The popular 3V's of Big Data

In 2001 industry expert Doug Laney defined the 3V’s of big data. The 3V’s of big data are the key to understand how big data is measured in companies to improve operations, make intelligent decisions faster and generate more revenue by reducing cost and risks.

Volume:

Large volume of data is usually in Terabytes or Petabytes. This data is generated from social media, websites portals, online applications, IOT sensors and credit cards etc. in the form of records or tables. The volume of data is huge and difficult to analyse through traditional methods. Therefore, modern tools and techniques are used to access the data out there for relevance. (Haber, 2013)

Eg: Every day on social media, huge volume of data is generated every minute and every hour by sharing billions of images, posts, videos, tweets etc.

Variety:

Variety refers to the type and nature of data. The information is collected from humans or machines and more than 80% of data that is collected is unstructured like text documents, emails, voicemails, hand-written text, ECG reading, audio recordings etc.(Hansen, 2019) New and innovative technology is being implemented to analyse such data and classifying them into various categories for a specific use. (Soubra, 2012)

Velocity:

Velocity refers to the speed at which the data is getting generated. Big data comes from various sources like sensors and smart metering that spell out large data within short period. Reacting fast enough to deal with high velocity data is one of the challenges that companies face. Therefore, the data must be managed with a timely manner to exploit the potential business opportunities. (Sicular, 2013)

Eg: Click stream that is generated when an user clicks on Amazon shopping cart which will be stored as log file and is used to find customer interest or buying patterns so as to such as the relevant product for the customer.

References

Haber, L., 2013. WhatIs.com. [Online]
Available at: https://whatis.techtarget.com/definition/3Vs
[Accessed 04 Feb 2020].

Hansen, S., 2019. Hackernoon. [Online]
Available at: https://hackernoon.com/the-3-vs-of-big-data-analytics-1afd59692adb
[Accessed 03 Feb 2020].

Sicular, S., 2013. Forbes. [Online]
Available at: https://www.forbes.com/sites/gartnergroup/2013/03/27/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-three-vs/#3ccc5ee142f6
[Accessed 05 Feb 2020].

Soubra, D., 2012. Datasciencecentral. [Online]
Available at: https://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data
[Accessed 05 Feb 2020].