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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 cu ration, 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 reduction and reduced risk. Topics like Data integration, Data warehousing, Computational modelling.
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Scope and importance :
Analysis of data sets can find new correlations, to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, 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.
Market analysis :
The Big data market has been achieving strong revenues. The Global Market Statistics shows that it has reached a revenue height of 5.39 USD (billion), 9.15 USD (billion) and 4.12 USD (billion) for services, hardware and software, respectively for the year 2013. The global market statistic also shows a revenue forecast for the global big data market from 2011 to 2017. For 2016, the source projects the global big data market is predicted to grow to more than 45 billion U.S. dollars in revenue.
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This page was last updated on April 3, 2020