think essentially that's problem-solving. That's like there is a community, there is like say maybe even just one person who has, well, some problem about something, and then we're using data. We're, by giving them a voice, by portraying them in news and like representing them in the media, we're solving this problem somehow. We're at least trying to solve this problem, trying to make some impact. And I think that's like what Data Science is about, is problem-solving, and, yeah, I think I heard a lot from today's conversation, also today's speakers. So, yeah, I think that's like something we should also think about as Journalists when we do pitches or like what kind of problem are we solving? >> I love that. >> Or like kind of what community are we trying to make an impact in? >> Yes. >> Absolutely. Yeah, I think one of the main learnings for me that I want to apply like to my career in Data Journalism is that I don't shy away from complexity because like Data Science is oftentimes very complex. >> Complex. >> And also data, you're using for your stories is complex. >> Mm-hmm. >> So, how can we, on the one hand, reduce complexity in a way that we make it accessible for broader audience? 'Cause, we don't want to be this like tech bubble talking in data jargon, we want to, you know, make it accessible for a broader audience. >> Yeah. >> I think that's like my purpose as a Data Journalist. But at the same time, don't reduce complexity when it's needed, you know, and be open to dive into new topics, and data sets and circling back to this of like raising your hand and asking questions if you don't understand like a certain part. >> Yeah. >> So, that's definitely a main learning from this conference. >> Definitely. >> That like, people are willing to talk to you and explain complex topics, and this will definitely facilitate your work as a Data Journalist. >> Mm-hmm. >> So, that inspired me. >> Well, I can't wait to see where you guys go from here. I've loved co-hosting with you today, thank you. >> Thank you. >> For joining me at our conference. >> Wasn't it fun? >> Thank you. >> It's a great event. It's, we, I think we've all been very inspired and I'm going to leave here probably floating above the ground a few inches, high on the inspiration of what this community can deliver, isn't that great? >> It feels great, I don't know, I just feel great. >> Me too. (laughs) >> So much good energy, positive energy, we love it. >> Yeah, so we want to thank all the organizers of WiDS, Judy Logan, Margot Gerritsen in particular. We also want to thank John Furrier who is here. And if you know Johnny, know he gets FOMO when he is not hosting. But John and Dave Vellante are such great supporters of women in technology, women in technical roles. We wouldn't be here without them. So, shout out to my bosses. Thank you for giving me the keys to theCube at this event. I know it's painful sometimes, but we hope that we brought you great stories all day. We hope we inspired you with the females and the one male that we had on the program today in terms of raise your hand, ask a question, be curious, don't be afraid to pursue what you're interested in. That's my soapbox moment for now. So, for my co-host, I'm Lisa Martin, we want to thank you so much for watching our program today. You can watch all of this on-demand on thecube.net. You'll find write-ups on siliconeangle.com, and, of course, YouTube. Thanks, everyone, stay safe and we'll see you next time. (energetic 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)

(upbeat music) >> Hi everyone. Welcome back to this Cube conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE." Got a great conversation around Cloud Native, Cloud Native Journey, how enterprises are looking at Cloud Native and putting it all together. And it comes down to operations, developer productivity, and security. It's the hottest topic in technology. We got Chris Jones here in the studio, director of Product Management for Platform9. Chris, thanks for coming in. >> Hey, thanks. >> So when we always chat about, when we're at KubeCon. KubeConEU is coming up and in a few, in a few months, the number one conversation is developer productivity. And the developers are driving all the standards. It's interesting to see how they just throw everything out there and whatever gets adopted ends up becoming the standard, not the old school way of kind of getting stuff done. So that's cool. Security Kubernetes and Containers are all kind of now that next level. So you're starting to see the early adopters moving to the mainstream. Enterprises, a variety of different approaches. You guys are at the center of this. We've had a couple conversations with your CEO and your tech team over there. What are you seeing? You're building the products. What's the core product focus right now for Platform9? What are you guys aiming for? >> The core is that blend of enabling your infrastructure and PlatformOps or DevOps teams to be able to go fast and run in a stable environment, but at the same time enable developers. We don't want people going back to what I've been calling Shadow IT 2.0. It's, hey, I've been told to do something. I kicked off this Container initiative. I need to run my software somewhere. I'm just going to go figure it out. We want to keep those people productive. At the same time we want to enable velocity for our operations teams, be it PlatformOps or DevOps. >> Take us through in your mind and how you see the industry rolling out this Cloud Native journey. Where do you see customers out there? Because DevOps have been around, DevSecOps is rocking, you're seeing AI, hot trend now. Developers are still in charge. Is there a change to the infrastructure of how developers get their coding done and the infrastructure, setting up the DevOps is key, but when you add the Cloud Native journey for an enterprise, what changes? What is the, what is the, I guess what is the Cloud Native journey for an enterprise these days? >> The Cloud Native journey or the change? When- >> Let's start with the, let's start with what they want to do. What's the goal and then how does that happen? >> I think the goal is that promise land. Increased resiliency, better scalability, and overall reduced costs. I've gone from physical to virtual that gave me a higher level of density, packing of resources. I'm moving to Containers. I'm removing that OS layer again. I'm getting a better density again, but all of a sudden I'm running Kubernetes. What does that, what does that fundamentally do to my operations? Does it magically give me scalability and resiliency? Or do I need to change what I'm running and how it's running so it fits that infrastructure? And that's the reality, is you can't just take a Container and drop it into Kubernetes and say, hey, I'm now Cloud Native. I've got reduced cost, or I've got better resiliency. There's things that your engineering teams need to do to make sure that application is a Cloud Native. And then there's what I think is one of the largest shifts of virtual machines to containers. When I was in the world of application performance monitoring, we would see customers saying, well, my engineering team have this Java app, and they said it needs a VM with 12 gig of RAM and eight cores, and that's what we gave it. But it's running slow. I'm working with the application team and you can see it's running slow. And they're like, well, it's got all of its resources. One of those nice features of virtualization is over provisioning. So the infrastructure team would say, well, we gave it, we gave it all a RAM it needed. And what's wrong with that being over provisioned? It's like, well, Java expects that RAM to be there. Now all of a sudden, when you move to the world of containers, what we've got is that's not a set resource limit, really is like it used to be in a VM, right? When you set it for a container, your application teams really need to be paying attention to your resource limits and constraints within the world of Kubernetes. So instead of just being able to say, hey, I'm throwing over the fence and now it's just going to run on a VM, and that VMs got everything it needs. It's now really running on more, much more of a shared infrastructure where limits and constraints are going to impact the neighbors. They are going to impact who's making that decision around resourcing. Because that Kubernetes concept of over provisioning and the virtualization concept of over provisioning are not the same. So when I look at this problem, it's like, well, what changed? Well, I'll do my scale tests as an application developer and tester, and I'd see what resources it needs. I asked for that in the VM, that sets the high watermark, job's done. Well, Kubernetes, it's no longer a VM, it's a Kubernetes manifest. And well, who owns that? Who's writing it? Who's setting those limits? To me, that should be the application team. But then when it goes into operations world, they're like, well, that's now us. Can we change those? So it's that amalgamation of the two that is saying, I'm a developer. I used to pay attention, but now I need to pay attention. And an infrastructure person saying, I used to just give 'em what they wanted, but now I really need to know what they've wanted, because it's going to potentially have a catastrophic impact on what I'm running. >> So what's the impact for the developer? Because, infrastructure's code is what everybody wants. The developer just wants to get the code going and they got to pay attention to all these things, or don't they? Is that where you guys come in? How do you guys see the problem? Actually scope the problem that you guys solve? 'Cause I think you're getting at I think the core issue here, which is, I've got Kubernetes, I've got containers, I've got developer productivity that I want to focus on. What's the problem that you guys solve? >> Platform operation teams that are adopting Cloud Native in their environment, they've got that steep learning curve of Kubernetes plus this fundamental change of how an app runs. What we're doing is taking away the burden of needing to operate and run Kubernetes and giving them the choice of the flexibility of infrastructure and location. Be that an air gap environment like a, let's say a telco provider that needs to run a containerized network function and containerized workloads for 5G. That's one thing that we can deploy and achieve in a completely inaccessible environment all the way through to Platform9 running traditionally as SaaS, as we were born, that's remotely managing and controlling your Kubernetes environments on-premise AWS. That hybrid cloud experience that could be also Bare Metal, but it's our platform running your environments with our support there, 24 by seven, that's proactively reaching out. So it's removing a lot of that burden and the complications that come along with operating the environment and standing it up, which means all of a sudden your DevOps and platform operations teams can go and work with your engineers and application developers and say, hey, let's get, let's focus on the stuff that, that we need to be focused on, which is running our business and providing a service to our customers. Not figuring out how to upgrade a Kubernetes cluster, add new nodes, and configure all of the low level. >> I mean there are, that's operations that just needs to work. And sounds like as they get into the Cloud Native kind of ops, there's a lot of stuff that kind of goes wrong. Or you go, oops, what do we buy into? Because the CIOs, let's go, let's go Cloud Native. We want to, we got to get set up for the future. We're going to be Cloud Native, not just lift and shift and we're going to actually build it out right. Okay, that sounds good. And when we have to actually get done. >> Chris: Yeah. >> You got to spin things up and stand up the infrastructure. What specifically use case do you guys see that emerges for Platform9 when people call you up and you go talk to customers and prospects? What's the one thing or use case or cases that you guys see that you guys solve the best? >> So I think one of the, one of the, I guess new use cases that are coming up now, everyone's talking about economic pressures. I think the, the tap blows open, just get it done. CIO is saying let's modernize, let's use the cloud. Now all of a sudden they're recognizing, well wait, we're spending a lot of money now. We've opened that tap all the way, what do we do? So now they're looking at ways to control that spend. So we're seeing that as a big emerging trend. What we're also sort of seeing is people looking at their data centers and saying, well, I've got this huge legacy environment that's running a hypervisor. It's running VMs. Can we still actually do what we need to do? Can we modernize? Can we start this Cloud Native journey without leaving our data centers, our co-locations? Or if I do want to reduce costs, is that that thing that says maybe I'm repatriating or doing a reverse migration? Do I have to go back to my data center or are there other alternatives? And we're seeing that trend a lot. And our roadmap and what we have in the product today was specifically built to handle those, those occurrences. So we brought in KubeVirt in terms of virtualization. We have a long legacy doing OpenStack and private clouds. And we've worked with a lot of those users and customers that we have and asked the questions, what's important? And today, when we look at the world of Cloud Native, you can run virtualization within Kubernetes. So you can, instead of running two separate platforms, you can have one. So all of a sudden, if you're looking to modernize, you can start on that new infrastructure stack that can run anywhere, Kubernetes, and you can start bringing VMs over there as you are containerizing at the same time. So now you can keep your application operations in one environment. And this also helps if you're trying to reduce costs. If you really are saying, we put that Dev environment in AWS, we've got a huge amount of velocity out of it now, can we do that elsewhere? Is there a co-location we can go to? Is there a provider that we can go to where we can run that infrastructure or run the Kubernetes, but not have to run the infrastructure? >> It's going to be interesting too, when you see the Edge come online, you start, we've got Mobile World Congress coming up, KubeCon events we're going to be at, the conversation is not just about public cloud. And you guys obviously solve a lot of do-it-yourself implementation hassles that emerge when people try to kind of stand up their own environment. And we hear from developers consistency between code, managing new updates, making sure everything is all solid so they can go fast. That's the goal. And that, and then people can get standardized on that. But as you get public cloud and do it yourself, kind of brings up like, okay, there's some gaps there as the architecture changes to be more distributed computing, Edge, on-premises cloud, it's cloud operations. So that's cool for DevOps and Cloud Native. How do you guys differentiate from say, some the public cloud opportunities and the folks who are doing it themselves? How do you guys fit in that world and what's the pitch or what's the story? >> The fit that we look at is that third alternative. Let's get your team focused on what's high value to your business and let us deliver that public cloud experience on your infrastructure or in the public cloud, which gives you that ability to still be flexible if you want to make choices to run consistently for your developers in two different locations. So as I touched on earlier, instead of saying go figure out Kubernetes, how do you upgrade a hundred worker nodes in place upgrade. We've solved that problem. That's what we do every single day of the week. Don't go and try to figure out how to upgrade a cluster and then upgrade all of the, what I call Kubernetes friends, your core DNSs, your metrics server, your Kubernetes dashboard. These are all things that we package, we test, we version. So when you click upgrade, we've already handled that entire process. So it's saying don't have your team focused on that lower level piece of work. Get them focused on what is important, which is your business services. >> Yeah, the infrastructure and getting that stood up. I mean, I think the thing that's interesting, if you look at the market right now, you mentioned cost savings and recovery, obviously kind of a recession. I mean, people are tightening their belts for sure. I don't think the digital transformation and Cloud Native spend is going to plummet. It's going to probably be on hold and be squeezed a little bit. But to your point, people are refactoring looking at how to get the best out of what they got. It's not just open the tap of spend the cash like it used to be. Yeah, a couple months, even a couple years ago. So okay, I get that. But then you look at the what's coming, AI. You're seeing all the new data infrastructure that's coming. The containers, Kubernetes stuff, got to get stood up pretty quickly and it's got to be reliable. So to your point, the teams need to get done with this and move on to the next thing. >> Chris: Yeah, yeah, yeah. >> 'Cause there's more coming. I mean, there's a lot coming for the apps that are building in Data Native, AI-Native, Cloud Native. So it seems that this Kubernetes thing needs to get solved. Is that kind of what you guys are focused on right now? >> So, I mean to use a customer, we have a customer that's in AI/ML and they run their platform at customer sites and that's hardware bound. You can't run AI machine learning on anything anywhere. Well, with Platform9 they can. So we're enabling them to deliver services into their customers that's running their AI/ML platform in their customer's data centers anywhere in the world on hardware that is purpose-built for running that workload. They're not Kubernetes experts. That's what we are. We're bringing them that ability to focus on what's important and just delivering their business services whilst they're enabling our team. And our 24 by seven proactive management are always on assurance to keep that up and running for them. So when something goes bump at the night at 2:00am, our guys get woken up. They're the ones that are reaching out to the customer saying, your environments have a problem, we're taking these actions to fix it. Obviously sometimes, especially if it is running on Bare Metal, there's things you can't do remotely. So you might need someone to go and do that. But even when that happens, you're not by yourself. You're not sitting there like I did when I worked for a bank in one of my first jobs, three o'clock in the morning saying, wow, our end of day processing is stuck. Who else am I waking up? Right? >> Exactly, yeah. Got to get that cash going. But this is a great use case. I want to get to the customer. What do some of the successful customers say to you for the folks watching that aren't yet a customer of Platform9, what are some of the accolades and comments or anecdotes that you guys hear from customers that you have? >> It just works, which I think is probably one of the best ones you can get. Customers coming back and being able to show to their business that they've delivered growth, like business growth and productivity growth and keeping their organization size the same. So we started on our containerization journey. We went to Kubernetes. We've deployed all these new workloads and our operations team is still six people. We're doing way more with growth less, and I think that's also talking to the strength that we're bringing, 'cause we're, we're augmenting that team. They're spending less time on the really low level stuff and automating a lot of the growth activity that's involved. So when it comes to being able to grow their business, they can just focus on that, not- >> Well you guys do the heavy lifting, keep on top of the Kubernetes, make sure that all the versions are all done. Everything's stable and consistent so they can go on and do the build out and provide their services. That seems to be what you guys are best at. >> Correct, correct. >> And so what's on the roadmap? You have the product, direct product management, you get the keys to the kingdom. What is, what is the focus? What's your focus right now? Obviously Kubernetes is growing up, Containers. We've been hearing a lot at the last KubeCon about the security containers is getting better. You've seen verification, a lot more standards around some things. What are you focused on right now for at a product over there? >> Edge is a really big focus for us. And I think in Edge you can look at it in two ways. The mantra that I drive is Edge must be remote. If you can't do something remotely at the Edge, you are using a human being, that's not Edge. Our Edge management capabilities and being in the market for over two years are a hundred percent remote. You want to stand up a store, you just ship the server in there, it gets racked, the rest of it's remote. Imagine a store manager in, I don't know, KFC, just plugging in the server, putting in the ethernet cable, pressing the power button. The rest of all that provisioning for that Cloud Native stack, Kubernetes, KubeVirt for virtualization is done remotely. So we're continuing to focus on that. The next piece that is related to that is allowing people to run Platform9 SaaS in their data centers. So we do ag app today and we've had a really strong focus on telecommunications and the containerized network functions that come along with that. So this next piece is saying, we're bringing what we run as SaaS into your data center, so then you can run it. 'Cause there are many people out there that are saying, we want these capabilities and we want everything that the Platform9 control plane brings and simplifies. But unfortunately, regulatory compliance reasons means that we can't leverage SaaS. So they might be using a cloud, but they're saying that's still our infrastructure. We're still closed that network down, or they're still on-prem. So they're two big priorities for us this year. And that on-premise experiences is paramount, even to the point that we will be delivering a way that when you run an on-premise, you can still say, wait a second, well I can send outbound alerts to Platform9. So their support team can still be proactively helping me as much as they could, even though I'm running Platform9s control plane. So it's sort of giving that blend of two experiences. They're big, they're big priorities. And the third pillar is all around virtualization. It's saying if you have economic pressures, then I think it's important to look at what you're spending today and realistically say, can that be reduced? And I think hypervisors and virtualization is something that should be looked at, because if you can actually reduce that spend, you can bring in some modernization at the same time. Let's take some of those nos that exist that are two years into their five year hardware life cycle. Let's turn that into a Cloud Native environment, which is enabling your modernization in place. It's giving your engineers and application developers the new toys, the new experiences, and then you can start running some of those virtualized workloads with KubeVirt, there. So you're reducing cost and you're modernizing at the same time with your existing infrastructure. >> You know Chris, the topic of this content series that we're doing with you guys is finding the right path, trusting the right path to Cloud Native. What does that mean? I mean, if you had to kind of summarize that phrase, trusting the right path to Cloud Native, what does that mean? It mean in terms of architecture, is it deployment? Is it operations? What's the underlying main theme of that quote? What's the, what's? How would you talk to a customer and say, what does that mean if someone said, "Hey, what does that right path mean?" >> I think the right path means focusing on what you should be focusing on. I know I've said it a hundred times, but if your entire operations team is trying to figure out the nuts and bolts of Kubernetes and getting three months into a journey and discovering, ah, I need Metrics Server to make something function. I want to use Horizontal Pod Autoscaler or Vertical Pod Autoscaler and I need this other thing, now I need to manage that. That's not the right path. That's literally learning what other people have been learning for the last five, seven years that have been focused on Kubernetes solely. So the why- >> There's been a lot of grind. People have been grinding it out. I mean, that's what you're talking about here. They've been standing up the, when Kubernetes started, it was all the promise. >> Chris: Yep. >> And essentially manually kind of getting in in the weeds and configuring it. Now it's matured up. They want stability. >> Chris: Yeah. >> Not everyone can get down and dirty with Kubernetes. It's not something that people want to generally do unless you're totally into it, right? Like I mean, I mean ops teams, I mean, yeah. You know what I mean? It's not like it's heavy lifting. Yeah, it's important. Just got to get it going. >> Yeah, I mean if you're deploying with Platform9, your Ops teams can tinker to their hearts content. We're completely compliant upstream Kubernetes. You can go and change an API server flag, let's go and mess with the scheduler, because we want to. You can still do that, but don't, don't have your team investing in all this time to figure it out. It's been figured out. >> John: Got it. >> Get them focused on enabling velocity for your business. >> So it's not build, but run. >> Chris: Correct? >> Or run Kubernetes, not necessarily figure out how to kind of get it all, consume it out. >> You know we've talked to a lot of customers out there that are saying, "I want to be able to deliver a service to my users." Our response is, "Cool, let us run it. You consume it, therefore deliver it." And we're solving that in one hit versus figuring out how to first run it, then operate it, then turn that into a consumable service. >> So the alternative Platform9 is what? They got to do it themselves or use the Cloud or what's the, what's the alternative for the customer for not using Platform9? Hiring more people to kind of work on it? What's the? >> People, building that kind of PaaS experience? Something that I've been very passionate about for the past year is looking at that world of sort of GitOps and what that means. And if you go out there and you sort of start asking the question what's happening? Just generally with Kubernetes as well and GitOps in that scope, then you'll hear some people saying, well, I'm making it PaaS, because Kubernetes is too complicated for my developers and we need to give them something. There's some great material out there from the likes of Intuit and Adobe where for two big contributors to Argo and the Argo projects, they almost have, well they do have, different experiences. One is saying, we went down the PaaS route and it failed. The other one is saying, well we've built a really stable PaaS and it's working. What are they trying to do? They're trying to deliver an outcome to make it easy to use and consume Kubernetes. So you could go out there and say, hey, I'm going to build a Kubernetes cluster. Sounds like Argo CD is a great way to expose that to my developers so they can use Kubernetes without having to use Kubernetes and start automating things. That is an approach, but you're going to be going completely open source and you're going to have to bring in all the individual components, or you could just lay that, lay it down, and consume it as a service and not have to- >> And mentioned to it. They were the ones who kind of brought that into the open. >> They did. Inuit is the primary contributor to the Argo set of products. >> How has that been received in the market? I mean, they had the event at the Computer History Museum last fall. What's the momentum there? What's the big takeaway from that project? >> Growth. To me, growth. I mean go and track the stars on that one. It's just, it's growth. It's unlocking machine learning. Argo workflows can do more than just make things happen. Argo CD I think the approach they're taking is, hey let's make this simple to use, which I think can be lost. And I think credit where credit's due, they're really pushing to bring in a lot of capabilities to make it easier to work with applications and microservices on Kubernetes. It's not just that, hey, here's a GitOps tool. It can take something from a Git repo and deploy it and maybe prioritize it and help you scale your operations from that perspective. It's taking a step back and saying, well how did we get to production in the first place? And what can be done down there to help as well? I think it's growth expansion of features. They had a huge release just come out in, I think it was 2.6, that brought in things that as a product manager that I don't often look at like really deep technical things and say wow, that's powerful. But they have, they've got some great features in that release that really do solve real problems. >> And as the product, as the product person, who's the target buyer for you? Who's the customer? Who's making that? And you got decision maker, influencer, and recommender. Take us through the customer persona for you guys. >> So that Platform Ops, DevOps space, right, the people that need to be delivering Containers as a service out to their organization. But then it's also important to say, well who else are our primary users? And that's developers, engineers, right? They shouldn't have to say, oh well I have access to a Kubernetes cluster. Do I have to use kubectl or do I need to go find some other tool? No, they can just log to Platform9. It's integrated with your enterprise id. >> They're the end customer at the end of the day, they're the user. >> Yeah, yeah. They can log in. And they can see the clusters you've given them access to as a Platform Ops Administrator. >> So job well done for you guys. And your mind is the developers are moving 'em fast, coding and happy. >> Chris: Yeah, yeah. >> And and from a customer standpoint, you reduce the maintenance cost, because you keep the Ops smoother, so you got efficiency and maintenance costs kind of reduced or is that kind of the benefits? >> Yeah, yep, yeah. And at two o'clock in the morning when things go inevitably wrong, they're not there by themselves, and we're proactively working with them. >> And that's the uptime issue. >> That is the uptime issue. And Cloud doesn't solve that, right? Everyone experienced that Clouds can go down, entire regions can go offline. That's happened to all Cloud providers. And what do you do then? Kubernetes isn't your recovery plan. It's part of it, right, but it's that piece. >> You know Chris, to wrap up this interview, I will say that "theCUBE" is 12 years old now. We've been to OpenStack early days. We had you guys on when we were covering OpenStack and now Cloud has just been booming. You got AI around the corner, AI Ops, now you got all this new data infrastructure, it's just amazing Cloud growth, Cloud Native, Security Native, Cloud Native, Data Native, AI Native. It's going to be all, this is the new app environment, but there's also existing infrastructure. So going back to OpenStack, rolling our own cloud, building your own cloud, building infrastructure cloud, in a cloud way, is what the pioneers have done. I mean this is what we're at. Now we're at this scale next level, abstracted away and make it operational. It seems to be the key focus. We look at CNCF at KubeCon and what they're doing with the cloud SecurityCon, it's all about operations. >> Chris: Yep, right. >> Ops and you know, that's going to sound counterintuitive 'cause it's a developer open source environment, but you're starting to see that Ops focus in a good way. >> Chris: Yeah, yeah, yeah. >> Infrastructure as code way. >> Chris: Yep. >> What's your reaction to that? How would you summarize where we are in the industry relative to, am I getting, am I getting it right there? Is that the right view? What am I missing? What's the current state of the next level, NextGen infrastructure? >> It's a good question. When I think back to sort of late 2019, I sort of had this aha moment as I saw what really truly is delivering infrastructure as code happening at Platform9. There's an open source project Ironic, which is now also available within Kubernetes that is Metal Kubed that automates Bare Metal as code, which means you can go from an empty server, lay down your operating system, lay down Kubernetes, and you've just done everything delivered to your customer as code with a Cloud Native platform. That to me was sort of the biggest realization that I had as I was moving into this industry was, wait, it's there. This can be done. And the evolution of tooling and operations is getting to the point where that can be achieved and it's focused on by a number of different open source projects. Not just Ironic and and Metal Kubed, but that's a huge win. That is truly getting your infrastructure. >> John: That's an inflection point, really. >> Yeah. >> If you think about it, 'cause that's one of the problems. We had with the Bare Metal piece was the automation and also making it Cloud Ops, cloud operations. >> Right, yeah. I mean, one of the things that I think Ironic did really well was saying let's just treat that piece of Bare Metal like a Cloud VM or an instance. If you got a problem with it, just give the person using it or whatever's using it, a new one and reimage it. Just tell it to reimage itself and it'll just (snaps fingers) go. You can do self-service with it. In Platform9, if you log in to our SaaS Ironic, you can go and say, I want that physical server to myself, because I've got a giant workload, or let's turn it into a Kubernetes cluster. That whole thing is automated. To me that's infrastructure as code. I think one of the other important things that's happening at the same time is we're seeing GitOps, we're seeing things like Terraform. I think it's important for organizations to look at what they have and ask, am I using tools that are fit for tomorrow or am I using tools that are yesterday's tools to solve tomorrow's problems? And when especially it comes to modernizing infrastructure as code, I think that's a big piece to look at. >> Do you see Terraform as old or new? >> I see Terraform as old. It's a fantastic tool, capable of many great things and it can work with basically every single provider out there on the planet. It is able to do things. Is it best fit to run in a GitOps methodology? I don't think it is quite at that point. In fact, if you went and looked at Flux, Flux has ways that make Terraform GitOps compliant, which is absolutely fantastic. It's using two tools, the best of breeds, which is solving that tomorrow problem with tomorrow solutions. >> Is the new solutions old versus new. I like this old way, new way. I mean, Terraform is not that old and it's been around for about eight years or so, whatever. But HashiCorp is doing a great job with that. I mean, so okay with Terraform, what's the new address? Is it more complex environments? Because Terraform made sense when you had basic DevOps, but now it sounds like there's a whole another level of complexity. >> I got to say. >> New tools. >> That kind of amalgamation of that application into infrastructure. Now my app team is paying way more attention to that manifest file, which is what GitOps is trying to solve. Let's templatize things. Let's version control our manifest, be it helm, customize, or just a straight up Kubernetes manifest file, plain and boring. Let's get that version controlled. Let's make sure that we know what is there, why it was changed. Let's get some auditability and things like that. And then let's get that deployment all automated. So that's predicated on the cluster existing. Well why can't we do the same thing with the cluster, the inception problem. So even if you're in public cloud, the question is like, well what's calling that API to call that thing to happen? Where is that file living? How well can I manage that in a large team? Oh my God, something just changed. Who changed it? Where is that file? And I think that's one of big, the big pieces to be sold. >> Yeah, and you talk about Edge too and on-premises. I think one of the things I'm observing and certainly when DevOps was rocking and rolling and infrastructures code was like the real push, it was pretty much the public cloud, right? >> Chris: Yep. >> And you did Cloud Native and you had stuff on-premises. Yeah you did some lifting and shifting in the cloud, but the cool stuff was going in the public cloud and you ran DevOps. Okay, now you got on-premise cloud operation and Edge. Is that the new DevOps? I mean 'cause what you're kind of getting at with old new, old new Terraform example is an interesting point, because you're pointing out potentially that that was good DevOps back in the day or it still is. >> Chris: It is, I was going to say. >> But depending on how you define what DevOps is. So if you say, I got the new DevOps with public on-premise and Edge, that's just not all public cloud, that's essentially distributed Cloud Native. >> Correct. Is that the new DevOps in your mind or is that? How would you, or is that oversimplifying it? >> Or is that that term where everyone's saying Platform Ops, right? Has it shifted? >> Well you bring up a good point about Terraform. I mean Terraform is well proven. People love it. It's got great use cases and now there seems to be new things happening. We call things like super cloud emerging, which is multicloud and abstraction layers. So you're starting to see stuff being abstracted away for the benefits of moving to the next level, so teams don't get stuck doing the same old thing. They can move on. Like what you guys are doing with Platform9 is providing a service so that teams don't have to do it. >> Correct, yeah. >> That makes a lot of sense, So you just, now it's running and then they move on to the next thing. >> Chris: Yeah, right. >> So what is that next thing? >> I think Edge is a big part of that next thing. The propensity for someone to put up with a delay, I think it's gone. For some reason, we've all become fairly short-tempered, Short fused. You know, I click the button, it should happen now, type people. And for better or worse, hopefully it gets better and we all become a bit more patient. But how do I get more effective and efficient at delivering that to that really demanding- >> I think you bring up a great point. I mean, it's not just people are getting short-tempered. I think it's more of applications are being deployed faster, security is more exposed if they don't see things quicker. You got data now infrastructure scaling up massively. So, there's a double-edged swords to scale. >> Chris: Yeah, yeah. I mean, maintenance, downtime, uptime, security. So yeah, I think there's a tension around, and one hand enthusiasm around pushing a lot of code and new apps. But is the confidence truly there? It's interesting one little, (snaps finger) supply chain software, look at Container Security for instance. >> Yeah, yeah. It's big. I mean it was codified. >> Do you agree that people, that's kind of an issue right now. >> Yeah, and it was, I mean even the supply chain has been codified by the US federal government saying there's things we need to improve. We don't want to see software being a point of vulnerability, and software includes that whole process of getting it to a running point. >> It's funny you mentioned remote and one of the thing things that you're passionate about, certainly Edge has to be remote. You don't want to roll a truck or labor at the Edge. But I was doing a conversation with, at Rebars last year about space. It's hard to do brake fix on space. It's hard to do a, to roll a someone to configure satellite, right? Right? >> Chris: Yeah. >> So Kubernetes is in space. We're seeing a lot of Cloud Native stuff in apps, in space, so just an example. This highlights the fact that it's got to be automated. Is there a machine learning AI angle with all this ChatGPT talk going on? You see all the AI going the next level. Some pretty cool stuff and it's only, I know it's the beginning, but I've heard people using some of the new machine learning, large language models, large foundational models in areas I've never heard of. Machine learning and data centers, machine learning and configuration management, a lot of different ways. How do you see as the product person, you incorporating the AI piece into the products for Platform9? >> I think that's a lot about looking at the telemetry and the information that we get back and to use one of those like old idle terms, that continuous improvement loop to feed it back in. And I think that's really where machine learning to start with comes into effect. As we run across all these customers, our system that helps at two o'clock in the morning has that telemetry, it's got that data. We can see what's changing and what's happening. So it's writing the right algorithms, creating the right machine learning to- >> So training will work for you guys. You have enough data and the telemetry to do get that training data. >> Yeah, obviously there's a lot of investment required to get there, but that is something that ultimately that could be achieved with what we see in operating people's environments. >> Great. Chris, great to have you here in the studio. Going wide ranging conversation on Kubernetes and Platform9. I guess my final question would be how do you look at the next five years out there? Because you got to run the product management, you got to have that 20 mile steer, you got to look at the customers, you got to look at what's going on in the engineering and you got to kind of have that arc. This is the right path kind of view. What's the five year arc look like for you guys? How do you see this playing out? 'Cause KubeCon is coming up and we're you seeing Kubernetes kind of break away with security? They had, they didn't call it KubeCon Security, they call it CloudNativeSecurityCon, they just had in Seattle inaugural events seemed to go well. So security is kind of breaking out and you got Kubernetes. It's getting bigger. Certainly not going away, but what's your five year arc of of how Platform9 and Kubernetes and Ops evolve? >> It's to stay on that theme, it's focusing on what is most important to our users and getting them to a point where they can just consume it, so they're not having to operate it. So it's finding those big items and bringing that into our platform. It's something that's consumable, that's just taken care of, that's tested with each release. So it's simplifying operations more and more. We've always said freedom in cloud computing. Well we started on, we started on OpenStack and made that simple. Stable, easy, you just have it, it works. We're doing that with Kubernetes. We're expanding out that user, right, we're saying bring your developers in, they can download their Kube conflict. They can see those Containers that are running there. They can access the events, the log files. They can log in and build a VM using KubeVirt. They're self servicing. So it's alleviating pressures off of the Ops team, removing the help desk systems that people still seem to rely on. So it's like what comes into that field that is the next biggest issue? Is it things like CI/CD? Is it simplifying GitOps? Is it bringing in security capabilities to talk to that? Or is that a piece that is a best of breed? Is there a reason that it's been spun out to its own conference? Is this something that deserves a focus that should be a specialized capability instead of tooling and vendors that we work with, that we partner with, that could be brought in as a service. I think it's looking at those trends and making sure that what we bring in has the biggest impact to our users. >> That's awesome. Thanks for coming in. I'll give you the last word. Put a plug in for Platform9 for the people who are watching. What should they know about Platform9 that they might not know about it or what should? When should they call you guys and when should they engage? Take a take a minute to give the plug. >> The plug. I think it's, if your operations team is focused on building Kubernetes, stop. That shouldn't be the cloud. That shouldn't be in the Edge, that shouldn't be at the data center. They should be consuming it. If your engineering teams are all trying different ways and doing different things to use and consume Cloud Native services and Kubernetes, they shouldn't be. You want consistency. That's how you get economies of scale. Provide them with a simple platform that's integrated with all of your enterprise identity where they can just start consuming instead of having to solve these problems themselves. It's those, it's those two personas, right? Where the problems manifest. What are my operations teams doing, and are they delivering to my company or are they building infrastructure again? And are my engineers sprinting or crawling? 'Cause if they're not sprinting, you should be asked the question, do I have the right Cloud Native tooling in my environment and how can I get them back? >> I think it's developer productivity, uptime, security are the tell signs. You get that done. That's the goal of what you guys are doing, your mission. >> Chris: Yep. >> Great to have you on, Chris. Thanks for coming on. Appreciate it. >> Chris: Thanks very much. 0 Okay, this is "theCUBE" here, finding the right path to Cloud Native. I'm John Furrier, host of "theCUBE." Thanks for watching. (upbeat music)

(energetic music plays) >> Lisa: Hey everyone, we're so glad you're here with us. theCUBE is covering Cloud Native Security Con 23. Lisa Martin here with John Furrier. This is our second day of coverage of the event. We've had some great conversations with a lot of intellectual, exciting folks, as you know cuz you've been watching. John and I are very pleased to welcome back one of our alumni to theCUBE Taylor Dolezal joins us the head of ecosystem at CNCF. Taylor, welcome back to theCUBE. Great to see you. >> Taylor: Hey everybody, great to see you again. >> Lisa: So you are on the ground in Seattle. We're jealous. We've got fomo as John would say. Talk to us about, this is a inaugural event. We were watching Priyanka keynote yesterday. Seemed like a lot of folks there, 72 sessions a lot of content, a lot of discussions. What's the buzz, what's the reception of this inaugural event from your perspective? >> Taylor: So it's been really fantastic. I think the number one thing that has come out of this conference so far is that it's a wonderful chance to come together and for people to see one another. It's, it's been a long time that we've kind of had that opportunity to be able to interact with folks or you know, it's just a couple months since last Cube Con. But this is truly a different vibe and it's nice to have that focus on security. We're seeing a lot of folks within different organizations work through different problems and then finally have a vendor neutral space in which to talk about all of those contexts and really raise everybody up with all this new knowledge and new talking points, topics, and different facets of knowledge. >> John: Taylor, we were joking on our yesterday's summary of the keynotes, Dave Vellante and I, and the guests, Lisa and I, about the CNCF having an event operating system, you know, very decoupled highly cohesive events, strung together beautifully through the Linux Foundation, you know, kind of tongue in cheek but it was kind of fun to play on words because it's a very technical community. But the business model of, of hackers is booming. The reality of businesses booming and Cloud Native is the preferred developer environment for the future application. So the emphasis, it's very clear that this is a good move to do and targeting the community around security's a solid move. Amazon's done it with reinforce and reinvent. We see that Nice segmentation. What's the goal? Because this is really where it connects to Cube Con and Cloud Native Con as well because this shift left there too. But here it's very much about hardcore Cloud Native security. What's your positioning on this? Am I getting it right or is there is that how you guys see it? >> Taylor: Yeah, so, so that's what we've see that's what we were talking about as well as we were thinking on breaking this event out. So originally this event was a co-located event during the Cube Con windows in both Europe and North America. And then it just was so consistently popular clearly a topic that people wanted to talk, which is good that people want to talk of security. And so when we saw this massive continued kind of engagement, we wanted to break this off into its own conference. When we were going through that process internally, like you had mentioned the events team is just phenomenal to work with and they, I love how easy that they make it for us to be able to do these kinds of events too though we wanted to talk through how we differentiate this event from others and really what's changed for us and kind of how we see this space is that we didn't really see any developer-centric open source kinds of conferences. Ones that were really favoring of the developer and focus on APIs and ways in which to implement these things across all of your workloads within your organization. So that's truly what we're looking to go for here during these, all of these sessions. And that's how it's been playing out so far which has been really great to see. >> John: Taylor, I want to ask you on the ecosystem obviously the built-in ecosystem at CNCF.IO with Cube Cons Cloud Cons there, this is a new ecosystem opportunity to add more people that are security focused. Is their new entrance coming into the fold and what's been the reaction? >> Taylor: So short answer is yes we've seen a huge uptick across our vendor members and those are people that are creating Cloud offerings and selling those and working with others to implement them as well as our end users. So people consuming Cloud Native projects and using them to power core parts of their business. We have gotten a lot of data from groups like IBM and security, IBM security and put 'em on institute. They gave us a cost of data breach report that Priyanka mentioned and talked about 43% of those organizations haven't started or in the early stages of updating security practices of their cloud environments and then here on the ground, you know, talking through some best practices and really sharing those out as well. So it's, I've gotten to hear pieces and parts of different conversations and and I'm certain we'll hear more about those soon but it's just really been great to, to hear everybody with that main focus of, hey, there's more that we can do within the security space and you know, let's let's help one another out on that front just because it is such a vast landscape especially in the security space. >> Lisa: It's a huge landscape. And to your point earlier, Taylor it's everyone has the feeling that it's just so great to be back together again getting folks out of the silos that they've been operating in for such a long time. But I'd love to get some of your, whatever you can share in terms of some of the Cloud Native security projects that you've heard about over the last day or so. Anything exciting that you think is really demonstrating the value already and this inaugural event? >> Taylor: Yes, so I I've been really excited to hear a lot of, personally I've really liked the talks around EBPF. There are a whole bunch of projects utilizing that as far as runtime security goes and actually getting visibility into your workloads and being able to see things that you do expect and things that you don't expect and how to remediate those. And then I keep hearing a lot of talks about open policy agents and projects like Caverno around you know, how do we actually automate different policies or within regulated industries, how do we actually start to solve those problems? So I've heard even more around CNCF projects and other contexts that have come up but truly most of them have been around the telemetry space EBPF and, and quite a few others. So really great to, to see all those projects choosing something to bind to and making it that much more accessible for folks to implement or build on top of as well. >> John: I love the reference you guys had just the ChatGPT that was mentioned in the keynote yesterday and also the reference to Dan Kaminsky who was mentioned on the reference to DNS and Bind, lot of root level security going on. It seems like this is like a Tiger team event where all the top alpha security gurus come together, Priyanka said, experts bottoms up, developer first practitioners, that's the vibe. Is that kind of how you guys want it to be more practitioners hardcore? >> Taylor: Absolutely, absolutely. I think that when it comes to security, we really want to help. It's definitely a grassroots movement. It's great to have the people that have such a deep understanding of certain security, just bits of knowledge really when it comes to EBPF. You know, we have high surveillance here that we're talking things through. Falco is here with Sysdig and so it it's great to have all of these people here, though I have seen a good spread of folks that are, you know, most people have started their security journey but they're not where they want to be. And so people that are starting at a 2 0 1, 3 0 1, 4 0 1 level of understanding definitely seeing a good spread of knowledge on that front. But it's really, it's been great to have folks from all varying experiences, but then to have the expertise of the folks that are writing these specifications and pushing the boundaries of what's possible with security to to ensure that we're all okay and updated on that front too, I think was most notable yesterday. Like you had said >> Lisa: Sorry Taylor, when we think of security, again this is an issue that, that organizations in every industry face, nobody is immune to this. We can talk about the value in it for the hackers in terms of ransomware alone for example. But you mentioned a stat that there's a good amount of organizations that are really either early in their security journeys or haven't started yet which kind of sounds a bit scary given the landscape and how much has changed in the last couple of years. But it sounds like on the good news front it isn't too late for organizations. Talk a little bit about some of the recommendations and best practices for those organizations who are behind the curve knowing that the next attack is going to happen. >> Taylor: Absolutely. So fantastic question. I think that when it comes to understanding the fact that people need to implement security and abide by best practices, it's like I I'm sure that many of us can agree on that front, you know, hopefully all of us. But when it comes to actually implementing that, that's I agree with you completely. That's where it's really difficult to find where where do I start, where do I actually look at? And there are a couple of answers on that front. So within the CNTF ecosystem we have a technical action group security, so tag security and they have a whole bunch of working groups that cover different facets of the Cloud Native experience. So if you, for example, are concerned about runtime security or application delivery concerns within there, those are some really good places to find people knowledgeable about, that even when the conference isn't going on to get a sense of what's going on. And then TAG security has also published recently version two of their security report which is free accessible online. They can actually look through that, see what some of the recent topics are and points of focus and of interest are within our community. There are also other organizations like Open SSF which is taking a deeper dive into security. You know, initially kind of having a little bit more of an academic focus on that space and then now getting further into things around software bill materials or SBOMs supply chain security and other topics as well. >> John: Well we love you guys doing this. We think it's very big deal. We think it's important. We're starting to see events post COVID take a certain formation, you know joking aside about the event operating systems smaller events are happening, but they're tied together. And so this is key. And of course the critical need is our businesses are under siege with threats, ransomware, security challenges, that's IT moves to Cloud Native, not everyone's moved over yet. So that's in progress. So there's a huge business imperative and the hackers have a business model. So this isn't like pie in the sky, this is urgent. So, that being said, how do you see this developing from who should attend the next one or who are you looking for to be involved to get input from you guys are open arms and very diverse and great great culture there, but who are you looking for? What's the makeup persona that you hope to attract and nurture and grow? >> Taylor: Absolutely. I, think that when it comes to trying the folks that we're looking for the correct answer is it varies you know, from, you know, you're asking Priyanka or our executive director or Chris Aniszczyk our CTO, I work mostly with the end users, so for me personally I really want to see folks that are operating within our ecosystem and actually pulling these down, these projects down and using them and sharing those stories. Because there are people creating these projects and contributing to them might not always have an idea of how they're used or how they can be exploited too. A lot of these groups that I work with like Mercedes or Intuit for example, they're out there in the world using these, these projects and getting a sense for, you know, what can come up. And by sharing that knowledge I think that's what's most important across the board. So really looking for those stories to be told and novel ways in which people are trying to exploit security and attacking the supply chain, or building applications, or just things we haven't thought about. So truly that that developer archetype is really helpful to have the consumers, the end users, the folks that are actually using these. And then, yeah, and I'm truly anywhere knowledgeable about security or that wants to learn more >> John: Super important, we're here to help you scale those stories up whatever you need, send them our way. We're looking forward to getting those. This is a super important movement getting the end users who are on the front lines bringing it back into the open, building, more software, making it secure and verified, all super important. We really appreciate the mission you guys are on and again we're here to help. So send those stories our way. >> Taylor: Cool, cool. We couldn't do it without you. Yeah, just everyone contributing, everyone sharing the news. This is it's people, people is the is the true operating system of our ecosystem. So really great to, really great to share. >> Lisa: That's such a great point Taylor. It is all about people. You talked about this event having a different vibe. I wanted to learn a little bit more about that as we, as we wrap up because there's so much cultural change that's required for organizations to evolve their security practices. And so people of course are at the center of culture. Talk a little bit about why that vibe is different and do you think that yeah, it's finally time. Everyone's getting on the same page here we're understanding, we're learning from each other. >> Taylor: Yes. So, so to kind of answer that, I think it's really a focus on, there's this term shift left and shift right. And talking about where do we actually put security in the mix as it comes to people adopting this and and figuring out where things go. And if you keep shifting at left, that meaning that the developers should care more deeply about this and a deeper understanding of all of these, you know, even if it's, even if they don't understand how to put it together, maybe understand a little bit about it or how these topics and, and facets of knowledge work. But you know, like with anything, if you shift everything off to one side or the other that's also not going to be efficient. You know, you want a steady stream of knowledge flowing throughout your whole organization. So I think that that's been something that has been a really interesting topic and, and hearing people kind of navigate and try to get through, especially groups that have had, you know, deployed an app and it's going to be around for 40 years as well. So I think that those are some really interesting and unique areas of focus that I've come up on the floor and then in a couple of the sessions here >> Lisa: There's got to be that, that balance there. Last question as we wrap the last 30 seconds or so what are you excited about given the success and the momentum of day one? What excites you about what's ahead for us on day two? >> Taylor: So on day two, I'm really, it's, there's just so many sessions. I think that it was very difficult for me to, you know pick which one I was actually going to go see. There are a lot of favorites that I had kind of doubled up at each of the time so I'm honestly going to be in a lot of the sessions today. So really excited about that. Supply chain security is definitely one that's close to my heart as well but I'm really curious to see what new topics, concepts or novel ideas people have to kind of exploit things. Like one for example is a package is out there it's called Browser Test but somebody came up with one called Bowser Test. Just a very simple misname and then when you go and run that it does a fake kind of like, hey you've been exploited and just even these incorrect name attacks. That's something that is really close and dear to me as well. Kind of hearing about all these wild things people wouldn't think about in terms of exploitation. So really, really excited to hear more stories on that front and better protect myself both at home and within the Cloud Community as I stand these things up. >> Lisa: Absolutely you need to clone yourself so that you can, there's so many different sessions. There needs to be multiple versions of Taylor that you can attend and then you can all get together and talk about and learn. But that's actually a really good problem to have as we mentioned when we started 72 sessions yesterday and today. Lots of great content. Taylor, we thank you for your participation. We thank you for bringing the vibe and the buzz of the event to us and we look forward as well to hearing and seeing what day two brings us today. Thank you so much for your time Taylor. >> Taylor: Thank you for having me. >> John: All right >> Lisa: Right, for our guest and John Furrier, I'm Lisa Martin. You're watching theCube's Day two coverage of Cloud Native Security Con 23. (energetic music plays)

(uplifting music) >> Hello, welcome back to theCUBE's coverage of CloudNativeSecurityCon, the inaugural event, in Seattle. I'm John Furrier, host of theCUBE, here in the Palo Alto Studios. We're calling it theCUBE Center. It's kind of like our Sports Center for tech. It's kind of remote coverage. We've been doing this now for a few years. We're going to amp it up this year as more events are remote, and happening all around the world. So, we're going to continue the coverage with this segment focusing on the data stack, entrepreneurial opportunities around all things security, and as, obviously, data's involved. And our next guest is a friend of theCUBE, and CUBE alumni from 2013, entrepreneur himself, turned, now, venture capitalist angel investor, with his own firm, Opher Kahane, Managing Director, Sonoma Ventures. Formerly the founder of Origami, sold to Intuit a few years back. Focusing now on having a lot of fun, angel investing on boards, focusing on data-driven applications, and stacks around that, and all the stuff going on in, really, in the wheelhouse for what's going on around security data. Opher, great to see you. Thanks for coming on. >> My pleasure. Great to be back. It's been a while. >> So you're kind of on Easy Street now. You did the entrepreneurial venture, you've worked hard. We were on together in 2013 when theCUBE just started. XCEL Partners had an event in Stanford, XCEL, and they had all the features there. We interviewed Satya Nadella, who was just a manager at Microsoft at that time, he was there. He's now the CEO of Microsoft. >> Yeah, he was. >> A lot's changed in nine years. But congratulations on your venture you sold, and you got an exit there, and now you're doing a lot of investments. I'd love to get your take, because this is really the biggest change I've seen in the past 12 years, around an inflection point around a lot of converging forces. Data, which, big data, 10 years ago, was a big part of your career, but now it's accelerated, with cloud scale. You're seeing people building scale on top of other clouds, and becoming their own cloud. You're seeing data being a big part of it. Cybersecurity kind of has not really changed much, but it's the most important thing everyone's talking about. So, developers are involved, data's involved, a lot of entrepreneurial opportunities. So I'd love to get your take on how you see the current situation, as it relates to what's gone on in the past five years or so. What's the big story? >> So, a lot of big stories, but I think a lot of it has to do with a promise of making value from data, whether it's for cybersecurity, for Fintech, for DevOps, for RevTech startups and companies. There's a lot of challenges in actually driving and monetizing the value from data with velocity. Historically, the challenge has been more around, "How do I store data at massive scale?" And then you had the big data infrastructure company, like Cloudera, and MapR, and others, deal with it from a scale perspective, from a storage perspective. Then you had a whole layer of companies that evolved to deal with, "How do I index massive scales of data, for quick querying, and federated access, et cetera?" But now that a lot of those underlying problems, if you will, have been solved, to a certain extent, although they're always being stretched, given the scale of data, and its utility is becoming more and more massive, in particular with AI use cases being very prominent right now, the next level is how to actually make value from the data. How do I manage the full lifecycle of data in complex environments, with complex organizations, complex use cases? And having seen this from the inside, with Origami Logic, as we dealt with a lot of large corporations, and post-acquisition by Intuit, and a lot of the startups I'm involved with, it's clear that we're now onto that next step. And you have fundamental new paradigms, such as data mesh, that attempt to address that complexity, and responsibly scaling access, and democratizing access in the value monetization from data, across large organizations. You have a slew of startups that are evolving to help the entire lifecycle of data, from the data engineering side of it, to the data analytics side of it, to the AI use cases side of it. And it feels like the early days, to a certain extent, of the revolution that we've seen in transition from traditional databases, to data warehouses, to cloud-based data processing, and big data. It feels like we're at the genesis of that next wave. And it's super, super exciting, for me at least, as someone who's sitting more in the coach seat, rather than being on the pitch, and building startups, helping folks as they go through those motions. >> So that's awesome. I want to get into some of these data infrastructure dynamics you mentioned, but before that, talk to the audience around what you're working on now. You've been a successful entrepreneur, you're focused on angel investing, so, super-early seed stage. What kind of deals are you looking at? What's interesting to you? What is Sonoma Ventures looking for, and what are some of the entrepreneurial dynamics that you're seeing right now, from a startup standpoint? >> Cool, so, at a macro level, this is a little bit of background of my history, because it shapes very heavily what it is that I'm looking at. So, I've been very fortunate with entrepreneurial career. I founded three startups. All three of them are successful. Final two were sold, the first one merged and went public. And my third career has been about data, moving data, passing data, processing data, generating insights from it. And, at this phase, I wanted to really evolve from just going and building startup number four, from going through the same motions again. A 10 year adventure, I'm a little bit too old for that, I guess. But the next best thing is to sit from a point whereby I can be more elevated in where I'm dealing with, and broaden the variety of startups I'm focused on, rather than just do your own thing, and just go very, very deep into it. Now, what specifically am I focused on at Sonoma Ventures? So, basically, looking at what I refer to as a data-driven application stack. Anything from the low-level data infrastructure and cloud infrastructure, that helps any persona in the data universe maximize value for data, from their particular point of view, for their particular role, whether it's data analysts, data scientists, data engineers, cloud engineers, DevOps folks, et cetera. All the way up to the application layer, in applications that are very data-heavy. And what are very typical data-heavy applications? FinTech, cyber, Web3, revenue technologies, and product and DevOps. So these are the areas we're focused on. I have almost 23 or 24 startups in the portfolio that span all these different areas. And this is in terms of the aperture. Now, typically, focus on pre-seed, seed. Sometimes a little bit later stage, but this is the primary focus. And it's really about partnering with entrepreneurs, and helping them make, if you will, original mistakes, avoid the mistakes I made. >> Yeah. >> And take it to the next level, whatever the milestone they're driving with. So I'm very, very hands-on with many of those startups. Now, what is it that's happening right now, initially, and why is it so exciting? So, on one hand, you have this scaling of data and its complexity, yet lagging value creation from it, across those different personas we've touched on. So that's one fundamental opportunity which is secular. The other one, which is more a cyclic situation, is the fact that we're going through a down cycle in tech, as is very evident in the public markets, and everything we're hearing about funding going slower and lower, terms shifting more into the hands of typical VCs versus entrepreneur-friendly market, and so on and so forth. And a very significant amount of layoffs. Now, when you combine these two trends together, you're observing a very interesting thing, that a lot of folks, really bright folks, who have sold a startup to a company, or have been in the guts of the large startup, or a large corporation, have, hands-on, experienced all those challenges we've spoken about earlier, in turf, maximizing value from data, irrespective of their role, in a specific angle, or vantage point they have on those challenges. So, for many of them, it's an opportunity to, "Now, let me now start a startup. I've been laid off, maybe, or my company's stock isn't doing as well as it used to, as a large corporation. Now I have an opportunity to actually go and take my entrepreneurial passion, and apply it to a product and experience as part of this larger company." >> Yeah. >> And you see a slew of folks who are emerging with these great ideas. So it's a very, very exciting period of time to innovate. >> It's interesting, a lot of people look at, I mean, I look at Snowflake as an example of a company that refactored data warehouses. They just basically took data warehouse, and put it on the cloud, and called it a data cloud. That, to me, was compelling. They didn't pay any CapEx. They rode Amazon's wave there. So, a similar thing going on with data. You mentioned this, and I see it as an enabling opportunity. So whether it's cybersecurity, FinTech, whatever vertical, you have an enablement. Now, you mentioned data infrastructure. It's a super exciting area, as there's so many stacks emerging. We got an analytics stack, there's real-time stacks, there's data lakes, AI stack, foundational models. So, you're seeing an explosion of stacks, different tools probably will emerge. So, how do you look at that, as a seasoned entrepreneur, now investor? Is that a good thing? Is that just more of the market? 'Cause it just seems like more and more kind of decomposed stacks targeted at use cases seems to be a trend. >> Yeah. >> And how do you vet that, is it? >> So it's a great observation, and if you take a step back and look at the evolution of technology over the last 30 years, maybe longer, you always see these cycles of expansion, fragmentation, contraction, expansion, contraction. Go decentralize, go centralize, go decentralize, go centralize, as manifested in different types of technology paradigms. From client server, to storage, to microservices, to et cetera, et cetera. So I think we're going through another big bang, to a certain extent, whereby end up with more specialized data stacks for specific use cases, as you need performance, the data models, the tooling to best adapt to the particular task at hand, and the particular personas at hand. As the needs of the data analysts are quite different from the needs of an NL engineer, it's quite different from the needs of the data engineer. And what happens is, when you end up with these siloed stacks, you end up with new fragmentation, and new gaps that need to be filled with a new layer of innovation. And I suspect that, in part, that's what we're seeing right now, in terms of the next wave of data innovation. Whether it's in a service of FinTech use cases, or cyber use cases, or other, is a set of tools that end up having to try and stitch together those elements and bridge between them. So I see that as a fantastic gap to innovate around. I see, also, a fundamental need in creating a common data language, and common data management processes and governance across those different personas, because ultimately, the same underlying data these folks need, albeit in different mediums, different access models, different velocities, et cetera, the subject matter, if you will, the underlying raw data, and some of the taxonomies right on top of it, do need to be consistent. So, once again, a great opportunity to innovate, whether it's about semantic layers, whether it's about data mesh, whether it's about CICD tools for data engineers, and so on and so forth. >> I got to ask you, first of all, I see you have a friend you brought into the interview. You have a dog in the background who made a little cameo appearance. And that's awesome. Sitting right next to you, making sure everything's going well. On the AI thing, 'cause I think that's the hot trend here. >> Yeah. >> You're starting to see, that ChatGPT's got everyone excited, because it's kind of that first time you see kind of next-gen functionality, large-language models, where you can bring data in, and it integrates well. So, to me, I think, connecting the dots, this kind of speaks to the beginning of what will be a trend of really blending of data stacks together, or blending of models. And so, as more data modeling emerges, you start to have this AI stack kind of situation, where you have things out there that you can compose. It's almost very developer-friendly, conceptually. This is kind of new, but kind of the same concept's been working on with Google and others. How do you see this emerging, as an investor? What are some of the things that you're excited about, around the ChatGPT kind of things that's happening? 'Cause it brings it mainstream. Again, a million downloads, fastest applications get a million downloads, even among all the successes. So it's obviously hit a nerve. People are talking about it. What's your take on that? >> Yeah, so, I think that's a great point, and clearly, it feels like an iPhone moment, right, to the industry, in this case, AI, and lots of applications. And I think there's, at a high level, probably three different layers of innovation. One is on top of those platforms. What use cases can one bring to the table that would drive on top of a ChatGPT-like service? Whereby, the startup, the company, can bring some unique datasets to infuse and add value on top of it, by custom-focusing it and purpose-building it for a particular use case or particular vertical. Whether it's applying it to customer service, in a particular vertical, applying it to, I don't know, marketing content creation, and so on and so forth. That's one category. And I do know that, as one of my startups is in Y Combinator, this season, winter '23, they're saying that a very large chunk of the YC companies in this cycle are about GPT use cases. So we'll see a flurry of that. The next layer, the one below that, is those who actually provide those platforms, whether it's ChatGPT, whatever will emerge from the partnership with Microsoft, and any competitive players that emerge from other startups, or from the big cloud providers, whether it's Facebook, if they ever get into this, and Google, which clearly will, as they need to, to survive around search. The third layer is the enabling layer. As you're going to have more and more of those different large-language models and use case running on top of it, the underlying layers, all the way down to cloud infrastructure, the data infrastructure, and the entire set of tools and systems, that take raw data, and massage it into useful, labeled, contextualized features and data to feed the models, the AI models, whether it's during training, or during inference stages, in production. Personally, my focus is more on the infrastructure than on the application use cases. And I believe that there's going to be a massive amount of innovation opportunity around that, to reach cost-effective, quality, fair models that are deployed easily and maintained easily, or at least with as little pain as possible, at scale. So there are startups that are dealing with it, in various areas. Some are about focusing on labeling automation, some about fairness, about, speaking about cyber, protecting models from threats through data and other issues with it, and so on and so forth. And I believe that this will be, too, a big driver for massive innovation, the infrastructure layer. >> Awesome, and I love how you mentioned the iPhone moment. I call it the browser moment, 'cause it felt that way for me, personally. >> Yep. >> But I think, from a business model standpoint, there is that iPhone shift. It's not the BlackBerry. It's a whole 'nother thing. And I like that. But I do have to ask you, because this is interesting. You mentioned iPhone. iPhone's mostly proprietary. So, in these machine learning foundational models, >> Yeah. >> you're starting to see proprietary hardware, bolt-on, acceleration, bundled together, for faster uptake. And now you got open source emerging, as two things. It's almost iPhone-Android situation happening. >> Yeah. >> So what's your view on that? Because there's pros and cons for either one. You're seeing a lot of these machine learning laws are very proprietary, but they work, and do you care, right? >> Yeah. >> And then you got open source, which is like, "Okay, let's get some upsource code, and let people verify it, and then build with that." Is it a balance? >> Yes, I think- >> Is it mutually exclusive? What's your view? >> I think it's going to be, markets will drive the proportion of both, and I think, for a certain use case, you'll end up with more proprietary offerings. With certain use cases, I guess the fundamental infrastructure for ChatGPT-like, let's say, large-language models and all the use cases running on top of it, that's likely going to be more platform-oriented and open source, and will allow innovation. Think of it as the equivalent of iPhone apps or Android apps running on top of those platforms, as in AI apps. So we'll have a lot of that. Now, when you start going a little bit more into the guts, the lower layers, then it's clear that, for performance reasons, in particular, for certain use cases, we'll end up with more proprietary offerings, whether it's advanced silicon, such as some of the silicon that emerged from entrepreneurs who have left Google, around TensorFlow, and all the silicon that powers that. You'll see a lot of innovation in that area as well. It hopefully intends to improve the cost efficiency of running large AI-oriented workloads, both in inference and in learning stages. >> I got to ask you, because this has come up a lot around Azure and Microsoft. Microsoft, pretty good move getting into the ChatGPT >> Yep. >> and the open AI, because I was talking to someone who's a hardcore Amazon developer, and they said, they swore they would never use Azure, right? One of those types. And they're spinning up Azure servers to get access to the API. So, the developers are flocking, as you mentioned. The YC class is all doing large data things, because you can now program with data, which is amazing, which is amazing. So, what's your take on, I know you got to be kind of neutral 'cause you're an investor, but you got, Amazon has to respond, Google, essentially, did all the work, so they have to have a solution. So, I'm expecting Google to have something very compelling, but Microsoft, right now, is going to just, might run the table on developers, this new wave of data developers. What's your take on the cloud responses to this? What's Amazon, what do you think AWS is going to do? What should Google be doing? What's your take? >> So, each of them is coming from a slightly different angle, of course. I'll say, Google, I think, has massive assets in the AI space, and their underlying cloud platform, I think, has been designed to support such complicated workloads, but they have yet to go as far as opening it up the same way ChatGPT is now in that Microsoft partnership, and Azure. Good question regarding Amazon. AWS has had a significant investment in AI-related infrastructure. Seeing it through my startups, through other lens as well. How will they respond to that higher layer, above and beyond the low level, if you will, AI-enabling apparatuses? How do they elevate to at least one or two layers above, and get to the same ChatGPT layer, good question. Is there an acquisition that will make sense for them to accelerate it, maybe. Is there an in-house development that they can reapply from a different domain towards that, possibly. But I do suspect we'll end up with acquisitions as the arms race around the next level of cloud wars emerges, and it's going to be no longer just about the basic tooling for basic cloud-based applications, and the infrastructure, and the cost management, but rather, faster time to deliver AI in data-heavy applications. Once again, each one of those cloud suppliers, their vendor is coming with different assets, and different pros and cons. All of them will need to just elevate the level of the fight, if you will, in this case, to the AI layer. >> It's going to be very interesting, the different stacks on the data infrastructure, like I mentioned, analytics, data lake, AI, all happening. It's going to be interesting to see how this turns into this AI cloud, like data clouds, data operating systems. So, super fascinating area. Opher, thank you for coming on and sharing your expertise with us. Great to see you, and congratulations on the work. I'll give you the final word here. Give a plugin for what you're looking for for startup seats, pre-seeds. What's the kind of profile that gets your attention, from a seed, pre-seed candidate or entrepreneur? >> Cool, first of all, it's my pleasure. Enjoy our chats, as always. Hopefully the next one's not going to be in nine years. As to what I'm looking for, ideally, smart data entrepreneurs, who have come from a particular domain problem, or problem domain, that they understand, they felt it in their own 10 fingers, or millions of neurons in their brains, and they figured out a way to solve it. Whether it's a data infrastructure play, a cloud infrastructure play, or a very, very smart application that takes advantage of data at scale. These are the things I'm looking for. >> One final, final question I have to ask you, because you're a seasoned entrepreneur, and now coach. What's different about the current entrepreneurial environment right now, vis-a-vis, the past decade? What's new? Is it different, highly accelerated? What advice do you give entrepreneurs out there who are putting together their plan? Obviously, a global resource pool now of engineering. It might not be yesterday's formula for success to putting a venture together to get to that product-market fit. What's new and different, and what's your advice to the folks out there about what's different about the current environment for being an entrepreneur? >> Fantastic, so I think it's a great question. So I think there's a few axes of difference, compared to, let's say, five years ago, 10 years ago, 15 years ago. First and foremost, given the amount of infrastructure out there, the amount of open-source technologies, amount of developer toolkits and frameworks, trying to develop an application, at least at the application layer, is much faster than ever. So, it's faster and cheaper, to the most part, unless you're building very fundamental, core, deep tech, where you still have a big technology challenge to deal with. And absent that, the challenge shifts more to how do you manage my resources, to product-market fit, how are you integrating the GTM lens, the go-to-market lens, as early as possible in the product-market fit cycle, such that you reach from pre-seed to seed, from seed to A, from A to B, with an optimal amount of velocity, and a minimal amount of resources. One big difference, specifically as of, let's say, beginning of this year, late last year, is that money is no longer free for entrepreneurs, which means that you need to operate and build startup in an environment with a lot more constraints. And in my mind, some of the best startups that have ever been built, and some of the big market-changing, generational-changing, if you will, technology startups, in their respective industry verticals, have actually emerged from these times. And these tend to be the smartest, best startups that emerge because they operate with a lot less money. Money is not as available for them, which means that they need to make tough decisions, and make verticals every day. What you don't need to do, you can kick the cow down the road. When you have plenty of money, and it cushions for a lot of mistakes, you don't have that cushion. And hopefully we'll end up with companies with a more agile, more, if you will, resilience, and better cultures in making those tough decisions that startups need to make every day. Which is why I'm super, super excited to see the next batch of amazing unicorns, true unicorns, not just valuation, market rising with the water type unicorns that emerged from this particular era, which we're in the beginning of. And very much enjoy working with entrepreneurs during this difficult time, the times we're in. >> The next 24 months will be the next wave, like you said, best time to do a company. Remember, Airbnb's pitch was, "We'll rent cots in apartments, and sell cereal." Boy, a lot of people passed on that deal, in that last down market, that turned out to be a game-changer. So the crazy ideas might not be that bad. So it's all about the entrepreneurs, and >> 100%. >> this is a big wave, and it's certainly happening. Opher, thank you for sharing. Obviously, data is going to change all the markets. Refactoring, security, FinTech, user experience, applications are going to be changed by data, data operating system. Thanks for coming on, and thanks for sharing. Appreciate it. >> My pleasure. Have a good one. >> Okay, more coverage for the CloudNativeSecurityCon inaugural event. Data will be the key for cybersecurity. theCUBE's coverage continues after this break. (uplifting music)