4 V’s of Big Data

Gartner term 3 V of big data is now modified as the 4 V. The 4 V’s signifies the unifies features of big data: volume, variety, velocity and value or veracity as elaborated below:

Volume: This signifies large amounts of data. Typically when people discus big data volumes, they discuss petabytes. But in reality, most real-life big data implementations are still in the 10’s to 100’s of terabytes range, which is still a lot of data.

Variety: This refers to the evolving types and growing sources of data, including semi-structured and unstructured data. An example of semi-structured data might be an e-mail message, where the might be in a common, structured format, but the e-mail text itself is more unstructured. An example of unstructured data would be notes that a customer support representation might type in free-form about a customer’s trouble ticket.

Velocity: Velocity in the context of big data refers to the speed of data acquisition and processing. Big data technologies provide horsepower that accelerates these processes, thereby making data provisioning and usage faster too.

Value or Veracity: In an effort to distinguish the business value of big data, the vendor community camp up with a 4th “V” – Value which has been added to the general big data lexicon. In other words, don’t go down the big data path just because you can. Or just because someone – like a vendor, consultant or airline article – told you to. Or just because you like to fiddle around with the latest technology. Go because it will bring demonstrative value to your business. Additionally, a new V “Veracity” is added by some organizations to describe it.