The 4 V's of Big Data

The 4 V’s of Big Data

The challenges associated with Big Data are the “4 V’s”: Volume, Velocity, Variety, and Value.

The "4 V's" of Big Data: Volume, Velocity, Variety, and Value.           <em>Source: Oracle.</em>

The “4 V’s” of Big Data: Volume, Velocity, Variety, and Value. Source: Oracle.


  • The Volume challenge exists because most businesses generate much more data than what their systems were designed to handle.
  • The Velocity challenge exists if a company’s data analysis or data storage runs slower than its data generation. This could be because of customer clicks on your website or thousands of sales transactions every second — a good problem to have.
  • The Variety challenge exists because of the need to process different types of data to produce the desired insights. This could include, for example, analyzing data from social networks, databases and customer service call records at the same time.
  • The Value challenge applies to deriving valuable insights from data, which is the most important of all V’s in my view. A company can usually collect all the data but the challenge is to ask the right questions to get value from it.

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