Charles Killam, LP.D. – a.k.a. Charlie – is an experienced lecturer, data analytics professional and a former Chief Information Officer (CIO) with over twenty-two years in technology. Prior to teaching at Northeastern University, Charlie worked at such companies as Teradata, Sybase, Visa International, and New England School of Law. Charlie holds a Bachelor of Art in Business Administration and Behavioral Sciences from Oglethorpe University, a Masters in Business Administration from Northeastern University and a Doctorate of Law and Policy (LP.D.) from Northeastern University. He is both a data enthusiast and a Ghiradelli enthusiast, as seen above. We decided to ask Charlie a few questions so you can get to know him better:
What was the most exciting challenge that you solved using analytics?
I figured out how to predict which wines someone will enjoy even though they have not previously consumed the recommended wines. I love wine – Malbecs in particular – but I don’t like spending money on bad wine!
What is your favorite movie?
Any movie with Saturday Night Live (SNL) actors is likely to be a favorite movie of mine.
What advice do you have for aspiring analysts, or, what do you wish you knew at the beginning of your career?
Think big! There is so much we still don’t know that is just waiting to be discovered using data. Understand the data you have, think of the big questions you or your company would like answered, figure out how to get data you need, and use the data to find the answers.
What would you do if you had access to all of Google’s data for 24 hours?
Google is estimated to store 15 exabytes of data (no one is completely certain since Google does not publish this number). That is about 15 million terabytes of data! I’m thinking I would turn the power off to the servers, and save some energy! However, I don’t think that is what was in mind with this question. Logistics aside, perhaps I would work on ways to reverse the effects of global warming (without shutting down Google’s servers).
How did you get into analytics?
Northeastern University’s Doctor of Law and Policy (LP.D.) program is where and when I really established my interest in analytics – specifically, Professor Jamie Fox’s statistic course. I was hooked. From there I went on exploring the world of predictive analytics / Big Data / Data Science.
What traits do you think are most important for students learning analytics?
Critical thinking and the ability to formulate the right questions represent the two most important traits one can possess in the analytics space. For example, when faced with a new piece of information, what are the implications of having that information? Is it valuable or simply interesting? What does it mean? Can it lead to other, more valuable insights? How do you visualize it? How do you communicate its significance to others? How does it fit with the big picture of your organization?