I think one of the issues is that academic statisticians, who publish theoretical articles not based on data analysis, are... not statisticians anymore. Also many statisticians think that data science is about analyzing data, but it is more than that. It also involves implementing algorithms that process data automatically, to provide automated predictions and actions, e.g.
- automated bidding systems
- estimating (in real time) the value of all houses in US (Zillow.com)
- high frequency trading
- matching a Google Ad with a user and a web page to maximize chances of conversion
- returning highly relevant results to any Google search
- book and friend recommendations on Amazon or Facebook
- tax fraud detection, detection of terrorism
- scoring all credit card transactions (fraud detection)
- computational chemistry to simulate new molecules for cancer treatment
- early detection of an epidemy
- analyzing NASA pictures to find new planets or asteroids
- weather forecasts
- automated piloting (planes, cars)
- client-customized pricing system (in real time) for all hotel rooms
All this involves both statistical science and terabytes of data. People doing this stuff do not call themselves statisticians, in general. They call themselves data scientists.