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An organization is increasingly concerned about loss of sensitive data and asks the risk practitioner to assess the current risk level. Which of the following should the risk practitioner do FIRST?
Correct Answer: A
Review Assignments of Data Ownership for Key Assets: Data Ownership: Ensuring that data ownership is clearly assigned helps establish accountability for data protection. Data owners are responsible for the classification, management, and protection of data. Baseline Understanding: Reviewing data ownership assignments provides a baseline understanding of who is responsible for sensitive data and ensures that the responsibilities are clearly defined and understood. Compliance and Control: Proper data ownership ensures that controls are in place and that there is compliance with data protection policies and regulations. Comparison with Other Options: Identify Staff Who Have Access to Sensitive Data: This is important but should follow the establishment of clear data ownership to ensure that access controls are appropriately applied. Identify Recent and Historical Incidents Involving Data Loss: Reviewing incidents helps understand past issues but does not address current data ownership and accountability. Review the Organization's Data Inventory: While important, a data inventory review is part of understanding data ownership and control but should not be the first step. Best Practices: Clear Documentation: Ensure that data ownership is clearly documented and communicated across the organization. Regular Reviews: Conduct regular reviews of data ownership assignments to ensure they remain accurate and up-to-date. Training and Awareness: Provide training to data owners on their roles and responsibilities regarding data protection and risk management. References: CRISC Review Manual: Highlights the importance of data ownership in managing and protecting sensitive information within an organization. ISACA Guidelines: Recommend establishing clear data ownership and accountability as a foundational step in effective data risk management.