 From the galvanized campus in San Francisco, it's theCUBE, covering Apache SparkMaker Community Event brought to you by IBM. Now, here are your hosts, John Walls and George Gilbert. And welcome back to San Francisco as we continue our coverage of Spark Week here on theCUBE, along with George Gilbert. I'm John Walls, and today, we're at the Apache SparkMaker Community Event, moving to the Spark Summit tomorrow, just across town at the Hilton, as a matter of fact, on Tuesday and Wednesday. But right now, we're in Galvanize, and one of seven campuses in the Galvanize family, you might say, and with us to talk about what Galvanize is all about, is the COO of that operation, Ben Data, and Ben, thanks for being with us. We appreciate the time. Thanks for having me. And thanks for hosting. First off, great facility. When I walked in, frankly, I wasn't sure if I was at an IBM event. And we've talked about that, about the whole, the culture, the shift, and really the optics and the vibe. So kudos to you for creating a really dynamic environment. Well, thank you. It's something else. Well, let's talk about Galvanize, for those who might be watching, who aren't familiar with all that you've done. You've been around for a few years now, and this is all about educating the, really the next generation, if you will, or the first generation of data scientists. No, absolutely. Galvanize is a dynamic learning community that brings together students, startups, and industry as well, and combines education, workspace, and events to really help to accelerate all their growth. So across our campuses, you have classes in web development, classes in data science, classes in data engineering, surrounded by startups growing their business, and then large corporations as well. They're looking to tap into that innovation and talent. And the motivation, and back in, on day one, back in 2013, when the first shovel was put in the ground, if you will, figuratively, of course, I mean, what was the motivation in terms of providing this kind of an educational platform for students? Well, I think what it was is we saw a real opportunity to help fill that talent gap. The idea that technology is just advancing so quickly that the more traditional spaces for both education and how you build your business were keeping up. So we wanted to help provide really a platform for that, a container to bring it all together so that all those people who wanted to make that leap with it could have a home. Now, IBM came out with a pretty bold statement about a year ago and saying, we are going to be committed to training one million data scientists. We're going to create this, not a community, we're going to create a metropolis, if you will, of this community. Where do you fit in to that picture? You said you ran through 6,700 in a given year here. So in terms of that big, bold number, how does Galvanize play into that? Well, it is such a big problem that it's nothing one person alone is going to solve, but we really see ourselves as being a big piece of that solution. And having great partners with IBM makes that a lot easier to do. So we're behind both the data pluse event with them, helped to host that at all of our different campuses across the country. IBM's been a great sponsor for scholarships, for students coming through our program. And then we're also able to help collaborate on both what's in our curriculum and the tools that we're teaching to make sure that our data scientists are leaving with the best set of tools that they're going to use out there with their hiring partners. And who are you attracting? Who do you find, if there's a model, if you will, of the kind of student you see coming through your door or the person whom you're educating? I mean, what are they made up of? What are their characteristics and their interests? Yeah, there can be a pretty big range in it, mainly from age and background, but what you usually tend to see are folks who have been in an analytical job. So there's some place where they're working with data and they're coming across these problems that they just really want to solve, but they don't have the tools that they need to be able to do that. So as long as they have kind of the prerequisite background in an object-oriented programming language, some experience with college-level mathematics, and they're going to be at the level where they're ready to step into our program, because it is pretty intense. It's three months of nonstop, five days a week, eight to 10 hours a day, and they really get all that tool, all the different tools that they need and all the knowledge that they need in that program. And what are the core areas then? The core, we start with, usually start with just the basic statistics, working into then machine learning, natural language processing, a lot of it then focusing then on their, really their capstone project. So actually working with our industry partners or some of our member companies, so that they're working with real world data. Because obviously when you're learning data science, that's a big part of it, is all the nastiness and dirtiness of getting into a real data set. And I would guess, I mean, because you're not teaching history here, right? You're not teaching English. I mean, this is a dynamic environment in which you're operating, so the subject matter is going to change almost at the drop of a hat, that keeping up with that, and then almost you're at the cusp in so many ways. That's got to be a challenge in many respects. It is, and it's another reason that having partners like IBM and our member companies as well is so important, because having those feedback loops of what we're teaching, because that's really who determines the skills that we teach. The curriculum and the learning experience is what, that's our specialty, but really knowing the skill sets, we want to follow what industry tells us they need, because they're the ones who are ultimately the customer of our talent coming out. Is this the model that, at least in some states like California, where community colleges try and fill that role, where they'll work with industry to say what skills they need, and then the college essentially comes up with the curriculum to impart those, to teach those skills? This absolutely is a, there's a lot of different programs that try to leverage this format for, because I think we've all realized the world's moving so quickly now that trying to build a set of mastering curriculum based on your own thoughts isn't necessarily gonna move at the speed of what industry does. So you are seeing some leaders in the education space who apply this model as well. And so where did this model come from? I mean, did you guys adopt it from community colleges? Are they adopting sort of industry-specific training or role-specific training from you? Well, ours actually came out of our CEO's previous company, which is a company called Ascendant, that got acquired by ADD and that they were a major IBM implementer. He couldn't hire enough engineers to work through. So they actually created their own six-month Java school within his company to help be able to train people who had the aptitude, drive, and determination to become that. And so when he left, he really saw this as an opportunity that this could be a solution that's applied widely across technology. We first started web development, but then the next big gap we saw was in the data science and data engineering space. And so for those who are enrolled in the three-month program, I assume it's a little early for the one-year program since that probably really only ramped up with IBM's commitment. But are you seeing your industry partners, like hiring, almost everyone who's coming out of the end of the program? Yeah, absolutely. Current placement stats for our data science program are at 94% are being placed within six months upon graduation just because there is such a demand for folks with a skill set across a wide range of companies. Changing them, the pool of applicants, either in number or in kind? We've definitely seen more as there's more awareness of this opportunity out there, a lot bigger demand in the number of applicants that are coming through. And the other piece of it is starting to see a lot more demand from the hiring side. Probably the biggest challenge we see there are companies know that they have the data, they know they want to do something with it, but they're not even sure exactly what to do. I guess what I want to ask you about is that I think if I'm on, we've been talking a lot about the employee side, but on the employer side, what kind of interaction do you have with them about the areas of weakness maybe they see within their own operations where they think they need additional expertise or the areas that they see are great growth opportunities for them and what they need is people to come in and be prepared to advance the cause in those particular areas. We try to work with our industry partners as close as possible to really identify what those gaps are. We have actually been starting to put together some different programs, some with IBM actually, to focus on how do you train those executives? How do you train that next level down to really understand what's even possible with data science and data engineering? So then they can, okay, this is what we want to build out. Here's both the talent that we need and here's the tool set that we need to solve these problems. And you just said executive training. Is there a place then here or do you already do that to where you're educating on the C-suite level to give them an idea about the opportunity? So at least it's one thing to have a great tool. It's another thing to know what to do with it. Yeah, exactly. So are you seeing some of that? We have a couple of products that we're in the process of beta testing right now and getting ready to roll out, but really excited with the feedback that we've gotten so far from some of our industry partners. It's interesting that question and your comment about how you've got this core sort of pipeline now of skills coming out, but some of the companies don't have all the pieces in place to consume them and turn out applications. Well, I think the demand is absolutely there. What this is even more of is that the demand could be even bigger than it is right now. It's just the fact that you have a lot of times some of these companies who haven't even realized yet what's possible. Great example is one of the larger engineering companies in the world. I mean, they're collecting now with internet of things and all their sensors, just reams and reams of data and they haven't been doing anything with it. They've been letting their partners potentially build some of the solutions on that. Now they want to get in, they just don't know where to start quite yet. So it's going to be exciting to see once they all start figuring that out. So from in terms of expansion, if there is this huge demand on the employer side, they said we need these data scientists to come out and help us move into the next generation of analytics. I mean, can you go 10 campuses, 12 campuses, 15 campuses, do you look international? Do you go East Coast? Are any of those things on your drawing board right now or being talked about? Absolutely, I think there's a lot of opportunity to both grow geographically, also grow by modalities. Right now we primarily do this in an in-person immersive, but that's really for people looking to get into the industry. But there's a lot of folks who are in the industry who just want to pick up maybe some additional skills. So having stuff that's more part-time or online is a great solution for them as well. Luke, have you experimented with? Yeah, absolutely, we have some great partnerships with some already and some of our instructors have content on others, but I think there's even more benefit to it if you could start a class online and then maybe have access to an in-person instructor or study group or anything along those lines as well. There's a story, and it happens to be true, that Yale's most popular computer science class, I think it's their most popular class, it's Intro to Computer Science, and all the content comes from a MOOC that's Harvard's Intro to Computer Science, and Harvard folks are kind of proud of that. I can imagine. But then they're slept back down into a place by now being called the Stanford of the East, this little off topic. Well, Ben, thank you for being with us. Absolutely. We appreciate the time, and thank you for hosting. Again, great surroundings and a great environment, and I can see why you've had the success that you have, and I'm sure that will continue as well. Well, thank you very much. Thank you. Ben Data, being with us from Galvanize. We are back from Galvanize with more here on theCUBE as we continue our coverage of the Apache Sparkmaker community event here in San Francisco.