They are the so-called three V's of big data: Volume refers to the size of the data; Velocity refers to the data provisioning rate and to the time within which it is necessary to act on them.
The paper also investigates how various inherent characteristics of big data – volume, velocity, variety, variability and complexity – are related to the assessment of the creditworthiness of low-income families and micro-enterprises.
The world is becoming more and more connected, intelligent and device driven, resulting in the Three Vs of big data: Volume, Velocity and Variety.
The research also emphasized that as an entity, big data comprises volume of information that usually cannot be processed using traditional database and software techniques.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be captured, analysed and used for decision-making.
In the current era of Big data, high volumes of valuable data can be generated at a high velocity from high-varieties of data sources in various real-life applications ranging from sensor networks to social networks, from bio-informatics to chemical informatics.
This already is representative of one dimension of big data, its volume or size: data is considered big if it has reached TB or PB in size, and is typically so large that it exceeds a single organization's storage capacity.
The most common definition describes characteristics of big data as volume, velocity and variety (Laney 2001).
The three characteristics often mentioned as distinctive of big data are volume, variety and velocity.
"Over the past few years, we've focused a tremendous amount of attention on what people like to call the 'three Vs' of big data: variety, volume and velocity," he said.
