The data podcast for CEOs, founders, and innovators. How are successful leaders using data and analytics to build companies, find efficiencies, and develop new capabilities to solve some of the world’s most challenging problems? Hear directly from top leaders, across industries. We'll explore the opportunities and limitations of data, analytics, machine learning, and AI.
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Making Data Assets Profitable with VDC
Many companies are sitting on data assets that could be revenue streams for them, without knowing it. Matt Staudt of VDC discusses making latent data profitable.
Ginette: I'm Ginette, Curtis: and I'm Curtis, Ginette: and you are listening to Data Crunch, Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world. Ginette: Data Crunch is produced by the Data Crunch Corporation, an analytics, training, and consulting company. Ginette: Today, we chat with the president and CEO at the Venture Development Center, Matt Staudt. Matt Staudt: The company that I'm with is VDC, Venture Development Center. Basically VDC is an organization that works in the alternative big data, bringing buyer and seller together. So we have a unique perspective on available data assets that are out in the marketplace and a unique perspective of the companies that utilize them, and what they're specifically looking for in the way of points of, uh, value for various data assets. My background was originally in the marketing and advertising area, where I owned a company for 20 years, IMG, Interactive Marketing Group. I left that in 2007 and joined this, which was more or less of a lifestyle organization. And we made it a full-fledged organization company back in 2010.Curtis: Now, when you say data assets, can you put a little bit of definition around that for the listeners? Just so they understand how you define a data asset? 'Cause I imagine there may be some things that you think are valuable that maybe they haven't thought of, or maybe it'll help expand our thinking around what a data asset is.Matt: Yeah, sure. In my, in my terminology "data asset" basically falls into eight different categories, where assets basically come from within the information world. So they could be things like transaction data or crowdsource data. They could be things like search data or social data sets. They fall into various categories, traditional data, meaning assets that are business to business or business to consumer generally aggregated by large companies that most everybody's heard of Dun & Bradstreet, Infogroup, Axcium, the credit bureaus, et cetera. Alternative data in our world are companies that have unique data points, unique. They're collecting unique pieces of information, usually as a byproduct of their core business. And we look at the assets that the data sets, the actual data points that they collect. And we figure out if there might be something of value to take to the marketplace, usually to the large consumers of the data, the big aggregators that I previously mentioned, but oftentimes it also fits well with some of our mid-tier players. And we have a significant amount of relationships in the brand grouping, meaning large organizations that they themselves are looking to try and take advantage of big data and utilize data in sales, marketing operations, in order to transform or help to administer certain activities that they have going on.Curtis: Do you find that this is maybe industry specific, like for example, a big insurance company, or if you're in healthcare or something like this, it tends to be more data intensive that you see more activity there or, or is this really applicable across the board? What kind of industries do you find have a lot of applications?Matt: Yeah. Well, it's interesting on the surface, you certainly think that there's probably industries that would have a larger appetite and a larger need for data than, than other organizations, but going, you know, through the list of companies that we've helped over the last 15 or 20 years, it really runs the gamut. I mean, we've worked with insurances, you mentioned insurance, insurance companies. I mentioned credit bureaus. We work with credit bureaus, risk and fraud, sales and marketing, sometimes large brands within those
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Data, Epidemiology, and Public Health
With recent events being what they are, epidemiology has come into the spotlight. What do epidemiologists do and how does data shape their everyday experience? Sitara and Mee-a from "Donuts and Data" fill us in.
Ginette: I'm Ginette, Curtis: and I'm Curtis, Ginette: and you are listening to Data Crunch, Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world. Ginette: Data crunch is produced by the Data Crunch Corporation, an analytics training and consulting company. Many people are on the lookout for online math and science resources right now, particularly data and statistics courses, and whether you're a student looking to get ahead, a professional brushing up on cutting-edge topics, or someone who just wants to use this time to understand the world better, you should check out Brilliant. Brilliant’s thought-provoking math, science, and computer science content helps guide you to mastery by taking complex concepts and breaking them up into bite-sized understandable chunks. You'll start by having fun with their interactive explorations, over time you'll be amazed at what you can accomplish. Sign up for free and start learning by going to Brilliant.org slash Data Crunch, and also the first 200 people that go to that link will get 20% off the annual premium subscription. Now onto the show. Curtis: I'd like to welcome Sitara and Mee-a from the Instagram account Donuts and Data to talk to us today. I guess let's just have you guys introduce yourselves, as opposed to me trying to introduce you cause you know what you do better than I do. So maybe we just have some introductions. Sitara: So I'm Sitara one half of Donuts and Data. I'm a PhD student in epidemiology at the University of Texas Health Science Center. I'm also a research assistant in a lab that I work in. Mee-a: And I'm Mee-a. I am an infectious disease epidemiologist that works in the public sector. I actually met Sitara through the lab that she's currently working in. Curtis: Nice. And I'm excited to have you guys on. I just, I think epidemiology is a really interesting space, especially with what, you know, with what's going on now with COVID. I think it's more pertinent than it ever has been. Not that it ever hasn't been pertinent, but maybe it's more top of mind for people. So I'd love maybe just to have you guys level set with everybody, like what is epidemiology. There's probably some confusion about what that is and maybe how you guys got into it. And then we can get into what your day to day is and, and what it's all about. Sitara: So, epidemiology, I think everyone's kind of understanding is setting patterns of disease in the, in the human population. And so in that sense, what Mee-a and I do are the same, but instead of studying infectious diseases or the natural science part of epidemiology, what I focus on is how human behavior contributes to those patterns of disease. So I look for patterns in data associated like demographics or just behaviors, diet, nutrition, and how that contributes to getting diseases. Mee-a: For me in the public sector, it's going to be a lot of looking at incidents, rates of infectious diseases. It . . . primarily with COVID-19 right now, and just different ways that we can try to possibly implement infection prevention measures. So we are dealing a little bit more with, I don't want to say the medical side of it because we aren't clinicians, but we are dealing more with the medical side of, of the infectious disease than we are with, with the data compared to when I was in academia, at least. Curtis: So take us through maybe the end goal, right? So what you guys are working on. You're hoping to come out with, I think, some recommendations for people to, to take maybe a better understanding of how the disease spreads, so we get in front of it. What does tha
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Customer ReviewsSee All
If you have a remote fascination for data and storytelling of data applications this is worth the listen.
Ginette and Curtis are some of my favs. On the court the content is interesting and informative, to the point that I sometimes take bullet point notes to use in explaining machine learning to clients. Off the court they took a personal call with me to help me brainstorm and evaluate whether joining a data science consulting company was the right fit for me. 8 months later I’m really enjoying the career move.
Thought provoking, great interviews, excellent background research, informative and entertaining!