Explanation
Data anonymization is a method of protecting personal data by modifying or removing any information that can be used to identify an individual, either directly or indirectly, in a data set. Data anonymization aims to prevent the re-identification of the data subjects, even by the data controller or processor, or by using additional data sources or techniques. Data anonymization also helps to comply with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA), which require data controllers and processors to respect the privacy rights and preferences of the data subjects.
The data is transformed such that re-identification is impossible is an example of data anonymization, as it involves applying irreversible techniques, such as aggregation, generalization, perturbation, or synthesis, to alter the original data in a way that preserves their utility and meaning, but eliminates their identifiability. For example, a database of customer transactions can be anonymized by replacing the names and addresses of the customers with random codes, and by adding noise or rounding to the amounts and dates of the transactions.
The other options are not examples of data anonymization, but of other methods of protecting personal data that do not guarantee the impossibility of re-identification. The data is encrypted and a key is required to re-identify the data is an example of data pseudonymization, which is a method of replacing direct identifiers with pseudonyms, such as codes or tokens, that can be linked back to the original data with a key or algorithm.
Data pseudonymization does not prevent re-identification by authorized parties who have access to the key or algorithm, or by unauthorized parties who can break or bypass the encryption. Key fields are hidden and unmasking is required to access to the data is an example of data masking, which is a method of concealing or obscuring sensitive data elements, such as names or credit card numbers, with characters, symbols or blanks.
Data masking does not prevent re-identification by authorized parties who have permission to unmask the data, or by unauthorized parties who can infer or guess the hidden data from other sources or clues. Names and addresses are removed but the rest of the data is left untouched is an example of data deletion, which is a method of removing direct identifiers from a data set. Data deletion does not prevent re-identification by using indirect identifiers, such as age, gender, occupation or location, that can be combined or matched with other data sources to re-establish the identity of the data subjects.
References:
* Big Data Deidentification, Reidentification and Anonymization – ISACA, section 2: “Anonymization is the ability for the data controller to anonymize the data in a way that it is impossible for anyone to establish the identity of the data.”
* Data Anonymization – Overview, Techniques, Advantages, section 1: “Data anonymization is a method of ensuring that the company understands and enforces its duty to secure sensitive, personal, and confidential data in a world of highly complex data protection mandates that can vary depending on where the business and the customers are based.”

Explanation
The proportionality of the data collected for the intended purpose is the most important privacy consideration when developing a contact tracing application. This means that the application should only collect the minimum amount of personal data necessary to achieve the specific and legitimate purpose of preventing and controlling the spread of COVID-191. The application should also ensure that the data collected are relevant, adequate, and not excessive in relation to the purpose2. The application should avoid collecting or processing any data that are not essential for the purpose, such as location data, biometric data, or health data unrelated to COVID-193. The application should also respect the data minimization principle, which requires that the data are kept for no longer than necessary for the purpose4. References:
European Data Protection Board Guidelines 04/2020 on the use of location data and contact tracing tools in the context of the COVID-19 outbreak Article 5(1) of the General Data Protection Regulation (GDPR) Article 29 Data Protection Working Party Opinion 04/2017 on the Proposed Regulation for the ePrivacy Regulation Article 5(1)(e) of the GDPR

Explanation
A third-party privacy control assessment is an independent and objective evaluation of the design and effectiveness of the privacy controls implemented by an organization to protect personal data and comply with privacy laws and regulations. A third-party privacy control assessment can help senior management to verify the success of its commitment to privacy by design, by providing the following benefits:
It can measure the extent to which the organization has adopted and integrated the principles and practices of privacy by design throughout its products, services, processes and systems.
It can identify the strengths and weaknesses of the organization’s privacy governance, policies, procedures, standards and guidelines, and provide recommendations for improvement.
It can validate the organization’s compliance with the applicable privacy requirements and expectations of its customers, stakeholders, regulators and auditors.
It can enhance the organization’s reputation and trustworthiness as a responsible and transparent data controller and processor.
The other options are less effective or irrelevant for verifying the success of the commitment to privacy by design. Reviewing the findings of an industry benchmarking assessment may provide some insights into how the organization compares with its peers or competitors in terms of privacy performance, but it may not reflect the specific privacy goals, risks and challenges of the organization. Identifying trends in the organization’s amount of compromised personal data or number of privacy incidents may indicate some aspects of the organization’s privacy maturity, but they are reactive and lagging indicators that do not capture the proactive and preventive nature of privacy by design. Moreover, these metrics may not account for other factors that may influence the occurrence or impact of data breaches or privacy violations, such as external threats, human errors or environmental changes.
References:
Privacy by Design: How Far Have We Come? – ISACA, section 1: “Privacy by design challenges conventional system thinking. It mandates that any system, process or infrastructure that uses personal data consider privacy throughout its development life cycle.” Privacy Control Assessment – ISACA, section 1: “A Privacy Control Assessment (PCA) is an independent evaluation performed by a qualified assessor to determine whether an entity’s controls are suitably designed and operating effectively to meet its objectives related to protecting personal information.” Privacy by Design: The New Competitive Advantage – ISACA, section 2: “Privacy by design is a proactive approach to embedding privacy into the design specifications of various technologies, business practices and networked infrastructure.”

Explanation
Senior leadership must define the roles and responsibilities of the person with oversight, who is responsible for ensuring compliance with the data privacy policy and applicable laws and regulations. This person may also be known as the data protection officer, the privacy officer, or the chief privacy officer, depending on the organization and jurisdiction. The person with oversight should have the authority, resources, and independence to perform their duties effectively.
References:
* ISACA, CDPSE Review Manual 2021, Chapter 2: Privacy Governance, Section 2.1: Privacy Governance Framework, p. 35-36.
* ISACA, Data Privacy Audit/Assurance Program, Control Objective 1: Data Privacy Governance, p. 4-51

Reference:
When evaluating cloud-based services for backup, one of the most important factors to consider from a privacy regulation standpoint is data residing in another country. This is because different countries may have different privacy laws and regulations that apply to the personal data stored or processed in their jurisdictions. Some countries may have more stringent or protective privacy laws than others, while some countries may have more intrusive or invasive practices that pose threats to data privacy. Therefore, an organization should be aware of the location of its cloud-based backup service provider and its servers, and ensure that there are adequate safeguards and agreements in place to protect the personal data from unauthorized or unlawful access, use, disclosure, or transfer. Reference: : CDPSE Review Manual (Digital Version), page 159

Data mapping is the process of defining how data elements from different sources are related, transformed, and transferred to a common destination. Data mapping is the first step when developing an application link because it helps to ensure that the data exchanged between the API and the third-party application is consistent, accurate, and compatible. Data mapping also helps to identify any gaps, errors, or conflicts in the data and resolve them before the data transfer occurs.
Reference:
What is Data Mapping?, Talend
Data Mapping: What It Is and How to Do It, Xplenty

The most effective way to support organizational privacy awareness objectives is D. Customizing awareness training by business unit function.
A comprehensive explanation is:
Organizational privacy awareness objectives are the goals and expectations that an organization sets for its employees and stakeholders regarding the protection and management of personal dat a. Privacy awareness objectives may vary depending on the nature, scope, and purpose of the organization’s data processing activities, as well as the legal, regulatory, contractual, and ethical obligations and implications that apply to them.
One of the best practices to support organizational privacy awareness objectives is to customize awareness training by business unit function. This means that the organization should design and deliver privacy awareness training programs that are tailored to the specific roles, responsibilities, and needs of each business unit or department within the organization. Customizing awareness training by business unit function can have several benefits, such as:
Enhancing the relevance and effectiveness of the training content and methods for each audience group, by addressing their specific privacy challenges, risks, and opportunities.
Increasing the engagement and motivation of the trainees, by showing them how privacy relates to their daily tasks, goals, and performance.
Improving the retention and application of the training knowledge and skills, by providing practical examples, scenarios, and exercises that reflect the real-world situations and problems that the trainees may encounter.
Fostering a culture of privacy across the organization, by creating a common language and understanding of privacy concepts, principles, and practices among different business units or departments.
Some examples of how to customize awareness training by business unit function are:
Providing different levels or modules of training based on the degree of access or exposure to personal data that each business unit or department has. For example, a basic level of training for all employees, an intermediate level of training for employees who handle personal data occasionally or incidentally, and an advanced level of training for employees who handle personal data regularly or extensively.
Providing different topics or themes of training based on the type or category of personal data that each business unit or department processes. For example, a general topic of training for employees who process non-sensitive or non-personal data, a specific topic of training for employees who process sensitive or special data categories (such as health, biometric, financial, or political data), and a specialized topic of training for employees who process high-risk or high-value data (such as intellectual property, trade secrets, or customer loyalty data).
Providing different formats or modes of training based on the preferences or constraints of each business unit or department. For example, a face-to-face format of training for employees who work in the same location or office, an online format of training for employees who work remotely or across different time zones, and a blended format of training for employees who work in a hybrid mode or have flexible schedules.
The other options are not as effective as option D.
Funding in-depth training and awareness education for data privacy staff (A) may improve the competence and confidence of the data privacy staff who are responsible for designing and implementing the privacy policies and practices of the organization, but it does not necessarily support the organizational privacy awareness objectives for the rest of the employees and stakeholders.
Implementing an annual training certification process (B) may ensure that the employees and stakeholders are updated and refreshed on the privacy policies and practices of the organization on a regular basis, but it does not necessarily address their specific privacy needs and challenges based on their business unit function.
Including mandatory awareness training as part of performance evaluations may incentivize the employees and stakeholders to participate in and complete the privacy awareness training programs offered by the organization, but it does not necessarily enhance their understanding and application of privacy concepts and principles based on their business unit function.
Reference:
The Benefits of Information Security and Privacy Awareness Training Programs1 What Is Your Privacy and Data Protection Strategy?2 What is Data Privacy Awareness?3

Explanation
The best way for an organization to maintain the effectiveness of its privacy breach incident response plan is to conduct annual data privacy tabletop exercises. A tabletop exercise is a simulated scenario that tests the organization’s ability to respond to a privacy breach incident in a realistic and interactive way. A tabletop exercise can help the organization to evaluate the roles and responsibilities of the incident response team, identify the gaps and weaknesses in the plan, improve the communication and coordination among the stakeholders, and update the plan based on the lessons learned and best practices12. A tabletop exercise can also enhance the awareness and readiness of the organization to handle privacy breach incidents in a timely and effective manner3. References:
* ISACA CDPSE Review Manual, Chapter 4, Section 4.3.2
* ISACA Journal, Volume 4, 2019, “Tabletop Exercises: Three Sample Scenarios”
* ISACA Journal, Volume 6, 2017, “Privacy Breach Response: Preparing for the Inevitable”

Reference:
Integrity controls are the types of controls that ensure accuracy at all stages of processing, storage, and deletion throughout the data life cycle. They include methods such as validation, verification, checksums, encryption, hashing, digital signatures, and audit trails. Processing flow controls, time-based controls, and purpose limitation controls are important for privacy, but they do not directly address accuracy. Reference: CDPSE Exam Content Outline, Domain 3, Task 3.1

Privacy threat modeling is a methodology for identifying and mitigating privacy threats in a software architecture. It helps to ensure that privacy is considered in the design and development of software systems, and that privacy risks are minimized or eliminated. Privacy threat modeling typically involves the following steps: defining the scope and context of the system, identifying the data flows and data elements, identifying the privacy threats and their sources, assessing the impact and likelihood of the threats, and applying appropriate countermeasures to mitigate the threats. Reference: : CDPSE Review Manual (Digital Version), page 97

Explanation
A multinational organization that operates across different countries and regions should perform an annual review of changes to privacy regulations in all jurisdictions where its corporate data is processed. This is because different jurisdictions may have different privacy laws and requirements that apply to the collection, use, storage, transfer, and disposal of personal data. For example, the EU General Data Protection Regulation (GDPR) applies to any organization that processes personal data of individuals in the EU, regardless of where the organization is located or where the data is processed. Therefore, the organization should keep track of the changes to privacy regulations in all relevant jurisdictions and update its data privacy policy accordingly to ensure compliance and avoid penalties or lawsuits.

Explanation
Data privacy and data security are related but distinct concepts that are both essential for protecting personal data. Data privacy is about ensuring that personal data are collected, used, shared and disposed of in a lawful, fair and transparent manner, respecting the rights and preferences of the data subjects. Data privacy also involves implementing policies, procedures and controls to comply with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA).
Data privacy protects users from unauthorized disclosure of their personal data, which may result in harm, such as identity theft, fraud, discrimination or reputational damage.
Data security is about safeguarding the confidentiality, integrity and availability of data from unauthorized or malicious access, use, modification or destruction. Data security also involves implementing technical and organizational measures to prevent or mitigate data breaches or incidents, such as encryption, authentication, backup or incident response. Data security prevents compromise of data, which may result in loss, corruption or disruption of data.
References:
The Difference Between Data Privacy and Data Security – ISACA, section 1: “Data privacy is focused on the use and governance of personal data-things like putting policies in place to ensure that consumers’ personal information is being collected, shared and used in appropriate ways.” Practical Data Security and Privacy for GDPR and CCPA – ISACA, section 1: “Data security is the practice of protecting digital information from unauthorized access, corruption or theft throughout its life cycle.”

Reference:
The data owner is the key stakeholder within an organization who should be responsible for approving the outcomes of a privacy impact assessment (PIA). A PIA is a systematic process of identifying and evaluating the potential privacy risks and impacts of a data processing activity or system. The data owner is the person who has the authority and accountability for the data processing activity or system, and who determines the purpose and means of the data processing. The data owner should approve the outcomes of a PIA, such as the risk assessment, the risk mitigation plan, and the residual risk level, to ensure that they are consistent with the business objectives and legal obligations of the data processing activity or system. Reference: : CDPSE Review Manual (Digital Version), page 99