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Comment by hyperbovine | Hacker News Reader

It's time for this term to die.

If it doesn't involve data, it's not science.

Yes, and this is the Science of analyzing Data. The term isn't trying to say there is an alternative science that is "non-data", or that people in other kinds of science are not involved with data - it's just specifying what kind of thing is receiving the scientific method: the data itself.

I agree. I absolutely love almost everything on this list but I only despise the term "data science" slightly less than "big data". Sadly what is often called "data science" is the rather narrow analysis of log files generated by websites.

Back in the good old days, Data Science used to be called Statistics.

Statistics (noun) - The practice or science of collecting and analyzing numerical data in large quantities.

http://www.google.com/search?q=definition+statistics

And I would argue that qualification that the data be "numerical" in this definition is wrong. Plenty of statistical analysis invokes categorical text data (e.g. sex, race, occupation...).

I used to feel the same way, but (1) calling it statistics downplays the importance of data munging and grabbing/normalizing/managing data and (2) the advent of computational methods and off-the-shelf machine learning and natural language analysis has turned statistics into "one tool in our toolbox" rather than The Tool.

And frankly, even if data science is just statistics rebranded, anything that can get more people to take an interest in statistics is a good thing. If a hype-fueled new sticker is what it takes, then why not.

But this way, my $employer's Business School can charge 19 thousand for an MSc in Data Science and Management!

Quantitative business analyst just doesn't sound as wallet-opening.

yea exactly - who does science without data. We've all been doing data science for years!

Yes and no - the component pieces of data science have been used for years, but as the OP describes, the field of data science assembles skills and tools that really haven't been universally understood and effectively applied to problem solving - it is a relatively fundamental shift to a new way of interacting with data.

Please. Statisticians have been doing this for over 300 years. Cooking up some infographic on your Hadoop cluster is not the paradigm shift you are making it out to be.

It sounds like we're not talking about the same thing.

No, we are. You are talking about gathering, modeling and summarizing data. To claim that those skills "really haven't been universally understood and effectively applied to problem solving" is ludicrous. What do you think scientists did prior to the advent of "data science"?

Every field of science is about gathering, modeling and summarizing data - that is not exclusive to statistics or any other field, which means we need to be more specific than that to determine whether Data Science is doing anything different than statistics.

Unfortunately data science is not well defined (in part because it is a young field), but it draws extensively from computer science and is targeted toward data sets that are different from those that have typically been used in 'traditional' statistics - huge, dirty data sets.

This debate has a similar flavor to Physicists saying that Chemistry is not a science because it's all just physics, and Chemists saying that Biology is not a science because it's all just chemistry. They are extensions, just like Data science, and pretending that an expert statistician will be and expert data scientist is just not tenable.

There is room for something more.

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