This question was recently posted by Larry Wasserman on the Normal Deviate blog (see extract below). Larry is a statistics and machine learning professor at Carnegie Mellon University.
Here is my answer:
Data science is more than statistics: it also encompasses computer science and business concepts, and it's far more than a set of techniques and principles. I could imagine a data scientist not having a degree - this is not possible for a statistician. But the core of the issue, in my opinion, is explained below.
This diagram misses a few key concepts - including business and domain knowledge
Here's the article:
As I see newspapers and blogs filled with talk of “Data Science” and “Big Data” I find myself filled with a mixture of optimism and dread. Optimism, because it means statistics is finally a sexy field. Dread, because statistics is being left on the sidelines.
The very fact that people can talk about data science without even realizing there is a field already devoted to the analysis of data — a field called statistics — is alarming. I like what Karl Broman says:
When physicists do mathematics, they don’t say they’re doing “number science”. They’re doing math.
If you’re analyzing data, you’re doing statistics. You can call it data science or informatics or analytics or whatever, but it’s still statistics.
Maybe I am just pessimistic and am just imagining that statistics is getting left out. Perhaps, but I don’t think so. It’s my impression that the attention and resources are going mainly to Computer Science. Not that I have anything against CS of course, but it is a tragedy if Statistics gets left out of this data revolution.
Two questions come to mind:
1. Why do statisticians find themselves left out?
2. What can we do about it?