Enterprise Test Data Management: A Comprehensive Framework for Regulatory Compliance and Security in Modern Software Development

Arfi Siddik Mollashaik

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 422-431

Abstract: Test data management (TDM) has emerged as a critical component in enterprise software development, yet organizations face significant challenges in implementing robust frameworks that balance efficiency, security, and regulatory compliance. This article presents a comprehensive framework for enterprise test data management that addresses the complexities of modern software testing environments. The systematically analyze existing methodologies and industry practices and propose an integrated approach encompassing data classification, protection mechanisms, automation strategies, and governance protocols. The framework incorporates automated data provisioning, masking techniques, and lifecycle management while aligning with global privacy regulations. The findings demonstrate that organizations implementing this framework experience enhanced testing efficiency, improved compliance posture, and reduced operational risks. The article contributes to the body of knowledge in software testing by providing actionable insights for enterprises seeking to modernize their test data management practices. Additionally, we identify emerging challenges and future research directions in the context of evolving technology landscapes and regulatory requirements. This article has significant implications for practitioners and researchers in software quality assurance, data governance, and enterprise architecture.

Keywords: Test Data Management (TDM); Enterprise Data Governance; Automated Data Provisioning; Regulatory Compliance; Data Masking Techniques (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25111241
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT25111241 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT25111241/CSEIT25111241 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:697

DOI: 10.32628/CSEIT25111241

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().