异构数据库数据集成挑战分析

M. Almutairi, M. Yamin, G. Halikias
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引用次数: 1

摘要

互联网产生了大量的结构化和非结构化数据,这给存储、维护、管理、共享、隐私和安全带来了挑战。在当今世界,各组织在一个集中位置交换和合并不同类型的数据,以进行分析,并使组织和个人在实现其业务、经济、社会、教育、文化和卫生目标方面受益。由于存在不同类型的数据格式、结构、模型、模式、实体、属性和特性,数据合并或集成是一个具有挑战性的过程。集成是一个复杂而繁琐的过程,涉及许多技术和广泛的处理,因此集成具有各种数据格式和类型的非常大的数据并不是直截了当的。本文讨论了数据集成过程中面临的问题和复杂性。本文还讨论了不同的数据集成方法及其优缺点,并提供了比较分析,以便从最近完成的项目的例子中获得更好的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Analysis of Data Integration Challenges from Heterogeneous Databases
The Internet generates very large amounts of structured and unstructured data which creates storage, maintenance, management, sharing, privacy and security challenges. In the world today, organizations exchange and merge different types of data at a centralized location for the purpose of analysis and benefitting the organisations and individuals in achieving their business, economic, social, educational, cultural, and health objectives. The data merging or integration is a challenging process because of different type of data formats, structures, models, schemas, entities, attributes, and features. Integration is a complex and tedious process, and involves a number of technologies and extensive processing, and so it is not straightforward to integrate very large data with a variety of data formats and types. This paper discusses issues and complexities faced in data integration processes. The paper also discusses different methods of data integration, their advantages and disadvantages, and provides a comparative analysis to gain better insights from examples of recently completed projects.
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