What does the attribute “Value” imply in the context of Big data?

Value is one of the five V’s of Big data. In addition to the 3 V’s of Big data (i.e., Volume, Velocity, and Variety) there are other two V’s such as Veracity and Value are collectively known as the 5 V’s of Big data. Value in Big data refers to the usefulness of gathered data from a business perspective. This refers to the value that big data can provide, and it relates directly to what organizations can do with the collected data.

Just because we collect lots of data, it’s of no value unless we gain some useful insights out of it. We are required to pull value from big data, to gain insights depending on the business operations. Regardless of the volume of data, it should be very useful and valuable, so that it can be converted into proper information. We can achieve this by using custom processing software for the gathered data.

Organizations use big data tools to gather and analyze the data, but how they derive value from that data should be unique to them. The bulk of data having no value is of no good to the company, unless you turn it into something useful. Data in itself is of no use or importance but it needs to be converted into something valuable to extract Information. Hence, we can say that Value is the most important V of all the 5 V’s.

In the past few decades, the data generated and consumed increased day by day through various resources. As you see, users on social media as well as the content increasing every day, by which a massive bunch of data is generated. The main goal of Big data is to achieve some valuable insights from those data.

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Author: Keerthana Buvaneshwaran