Explanation
The best way to maintain the quality of personal data is to implement routine automatic validation, which is a process of checking the accuracy, completeness, consistency, and timeliness of the data using automated tools or scripts. Routine automatic validation can help identify and correct any errors, anomalies, or discrepancies in the data, as well as ensure that the data meets the specified quality standards and requirements. Routine automatic validation can also help improve the efficiency and reliability of the data processing and analysis12.
References:
* CDPSE Exam Content Outline, Domain 3 - Data Lifecycle (Data Quality), Task 2: Implement data quality measures3.
* CDPSE Review Manual, Chapter 3 - Data Lifecycle, Section 3.2 - Data Quality4.

Explanation
The practice that best indicates an organization follows the data minimization principle is that data is regularly reviewed for its relevance. The data minimization principle is one of the core principles of data protection under various laws and regulations, such as the GDPR or the CCPA. It states that personal data should be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed.
By regularly reviewing the data they hold, organizations can ensure that they do not collect or retain excessive or unnecessary data that may pose privacy risks or violate data subject rights.
Data is pseudonymized when being backed up, data is encrypted before storage, or data is only accessible on a need-to-know basis are also good practices for data protection, but they do not directly indicate that the organization follows the data minimization principle. Pseudonymization is a process of replacing identifying information in data with artificial identifiers or pseudonyms. Pseudonymization can help enhance the privacy of data by reducing the linkability between data and data subjects, but it does not prevent re-identification or inference attacks. Encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Encryption can help protect the confidentiality, integrity, and availability of data by preventing unauthorized access, disclosure, or modification. Access control is a process of restricting who can access, modify, or delete data based on their roles, permissions, or credentials. Access control can help prevent unauthorized or inappropriate use of data by limiting the scope of access.
References: Data Minimization | Washington Technology Solutions, What Is Data Minimization? The Principles According to GDPR | 2BAdvice, Data Protection Principles: Core Principles of the GDPR - Cloudian

Explanation
The principle of data minimization states that personal data should be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed. By using only the data required by the application, the organization can reduce the amount of data that is collected, stored, processed and potentially exposed. This can also help the organization comply with privacy laws and regulations that require data minimization, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
References:
* CDPSE Review Manual, 2021 Edition, ISACA, page 98
* [Data minimization], European Commission