Introduction - Big Data: Related Technologies, Challenges and Future Prospects - page 5

technological aspect of big data. It indicates that efficient methods or technologies
need to be developed and used to analyze and process big data.
There have been considerable discussions from both industry and academia on
the definition of big data [ 10 , 11 ]. In addition to developing a proper definition, the
big data research should also focus on how to extract its value, how to make use of
data, and how to transform“a bunch of data” into “big data.”

1.3 Big Data Value

McKinsey & Company observed how big data created values after in-depth research
on the U.S. healthcare, the EU public sector administration, the U.S. retail, the
global manufacturing, and the global personal location data. Through research on
the five core industries that represent the global economy, the McKinsey report
pointed out that big data may give a full play to the economic function, improve
the productivity and competitiveness of enterprises and public sectors, and create
huge benefits for consumers. In [ 12 ], McKinsey summarized the values that big
data could create: if big data could be creatively and effectively utilized to improve
efficiency and quality, the potential value of the U.S. medical industry gained
through data may surpass USD 300 billion, thus reducing the U.S. healthcare
expenditure by over 8 %; retailers that fully utilize big data may improve their
profit by more than 60 %; big data may also be utilized to improve the efficiency
of government operations, such that the developed economies in Europe could save
over EUR 100 billion (which excludes the effect of reduced frauds, errors, and tax
difference).
The McKinsey report is regarded as prospective and predictive, while the
following facts may validate the values of big data. During the 2009 flu pandemic,
Google obtained timely information by analyzing big data, which even provided
more valuable information than that provided by disease prevention centers. Nearly
all countries required hospitals inform agencies such as disease prevention centers
of new type of influenza cases. However, patients usually did not see doctors
immediately when they got infected. It also took some time to send information
from hospitals to disease prevention centers, and for disease prevention centers to
analyze and summarize such information. Therefore, when the public is aware of the
pandemic of a new type of influenza, the disease may have already spread for one to
two weeks with a serious hysteretic nature. Google found that during the spreading
of influenza, entries frequently sought at its search engines would be different from
those at ordinary times, and the usage frequencies of the entries were correlated
to the influenza spreading in both time and location. Google found 45 search entry
groups that were closely relevant to the outbreak of influenza and incorporated them
in specific mathematic models to forecast the spreading of influenza and even to
predict places where influenza will spread from. The related research results have
been published in Nature [ 18 ].