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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

A conceptual framework for data governance in big data and cloud environments: Integrating security, compliance, and data quality

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  • A conceptual framework for data governance in big data and cloud environments: Integrating security, compliance, and data quality

Osinachi Deborah Segun-Falade 1, *, Iveren M. Leghemo 2, Chinekwu Somtochukwu Odionu 3 and Chima Azubuike 4

1 TD Bank, Toronto Canada.
2 Kennesaw State University, USA.
3 Independent Researcher, Texas.
4 Guaranty Trust Bank (Nigeria) Limited.

Review Article
 

International Journal of Science and Research Archive, 2024, 12(02), 2984-3002.
Article DOI: 10.30574/ijsra.2024.12.2.1177
DOI url: https://doi.org/10.30574/ijsra.2024.12.2.1177

Received on 21 May 2024; revised on 02 July 2024; accepted on 05 July 2024

The proliferation of big data and cloud computing has transformed the digital landscape, enabling organizations to harness vast amounts of information for strategic decision-making. However, this shift has introduced complex challenges related to data governance, necessitating a comprehensive framework that integrates security, compliance, and data quality. This paper proposes a conceptual framework for data governance in big data and cloud environments, addressing the critical need for a cohesive approach to managing data assets. The framework emphasizes the importance of establishing robust security measures to protect sensitive information from unauthorized access and cyber threats, while ensuring compliance with legal and regulatory requirements across different jurisdictions. The framework also highlights the role of data quality management in maintaining the integrity, accuracy, and reliability of data, which is crucial for deriving meaningful insights and making informed decisions. By integrating these three pillars—security, compliance, and data quality—the proposed framework aims to provide organizations with a structured approach to data governance that enhances data integrity, minimizes risks, and ensures compliance with evolving regulations. Key components of the framework include governance policies, data stewardship roles, data lifecycle management, and continuous monitoring and auditing processes. The framework also addresses the challenges of data governance in distributed and dynamic cloud environments, where data is often decentralized and subject to constant changes. Additionally, it underscores the significance of cross-functional collaboration among IT, legal, and business teams to achieve a unified governance strategy. This conceptual framework offers a holistic approach to data governance, enabling organizations to effectively manage their data assets in the context of big data and cloud computing. It serves as a foundation for developing and implementing data governance practices that are adaptable, scalable, and aligned with organizational goals, ultimately contributing to enhanced data-driven decision-making and competitive advantage.

Data Governance; Big Data; Cloud Computing; Security; Compliance; Data Quality; Framework; Data Stewardship

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2024-1177.pdf

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Osinachi Deborah Segun-Falade, Iveren M. Leghemo, Chinekwu Somtochukwu Odionu and Chima Azubuike. A conceptual framework for data governance in big data and cloud environments: Integrating security, compliance, and data quality. International Journal of Science and Research Archive, 2024, 12(02), 2984-3002. https://doi.org/10.30574/ijsra.2024.12.2.1177

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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