Systems, Man & Cybernetics - April 2016 - 26

Learning from
Uncertainty for
Big Data
Future Analytical Challenges
and Strategies
by Xizhao Wang
and Yulin He

B

ig data refers to data sets that are so large
that conventional database management
and data analysis tools are insufficient to
work with them [1]. Presently, we are in an
era of big data, which exists in various
fields, such as social media, telecom, finance, medicine, biinformatics, and power networks. Big data results mainly
from the evolutionary development of data storage and
data collection techniques in recent years. Big data has
become a bigger-than-ever problem with the quick developments of data collection technologies. In fact, the word
big is a fuzzy concept. So far, we do not have a mathematical definition of big data. But we can use several features
or coordinates to describe it, for example, the well-known
5V characteristics.
The 5V characteristics of big data refer to huge volume, high velocity, much variety, low veracity, and high
value [2].
1) Huge volume indicates that the size of data is extremely
high. Currently it is very common to have the storage
systems with TB (c103 GB) and PB (c106 GB) grade

Digital Object Identifier 10.1109/MSMC.2016.2557479
Date of publication: 23 August 2016

26

IEEE SyStEmS, man, & CybErnEtICS magazInE Apri l 2016

2333-942X/16©2016IEEE



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2016

Systems, Man & Cybernetics - April 2016 - Cover1
Systems, Man & Cybernetics - April 2016 - Cover2
Systems, Man & Cybernetics - April 2016 - 1
Systems, Man & Cybernetics - April 2016 - 2
Systems, Man & Cybernetics - April 2016 - 3
Systems, Man & Cybernetics - April 2016 - 4
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Systems, Man & Cybernetics - April 2016 - 55
Systems, Man & Cybernetics - April 2016 - 56
Systems, Man & Cybernetics - April 2016 - Cover3
Systems, Man & Cybernetics - April 2016 - Cover4
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