Data Science for the Non-Scientists
Last week, The New York Times discussed the emerging academic discipline known as Data Science, and how students will be able to become what’s known, according to Rachel Schutt, as “a hybrid computer scientist software engineer statistician.” I have no doubt that data science will supplant computer science as one of the hot degrees for the ambitious and intelligent over the next decade. But what about the rest of us? We’re out of school and in the workforce. Are we also on the road to becoming obsolete? Read More →

I was reminded again of the importance of knowing how to harness and utilize big data in the run-up to this month’s US presidential election. By many accounts, more than $2 billion was spent by the two main candidates this election cycle. On the basis of being able to aggregate and read massive electoral datasets, that money was well-spent. Deciding how to spend that money was largely a function of being able to correctly analyze electoral “big data” – demographics, likely vs. registered voters, the public’s responses to various issues, etc. One side, however, utilized big data better than the other.
The way that people find jobs, particularly digital jobs, has changed substantially in just the last three years. These days, by the time someone is requesting your resume, they probably know quite a bit about you, not just via Google but also by digging a little on social-media sites like LinkedIn and Facebook.





