Explanation
Pseudonymization is a technique that replaces direct identifiers in a data set with pseudonyms or artificial identifiers that do not reveal the identity of the data subjects. Pseudonymization is the best method to protect customers' personal data that is forwarded to a central system for analysis, as it reduces the linkability of the data set with the original identity of the customers and thus enhances the privacy and security of the data.
Pseudonymization also preserves some characteristics or patterns of the original data that can be used for analysis or research purposes, without compromising the accuracy or quality of the results. The other options are not as effective as pseudonymization in protecting customers' personal data that is forwarded to a central system for analysis. Deletion is a technique that removes or destroys data from a storage device or media to prevent unauthorized access or recovery of the data, but it does not allow for any analysis or research purposes. Encryption is a technique that transforms plain text data into cipher text using an algorithm and a key, making it unreadable by unauthorized parties, but it does not reduce the linkability of the data set with the original identity of the customers and may require additional security measures to protect the encryption keys or certificates. Anonymization is a technique that removes or modifies all identifiers in a data set to prevent or limit the identification of the data subjects, but it may affect the accuracy or quality of the analysis or research results, as some characteristics or patterns of the original data may be lost or distorted1, p. 74-75 References: 1: CDPSE Review Manual (Digital Version)

Explanation
Incorporating privacy checkpoints into the secure development life cycle (SDLC) is the best way to avoid collecting personal data that was not part of the privacy impact assessment (PIA). Privacy checkpoints are stages in the SDLC where privacy requirements and risks are reviewed and validated, and any changes or deviations from the original PIA are identified and addressed. Privacy checkpoints help ensure that privacy is embedded throughout the system design and development, and that any changes are documented and approved.
References:
ISACA, CDPSE Review Manual 2021, Chapter 3: Privacy by Design, Section 3.2: Privacy Engineering, p. 97-98.

Explanation
A privacy impact assessment (PIA) is a systematic process to identify and evaluate the potential privacy impacts of a system, project, program or initiative that involves the collection, use, disclosure or retention of personal data. A PIA should be done first to address privacy risk when migrating customer relationship management (CRM) data to a new system, as it would help to ensure that privacy risks are identified and mitigated before the migration is executed. A PIA would also help to ensure compliance with privacy principles, laws and regulations, and alignment with customer expectations and preferences. The other options are not as important as performing a PIA when addressing privacy risk when migrating CRM data to a new system. Developing a data migration plan is a process of defining and documenting the objectives, scope, approach, methods and steps for transferring data from one system to another, but it does not necessarily address privacy risk or impact. Conducting a legitimate interest analysis (LIA) is a process of assessing whether there is a legitimate interest for processing personal data that outweighs the rights and interests of the data subjects, but it is only applicable in certain jurisdictions and situations where legitimate interest is a valid legal basis for processing. Obtaining consent from data subjects is a process of obtaining their permission or agreement before collecting, using, disclosing or transferring their personal data for specific purposes, but it may not be required or sufficient for migrating CRM data to a new system, depending on the context and nature of the migration and the applicable laws and regulations1, p. 67 References: 1: CDPSE Review Manual (Digital Version)

Explanation
The right to be forgotten is a privacy right that allows individuals to request the deletion or removal of their personal data from a data controller's records or systems under certain conditions. One of these conditions is when the data is no longer required for the purpose originally collected, meaning that the data has become obsolete, irrelevant or excessive for fulfilling the initial purpose for which it was obtained or processed by the data controller. The other options are not valid conditions for exercising the right to be forgotten. The data is being used to comply with legal obligations or public interest is an exception that may prevent the data controller from deleting or removing the data upon request, as there may be overriding legitimate grounds for retaining the data for legal compliance or public interest reasons. The individual objects despite legitimate grounds for processing is a condition for exercising the right to object, not the right to be forgotten, which allows individuals to oppose the processing of their personal data based on their particular situation or for direct marketing purposes. The individual's legal residence status has recently changed is not a relevant factor for exercising the right to be forgotten, as it does not affect the necessity or relevance of the data for its original purpose1, p. 107-108 References: 1: CDPSE Review Manual (Digital Version)