The first step toward the effective management of personal data assets is to create a personal data inventory, which is a comprehensive list of the personal data that an organization collects, processes, stores, transfers, and disposes of. A personal data inventory helps an organization to understand the types, sources, locations, owners, purposes, and retention periods of the personal data it holds, as well as the risks and obligations associated with them. A personal data inventory is essential for complying with data privacy laws and regulations, such as the GDPR or the PDPA, which require organizations to implement data protection principles and practices, such as obtaining consent, providing notice, ensuring data quality and security, respecting data subject rights, and reporting data breaches. A personal data inventory also helps an organization to identify and mitigate data privacy risks and gaps, and to implement data minimization and data security controls.
Reference:
ISACA, Data Privacy Audit/Assurance Program, Control Objective 3: Data Inventory and Classification1 ISACA, Simplify and Contextualize Your Data Classification Efforts2 PDPC, Managing Personal Data3 PDPC, PDPA Assessment Tool for Organisations4

A virtual private network (VPN) is a technology that creates a secure and encrypted connection over a public network, such as the internet. A VPN should be established first before authorizing remote access to a data store containing personal data, as it protects the data from unauthorized interception, modification, or disclosure by third parties. A VPN also helps to ensure the identity and authenticity of the remote users and devices accessing the data store. Reference: 2 Domain 2, Task 8

Transport Layer Security (TLS) is a protocol that provides secure communication over the internet by encrypting and authenticating data. TLS provides data integrity through the calculation of message digests, which are cryptographic hashes that summarize the content and structure of a message. The sender and the receiver of a message can compare the message digests to verify that the message has not been altered or corrupted during transmission. TLS also uses digital certificates, asymmetric encryption, and symmetric encryption to provide confidentiality and authentication, but these are not directly related to data integrity.

Pseudonymization is a technique that replaces or removes direct identifiers from personal data, such as names, addresses, or social security numbers, with pseudonyms, such as codes, tokens, or random values. However, pseudonymization does not eliminate the possibility of re-identification, as the original data can still be linked back to the pseudonyms using additional information or techniques. Therefore, if a database containing pseudonymized personal data is breached, the IT privacy practitioner should be most concerned about the risk of re-identification, which could compromise the privacy and security of the data subjects. The other options are less relevant or important than the risk of re-identification.

Anonymization is a technique that removes or modifies all identifiers in a data set to prevent or limit the identification of the data subjects. Anonymization is an IT privacy practitioner's best recommendation to reduce privacy risk before an organization provides personal data to a third party, as it would protect the privacy of the data subjects by reducing the linkability of the data set with their original identity, and also comply with the data minimization principle that requires limiting the collection, storage and processing of personal data to what is necessary and relevant for the intended purposes. Anonymization would also preserve some characteristics or patterns of the original data that can be used for analysis or research purposes by the third party, without compromising the accuracy or quality of the results. The other options are not as effective as anonymization in reducing privacy risk before an organization provides personal data to a third party. Tokenization is a technique that replaces sensitive or confidential data with non-sensitive tokens or placeholders that do not reveal the original data, but it does not prevent or limit the identification of the data subjects, as tokens can be reversed or linked back to the original data using a tokenization system or key. Aggregation is a technique that combines individual data into groups or categories that do not reveal the identity of the data subjects, but it may not prevent or limit the identification of the data subjects, as aggregated data can be de-aggregated or re-identified using other sources of information or techniques. 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 prevent or limit the identification of the data subjects, as encrypted data can be decrypted or linked back to the original data using an encryption system or key1, p. 74-75 Reference: 1: CDPSE Review Manual (Digital Version)