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Five V’s of Big Data

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Five V’s of Big Data

New Contributor

Hello All, I am new in this community and I am learning Hadoop for my upcoming interview next week. I want to know the exact work of five V’s of Big Data? I know about the five V’s of Big Data are Value, Variety, Velocity, Veracity, and Volume but what the exact importance in Big Data. Can anyone know?

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Re: Five V’s of Big Data

New Contributor

The five V's of big data. Volume, velocity, variety, veracity, and value are the five keys to making big data a huge business. 

Volume

If we see big data as a pyramid, the volume is the base. The volume of data that companies manage skyrocketed around 2012 when they began collecting more than three million pieces of data every data. “Since then, this volume doubles about every 40 months,” Herencia said.

Velocity

In addition to managing data, companies need that information to flow quickly – as close to real-time as possible. So much so that the MetLife executive stressed that: “Velocity can be more important than volume because it can give us a bigger competitive advantage. Sometimes it’s better to have limited data in real-time than lots of data at a low speed.”

The data have to be available at the right time to make appropriate business decisions. Data analysis expert Gemma Muñoz provided an example: on the days when Champions League soccer matches are held, the food delivery company La Nevera Roja decides whether to buy a Google AdWords campaign based on its sales data 45 minutes after the start of the game. Three hours later, this information is not nearly as important.

Variety

The third V of big data is variety. A company can obtain data from many different sources: from in-house devices to smartphone GPS technology or what people are saying on social networks. The importance of these sources of information varies depending on the nature of the business. For example, a mass-market service or product should be more aware of social networks than an industrial business.

These data can have many layers, with different values. As Muñoz explained, “When launching an email marketing campaign, we don’t just want to know how many people opened the email, but more importantly, what these people are like.”

Veracity

The fourth V is veracity, which in this context is equivalent to quality. We have all the data, but could we be missing something? Are the data “clean” and accurate? Do they really have something to offer?

Value

Finally, the V for value sits at the top of the big data pyramid. This refers to the ability to transform a tsunami of data into business.

Herencia offered an example that is the source of company pride at MetLife: “We now know within a two-month period when it is highly likely that a customer will cancel his or her policy or purchase a new one.”

 

After a significant investment in time and resources, if a company correctly uses big data, its ability to get to know customers and monetize all that information is enormous. They can offer customers what they want or need at the right time.

 

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