确定大数据的维度和结构

Meenu Dave, Jahangir Kamal
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引用次数: 5

摘要

随着大数据得到认可,所有以电子方式大量存储的东西都不能被称为大数据。如今,人们正在努力从分析大数据中提取最大限度的有用信息,因为大数据对组织的价值越来越大,与小数据商店相比,大数据商店中有大量可操作的关系。来自各个组织或行业的大数据是基于一定的特征(维度)和结构被认可的。大数据的特征从3v (Volume, Velocity, Variety)开始,但新的维度也在不断进化,从而拓宽了大数据的维度和定义。本文阐述了学术界和企业界对大数据的新定义以及大数据日益增长的特点和结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying big data dimensions and structure
As the Big Data gets recognition, everything that is being stored electronically in bulk cannot be termed as Big Data. Nowadays efforts are being made to extract maximum useful information from analyzing Big Data, as it contains growing value to the organization and actionable relationships are abundantly found in Big Data stores as compared to the small stores. Big Data from various organizations or industries is being recognized on the basis of certain characteristics (dimensions) and structure. The characteristics of Big Data started with 3Vs (Volume, Velocity, and Variety), but new dimensions are getting evolved day by day and thus broadening the dimensions and definition of Big Data. In this paper, the growing characteristics and structure of Big Data with new definitions from academia and corporate world have been elaborated.
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