Enterprise Data Governance : A Comprehensive Framework for Ensuring Data Integrity, Security, and Compliance in Modern Organizations

Authors

  • Deepa Madhavan Amerisoft, USA Author

DOI:

https://doi.org/10.32628/CSEIT241051062

Keywords:

Data Governance, Information Management, Regulatory Compliance, Data Security, Data Quality

Abstract

Enterprise data governance has emerged as a critical function for organizations seeking to maximize the value of their data assets while mitigating risks associated with data management. This article presents a comprehensive framework for implementing effective data governance strategies in modern enterprises. It examines the key components of robust governance structures, including clear policies, well-defined roles and responsibilities, and the establishment of data quality standards. The article explores methods for ensuring regulatory compliance and enhancing data security, emphasizing the importance of risk management and data protection measures. By analyzing case studies across various industries, the article identifies best practices and common challenges in data governance implementation. Additionally, it investigates the impact of emerging technologies such as artificial intelligence and blockchain on data governance practices. The findings underscore the necessity of a holistic approach to data governance that aligns with organizational objectives, fosters a data-driven culture, and adapts to evolving regulatory landscapes. This article contributes to the growing body of knowledge on enterprise data management and provides practical insights for organizations striving to improve their data governance capabilities in an increasingly complex digital environment.

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References

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Published

01-11-2024

Issue

Section

Research Articles

How to Cite

[1]
Deepa Madhavan, “Enterprise Data Governance : A Comprehensive Framework for Ensuring Data Integrity, Security, and Compliance in Modern Organizations”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 10, no. 5, pp. 731–743, Nov. 2024, doi: 10.32628/CSEIT241051062.

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