Access your Pro+ Content below.
Split personalities put data scientists in play
This article is part of the BI Trends + Strategies issue of Issue 5 May 2012
Data scientists are a new type of analyst: part data engineer, part statistician and part experienced business analyst. And they're in high demand: Companies are combing through resumes and job websites, interviewing recent university grads and poaching from their competitors in an effort to bring these new talents into their organizations. Of course, we've had statistical analysts -- or "quants" -- in our organizations for years. They're often doctorate-bearing, white-jacketed folks who spend their days in the rarified towers of the back office. Unfortunately, while they are great at analyzing data, they are not always the best at explaining their findings to corporate executives and lower-level business workers in understandable terms. In many cases, it is nearly impossible to get clear answers from them to questions such as the following: I see the trends, but why are they important and what should I do to change them? What impact will changing customers' buying behaviors have on our revenues? How do we change the causes ...
Access this PRO+ Content for Free!
By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers.
Features in this issue
Successful BI for small and midsize businesses isn’t just about implementing software. They have work to do before deployments to make sure systems will be readily adopted and produce valid results.
News in this issue
With business users looking to get their hands on business intelligence data more quickly, making BI systems more flexible and responsive is becoming a priority in many organizations.
These specialists are in high demand these days, but who are they really? Scientists? Analysts? Statisticians? In fact, they are each of these and more.