Big Data Features As Crucial Concept which Effects Data Interoperability

Sana Ibrahim Shatwan, Weiam S. Elsaghair
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Abstract

Big data has become an exciting term in the last decades, and it conducts a significant rate of data with different features of velocity, variety, value, volume, and veracity. Those features describe big data identity. Think about the data generated by social media websites and apps, such as Facebook, Twitter, and WhatsApp…...Etc. This data is crucial because of the amount, variety, and growth acceleration, but it is exhausting to manage. Big data interoperability indicates the capability to interchange and share the data, information, and knowledge between organizations and devices that knowledge and information were extracted from different data sources. This complex mutual process grows an organization's performance. According to the previous, big data and its five features are essential because of its usability and analytics. Organizations need to extract the expected benefit from preserving and retrieving data. We develop a data interoperability concept, which is improved as data exchangeability can be enriched. In this study, we will discuss the impact of big data feature's value, volume, variety, velocity, and veracity on the interoperability of the data and data exchangeability feasibility and how these features affect the prediction of future decisions in the institution, as well as the interaction and exchange of data between the organizations.
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大数据是影响数据互操作性的关键概念
近几十年来,大数据已经成为一个令人兴奋的术语,它引导着具有速度、种类、价值、数量和准确性等不同特征的大量数据。这些特征描述了大数据身份。想想社交媒体网站和应用程序产生的数据,比如Facebook、Twitter和WhatsApp......等。由于数据的数量、种类和增长速度,这些数据是至关重要的,但管理起来却令人筋疲力尽。大数据互操作性是指从不同数据源中提取知识和信息的组织和设备之间交换和共享数据、信息和知识的能力。这一复杂的相互过程可以提高组织的绩效。根据之前的说法,大数据及其五大特性是必不可少的,因为它的可用性和分析性。组织需要从保存和检索数据中获得预期的好处。我们开发了一个数据互操作性概念,随着数据可交换性的增强,该概念得到了改进。在本研究中,我们将讨论大数据特征的价值、数量、种类、速度和准确性对数据互操作性和数据可交换性可行性的影响,以及这些特征如何影响机构未来决策的预测,以及组织之间数据的交互和交换。
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