Volume

Volume, velocity, and variety: Understanding the three V’s of big data

Volume, velocity, and variety: Understanding the three V’s of big data
We practitioners of the technological arts have a tendency to use specialized jargon. That’s not unusual. Most guilds, priesthoods, and professions have had their own style of communication, either for convenience or to establish a sense of exclusivity. In technology, we also tend to attach very simple buzzwords to very complex topics, and then expect the rest of the world to go along for the ride.

Take, for example, the tag team of “cloud” and “big data.” The term “cloud” came about because we systems engineers used to draw network diagrams of local area networks. Between the LANs, we’d draw a cloud-like jumble meant to refer to, pretty much, “the undefined stuff in between.” Of course, the Internet became the ultimate undefined stuff in between, and the cloud became The Cloud.

To Mom and Dad and Janice in Accounting, “The Cloud” means the place where you store your photos and other stuff. Many people don’t really know that “cloud” is a shorthand, and the reality of the cloud is the growth of almost unimaginably huge data centers holding vast quantities of information.

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Big data is another one of those shorthand words, but this is one that Janice in Accounting and Jack in Marketing and Bob on the board really do need to understand. Not only can big data answer big questions and open new doors to opportunity, your competitors are using big data for their own competitive advantage.

That, of course, begs the question: what is big data? The answer, like most in tech, depends on your perspective. Here’s a good way to think of it. Big data is data that’s too big for traditional data management to handle. Big, of course, is also subjective. That’s why we’ll describe it according to three vectors: volume, velocity, and variety — the three Vs.

Volume is the V most associated with big data because, well, volume can be big. What we’re talking about here is quantities of data that reach almost incomprehensible proportions.

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