Mike Stringer

Hi, it’s Mike again with Ubtastic. I’m sitting down tonight with Mike Stringer who runs the Data Science Chicago group. It’s been around about a year and you know, well, thank you very much for taking the time to sit down. What is Data Science Chicago? So we’re a meetup group. We started, like you said, about a year ago. We use the trendy buzzword, data science. Not big data. Yeah, not big data. It sounds more respectable. Yeah, yeah. It sounds more respectable, but maybe it’s a little bit more devious. But so basically we try to bring together kind of the way that we frame it is kind of three groups of people. So data people with kind of analytics backgrounds, so maybe with a background in statistics or hard science. We also try to bring in people who have a design background, so maybe user experience design or even kind of design in the sense of an approach towards problem-solving. Okay, so when you say design, you are talking about front-end human interface? Actually, in the broader sense, maybe like a designer might take a particular approach towards designing some piece of hardware, a device or a medical device, or it could even be an architecture type of design. But it’s not necessarily the traditional use or the more common use of design where I’m making something pretty. Yeah, not making something pretty, but trying. So the way that I like to think of it is that designers do a really good job at trying to identify a good problem to solve. And that’s actually one of the core reasons why we thought that, and I say “we” because the idea for the data science group kind of grew out of Datascope Analytics, which is the company that I’m working on. I’m one of the founders of it. So we saw this kind of need to bring the technical community together with maybe a less less technical community. Sometimes, in our experience, the technical folks that have a kind of a data analytics background often start and say kind of “here’s some data, what can we do with it?” Whereas the design community, they’ve basically kind of perfected, instead of asking questions like that, they say “what’s important to do?” And then figure out how to do something valuable and solve that problem. Ask the right question. It’s not like I have a lot of lumber, I need to build something. What do I need to build? Do I have lumber? Exactly. That’s a great analogy because I like to think of data as like a resource, maybe not a natural resource, but it’s a resource that you can use to solve problems. But it’s really important to figure out what needs to be done first, and then how can data be used as a resource to do that. And so we want to cultivate with the group that way of thinking about this new resource that’s just, I mean, it’s like if you think of it as lumber, it’s like data is doubling every three years or something ridiculous, the amount of data that’s stored. And so it’s like this resource that’s just exploding in the amount of it. So how do we use that resource? What are the journeys you found in the group? Where did the idea of the data science group come from? So actually, I went to a couple of meetups actually. One of them is Hacks Hackers here in Chicago. I went to that, thought it was a really cool idea, went and explored the meetup page. Hacks Hackers? Yes. At the time it was Erin Poldrin, she still organizes it. And Brian Boyer. And so I went to that, thought it was really cool, explored the meetup site, saw that there’s a bunch of really cool and interesting kind of data oriented groups. There’s the big data group, the Hadoop user group, machine learning meetup, and now there’s data visualization also. Okay. And the data science is kind of, I would call it kind of like a, it’s a vague term, nobody really knows what its definition is, and it’s meant to kind of encompass like solving the right problems, visualizing it in a way that these kind of more analytical things can really be communicated. And so we saw that as kind of a missing piece of the meetup community. Right. And really our goal is, I mean, it’s a growing, vibrant community of people that want to figure out valuable ways to use data and to solve important problems for the city and for all types of organizations. Have you ever worked with the open government group? Yeah, absolutely. There’s a ton of cross membership between those groups. So like these groups tend to have their own kind of sub community. Yeah. It’s also kind of interesting seeing the idea of dealing with large data sets and looking at new tool sets and starting, I saw that there’s an R tutorial. Just, you know, all the languages, for years it was Ruby and JavaScript. Now we’re seeing an Arch interface. Have you even seen, not just people who were already in the industry of dealing with these big problems, but you see a lot more people coming from outside than maybe were doing just UX or Rails apps that are now starting to be interested in that? Yeah, absolutely. And with, there are a few things that have kind of popularized kind of that approach too. I mean, a big one is Nate Silver in the recent election. 3-5-8, right? Yeah, 5-5-38. 5-3-0. Yeah. So, I mean, that, the fact that his predictions were right on and that he was able to communicate that, I think that’s an actual key point that there’s a lot of people who are making the same predictions actually, but Nate Silver with his blog did a fantastic way of communicating that and that really resonates with people. And so it does bring in kind of a Ruby community. Yeah. And people from all over the place that see like, wow, this is a really, really powerful new way of communicating. And it’s kind of an objective view on things that… So he didn’t just do good analytics. He also made them accessible. Exactly. And that’s, maybe that’s why we were looking at the designers and people who can express. Exactly. That’s in the view of like the kind of data science Chicago meetup view is that that’s kind of the missing piece. The technical side. There’s a large community of people that kind of get that, but we want to try to cultivate the sense of you have to have that in the communication and you have to be doing and solving the right problem in the first place. So it’s kind of like those three key aspects to really bring in speakers and prompt discussion about how we can all do that better. That’s kind of the goal. Well, thank you very much for taking the time to sit down. Appreciate it. Thank you.