Data Crunch

Potential Advantages of Blockchain for Data Scientists

10.22.2019 - By Data Crunch CorporationPlay

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Luciano Pesci is bullish on blockchain and data science. Since blockchain offers a complete historical record, no one can delete or alter prior information written into the record. He sees this characteristic as a massive advantage for data scientists. Luciano Pesci: And the key for data scientists and leaders who are gonna oversee data sciences, you've got to get a narrow enough problem to demonstrate one quick win and I mean in 90 days. If in 90 days you can't come back to the organization and show, "we have made real progress on these metrics in your understanding so that you can make these decisions," they're not going to continue to do it. Ginette Methot: I’m Ginette, Curtis Seare: 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: No matter what your position in a company is, knowing about data, how it works, and what it can do for you is vital to the success of your organization. Fortunately there are ways for you and those in your organization to learn about data. Brilliant dot org, an online educational resource, has on-demand classes in data basics that can help you understand this growing area, providing you with tools and the framework you need to break up complex concepts into bite-sized chunks. You can sign up for free, preview courses, and start learning by going to Brilliant.org/DataCrunch, and also the first 200 people that go to that link will get 20% off the annual premium subscription. Ginette: The CEO of Emperitas, Luciano Pesci, joins us today. Let’s get right into the episode. Curtis: What inspired you to get into data? What inspired you to to start the company you're working at now and how'd you get going? Luciano: All of it was a complete accident. Yeah, none of it, not the schooling, the business, none of it was intentional. Curtis: Okay, let's hear about it. Luciano: My first business was actually recording studio and a record label, and I had signed, among other acts, my own band, and we got a management deal, and we went to LA. We started to tour with national acts, and I thought that was going to be my career path without a doubt, and so I didn't take the ACT/SAT at the time, barely graduated high school, and then the band fell apart. And I was like, "well, what am I going to do?" So I went back to school, had a transformative experience, got drawn into economics, and then within economics really found data. Curtis: And what drew you to economics? Luciano: I like studying people. I think it's the most complete picture of people. So there's a lot of other disciplines that sort of dive deeper when it comes to people's psychological characteristics, their behavioral components. But economics was about the entire system and how an individual functions within that bigger system. And the reason I got to data from that was that the key assumption of modern economics is perfect information. So this is usually where critics of what is called the classical model in economics come in and say, "well, you can't have perfect information, so therefore you can't have optimizing behavior." And one of the beautiful lessons of the last 20 years, especially with data science is it might not be perfect information, but you can get really good information to make optimized choices. And so the represented that, that method of going into the real world and optimizing all these processes that we were learning about in the textbooks and at the abstract theory level. Curtis: Interesting. And that's, there's not a lot of places, if any, that I know of that teach that approach, right? Or have good coursework around that. Did you kind of figure this out on your own or how'd you, how'd you come to that?

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