Complete CISA Isaca Materials

The best reason to implement a data retention policy is to limit the liability associated with storing and protecting information. A data retention policy is a business’ established protocol for maintaining information, typically defining what data needs to be retained, the format in which it should be kept, how long it should be stored for, whether it should eventually be archived or deleted, who has the authority to dispose of it, and what procedure to follow in the event of a policy violation1. A data retention policy can help an organization to:

Comply with legal and regulatory requirements that mandate the retention and disposal of certain types of data, such as financial records, health records, or personal data

Reduce the risk of data breaches, theft, loss, or corruption by minimizing the amount of data stored and ensuring proper security measures are in place

Save costs and resources by optimizing the use of storage space and reducing the need for backup and recovery operations

Enhance operational efficiency and performance by eliminating unnecessary or outdated data and improving data quality and accessibility

Support business continuity and disaster recovery plans by ensuring critical data is available and recoverable in case of an emergency

Facilitate audit trails and investigations by providing evidence of data authenticity, integrity, and provenance

Therefore, by implementing a data retention policy, an organization can limit its liability associated with storing and protecting information, as well as improve its data governance and management practices.

References:

Data Retention Policy 101: Best Practices, Examples & More

If the audit team lacks the necessary knowledge to audit a system that uses an AI algorithm, engaging external consultants who have audit experience and knowledge of AI would be the best approach12. These consultants can provide the expertise needed to effectively audit the AI system12. This approach ensures that the audit is conducted thoroughly and accurately, without requiring the audit team to acquire new skills or knowledge12.

References:

Auditing Guidelines for Artificial Intelligence - ISACA

An In-Depth Guide To Audit AI Models - Censius

Beta testing is the process of releasing a near-final version of a software product to a group of external users, known as beta testers, who provide feedback and report bugs based on their real-world experiences. Beta testingoffers various benefits for both the developers and the users of the software product. Some of these benefits are:

It reduces product failure risk via customer validation12.

It helps to test post-launch infrastructure1.

It helps to improve product quality via customer feedback12.

It allows for thorough bug detection and issue resolution3.

It enhances usability and user experience3.

It increases customer satisfaction and loyalty3.

Based on these benefits, the most important advantage of participating in beta testing of software products is D. It enables an organization to gain familiarity with new products and their functionality. By being involved in beta testing, an organization can learn how to use the new product effectively, discover its features and benefits, and provide suggestions for improvement. This can help the organization to adopt the new product faster, easier, and more efficiently when it is officially released. It can also give the organization a competitive edge over other users who are not familiar with the new product.

The best option for the question is C, information owner. This is because:

The information owner is the person or entity that has the authority and responsibility for the business processes and functions that collect, use, store, and dispose of data1.

The information owner is accountable for ensuring that the data is handled in compliance with the applicable laws, regulations, policies, and standards, such as the GDPR and the PIPEDA1234.

The information owner is in the best position to determine the purpose and necessity of collecting and retaining data, as well as the risks and benefits associated with it1.

The information owner should consult with other stakeholders, such as the risk manager, the database administrator (DBA), and the privacy manager, to establish and implement appropriate data classification policies and procedures2.

Data classification is the process of organizing data in groups based on their attributes and characteristics, and then assigning class labels that describe a set of attributes that hold true for the corresponding data sets345.

Data classification helps organizations to identify, manage, protect, and understand their data, as well as to comply with modern data privacy regulations345.

Data classification also helps to determine appropriate user access levels, which means defining who can access, modify, share, or delete data based on their roles, responsibilities, and needs345.

Therefore, the information owner should be responsible for the data classification in an ERP migration project from local systems to the cloud (option C), as they have the authority and accountability for the data and its protection.

The other options are not correct because:

The information security officer (option A) is responsible for overseeing and coordinating the security policies and practices of the organization that involve data6. The information security officer should advise and assist the information owner on the best practices and standards for data security, but not determine the data classification.

The database administrator (DBA) (option B) is responsible for installing, configuring, monitoring, maintaining, and improving the performance of databases and data stores that contain data5. The DBA should support the information owner in implementing and enforcing the data classification policies and procedures, but not determine them.

The data architect (option D) is responsible for designing, modeling, and documenting the logical and physical structures of databases and data stores that contain data7. The data architect should collaborate with the information owner in creating and maintaining the data classification schema and metadata, but not determine them.