Big Data as a Driving Tool of Digital Transformation

Harshini Priya Adusumalli
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引用次数: 1

Abstract

As a result of this research, it was discovered how Big Data is characterized by the five Vs: Velocity, Volume, Variety, Veracity, and Value; and how Hadoop and other tools, in conjunction with distributed computing capacity, are utilized to meet the needs of Big Data. The research defines the abilities necessary to analyze Big Data, as well as the method of Data Mining and how it generates results, and it also includes recommendations. Physicians may use data science to give the best care possible for their patients, and meteorologists can use it to anticipate the scope of local meteorological occurrences. Data science can even be used to predict natural disasters such as earthquakes and tornadoes. Capturing data is an excellent way for businesses to begin their data science journeys. They can begin evaluating the data as soon as they obtain it. Here are some examples of how people produce data and how corporations such as Netflix, Amazon, United Parcel Service (UPS), Google, and Apple exploit the data generated by their customers and workers. When a Data Science project is completed, the final output should be used to communicate new information and insights gained from the data analysis to important decision-makers.  
大数据作为数字化转型的驱动工具
通过这项研究,我们发现了大数据的五个v特征:速度(Velocity)、体积(Volume)、多样性(Variety)、准确性(Veracity)和价值(Value);以及如何利用Hadoop和其他工具,结合分布式计算能力来满足大数据的需求。该研究定义了分析大数据所需的能力,以及数据挖掘的方法及其产生结果的方式,还包括建议。医生可以使用数据科学为病人提供最好的护理,气象学家可以使用它来预测当地气象事件的范围。数据科学甚至可以用来预测自然灾害,如地震和龙卷风。获取数据是企业开始数据科学之旅的绝佳方式。他们可以在获得数据后立即开始评估数据。以下是一些例子,说明人们如何产生数据,以及Netflix、亚马逊、联合包裹服务公司(UPS)、谷歌和苹果等公司如何利用客户和员工产生的数据。当一个数据科学项目完成后,最终的输出应该用于向重要的决策者传达从数据分析中获得的新信息和见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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