Data literacy is now a baseline benchmark for being an intelligent manager.
Bill Franks is the Director of the Center for Statistics and Analytical Research within the School of Data Science and Analytics at Kennesaw State University. In this role, he helps companies and governmental agencies pair with faculty and student resources to further research in the area of analytics and data science.
He is also Chief Analytics Officer for The International Institute For Analytics (IIA) and serves on the advisory board of ActiveGraf, Aspirent, DataPrime, DataSeers, and Kavi Global.
Franks is also the author of the books: Winning The Room, 97 Things About Ethics Everyone In Data Science Should Know, Taming The Big Data Tidal Wave, and The Analytics Revolution.
Greg and Bill explore in this episode data literacy, AI tools in the data space, and why you might want to hire a Chief Data Officer.
Episode Quotes:
What “bias” really means
People think of bias always being about, it has to be race or economic. It can just be bias towards factors that are important from a business perspective that no one else would care about. But if it's biased towards, I'm going to have more errors in my large size than my small size, that could be a problem if my large size has a cost model that's much higher than my small size. I either want no bias or, or I want a bias that biases towards more errors on the small side.
Data officers are important now
I think the cool thing today in many companies, we actually have analytics, data science oriented people at that table now. And that's what I think this whole trend of the Chief Analytics, Chief Data Officer represents. It’s recognizing that it deserves a seat at the table.
Data ethics & biases
That's where the ethics has to become proactive where you're not only thinking of it on the frontend, but you're also doing diagnostics on the backend to make sure is there a bias inherent in this on the backend that we could not have predicted? Or is it working in a way that appears correct and is wrong?
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