The Impact of Big Data on Enterprise Architectural Design: A Conceptual Review

Ira Diana  Sholihati; Bayu Yasa  Wedha; Sari  Ningsih; Ratih Titi Komala  Sari

doi:10.47709/cnahpc.v6i1.3449

Authors

Ira Diana Sholihati Prodi Sistem Informasi, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional Jakarta
Bayu Yasa Wedha Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional Jakarta
Sari Ningsih Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional Jakarta
Ratih Titi Komala Sari Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional Jakarta

DOI:

10.47709/cnahpc.v6i1.3449

Keywords:

Enterprise Architecture, Big Data, Architectural Design, Big Data Integration, Conceptual Overview

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Abstract

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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References

Afarini, N., & Hindarto, D. (2023). The Proposed Implementation of Enterprise Architecture in E-Government Development and Services. 3(December), 219–229.

Hindarto, D. (2023a). Application Of Customer Service Enterprise Architecture In The Transportation Industry. Journal of Computer Networks , Architecture and High Performance Computing, 5(2), 682–692.

Hindarto, D. (2023b). Blockchain-Based Academic Identity and Transcript Management in University Enterprise Architecture. 8(4), 2547–2559.

Hindarto, D. (2023c). The Management of Projects is Improved Through Enterprise Architecture on Project Management Application Systems. 3(August), 151–161.

Judijanto, L., & Hindarto, D. (2023). Edge of Enterprise Architecture in Addressing Cyber Security Threats and Business Risks. 3(December), 386–396.

Kornyshova, E., & Deneckère, R. (2022). A Proposal of a Situational Approach for Enterprise Architecture Frameworks: Application to TOGAF. Procedia Computer Science, 207, 3493–3500. https://doi.org/10.1016/j.procs.2022.09.408

Lnenicka, M., & Komarkova, J. (2019). Developing a government enterprise architecture framework to support the requirements of big and open linked data with the use of cloud computing. International Journal of Information Management, 46(December 2018), 124–141. https://doi.org/10.1016/j.ijinfomgt.2018.12.003

Microsoft. (2023). Big data analytics with enterprise-grade security using Azure Synapse. Microsoft. https://learn.microsoft.com/id-id/azure/architecture/solution-ideas/articles/big-data-analytics-enterprise-grade-security

Peng, J., & Bao, L. (2023). Construction of enterprise business management analysis framework based on big data technology. Heliyon, 9(6), e17144. https://doi.org/10.1016/j.heliyon.2023.e17144

Smith, S. M., & Nichols, T. E. (2018). Statistical Challenges in ‘“Big Data”’ Human Neuroimaging. 263–268.

Tamym, L., Benyoucef, L., Nait, A., Moh, S., Driss, M., & Ouadghiri, E. (2023). Big data analytics-based approach for robust, flexible and sustainable collaborative networked enterprises. 55(January).

Yu, Y., & Madiraju, S. (2014). Enterprise application transformation strategy and roadmap design: A business value driven and IT supportability based approach. Proceedings - 2nd International Conference on Enterprise Systems, ES 2014, 66–71. https://doi.org/10.1109/ES.2014.37

Zhao, L., Tan, W., Xie, N., & Huang, L. (2020). An optimal service selection approach for service-oriented business collaboration using crowd-based cooperative computing. 92.

Zhao, X. (2022). Research on management informatization construction of electric power enterprise based on big data technology. 8, 535–545.

Zhou, Z., Matsubara, Y., & Takada, H. (2023). Resilience analysis and design for mobility-as-a-service based on enterprise architecture modeling. 229(March 2022).