Big data is a broad term for data sets so large
or complex that traditional data processing applications are inadequate.
Challenges include analysis, capture, data curation, search, sharing, storage,
transfer, visualization, and information privacy. The term often refers simply
to the use of predictive analytics or other certain
advanced methods to extract
value from data, and seldom to a particular size of data set. Accuracy in big
data may lead to more confident decision making. And better decisions can mean
greater operational efficiency, cost reductions and reduced risk.
Analysis of data sets can find new
correlations, to "spot business trends, prevent diseases, combat crime and
so on." Scientists, practitioners of media and advertising and governments
alike regularly meet difficulties with large data sets in areas including
Internet search, finance and business informatics. Scientists encounter
limitations in e-Science work, including meteorology, genomics, connectomics, complex
physics simulations, and biological and environmental research.
Data sets grow in size in part because they
are increasingly being gathered by cheap and numerous information-sensing
mobile devices, aerial (remote sensing), software logs, cameras, microphones,
radio-frequency identification (RFID) readers, and wireless sensor networks.
The world's technological per-capita capacity to store information has roughly
doubled every 40 months since the 1980s; as of 2012, every day 2.5 Exabyte
(2.5×1018) of data were created; The challenge for large enterprises is
determining who should own big data initiatives that straddle the entire
organization.
Work with big data is necessarily uncommon;
most analysis is of "PC size" data, on a desktop PC or notebook that
can handle the available data set.
Relational database
management systems and desktop statistics and visualization packages often have
difficulty handling big data. The work instead requires "massively
parallel software running on tens, hundreds, or even thousands of
servers". What is considered "big data" varies depending on the
capabilities of the users and their tools, and expanding capabilities make Big
Data a moving target.
Thus, what is considered to
be "Big" in one year will become ordinary in later years. "For
some organizations, facing hundreds of gigabytes of data for the first time may
trigger a need to reconsider data management options. For others, it may take
tens or hundreds of terabytes before data size becomes a significant consideration."
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