Tag - Those

How To Debug Your Approach To Data Analysis

Seven common biases that influence how we understand, use, and interpret the world around us. comments By Shafique Gajdhar, FusionCharts. In 2005, UCLA Econ Graduate, Michael Burry, saw the writing on the wall – the ticking numbers that form the Amer...

Jeremie Harris

Why you shouldn’t be a data science generalist I work at a data science mentorship startup, and I’ve found there’s a single piece of advice that I catch myself giving over and over again to aspiring mentees. And it’s really not what I would have expe...

Overcoming distrust on the path to productive analytics

We outline the importance of overcoming distrust in __data optimist, streamlining the process, and more. comments By Dejan Duzevik, Chief Product Officer at Concentric Where there’s data, there’s often skepticism. With the ability to distribute and a...

The Parallel Universe of Dark Data and Dark Matter

Scientists estimate that 95 percent of the matter in the universe is dark. Not strictly the domain of “billions and billions of galaxies,” as Carl Sagan was fond of saying, the universe is composed of unobservable matter completely invisible to light...

Why you need version control

(This article was first published on Peter's stats stuff - R, and kindly contributed to R-bloggers) I recently had an email exchange with a seasoned, well respected analytical professional which included the following (from them, not me): “… my versi...

Why You Shouldn’t be a Data Science Generalist

But it’s hard to avoid becoming a generalist if you don’t know which common problem classes you could specialize in in the fist place. That’s why I put together a list of the five problem classes that are often lumped together under the “data science...