Which practices help maintain data integrity throughout its lifecycle?

• A. Data accuracy and consistency across all processes even when data is duplicated.
• B. Data deletion when not needed.
• C. Frequent random modification of datasets.
• D. Validation, audits, and secure systems.

Answer: (C)

Keeping data accurate, consistent, and trustworthy from creation to deletion requires verification, monitoring, and strong protection. Validation checks ensure data meets required formats and rules at entry and during processing, preventing bad data from entering the system. Audits provide ongoing oversight, detect anomalies or unauthorized changes, and help verify the data’s history. Secure systems—encompassing access controls, encryption, reliable backups, and protected storage—reduce the risk of tampering or loss. Together, these practices uphold data quality throughout its lifecycle.

Data deletion is about retention and disposal policies, not ensuring ongoing integrity. Frequent random modification introduces errors and undermines trust in the data. While data accuracy and consistency are essential, duplicating data without proper controls can create inconsistencies rather than preserve integrity.