大数据分析工具的比较研究:一项分析研究

Sanjib Kumar Sahu, M. M. Jacintha, A. Singh
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引用次数: 11

摘要

由于数字化,数据集以不同的形式迅速增长。当数据或信息集过于庞大和复杂,传统的数据处理技术无法处理这些复杂的数据时,这种数据就被称为大数据。研究人员、科学家、商业组织、政府机构、广告公司、医学研究人员在处理任何决策的数据时往往遇到更多的困难。可用于研究的数据必须通过使用各种数据分析技术进行处理,这被称为大数据分析。这些技术有助于处理大量快速变化的非结构化、结构化或半结构化数据内容,这些内容也无法使用传统数据库技术进行处理。本文通过比较可用于大数据验证的不同工具,讨论了大数据分析的主要用途。此外,本文还讨论了为克服大数据挑战和需求而进行的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative study of tools for big data analytics: An analytical study
Data sets grow rapidly in different forms due to digitalization. When the data or information sets which are too large and are complex in nature in which traditional data processing techniques are not able to deal with those complex data, then that data is called B ig data. Researchers, scientists, business organizations, government agencies, advertising agencies, medical researchers often come across more difficulty in dealing with data for any decision making. The data available for research has to be processed by using various techniques of data analytics which is called Big Data Analytics. These techniques helps in getting benefits in dealing with massive volume of either unstructured, structured or semi-structured data content that is fast changing nature, also not possible to process using conventional database techniques. This paper discusses the major utilization of big data analytics by comparing different tools available for big data validation. Furthermore, this paper discusses the case study conducted to overcome the big data challenges and needs.
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