4 Vs of Big Data 4U

April 16th, 2014









In case you hadn’t heard.

Yes, big data is all the rage. And it should be. My friends who are big statistics nerds are suddenly finding themselves in one of the “sexiest” jobs of today: data scientist.

Sexy? Data scientist?


So, I’m not going to get very deep into this subject because I am not, you know, a big statistics nerd (although one of my greatest and most surprising triumphs was, after stumbling and bumbling repeatedly in class, earning a near-perfect score on the statistics mid-term my first year of business school; as the professor handed me back my blue exam book he said with a low voice and a wry smile, “So I guess you’ve been faking it all this time.”).

You’re probably not a statistics nerd, either. But regardless of what you do or where, ya gotta at least speak the language of data. So I want to (glibly, I’ll admit) arm you with just a tiny bit of data science vocabulary, namely the “4 Vs of big data,” to get you started on your way to big data mastery.

Without further ado, they are:

  • Volume: How darn much of it there is. There’s, like, SO MUCH.
  • Velocity: How darn fast we are creating it. Kazillions of Facebook posts and cellphone calls, all the time.
  • Variety: Who could possibly keep track of all the different KINDS of data being created? (Uh, data scientists?)
  • Veracity: Here’s the rub – it ain’t all reliable or accurate. Fer reals.

For a slightly more, shall we say, in-depth look at big data, click on the nifty infographic from the sexy data scientists at IBM (or click here).



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