大数据对企业架构设计的影响:概念回顾

Ira Diana Sholihati, Bayu Yasa Wedha, Sari Ningsih, Ratih Titi Komala Sari
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摘要

本文从概念上分析了大数据对企业架构设计的影响。在不断扩大的数字化框架内,大数据已成为划分组织战略和框架的关键组成部分。本研究旨在探讨大数据如何影响和促进高效企业架构的发展。定性分析是研究人员用来理解企业架构与大数据之间错综复杂的互动关系的方法。本文通过对文献进行广泛综述,研究了几个方面,包括大数据促进分析能力提升、业务流程创新和战略决策的方式。本研究还考虑了新出现的挑战,包括数据安全、隐私和 IT 基础设施调整的必要性。审查结果表明,在企业架构中实施大数据可能会大大改变业务战略和运营。这包括增强系统适应性、提供定制服务和预测功能。不过,这些改变需要对隐私政策、风险管理和数据治理进行修改。本研究就大数据对企业架构的影响提出了新的发现,并为研究人员和从业人员提供了制定和执行成功的大数据战略的建议。因此,本研究增强了现有文献的内容,并为该领域提供了实用指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of Big Data on Enterprise Architectural Design: A Conceptual Review
A conceptual analysis of the impact of big data on enterprise architecture design is provided in this article. Within the framework of expanding digitalization, big data has emerged as a pivotal component in delineating the strategy and framework of organizations. The objective of this study is to investigate the ways in which big data can impact and facilitate the growth of efficient enterprise architecture. Qualitative analysis is the method utilized by researchers to comprehend the intricacies of the interaction between enterprise architecture and big data. This article examines several facets by conducting an extensive review of the literature, including the ways in which big data can facilitate the enhancement of analytical capabilities, innovation in business processes, and strategic decision-making. Emerging challenges, including data security, privacy, and the necessity for IT infrastructure adaptation, are also considered in this study. The outcomes of the review indicate that the implementation of big data in enterprise architecture may substantially alter business strategies and operations. These encompass enhanced system adaptability, customized service provision, and predictive functionalities. Nonetheless, these modifications necessitate modifications to privacy policies, risk management, and data governance. This study presents novel findings regarding the influence of big data on enterprise architecture and provides researchers and practitioners with recommendations for developing and executing successful big data strategies. This research thereby enhances the current body of literature and offers practical guidance in the field.
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