Information Technology Reference
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various means: for example, online, through mobile devices, location tracking
systems, and data sharing applications. Think of Google: user data is collected from
email data (gmail), search data (google search engine), web navigation data,
geographic location (google maps), voice and video communication data (gmail),
image management and processing data, foreign language interest data (translate
google), and more. The sobering fact is that there are many “google-like” applications
out there.
Then there is the web 2.0 user generated data from popular social networking sites
that includes personal data that is incredibly voluntarily shared among users. Think of
Facebook, for example: there are almost one billion users uploading and sharing
personal information. Terry predicts that much of data contributing to Big Data will
be what he terms 'exhaust data' “created unintentionally as a byproduct of social
networks, web searches, smartphones, and other online behaviors” [2].
To top it all, we are increasingly seeing smart environment interactions and
monitoring as more and more devices get connected with each other through online
communication, in the world of the so-called Internet of Things. In fact, some
scholars predict that it is from the Internet of Things that Big Data will increasingly
be derived [2].
1.2
Data Mining
Data mining refers to the extraction of information from the mass of data contained in
Big Data. What is special about data mining is that the use of sophisticated statistical
methods complex algorithms leads to the emergence of new patterns not previously
discernible. These patterns may lead to the development of new associations, new
meanings, and new knowledge [1].
It is therefore not too difficult to imagine the kind of treasure trove that is available
to social media networks and search engine companies such as Google. For instance,
Google has at its disposal personal data in the form of email, voice and video data
from its gmail service, search data from its search engine, translation data from its
translation service, geographic locational data from its maps service, among others.
Facebook has about a billion users uploading personal information on a daily basis.
While there are major benefits of data mining to industry and society, for example
in the areas of health and traffic management, there are downsides as well, in the form
of threats to individual privacy [3]. Rubinstein [1] has noted several intertwined
trends that he says pose serious challenges to privacy. He points to the proliferation of
social networking sites, developments in cloud computing, ubiquity of mobile devices
physical sensors and advances in data mining technologies. These trends encourage
the sharing of personal data by individuals, the transmission of geo-locational data,
and the aggregation and analysis of data sourced from a variety of sources. Terry [2]
reminds us that data aggregation and customer profiling is not a new phenomenon.
What is remarkable about Big Data now is the scale at which data is collected, and the
developing sophistication of predictive analytics.
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