Introduction - Big Data: Related Technologies, Challenges and Future Prospects - page 4

about by the increased data with a 3Vs model, i.e., the increase of Volume, Velocity,
and Variety, in a research report [ 14 ]. Although such a model was not originally
used to define big data, Gartner and many other enterprises, including IBM [ 15 ]and
some research departments of Microsoft [ 16 ] still used the “3Vs” model to describe
big data within the following 10 years [ 17 ]. In the “3Vs” model, Volume means,
with the generation and collection of massive data, data scale becomes increasingly
huge; Velocity means the timeliness of big data, specifically, data collection and
analysis, etc., must be rapidly and timely conducted, so as to maximumly utilize
the commercial value of big data; Variety indicates the various types of data, which
include semi-structured and unstructured data such as audio, video, webpage, and
text, as well as traditional structured data.
However, others have different opinions, including IDC, one of the most
influential leaders in big data and its research fields. In 2011, an IDC report defined
big data as “big data technologies describe a new generation of technologies and
architectures, designed to economically extract value from very large volumes of
a wide variety of data, by enabling the high-velocity capture, discovery, and/or
analysis” [ 1 ]. With this definition, characteristics of big data can be summarized as
four Vs, i.e., Volume (great volume), Variety (various modalities), Velocity (rapid
generation), and Value (huge value but very low density), as shown in Fig. 1.2 .Such
4Vs definition was widely recognized since it highlights the meaning and necessity
of big data, i.e., exploring the huge hidden values. This definition indicates the most
critical problem in big data, which is how to discover values from datasets with an
enormous scale, various types, and rapid generation. As Jay Parikh, Deputy Chief
Engineer of Facebook, said, “you could only own a bunch of data other than big
data if you do not utilize the collected data” [ 13 ].

Fig. 1.2 The 4Vs feature of big data

In addition, the US National Institute of Standards and Technology (NIST)
defines big data as “Big data shall mean the data of which the data volume,
acquisition speed, or data representation limits the capacity of using traditional
relational methods to conduct effective analysis or the data which may be effectively
processed with important horizontal zoom technologies,” which focuses on the