Big data investment and knowledge integration in academic libraries

S. Manaseer, Afnan Alawneh, Dua Asoudi
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引用次数: 5

Abstract

Recently, big data investment has become important for organizations, especially with the fast growth of data following the huge expansion in the usage of social media applications, and websites. Many organizations depend on extracting and reaching the needed reports and statistics. As the investments on big data and its storage have become major challenges for organizations, many technologies and methods have been developed to tackle those challenges. One of such technologies is Hadoop, a framework that is used to divide big data into packages and distribute those packages through nodes to be processed, consuming less cost than the traditional storage and processing methods. Moreover, it allows an organization to store all its data, unlike the traditional methods of selecting and discarding some data. In this study, researchers investigate the investment of Hadoop in managing the academic libraries’ big data, focusing on three Vs (velocity, variety, and volume). The studied population is academic libraries in Jordanian universities, and the results show how Hadoop framework using the map/reduce technique can be used to manage the big data of such libraries.
高校图书馆大数据投资与知识整合
最近,大数据投资对组织来说变得越来越重要,特别是随着社交媒体应用程序和网站的使用急剧扩大,数据的快速增长。许多组织依赖于提取和获得所需的报告和统计数据。随着对大数据及其存储的投资成为组织面临的主要挑战,许多技术和方法已经开发出来应对这些挑战。其中一种技术是Hadoop,它是一个框架,用于将大数据分成包,并通过节点分发这些包进行处理,比传统的存储和处理方法消耗的成本更低。此外,它允许组织存储其所有数据,而不像传统方法那样选择和丢弃一些数据。在这项研究中,研究人员调查了Hadoop在管理学术图书馆大数据方面的投资,重点关注三个v(速度、种类和数量)。研究对象是约旦大学的学术图书馆,结果显示了Hadoop框架如何使用map/reduce技术来管理这些图书馆的大数据。
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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