What is a key aspect of DG procedures?

What is a key aspect of DG procedures?

• A. Tracking employee performance only
• B. Identifying, capturing, and logging issues
• C. Ignoring issues to maintain workflow
• D. Decreasing stakeholder involvement

Answer: (B)

A key aspect of data governance (DG) procedures involves identifying, capturing, and logging issues related to data management practices. This process is essential for maintaining data quality, compliance, and overall governance. By systematically identifying and documenting issues, organizations can implement strategies to resolve them and improve their data management frameworks. This proactive approach helps ensure that data remains trustworthy, accurate, and effectively utilized across the organization. In contrast, focusing solely on tracking employee performance does not address the broader scope of data governance, which encompasses data accuracy and quality among other things. Ignoring issues to maintain workflow runs counter to the principles of data governance, as it would ultimately lead to unaddressed problems that could escalate and affect data integrity. Additionally, a decrease in stakeholder involvement would undermine the collaborative nature of effective data governance, where stakeholder engagement is crucial for comprehensively addressing data-related challenges and ensuring that governance procedures are aligned with business objectives.

A key aspect of data governance (DG) procedures involves identifying, capturing, and logging issues related to data management practices. This process is essential for maintaining data quality, compliance, and overall governance. By systematically identifying and documenting issues, organizations can implement strategies to resolve them and improve their data management frameworks. This proactive approach helps ensure that data remains trustworthy, accurate, and effectively utilized across the organization.

In contrast, focusing solely on tracking employee performance does not address the broader scope of data governance, which encompasses data accuracy and quality among other things. Ignoring issues to maintain workflow runs counter to the principles of data governance, as it would ultimately lead to unaddressed problems that could escalate and affect data integrity. Additionally, a decrease in stakeholder involvement would undermine the collaborative nature of effective data governance, where stakeholder engagement is crucial for comprehensively addressing data-related challenges and ensuring that governance procedures are aligned with business objectives.