Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.
Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics,
or certain other advanced data analytics methods that extract value
from data, and seldom to a particular size of data set. "There is little
doubt that the quantities of data now available are indeed large, but
that’s not the most relevant characteristic of this new data ecosystem."[2] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on."[3] Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics,[4] connectomics, complex physics simulations, biology and environmental research.[5]
Data sets grow rapidly - in part because they are increasingly gathered by cheap and numerous information-sensing Internet of things devices such as mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.[6][7] The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s;[8] as of 2012, every day 2.5 exabytes (2.5×1018) of data are generated.[9] One question for large enterprises is determining who should own big-data initiatives that affect the entire organization.[10]
Relational database management systems
and desktop statistics- and visualization-packages often have
difficulty handling big data. The work may require "massively parallel
software running on tens, hundreds, or even thousands of servers".[11]
What counts as "big data" varies depending on the capabilities of the
users and their tools, and expanding capabilities make big data a moving
target. "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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