>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. Okay, >>we're now going to explore the vision of the future of cloud computing From the perspective of one of the leaders in the field, J G >>Share >>a pure off is the vice president of As Your Data ai and Edge at Microsoft G. Welcome to the Cuban cloud. Thanks so much for participating. >>Well, thank you, Dave, and it's a real pleasure to be here with you. And I just wanna welcome the audience as well. >>Well, jg judging from your title, we have a lot of ground to cover, and our audience is definitely interested in all the topics that are implied there. So let's get right into it. You know, we've said many times in the Cube that the new innovation cocktail comprises machine intelligence or a I applied to troves of data. With the scale of the cloud. It's it's no longer, you know, we're driven by Moore's law. It's really those three factors, and those ingredients are gonna power the next wave of value creation and the economy. So, first, do you buy into that premise? >>Yes, absolutely. we do buy into it. And I think, you know, one of the reasons why we put Data Analytics and Ai together is because all of that really begins with the collection of data and managing it and governing it, unlocking analytics in it. And we tend to see things like AI, the value creation that comes from a I as being on that continues off, having started off with really things like analytics and proceeding toe. You know, machine learning and the use of data. Interesting breaks. Yes. >>I'd like to get some more thoughts around a data and how you see the future data and the role of cloud and maybe how >>Microsoft, you >>know, strategy fits in there. I mean, you, your portfolio, you got you got sequel server, Azure, Azure sequel. You got arc, which is kinda azure everywhere for people that aren't familiar with that. You've got synapse. Which course that's all the integration a data warehouse, and get things ready for B I and consumption by the business and and the whole data pipeline and a lot of other services as your data bricks you got You got cosmos in their, uh, Blockchain. You've got open source services like Post Dress and my sequel. So lots of choices there. And I'm wondering, you know, how do you think about the future of Of of Cloud data platforms? It looks like your strategies, right tool for the right job? Is that fair? >>It is fair, but it's also just to step back and look at it. It's fundamentally what we see in this market today is that customer was the Sikh really a comprehensive proposition? And when I say a comprehensive proposition, it is sometimes not just about saying that. Hey, listen way No, you're a sequel server company. We absolutely trust that you have the best Azure sequel database in the cloud, but tell us more. We've got data that's sitting in her group systems. We've got data that's sitting in Post Press in things like mongo DB, right? So that open source proposition today and data and data management and database management has become front and center, so are really sort of push. There is when it comes to migration management, modernization of data to present the broadest possible choice to our customers so we can meet them where they are. However, when it comes to analytics. One of the things they asked for is give us a lot more convergence use. You know it, really, it isn't about having 50 different services. It's really about having that one comprehensive service that is converged. That's where things like synapse Fitzer, where in just land any kind of data in the leg and then use any compute engine on top of it to drive insights from it. So, fundamentally, you know, it is that flexibility that we really sort of focus on to meet our customers where they are and really not pushing our dogma and our beliefs on it. But to meet our customers according to the way they have deployed stuff like this. >>So that's great. I want to stick on this for a minute because, you know, I know when when I have guests on like yourself, do you never want to talk about you know, the competition? But that's all we ever talk about. That's all your customers ever talk about, because because the counter to that right tool for the right job and that I would say, is really kind of Amazon's approach is is that you got the single unified data platform, the mega database that does it all. And that's kind of Oracle's approach. It sounds like you wanna have your cake and eat it, too, so you you got the right tool for the right job approach. But you've got an integration layer that allows you to have that converge database. I wonder if you could add color to that and you confirm or deny what I just said. >>No, that's a That's a very fair observation, but I I say there's a nuance in what I sort of describe when it comes to data management. When it comes to APS, we have them customers with the broadest choice. Even in that, even in that perspective, we also offer convergence. So, case in point, when you think about Cosmos TV under that one sort of service, you get multiple engines, but with the same properties, right global distribution, the five nines availability. It gives customers the ability to basically choose when they have to build that new cloud native AB toe, adopt cosmos Davey and adopted in a way that it's and choose an engine that is most flexible. Tow them, however you know when it comes to say, you know, writing a sequel server, for example from organizing it you know you want. Sometimes you just want to lift and shift it into things. Like I asked In other cases, you want to completely rewrite it, so you need to have the flexibility of choice there that is presented by a legacy off What's its on premises? When it moved into things like analytics, we absolutely believe in convergence, right? So we don't believe that look, you need to have a relation of data warehouse that is separate from a loop system that is separate from, say, a B I system. That is just, you know, it's a bolt on for us. We love the proposition off, really building things that are so integrated that once you land data, once you prep it inside the lake, you can use it for analytics. You can use it for being. You can use it for machine learning. So I think you know, are sort of differentiated. Approach speaks for itself there. Well, >>that's that's interesting, because essentially, again, you're not saying it's an either or, and you're seeing a lot of that in the marketplace. You got some companies say no, it's the Data Lake and others saying No, no put in the data warehouse and that causes confusion and complexity around the data pipeline and a lot of calls. And I'd love to get your thoughts on this. Ah, lot of customers struggled to get value out of data and and specifically data product builders of frustrated that it takes too long to go from. You know, this idea of Hey, I have an idea for a data service and it could drive monetization, but to get there, you gotta go through this complex data lifecycle on pipeline and beg people to add new data sources. And do you do you feel like we have to rethink the way that we approach data architectures? >>Look, I think we do in the cloud, and I think what's happening today and I think the place where I see the most amount of rethink the most amount of push from our customers to really rethink is the area of analytics in a I. It's almost as if what worked in the past will not work going forward. Right? So when you think about analytics on in the Enterprise today, you have relational systems, you have produced systems. You've got data marts. You've got data warehouses. You've got enterprise data warehouses. You know, those large honking databases that you use, uh, to close your books with right? But when you start to modernize it, what deep you are saying is that we don't want to simply take all of that complexity that we've built over say, you know, 34 decades and simply migrated on mass exactly as they are into the cloud. What they really want is a completely different way of looking at things. And I think this is where services like synapse completely provide a differentiated proposition to our customers. What we say there is land the data in any way you see shape or form inside the lake. Once you landed inside the lake, you can essentially use a synapse studio toe. Prep it in the way that you like, use any compute engine of your choice and and operate on this data in any way that you see fit. So, case in point, if you want to hydrate relation all data warehouse, you can do so if you want to do ad hoc analytics using something like spark. You can do so if you want to invoke power. Bi I on that data or b i on that data you can do so if you want to bring in a machine learning model on this breath data you can do so, so inherently. So when customers buy into this proposition, what it solves for them and what it gives them is complete simplicity, right? One way to land the data, multiple ways to use it. And it's all eso. >>Should we think of synapse as an abstraction layer that abstracts away the complexity of the underlying technology? Is that a fair way toe? Think about it. >>Yeah, you can think of it that way. It abstracts away, Dave a couple of things. It takes away the type of data, you know, sort of the complexities related to the type of data. It takes away the complexity related to the size of data. It takes away the complexity related to creating pipelines around all these different types of data and fundamentally puts it in a place where it can be now consumed by any sort of entity inside the actual proposition. And by that token, even data breaks. You know, you can, in fact, use data breaks in in sort off an integrated way with a synapse, Right, >>Well, so that leads me to this notion of and then wonder if you buy into it s Oh, my inference is that a data warehouse or a data lake >>could >>just be a node in inside of a global data >>mesh on. >>Then it's synapses sort of managing, uh, that technology on top. Do you buy into that that global data mesh concept >>we do. And we actually do see our customers using synapse and the value proposition that it brings together in that way. Now it's not where they start. Often times when a customer comes and says, Look, I've got an enterprise data warehouse, I want to migrate it or I have a group system. I want to migrate it. But from there, the evolution is absolutely interesting to see. I give you an example. You know, one of the customers that we're very proud off his FedEx And what FedEx is doing is it's completely reimagining its's logistics system that basically the system that delivers What is it? The three million packages a day on in doing so in this covert times, with the view of basically delivering our covert vaccines. One of the ways they're doing it is basically using synapse. Synapse is essentially that analytic hub where they can get complete view into their logistic processes. Way things are moving, understand things like delays and really put all that together in a way that they can essentially get our packages and these vaccines delivered as quickly as possible. Another example, you know, is one of my favorite, uh, we see once customers buy into it, they essentially can do other things with it. So an example of this is, uh is really my favorite story is Peace Parks Initiative. It is the premier Air White Rhino Conservancy in the world. They essentially are using data that has landed in azure images in particular. So, basically, you know, use drones over the vast area that they patrol and use machine learning on this data to really figure out where is an issue and where there isn't an issue so that this part with about 200 rangers can scramble surgically versus having to read range across the last area that they cover. So What do you see here is you know, the importance is really getting your data in order. Landed consistently. Whatever the kind of data ideas build the right pipelines and then the possibilities of transformation are just endless. >>Yeah, that's very nice how you worked in some of the customer examples. I appreciate that. I wanna ask you, though, that that some people might say that putting in that layer while it clearly adds simplification and e think a great thing that they're begins over time to be be a gap, if you will, between the ability of that layer to integrate all the primitives and all the peace parts on that, that you lose some of that fine grain control and it slows you down. What would you say to that? >>Look, I think that's what we excel at, and that's what we completely sort of buy into on. It's our job to basically provide that level off integration that granularity in the way that so it's an art, absolutely admit it's an art. There are areas where people create simplicity and not a lot of you know, sort of knobs and dials and things like that. But there are areas where customers want flexibility, right? So I think just to give you an example of both of them in landing the data inconsistency in building pipelines, they want simplicity. They don't want complexity. They don't want 50 different places to do this. Just 100 to do it. When it comes to computing and reducing this data analyzing this data, they want flexibility. This is one of the reasons why we say, Hey, listen, you want to use data breaks? If you're you're buying into that proposition and you're absolutely happy with them, you can plug plug it into it. You want to use B I and no, essentially do a small data mart. You can use B I If you say that. Look, I've landed in the lake. I really only want to use em melt, bringing your animal models and party on. So that's where the flexibility comes in. So that's sort of really sort of think about it. Well, >>I like the strategy because, you know, my one of our guest, Jim Octagon, e E. I think one of the foremost thinkers on this notion of off the data mesh and her premises that that that data builders, data product and service builders air frustrated because the the big data system is generic to context. There's no context in there. But by having context in the big data architecture and system, you could get products to market much, much, much faster. So but that seems to be your philosophy. But I'm gonna jump ahead to do my ecosystem question. You've mentioned data breaks a couple of times. There's another partner that you have, which is snowflake. They're kind of trying to build out their own, uh, data cloud, if you will, on global mesh in and the one hand, their partner. On the other hand, there are competitors. How do you sort of balance and square that circle? >>Look, when I see snowflake, I actually see a partner. You know that when we essentially you know, we are. When you think about as you know, this is where I sort of step back and look at Azure as a whole and in azure as a whole. Companies like snowflakes are vital in our ecosystem, right? I mean, there are places we compete, but you know, effectively by helping them build the best snowflake service on Asia. We essentially are able toe, you know, differentiate and offer a differentiated value proposition compared to, say, a Google or on AWS. In fact, that's being our approach with data breaks as well, where you know they are effectively on multiple club, and our opportunity with data breaks is toe essentially integrate them in a way where we offer the best experience. The best integrations on Azure Barna That's always been a focus. >>That's hard to argue with. Strategy. Our data with our data partner eat er, shows Microsoft is both pervasive and impressively having a lot of momentum spending velocity within the budget cycles. I wanna come back thio ai a little bit. It's obviously one of the fastest growing areas in our in our survey data. As I said, clearly, Microsoft is a leader in this space. What's your what's your vision of the future of machine intelligence and how Microsoft will will participate in that opportunity? >>Yeah, so fundamentally, you know, we've built on decades of research around, you know, around, you know, essentially, you know, vision, speech and language that's being the three core building blocks and for the for a really focused period of time we focused on essentially ensuring human parody. So if you ever wondered what the keys to the kingdom are it, czar, it's the most we built in ensuring that the research posture that we've taken there, what we then done is essentially a couple of things we focused on, essentially looking at the spectrum. That is a I both from saying that, Hollis and you know it's gotta work for data. Analysts were looking toe basically use machine learning techniques, toe developers who are essentially, you know, coding and building a machine learning models from scratch. So for that select proposition manifesto us, as you know, really a. I focused on all skill levels. The other court thing we've done is that we've also said, Look, it will only work as long as people trust their data and they can trust their AI models. So there's a tremendous body of work and research we do in things like responsibility. So if you ask me where we sort of push on is fundamentally to make sure that we never lose sight of the fact that the spectrum off a I, and you can sort of come together for any skill level, and we keep that responsibly. I proposition. Absolutely strong now against that canvas, Dave. I'll also tell you that you know, as edge devices get way more capable, right where they can input on the edge, see a camera or a mike or something like that, you will see us pushing a lot more of that capability onto the edge as well. But to me, that's sort of a modality. But the core really is all skill levels and that responsible denia. >>Yeah, So that that brings me to this notion of wanna bring an edge and and hybrid cloud Understand how you're thinking about hybrid cloud multi cloud. Obviously one of your competitors, Amazon won't even say the word multi cloud you guys have, Ah, you know, different approach there. But what's the strategy with regard? Toe, toe hybrid. You know, Do you see the cloud you bringing azure to the edge? Maybe you could talk about that and talk about how you're different from the competition. >>Yeah, I think in the edge from Annette, you know, I live in I'll be the first one to say that the word nge itself is conflated. Okay, It's, uh but I will tell you, just focusing on hybrid. This is one of the places where you know I would say the 2020 if I would have looked back from a corporate perspective. In particular, it has Bean the most informative because we absolutely saw customers digitizing moving to the cloud. And we really saw hybrid in action. 2020 was the year that hybrid sort of really became really from a cloud computing perspective and an example of this is we understood it's not all or nothing. So sometimes customers want azure consistency in their data centers. This is where things like Azure stack comes in. Sometimes they basically come to us and say, We want the flexibility of adopting flexible pattern, you know, platforms like, say, containers orchestra, Cuban Pettis, so that we can essentially deployed wherever you want. And so when we design things like art, it was built for that flexibility in mind. So here is the beauty of what's something like our can do for you. If you have a kubernetes endpoint anywhere we can deploy and as your service onto it, that is the promise, which means if for some reason, the customer says that. Hey, I've got this kubernetes endpoint in AWS and I love as your sequel. You will be able to run as your sequel inside AWS. There's nothing that stops you from doing it so inherently you remember. Our first principle is always to meet our customers where they are. So from that perspective, multi cloud is here to stay. You know, we're never going to be the people that says, I'm sorry, we will never see a But it is a reality for our customers. >>So I wonder if we could close. Thank you for that by looking, looking back and then and then ahead. And I wanna e wanna put forth. Maybe it's, Ah criticism, but maybe not. Maybe it's an art of Microsoft, but But first you know, you get Microsoft an incredible job of transitioning. It's business as your nominee president Azzawi said. Our data shows that so two part question First, Microsoft got there by investing in the cloud, really changing its mind set, I think, in leveraging its huge software state and customer base to put Azure at the center of its strategy, and many have said me included that you got there by creating products that air Good enough. You know, we do a 1.0, it's not that great. And the two Dato, and maybe not the best, but acceptable for your customers. And that's allowed you to grow very rapidly expanding market. >>How >>do you respond to that? Is that is that a fair comment? Ume or than good enough? I wonder if you could share your >>thoughts, gave you? You hurt my feelings with that question. I don't hate me, g getting >>it out there. >>So there was. First of all, thank you for asking me that. You know, I am absolutely the biggest cheerleader. You'll find a Microsoft. I absolutely believe you know that I represent the work off almost 9000 engineers and we wake up every day worrying about our customer and worrying about the customer condition and toe. Absolutely. Make sure we deliver the best in the first time that we do. So when you take the platter off products we've delivered in nausea, be it as your sequel, be it as your cosmos TV synapse as your data breaks, which we did in partnership with data breaks, a za machine learning and recently when we prevail, we sort off, you know, sort of offered the world's first comprehensive data government solution in azure purview. I would humbly submit to you that we're leading the way and we're essentially showing how the future off data ai and the actual work in the cloud. >>I'd be disappointed if you if you had If you didn't, if you capitulated in any way J g So so thank you for that. And the kind of last question is, is looking forward and how you're thinking about the future of cloud last decade. A lot about your cloud migration simplifying infrastructure management, deployment SAS if eyeing my enterprise, lot of simplification and cost savings. And, of course, the redeployment of resource is toward digital transformation. Other other other valuable activities. How >>do >>you think this coming decade will will be defined? Will it be sort of more of the same? Or is there Is there something else out there? >>I think I think that the coming decade will be one where customers start one law outside value out of this. You know what happened in the last decade when people leave the foundation and people essentially looked at the world and said, Look, we've got to make the move, you know, the largely hybrid, but we're going to start making steps to basically digitize and modernize our platforms. I would tell you that with the amount of data that people are moving to the cloud just as an example, you're going to see use of analytics ai for business outcomes explode. You're also going to see a huge sort of focus on things like governance. You know, people need to know where the data is, what the data catalog continues, how to govern it, how to trust this data and given all other privacy and compliance regulations out there. Essentially, they're complying this posture. So I think the unlocking of outcomes versus simply Hey, I've saved money Second, really putting this comprehensive sort off, you know, governance, regime in place. And then, finally, security and trust. It's going to be more paramount than ever before. Yeah, >>nobody's gonna use the data if they don't trust it. I'm glad you brought up your security. It's It's a topic that hits number one on the CEO list. J G. Great conversation. Obviously the strategy is working, and thanks so much for participating in Cuba on cloud. >>Thank you. Thank you, David. I appreciate it and thank you to. Everybody was tuning in today. >>All right? And keep it right there. I'll be back with our next guest right after this short break.

>> From San Francisco, it's the Cube, covering Girls In Tech Catalyst Conference. Brought to you by Girls in Tech. >> Hey welcome back everybody, Jeff Frick here with the Cube. We're at the Girls In Tech Catalyst event in downtown San Francisco about 700 people coming together, mainly women, two day single track event, where people are getting up and giving like 15-, 20-minute overviews of their story. Really sharing insights and how they got to where they were. Most of them had no idea that they were going to end up where they are now. So there's really a lot of great stories. And we're excited to be back for our second time. And our next guest we're excited to have is Lawdan Shojaee and she is the CEO of Axosoft, Lawdan welcome. >> Thank you, thanks for having me. >> So, what is Axosoft for people who aren't familiar? >> Axosoft builds tools for developers, mainly product management tool, a gate goi, a issue tracker. >> Okay. >> Yeah. >> And then, how long have you have you been involved with Girls In Tech? >> With Girls In Tech, about five years. We were the top sponsor and brought the Catalyst Conference to Phoenix when the first year they had it and this was back in I think five years ago. That's when I got involved with the board and loved the mission and couldn't stop. >> Awesome. >> I wanted to be involved in every way I could. >> Yeah, so we were there is Phoenix in 2016, I guess so a couple years ago. >> Okay, okay. >> So that's great. So it's such an important organization. What do you see some of the benefits, how are you guys really participating and helping take the advantages beyond the participation events? >> So I'll go just for today, right. And some of the things that I've listened to just this morning, just talking and re-familiarizing yourself with how important culture is. If you don't create a space for females in your corporation, they don't belong. So by creating spaces where they belong, then you automatically help them have voice. And the sessions today have all talked around that and I really am excited that I brought one of my employees with me here too. So she's definitely learning that and together we're going to take it back to the company, so. >> No I'm just curious how old is she in terms of... is she kind of young-- >> I think she's 27. >> and getting started in her career or (mumbles)? >> No, no she's 27 and she's a director of her departments. She the marketing director. >> That's great. Yeah, it's so important to have role models. And that's the other thing that keeps coming up over and over and over again. You know, they need to have the young girls. Young women need to have, >> Yeah. >> like looking people, women, >> Right. >> in women in senior executive positions, so they can envision themselves going there. >> Yes. >> So I know one of your passions is basically, obviously, your business is built around development and coding. >> It is. But having people have the knowledge, girls specifically, get some basic overview-- >> Yes. >> of what is coding, what is software development. So it's not this mysterious, this mysterious thing that's out there in the ether. >> Right. >> I know that's something that you've been putting a lot of time in. >> So here's how I view our education program right now. What we do with our kids is we put them in there, and we say go. And we educate them on how to become industrial workers. In the future, is everything software. All companies, if they're going to stick around, somehow are going to be software. From the person you get your sandwich from at a fast food place to everywhere else. So we're sending these kids to school. They're going and learning how to become industrial workers. We never introduce them to programming at all until they hit college. And then we say, pick a career path. How do they even know that they want to go into programming if during high school, or lower years, they haven't touched it. >> Right. >> And as we heard it, one of the other speakers yesterday say, she wanted to be an actor and singer and on a whim she took a computer science class, fell in love with it and she's the VP of Engineering at Birchbox now. So, on a whim. >> Even though she had lots of examples to look at on the music and entertainment side. >> Yeah she went into the other side. You know she just tried one class and from there, >> Right. >> you know, she fell in love. If you don't know what it is, if you're intimidated by it, then you don't try it and I think that waiting until college when it's career time, it's too late. You got to introduce kids to it earlier. >> So there's a lot of things are trying to help, that obviously, changing the public school system is not easy and we were talking offline about what Brenda Darden Wilkerson has done in Chicago with part of the school district there, getting basic CS, >> Yup. >> into the program. But it's really not easy. >> It's not. It's very grassroots, so my company's based out of Scottsdale, Arizona and our state is not doing very much as far as putting computer science into the schools. And, which means in 10 years, when I'm trying to look for developers, I'm not going to have enough. Not only am I not going to have enough developers period, I'm not going to have enough diverse developers, right, because, we're not even introducing it to girls at all. So a few years ago, actually in combination with Girls In Tech, I put a campaign together called, "It Was Never A Dress." With "It Was Never A Dress", we started a program where we took 15 to 16 year olds, sometimes 18 and we taught them programming. And we turned them into Ambassadors of anything STEAM. And we took 50, put 'em back into the public schools and they're now actually now creating their own clubs with sponsors in their own schools and we taught them skills like how to fundraise with, ya know, Go Fund Me-- >> Right, right. >> to come up with this and there's actually working. I mean it was very grassroots, it was very small. >> And how old were they, when you grabbed 'em? >> So our youngest was probably 12. >> Okay. And the way we found them was we went to the schools and we said, who's your smartest, ambitious, who do you think is motivated, who wants to do something different, send them to our conference. And we took 'em for two days. We taught 'em programming, basic programming. We taught 'em, wearable technology and we made sure that they were in different districts, sent them back into the school system. (Jeff laughs) >> That's great. >> Grassroots right? >> That's the way to see it. >> A little guerrilla-style. >> Right, right, right. Well, ya know, we see that more and more. Like I know LinkedIn does-- >> Yeah. >> weekend Hackathons all the time. So there is kind of the grassroot corporate effort from people who that are paying attention. >> Yup. >> And do the investment, but as you said the schools are lagging way behind on the CS (mumbles). >> They are, they are, but ya know, I feel like if each company took a small amount of time and created little grassroots movements, we could make a pretty large impact. We're not organized right, because you know, someone's doing it in San Francisco, someone's doing it in Arizona. If we kind of got together as just major corporations and said, let's do this, let's just... Because tomorrow we have to hire these people and if there's enough then we can't have the equality we want if we're not teaching girls early enough, then maybe we can make a difference. >> So I'd just love to get your perspective since you've been involved in Girls In Tech so long is trying to be one of the catalysts for that type of, you know, activity cross. >> Yup. >> Not only cross-state, but cross-country and around the world about the growth of this organization and how Adriana has taken it from... >> Yeah. >> I mean how big was it when you joined five years ago to where it is today? >> I mean the growth in numbers, I can't tell you what those are. But I can tell you the impact is huge. Every year I'm part of the Girls In Tech events and corporate boards. Seeing the impact and the feelings that it leaves for these woman is amazing. You now can talk internationally to woman and they know what Girls In Tech is, and they're familiar. And they're taking the Hackathons, they're taking the programs that this organization offers and they're learning and their getting jobs. And now I've been in it long enough where someone I met a couple years ago, who was just at a conference, kind of dabbling, took a course from Girls In Tech and is now in the career field, and they're kind of introducing Girls In Tech to others. So it's amazing. It's no longer grassroots. This is actually making a difference. >> Right, that's great. Well Lawdan, thanks for taking a few minutes. >> Thank you. >> And thanks for your longterm support of the organization, clearly you're not the only sponsor anymore and there's a lot of people-- >> Yes. >> that have jumped onto the bandwagon and that's all a good thing. >> Thank you. >> You're welcome. >> You have a great day. >> You too. (laughs) Alright, she's Lawdan and I'm Jeff. You're watching the Cube. We're Girls In Tech Catalyst 2018 in downtown San Francisco. Thanks for watching. (upbeat music)

>> From San Francisco, it's the Cube, covering Girls In Tech Catalyst Conference. Brought to you by Girls in Tech. >> Hey welcome back everybody, Jeff Frick here with the Cube. We're at the Girls In Tech Catalyst event in downtown San Francisco about 700 people coming together, mainly women, two day single track event, where people are getting up and giving like 15-, 20-minute overviews of their story. Really sharing insights and how they got to where they were. Most of them had no idea that they were going to end up where they are now. So there's really a lot of great stories. And we're excited to be back for our second time. And our next guest we're excited to have is Lawdan Shojaee and she is the CEO of Axosoft, Lawdan welcome. >> Thank you, thanks for having me. >> So, what is Axosoft for people who aren't familiar? >> Axosoft builds tools for developers, mainly product management tool, a gate goi, a issue tracker. >> Okay. >> Yeah. >> And then, how long have you have you been involved with Girls In Tech? >> With Girls In Tech, about five years. We were the top sponsor and brought the Catalyst Conference to Phoenix when the first year they had it and this was back in I think five years ago. That's when I got involved with the board and loved the mission and couldn't stop. >> Awesome. >> I wanted to be involved in every way I could. >> Yeah, so we were there is Phoenix in 2016, I guess so a couple years ago. >> Okay, okay. >> So that's great. So it's such an important organization. What do you see some of the benefits, how are you guys really participating and helping take the advantages beyond the participation events? >> So I'll go just for today, right. And some of the things that I've listened to just this morning, just talking and re-familiarizing yourself with how important culture is. If you don't create a space for females in your corporation, they don't belong. So by creating spaces where they belong, then you automatically help them have voice. And the sessions today have all talked around that and I really am excited that I brought one of my employees with me here too. So she's definitely learning that and together we're going to take it back to the company, so. >> No I'm just curious how old is she in terms of... is she kind of young-- >> I think she's 27. >> and getting started in her career or (mumbles)? >> No, no she's 27 and she's a director of her departments. She the marketing director. >> That's great. Yeah, it's so important to have role models. And that's the other thing that keeps coming up over and over and over again. You know, they need to have the young girls. Young women need to have, >> Yeah. >> like looking people, women, >> Right. >> in women in senior executive positions, so they can envision themselves going there. >> Yes. >> So I know one of your passions is basically, obviously, your business is built around development and coding. >> It is. But having people have the knowledge, girls specifically, get some basic overview-- >> Yes. >> of what is coding, what is software development. So it's not this mysterious, this mysterious thing that's out there in the ether. >> Right. >> I know that's something that you've been putting a lot of time in. >> So here's how I view our education program right now. What we do with our kids is we put them in there, and we say go. And we educate them on how to become industrial workers. In the future, is everything software. All companies, if they're going to stick around, somehow are going to be software. From the person you get your sandwich from at a fast food place to everywhere else. So we're sending these kids to school. They're going and learning how to become industrial workers. We never introduce them to programming at all until they hit college. And then we say, pick a career path. How do they even know that they want to go into programming if during high school, or lower years, they haven't touched it. >> Right. >> And as we heard it, one of the other speakers yesterday say, she wanted to be an actor and singer and on a whim she took a computer science class, fell in love with it and she's the VP of Engineering at Birchbox now. So, on a whim. >> Even though she had lots of examples to look at on the music and entertainment side. >> Yeah she went into the other side. You know she just tried one class and from there, >> Right. >> you know, she fell in love. If you don't know what it is, if you're intimidated by it, then you don't try it and I think that waiting until college when it's career time, it's too late. You got to introduce kids to it earlier. >> So there's a lot of things are trying to help, that obviously, changing the public school system is not easy and we were talking offline about what Brenda Darden Wilkerson has done in Chicago with part of the school district there, getting basic CS, >> Yup. >> into the program. But it's really not easy. >> It's not. It's very grassroots, so my company's based out of Scottsdale, Arizona and our state is not doing very much as far as putting computer science into the schools. And, which means in 10 years, when I'm trying to look for developers, I'm not going to have enough. Not only am I not going to have enough developers period, I'm not going to have enough diverse developers, right, because, we're not even introducing it to girls at all. So a few years ago, actually in combination with Girls In Tech, I put a campaign together called, "It Was Never A Dress." With "It Was Never A Dress", we started a program where we took 15 to 16 year olds, sometimes 18 and we taught them programming. And we turned them into Ambassadors of anything STEAM. And we took 50, put 'em back into the public schools and they're now actually now creating their own clubs with sponsors in their own schools and we taught them skills like how to fundraise with, ya know, Go Fund Me-- >> Right, right. >> to come up with this and there's actually working. I mean it was very grassroots, it was very small. >> And how old were they, when you grabbed 'em? >> So our youngest was probably 12. >> Okay. And the way we found them was we went to the schools and we said, who's your smartest, ambitious, who do you think is motivated, who wants to do something different, send them to our conference. And we took 'em for two days. We taught 'em programming, basic programming. We taught 'em, wearable technology and we made sure that they were in different districts, sent them back into the school system. (Jeff laughs) >> That's great. >> Grassroots right? >> That's the way to see it. >> A little guerrilla-style. >> Right, right, right. Well, ya know, we see that more and more. Like I know LinkedIn does-- >> Yeah. >> weekend Hackathons all the time. So there is kind of the grassroot corporate effort from people who that are paying attention. >> Yup. >> And do the investment, but as you said the schools are lagging way behind on the CS (mumbles). >> They are, they are, but ya know, I feel like if each company took a small amount of time and created little grassroots movements, we could make a pretty large impact. We're not organized right, because you know, someone's doing it in San Francisco, someone's doing it in Arizona. If we kind of got together as just major corporations and said, let's do this, let's just... Because tomorrow we have to hire these people and if there's enough then we can't have the equality we want if we're not teaching girls early enough, then maybe we can make a difference. >> So I'd just love to get your perspective since you've been involved in Girls In Tech so long is trying to be one of the catalysts for that type of, you know, activity cross. >> Yup. >> Not only cross-state, but cross-country and around the world about the growth of this organization and how Adriana has taken it from... >> Yeah. >> I mean how big was it when you joined five years ago to where it is today? >> I mean the growth in numbers, I can't tell you what those are. But I can tell you the impact is huge. Every year I'm part of the Girls In Tech events and corporate boards. Seeing the impact and the feelings that it leaves for these woman is amazing. You now can talk internationally to woman and they know what Girls In Tech is, and they're familiar. And they're taking the Hackathons, they're taking the programs that this organization offers and they're learning and their getting jobs. And now I've been in it long enough where someone I met a couple years ago, who was just at a conference, kind of dabbling, took a course from Girls In Tech and is now in the career field, and they're kind of introducing Girls In Tech to others. So it's amazing. It's no longer grassroots. This is actually making a difference. >> Right, that's great. Well Lawdan, thanks for taking a few minutes. >> Thank you. >> And thanks for your longterm support of the organization, clearly you're not the only sponsor anymore and there's a lot of people-- >> Yes. >> that have jumped onto the bandwagon and that's all a good thing. >> Thank you. >> You're welcome. >> You have a great day. >> You too. (laughs) Alright, she's Lawdan and I'm Jeff. You're watching the Cube. We're Girls In Tech Catalyst 2018 in downtown San Francisco. Thanks for watching. (upbeat music)