>> Hi, I'm Lisa Martin on the ground with The Cube at Google Headquarters for the sixth annual CloudNOW Top Women and Cloud Awards event. Very excited to be joined by one of the award winners tonight, Alice Steinglass the President of Code.org. Congrats on the award and welcome to The Cube >> Thank you. >> It's great to have you here but first of all tell us about Code.Org. It's a pretty big organization and so what's it all about? >> Yeah, so our goal is that every student should have the opportunity to learn Computer Science. And we're focused on equity and diversity. I was surprised to learn that most schools today don't teach Computer Science. And it's not that most kids don't take Computer Science, it's that even if they wanted to most K12 schools today, the kid can't even take a Computer Science class if they want to. And this unfairly affects students of color, students in poor schools, they even have less of that opportunity today. And so our goal is that every school should offer Computer Science and every child should have the opportunity to take it. >> That's outstanding. How long have you been involved in Code.org and what inspires you to donate so much of your time to this organization? >> Yeah, so I joined about a little bit over two years ago. I'd been working in the tech industry for about 15 years, so I'd seen first hand what the lack of opportunity looks like and I was volunteering in my free time, helping out in schools and I just really wanted to make that my full-time job. I also think as a woman in Computer Science I remember walking into my first Computer Science class and it's a lecture hall with 500 people and you just feel like you're sort of in the wrong place. And it can be intimidating and I think especially when you don't know all the words or all the buzz words, you can feel like, I don't know what that word means, I don't know what BBS is right? So therefore I don't belong in Computer Science and it turns out, you don't need to know what a BBS is to do Computer Science. It's basically Reddit and nobody needs to know Reddit to do Computer Science. >> But that's a really great point that there's a lot of intimidation from kids at young ages, "Do I belong here?" "I like it but..." Like you said, there are things like acronyms that can intimidate someone. But some of the stats I was reading that 25% of students in the US have an account but this isn't just in the United States, you guys are doing some great things globally to get kids involved. So tell us a little bit about the global expansion of Code.org. >> Yeah, so almost half of our students come from around the world. And I think that it's not just about America, it's about every student deserves this opportunity. It's actually cool, most of our translation work, almost all of it is done by volunteer translators and we have organizations around the world like, Programa Il futuro in Italy who has translated all of our content into Italian and is working with the Italian Government and making it part of the national curriculum in Italy. Working with partners in Mexico and all over the world, who are doing great work and right here at home. You don't have to go far away, we're partnered with the Oakland School District which is right here. And we're partnered with San Francisco and all sorts of schools right here in America don't have that opportunity and so that's what we're focused on fixing. Because I was talking about, it's challenging when you don't know it and giving the students an opportunity to learn that in High School gives them the confidence to go and do this if they want to in college. I was lucky, I had a high school Computer Science class and I had a teacher who believed in me. And it makes a huge difference. >> Absolutely. >> So we want to give all students that chance. >> That confidence that you mentioned really is key. If you can just help, you probably think one person, just feel a little bit better that if, "Hey I don't know what this acronym is, how many other people don't know?" and that can just really build upon that. Something that I think is really cool that I've just learned about is the Hour of Code. Tell us about that because this is the perfect week to be talking about it. >> Yeah, you are interviewing me during CS education week. And one way you can celebrate CS education week is the Hour of Code. The Hour of Code has become an international movement. We've had tens of millions of students participating all over the world. This week alone there are over a 100,000 different Hour of Code events that are organized. You can see a map of them all over the world. An Hour of Code is a way of letting a student try Computer Science because I can tell you till I'm blue in the face that it's fun, or that it's interesting or that you can do it. But we see a much bigger impact when students actually try it. Last year we had thousands of students, which we measured. Questions like, I like Computer Science or I want to study Computer Science before and after they tried an Hour of Code. And what we saw was that it really makes a huge difference to try it. But you know the group that it mattered the most to? High school girls. High school girls. >> Fantastic. >> Yeah. Because they had this impression that Computer Science wasn't for them. But then after trying it, they said, "Oh you know what? It's not about sitting around and coding the Fibonacci Series." You can do that with code but you can also make apps and you can design websites and you can create things that have this creativity aspect and they wanted to go on and take it. Most students who do the Hour of Code go beyond the Hour of Code. And our goal with the Hour of Code is not to do one hour of code. One hour of code is not Computer Science, you're not going to learn that much right? >> Right. Getting your toe wet maybe? >> Yeah, get your toe wet. But the real goal is to help teacher teach years of Computer Science. To go from that to saying, "I can teach Computer Science." It's about the students and helping them take it and it's about the teachers and helping them teach it. Most of what we do at Code.org is helping teachers who never learned Computer Science when they went to school, learn Computer Science and learn how to teach it to their students. Because our teachers, they didn't learn Computer Science right? >> Right. >> And so we're asking them to teach the subject which is critically important in the 21st century. But it's a challenge. >> It is. Do you have any favorite stories of maybe a student or a teacher or both that tried this and their eyes were opened, "Wow, this is way more than I thought it was." >> So, there's a local teacher near Seattle, his name is Juan and he also was not a Computer Scientist. He had never taken Computer Science, I think he was teaching Political Science. I'm not sure, but I think that's what he was teaching. And he came to our workshops and he said, "Hey, I can do this. I can teach Computer Science." And we have one week workshops over the summer to help the teachers learn how to teach it. And curriculum and professional development that we provide for schools at no cost to the school to help them get started teaching Computer Science. And he took that leap and he did it. And he said, he went into one of his classes and he's in a district that is mostly under represented minorities and he looked at his class, and his class was all male and there were not very many of the under represented minorities in his class and he said, "Well, I've got to fix this." So he went out and he went to the choir class and he found this woman, our Sally and he said to her, "Hey why are you not in Computer Science right now?" and she said, "Oh, I don't know. I don't even like to sing." >> Oh my gosh, wow. >> So he just marched her right up. He got the form, he switched her over to Computer Science. He got her friend Daisy, he got a whole bunch of women in his class. And they loved it. And our Sally took that class and she kept going and she took Python. >> Wow. >> And she's applying to colleges right now and she wants to be a Computer Science major. >> That's amazing. Recruiting from choir. >> Right. And her parents never went to college. One of them never went to high school. And for her this is an opportunity to be part of all the things that we see in Silicon Valley. And I want to see her do it. >> Great story. Last question, the CloudNOW, and this is the Sixth Annual Top Women in Cloud Award. Congratulations on winning and how did you hear about this and what does it mean to you? >> I think it's a great award. I really love that CloudNOW is doing work to encourage equity and to encourage women in the tech space. I think that has a lot of synergy with the work we're doing at Code.org. Trying to encourage women and young women to be able to have this opportunity and be able to take these courses. And you know, it's okay if they don't want to go into the tech space. Most of them won't but if they have the opportunity to see these courses I hope some of them will be inspired and that when they are inspired they'll have that background, so they can. And for the other ones who go into all sorts of different fields, whether it be design or education or medicine, or marketing or who knows? Knowing how Computer Science works, I think is a critical set of skills for all people everywhere in this day and age. >> I agree. It'll be a great part of their foundation. Well, speaking of inspiration, you've been quite inspirational. Again congratulations Alice on the award and thank you for stopping by the Cube. >> Thanks. >> You've been watching the Cube a lot and we're on ground at Google for the six annual CloudNOW, Top Women in Cloud Awards. I'm Lisa Martin, thanks for joining. We'll be right back.

(upbeat music) >> Live from Las Vegas, it's theCUBE covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We're joined by Steven Guggenheimer, he is the corporate vice president of AI and ISV engagement at Microsoft. Thank you so much for coming on theCUBE. >> Sure, thanks for having me. >> So one of the things that we're hearing so much at this conference is, "data needs AI but AI needs data." I'm wondering from your perspective, AI engagement, where do you come down on this? What are you hearing? what are your thoughts on that big theme? >> Um, well, data is the -- some people say the oil for AI, pick your terminology, but there is no AI without data. The reason that AI is such a hot topic right now is the combination of sort of compute storage and networking at scale, which means the access for developers and data scientists to work with large sets of data and then the actual data. If you don't have data you can't build models, if you can't build models, that's what is the definition of AI. So you need data. I always-- all the coaching I do is about sort of, BI before AI. If you can't actually get insight out of your data, let's not try to add intelligence. If you can't get insight out of your data, it means your data is not in a good-- your data state is not in order. So data first. >> A lot of architectural work is being done on data. I see a horizontally scalable cloud, gives a nice access to a lot of different you know, observational data sets. >> Yeah >> It used to be give the guy the silo, got the data, go get more data, slower. Now, data feeds the developer process because SaaS business models have been proven that data and SaaS work well together. So how do we get more-- what's the sequence of architecture to usability of data so that not only can you just have analytical systems, but where developers can start building their SaaS apps with data? >> Yeah, I mean we have this notion where we often talk about sort of, blades or feedback loops. There's sort of four or five things most companies do. You work with customers, you have employees, you have a supply chain or some type of partner chain, You run your finance and operations. So the question becomes, in each of those processes, there's data. Human-generated forms over data or pick your loop and now you getting tons and tons of data. The trick now is to make it reusable. Mostly what we've done for years, form over data, take the data, form over data. And what we do is we get all these different databases. We try and create some layer that brings it all together. We build cubes out of it to view and then we get this hopeless spaghetti. So the trick right now, we're working on something called Common Data Model, which others are well, or Common Data Service. Let's get the entities lined up from the very beginning. We've worked with Adobe and SAP on the Open Data Initiative. Let's start at the core, let's make the data layer reusable, We're you know, databases have become data warehouses have become data lakes. We're heading towards a data tidal wave, and if we don't get the data estate in order to run the line of business applications, to feed all of the things we do to use the ML and AI on top of it, we're going to drown in data and not get what we want out of it. So, architecturally I think about the Common Data Model and the Common Data Service both generically by industry, we build accelerators for that, getting the big organizations like the three I mentioned aligned around that, making it such that any, you know, organization can build from that and then building on top of that. For big companies you have to decide, what do I keep and what do I throw out? You know, what do I just give up on and start from fresh? What do I actually clean? Where do I use tools from Informatica or others to help me clean it, secure it? But you've got to put all that thought in. >> You know we were chatting before we came on camera about the internet days and the storied history that you had at Microsoft. And during the internet, search was the big application. And search on the internet actually worked really well because they didn't have a legacy. And the people that tried to crack the code on search inside an enterprise, much harder problem (Giggles). Because of the database things you mentioned. How does today's enterprise get the benefit of SaaS as if they were cloud-native SaaS with the data? So you know, the challenge we're hearing here is having a Common Data Model is all great, but I just want to be a SaaS player, I want to use my data to feed into my business value. How does a company move out of those legacy constraints? What do you see as-- >> Well there's different paths that different companies will take. I mean, the good news is that if you get your data in order to do what you said, then whether you build, buy or partner for the SaaS services, you can use that data underneath and you should be feeding it back in and making it such that it's sort of reusable and the pipeline is consistent. The truth is on all this, it's just going to end up infused anyway. When you used the internet, which is a funny analogy 'cause I remind people, you know, when the internet came out we had internet products, we had internet events, we had internet shows. We don't have any of that anymore. It's just woven into everything we do. AI is going to be the same. You have all this hype right now, you have AI shows, you have, you know, AI groups. The truth is, in 10, 15 years, AI it's just going to be woven into everything. The data is going to be set up for that. >> So what's the misconception on AI? 'Cause, first of all, I love the fact that AI is hyped up because my kids love it. Machine learning they learn because they hear about AI and they hear all this coolness. So machine learning goes hand-in-hand with AI, you feed machine learning, machine learning feeds the AI application. But a lot of people have aspirations around AI. Some of them are ungettable and so that's probably a misalignment around the hype. What's your feeling of where the reality is and what's the misconceptions, how should people approach AI? Any thoughts there. >> I think a lot about the AI journey, the first year we were having these AI conversations, we talked about AI for everybody, just go play. Now the conversation is, I call it pragmatic AI. Look, lets talk about, you know, how you want to think about AI, it's going to end up everywhere, so the question becomes, what's your differentiation as a company, and how is AI going to support it? Like any other new technology, in the beginning, people just want to play. Just because you can -- let's just say just you can build a virtual agent, doesn't mean every company should. So the question becomes, first off, BI before AI, get your data state in order. Second, in a build buy partner model, what's your differentiation as a company? Whether you want to use either your unique data or your unique skill sets to use AI against that differentiation to help you grow. Otherwise, like, expect somebody else to have infused AI into the products you buy, the SaaS services, you know, use that, then build whatever you want and then there's, you know, if you think you're going to build a new business based on your unique data or your unique AI capabilities, great, let's have that conversation, we need that too but rarely does that become the state. so, most of the conversations move from, you know, the hype to okay, let's get pragmatic which is why I always come back to data first 'cause if you not doing that, you're not setting up for the long run. Let's build for the long run, then let's just have a business conversation like, how do you differentiate yourself as a business? Okay, how is this tool going to help you? >> I want to ask about, uh about innovation, and particularly because Microsoft is a company that's now entering its middle age (giggling) and-- >> What does that say about me, oh no >> As one of famously innovative company, but how do you stay on the cutting edge? I mean, I'm wondering internally how you think about AI for Microsoft's business purposes. What are the conversations around AI? >> One of such is, core conversations around this notion of tech intensity you know, from where we focus on how we think about things we think about tech intensity against different areas, AI being one of those. Look, AI is really this interesting thing. I would say we're plumbers by trade, we build software plumbing for others. So, we do three things right, with AI. Basically, there's a layer growing on top of the core development stack, compute, storage, networking for AI. So we're building a layer, cognitive services, bot services, machine learning, set of tools for developers to infuse AI into things that they've built, so that's thing number one. Thing number two, is we infuse AI into our own products, into Windows, into Office, into Azure, into dynamics. You don't see it, we don't talk about it, we don't say Microsoft Windows Inking brought to you by Azure AI. It just works, but our inking works, our face login works, oh, you know, I can -- it's helping me write a better resume in LinkedIn, that's all AI behind the scenes. Now, the third thing you think about then is, "how do you actually use AI to run the business better"? So, how do you think about, AI assisting professionals, how do we think about the, how we do mocking better, How we forecasting sales, so AI is about plumbing, let's build a platform for others, let's use it ourselves on our own products, and then let's think about how you actually use it to run the company better. And that's how we think about it-- >> That's pragmatic >> Very pragmatic AI is kind of -- >> Yeah, that's how I think about it and we, you know, it's interesting 'cause back to the tech intensity point, we get together on an AI conversation, we searching with the senior leadership team about once every other week, and we're round robin between a research topic, the platform and one of the solutions. So it's, you're always getting constant feedback about is the platform doing what we need to build solutions? Is the research feeding the platform? So, you're getting this really nice feedback loop right now and that tech intensity. >> Quality data always has been a big part of the data modeling in the past, Cloud now allows for data marketplaces I've seen sharing of data as a dynamic, almost like sharing libraries of your developer back in the day, so data is now being merchandised in a new way. This is a trend, what's your thought on it? Because if this continues, you're going to have more data inputs, does that-- >> Err, there are places where data is aggregated and potentially can be re-used. We can -- Bing is an example, Google would be an example um, I know people who aggregate data for different industries, etcetera. It's not an easy business, the rules and rights around data, the GPR compliance, the rest of it. I think there's a deer there but you really have to be in the business for-- the trick you run into is, if you're going to be an aggregator, and then a reseller of data, where's that data coming from? What are the rights, what's the security? And then, are the people who are providing that data comfortable with their competitors getting the data? 'cause if you're really going to be a data provider marketplace, first person who's going to want on is the competitor, so, I think it's an interesting conversation, I think it's kind of growing and there's some real good work there, I don't think it's as-- >> not viable yet >> Easily to do it at scale, for as many people who think they have the data asset as believed they do. But that's Steve's view, that's not a Microsoft's statement. (laughing) >> good disclaimer >> Steve's view, so I want to hear Steve's view on the skills gap, this is a huge problem in the technology industry, as so few people to fill roles. How's Microsoft dealing-- what's your view-- >> my view is I'm glad I work at Microsoft, 'cause we spend a lot of energy on that, um, I wish there were a single solution, but we have Minecraft for education, starting with kids, how do you help, you know, Minecraft is this great tool that teachers use help kids get started, so that's a tool set we work on something called tills, which is uh, basically, our developers teach school kids remotely, junior, high school level, you know, coding. Um, we have made investments against this, we have online training, you know, we work with universities. I don't know the perfect answer, um, but I do know we invest and we work with Hadi Partovi and his group on code.org, I mean any place that there is work going on, we work with the military for people coming out of the military service. So we're heavily invested. I'm hopeful that the ease of use of some of the tools and just from a job area, it drives people but I don't know the perfect answer. Steve's view is I don't know the answer, I do know we try every trick in the book-- >> Multipronged attack >> I'm a parent of two kids, like I have my daughter, you know, working on more on the tech side and you know, it's hard to keep kids on a track for that-- >> There's no degree yet, but we had a first degree this year, graduated from the school but there's kind of like a skills portfolio of different things depending on the make-up I mean, domain expertise is critical, if you don't know what you're tryna do, that's -- >> I think we got a mix, because what you're starting to see is, the tools for subject matter experts, are getting better, we have something called the power platfrom, which allows people who aren't necessarily coders by trade, but want to be able to build, you know, sort of apps or services to be able to do that more easily and mix their subject matter expertise. And you see many more people come out of any program, take biology, with sort of computer knowledge to a decent level. AI and ML research, different area, hard skills gap right there >> Steve, great insights, thanks for spending some time with us, great insights on the skills gap and just overall >> thanks for coming on theCUBE >> We didn't talk about rugby, but okay, fine. Thanks, next time >> next time >> You're one of those ballsmen >> we'd track you down >> The ballsmen can throw >> Exactly, shout out to them >> There we go, >> thank you >> Ah, you are watching theCUBE we'd come right back with more from Informatica World I'm Rebecca Knight for John Furrier, stay tuned (upbeat music)