Which of the following best describes sample metrics in data governance (DG)?

Which of the following best describes sample metrics in data governance (DG)?

• A. Achievements of goals and user satisfaction
• B. Contributions to business objects and reduction of risk
• C. Speed of adoption and market share
• D. Cost reductions and efficiency gains

Answer: (B)

Sample metrics in data governance (DG) primarily aim to evaluate the effectiveness and impact of data governance initiatives on the overall business outcomes and risk management. The correct choice emphasizes the importance of assessing how well data governance contributes to business objectives, ensuring that data is properly utilized, and mitigating associated risks. In the context of data governance, contributions to business objectives involve ensuring that data assets align with the strategic goals of the organization, facilitating better decision-making, compliance, and operational efficiency. Additionally, managing data risks—such as data breaches, inaccuracies, and compliance issues—is paramount in maintaining trust and reliability in data. While other options present valuable aspects of business performance, they do not directly capture the essence of data governance metrics. For instance, achievements of goals and user satisfaction are important but are broader and less specific to the data governance context. Speed of adoption and market share focus more on the pace of implementing solutions rather than the governance of data itself. Cost reductions and efficiency gains reflect operational improvements but do not distinctly highlight the governance aspect of risk and business alignment. Thus, the emphasis on contributions to business objectives and reduction of risk makes this choice the most aligned with the core objectives of data governance metrics.

Sample metrics in data governance (DG) primarily aim to evaluate the effectiveness and impact of data governance initiatives on the overall business outcomes and risk management. The correct choice emphasizes the importance of assessing how well data governance contributes to business objectives, ensuring that data is properly utilized, and mitigating associated risks.

In the context of data governance, contributions to business objectives involve ensuring that data assets align with the strategic goals of the organization, facilitating better decision-making, compliance, and operational efficiency. Additionally, managing data risks—such as data breaches, inaccuracies, and compliance issues—is paramount in maintaining trust and reliability in data.

While other options present valuable aspects of business performance, they do not directly capture the essence of data governance metrics. For instance, achievements of goals and user satisfaction are important but are broader and less specific to the data governance context. Speed of adoption and market share focus more on the pace of implementing solutions rather than the governance of data itself. Cost reductions and efficiency gains reflect operational improvements but do not distinctly highlight the governance aspect of risk and business alignment.

Thus, the emphasis on contributions to business objectives and reduction of risk makes this choice the most aligned with the core objectives of data governance metrics.