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This randomized trial examines anonymization strategies to protect data privacy in SAP systems, suggesting effective compliance methods.
Privacy regulations such as the GDPR, CCPA, and HIPAA have narrowed the conditions under which enterprises may reuse personal data, and SAP teams feel this constraint acutely whenever production data is copied into non-production systems. This paper examines how organizations can protect sensitive information in SAP landscapes without destroying the functional realism that development, QA, and training environments depend on. It distinguishes anonymization from masking and encryption, surveys four practical anonymization strategies, and proposes field-level treatment guidance that preserves business-process validity. A field case from a European financial institution illustrates how rule-based anonymization can deliver audit-approved compliance while retaining full test capability. The paper concludes with an implementation checklist aimed at SAP Basis and data-management practitioners.
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Puneet Khatri (2026) studied this question.
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