Originally there were three V’s of Big Data. Doug Laney introduced Volume, Velocity, and Variety as the three V’s of data management in 2001 when he worked for the Meta Group, which was purchased by Gartner in 2005. He did not use the term Big Data in his 2001 publication.
IBM uses the same three V’s and added a fourth B of Veracity no later than 2013. The author Bernard Marr added a fifth V of Value. He describes his five V’s in these slides. Rob Livingstone added Validity and Visibility. In 2013, Doug Laney made the distinction between definitional and aspirational qualities of data. According to Doug, only Volume, Velocity, and Variety are definitional. All other V words are aspirational.
Mike Gualtieri of Forrester in 2012 asserted that Doug’s three V’s are not actionable. Mike offered what he calls a pragmatic definition of Store, Process, and Access.
Neil Biehn when still at PROS (now at Siemens) stated that the fourth and fifth V’s are Viability and Value.
If you are willing to have more than three V’s, Visualization is an obvious V to add and multiple authors have written about it. It’s hard to make sense of Big Data and difficult to derive value or take action if you can’t see what the data is telling you.
I think people should use as few or as many V’s as they find helpful. I will not go so far as to formally propose another V, but I will state that Vexing sometimes fits Big Data. It can be vexing because of the technical issues of Doug’s three V’s and it can be vexing to interpret and act upon.