A grand debate: is data science just a 'rebranding' of statistics?

My general opinion is that most of the "new stuff" is always re-branding of something old concept sprinkled with some minor modifications.

IMO, statistics shows macro patterns that humans can understand (through analytics/dashboard). Today's data science produces micro patterns that are actionable (through personalized ads/newsletters), even if it is not human comprehensible.

Ads on TV are based on statistics. On youtube, it is data science.

I don't think "data science" is a distinct science, but it is a distinct field of work.

The business guys need short buzz words. They can't comprehend "online distributed virtual machine on-demand hosting", but they can comprehend "cloud computing" and "data science".

For the most party it is rebranding. This stuff has been going on for years in various industries. There's nothing wrong with rebranding and it's great of it gets more industries involved. You could say that when statistical research is combined with programming then it is data science, or when the results of research are fed back into operational systems then it is data science, but there are examples of all of these things from before people started saying data science.

Yes. 'Statistics' makes it sound dull. 'Data Science' on the other hand, now you have both 'Big Data' (so hot right now) and 'Science' (like how adding an X in acronyms makes it sound cooler). Margaret Thatcher said 'Power is like being a lady. If you have to tell people you are, you aren't.' The same applies to 'Science'.

to me it's statistics with computers

I come from a background of quantitative social science by scientific training - used to think of myself as an applied or pragmatic statistician. In recent years I have added database skills, text mining, taxonomies and old school rules-based automated indexing - then I taught myself web programming for the presentation layer along with some combination of data and digital maps - when I put that all together it certainly feels like a lot more than when I was just a practicing applied statistician. I gave a presentation to some CIOs a couple of weeks ago. The following is my current definition of Data Science - though I will admit it has an engineering flavor as well.

"Multi-disciplinary knowledge, methods and skills for building systems that acquire, manage and analyze data to deliver insight and automate quantitative analyses like segmentation, classification and prediction in support of real-time business processes." Michael Swenson [2015 working definition of data science]

If statistics can be described tongue in cheek as gaining insight about groups of numbers by generating other numbers, data science is about gaining insight about groups of <files> by generating other <files / numbers / graphics / interactive displays etc >. Perhaps it is an extension of what statistics is but acknowledging that stats was the granddaddy app.

The word 'science' is used to justify lower salaries, while 'data' is there to make the job sound cool and trendy (like Big Data etc.)

For the most part, I'd say yes they are the same. But the focus on computing/business for data science leads to some parts that are really more CS than stats. Interacting with databases, for example, can fall under data science, but not really stats.

There are data scientists who specialize in mathematical modeling, some who specialize in visualization, others who specialize in algorithms (i.e. data mining, machine learning), and still others who specialize in business uses of data (modeling decision making processes, designing data communications). If you consider all those things to be branches of "statistics" then you may say data scientists are statisticians.