3 V's - Volume, Velocity and Variety

               The 3 V's of Big Data are Volume, Velocity and Variety. Volume, as the name suggests refers to the quantity of data. Velocity refers to the speed at which the data is tacked, stored and processed. Variety is nothing but the different types of data that are available. Among the 3 V's of Big Data most people think that Volume plays the key role to success. But this is not the case. Big Data can be used effectively only if all of the three are considered or treated accordingly.

           

                                          Source: datasciencecentral.com

Volume

The amount of data that is available today is very large. That is not only for businesses, but is also same for individuals as well. Few years ago, data was internally generated by the employees of an organisation. But this is not the case today. Data is available from various sources such as employees, customers and also the partners. Thanks to the advancement in technology, these huge amount of data can now be easily tracked, stored and analyzed.

Velocity

In the earlier days, the data was analyzed by companies by dividing them into different batches and each batch was done one by one. This was enough when the rate of incoming data was very slow and also the result, even though it arrived late, was useful. But this is not the case nowadays, because thee is huge amount of data coming from various sources and it needs to be processed in real time. The results are useful only if the delay is very short.

Variety

Companies have made a format for analyzing data in the earlier days as there was not much different types of data available. But the things have changed. data comes in different forms like texts, pictures, videos, documents, files etc. So new technologies have been introduced to analyze the different types of data.

Reference

1. What is 3Vs (volume, variety and velocity) ? - Definition from WhatIs.com

https://whatis.techtarget.com/definition/3Vs

2. The 3Vs that define Big Data

https://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data