Volume: This refers to the quantity of generated and stored data sets. The size of data helps in determining the value and potential insights into it, hence it helps us to know if a specifc set of data can actually be considered as big data or not.
Variety: This property deals with the difference in types and nature of the data. This actually helps people who analyse the large data sets to effectively use the resulting insights obtained after analysis.
Velocity: The speed of generation also plays a big role when we classify something as big data. The speed data is generated and further processed at to arrive at results that can be analysed for further us is one of the major properties of big data.
Variability: When we talk about big data there is always a some inconsistency associated with it. We consider the data set as inconsistent if it does not have a specific pattern or a structure. This can hamper the different processes required to handle and manage data.
Veracity: The quality of the captured data can also vary a lot, which affects the accurate analysis of the large data sets. If the captured data's quality is not good enough to be analysed then it needs to be processed before analysis.