The 4 V's of Big Data: Volume, Velocity, Variety, Veracity

Instructor: Kaitlin Oglesby
Big data may seem like a giant concept, but in reality it can be summed up in four words starting with V. This lesson explains them all and provides ample examples for each.

The Four Vs of Big Data

Just because there is a field that has a lot of data does not make it big data. Instead, to be described as good big data, a collection of information needs to meet certain criteria. Analysts sum these requirements up as the Four Vs of Big Data. In this lesson, we'll look at each of the Four Vs, as well as an example of each one of them in action.


Volume may be the most obvious of the Four Vs. After all, to be considered big data, there should be enough information worth analyzing. Think of it like a pollster would - if you were going to poll a city of 300,000 about the job that their mayor is doing, you would not rely on the opinions of the first three people you met.

To see this in action, take a video streaming service. They have millions of data points about what people like to watch and what they don't like to watch, spread out across a number of different demographics. They can then piece all of this information together to determine that if you like a certain franchise of sitcoms then this family comedy may be something you'd appreciate. In fact, they even make sure that they have information about each viewer - this is why many of them ask at the beginning of every session 'who's watching'. While you may think that they do this to bring up the proper queue, in reality it is just as much about gathering data given your demographic information.


Velocity refers to how quickly new data becomes available. After all, when performing analysis, the best kind of data is the type that is as up to the minute as possible. The ability to quickly gain new data is a hallmark of big data operations.

So how does this work? Let's say that you are running a political campaign and find out that your opponent is starting to trend in some social media circles for some bad investments that he made some time ago. Apparently there are allegations of insider trading. If you are able to act quickly enough on that information, you can hopefully convince more people to vote for your candidate. However, if you are acting on old data, you are likely to look bitter and will be accused of mud-slinging.


Variety refers to the different types of data that come in, as well as the different sources of data. To get a full picture with big data, we need both types of variety. After all, if you are just following bankers on LinkedIn, you very well might think that the only thing important in the world is the derivatives market.

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