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3Vs (volume, variety and velocity) are three defining properties or dimensions of big data. Volume refers to the amount of data, variety refers to the number of types of data and velocity refers to the speed of data processing. According to the 3Vs model, the challenges of big data management result from the expansion of all three properties, rather than just the volume alone -- the sheer amount of data to be managed.
Gartner analyst Doug Laney introduced the 3Vs concept in a 2001 MetaGroup research publication, 3D data management: Controlling data volume, variety and velocity. More recently, additional Vs have been proposed for addition to the model, including variability -- the increase in the range of values typical of a large data set -- and value, which addresses the need for valuation of enterprise data.
The infographic below (reproduced with permission from Diya Soubra's post, The 3Vs that define Big Data, on Data Science Central) illustrates the increasing expansion of the 3Vs.