Building a data science team is difficult enough, but growing one without losing the team’s effectiveness is a major challenge. Here’s why overspecialization is the wrong approach to growth. You’ve built a great data science team, and everything’s going fine until you realize you need more team members. It’s a scary endeavor to mess
I’d like to offer up some thoughts about what it means to practice data science in the real world, because merely knowing the math isn’t enough. Anyone who knows me well knows that I’m not the sharpest...
You’ll find much banter in the data science ecosystem these days about all the skill-sets required to effectively function as a data scientist. Some have gone so far as to label the perfect melange of experience and...
R remains popular with the PhDs of data science, but as data moves mainstream, Python is taking over. While R has traditionally been the programming language of choice for data scientists, it is quickly ceding ground...
Asked to name a big data company, many of us would say Google or Facebook or eBay. But for old-school giants such as General Electric Co. and Macy’s Inc., big data is fast becoming as central to...
As I frequently travel in data science circles, I’m hearing more and more about a new kind of tech war: Python vs. R. I’ve lived through many tech wars in the past, e.g. Windows vs. Linux, iPhone...
Rexer Analytics has been conducting regular polls of data miners and analytics professionals on their software choices since 2007, and the results of the 2013 Rexer Analytics Data Miner Survey were presented at last month’s Predictive...
