Big data refers to very large or complex data that conventional general data processing applications may not be able to work with. The main challenges in working with large data are analysis, compilation, search, storage, transfer, visualisation of data, querying, updating, and information. Confidentiality, etc. Big data is a large or complicated set of data due to the inadequacy of traditional data processing applications. Big data analysis frequently refers to the use of user behaviour analysis or some other innovative data examination method to extract inadequate data. Accuracy and greater confidence in big data lead to better decision making, while better decisions lead to greater efficiency, lower costs and lower risk. Big data "size" is always a moving target, as 2012 data ranged from a few dozen terabytes to several petabytes. Large data sets that are diverse and complex require a set of technologies with new forms and integrations to reveal statistics. Big data is the high volume, high speed, and or high diversity of information assets required to enable advanced decision-making, insight discovery, and optimization processes in new forms of processing. The authors divide massive data definitions into three categories in a popular lesson published in the journal: attribute definitions, comparison definitions, and architectural definitions.

Gokul Pradeep

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