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

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.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2024-08-30
DOI
https://doi.org/10.30574/ijsra.2024.12.2.1177
Citations
1
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
0.78
Controls
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article

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

Chinekwu Somtochukwu Odionu, Chima Azubuike, Iveren M. Leghemo, Osinachi Deborah Segun-Falade
1 citations
International Journal of Science and Research Archive
Cloud Data Security Solutions
0.78
article

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

Chinekwu Somtochukwu Odionu, Chima Azubuike, Iveren M. Leghemo, Osinachi Deborah Segun-Falade
article en
1 citations

Abstract

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.

International Journal of Science and Research ArchiveVol. 12(2)
Openalex Percentile: Top 18%
Cloud Data Security Solutions
0.78
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