How does data governance (DG) help in data quality (DQ) efforts?

How does data governance (DG) help in data quality (DQ) efforts?

• A. By eliminating the need for data policies
• B. By setting priorities and developing standards
• C. By prioritizing financial investments over quality
• D. By simplifying data access for stakeholders

Answer: (B)

Data governance plays a crucial role in enhancing data quality efforts by setting priorities and developing standards that guide how data is managed, maintained, and utilized across an organization. Establishing a framework for data governance ensures that there are clear guidelines and protocols in place that dictate what constitutes high-quality data, how to assess and improve that quality, and who is responsible for various aspects of data management. By prioritizing the strategic elements of data management, data governance helps organizations determine where to focus their efforts and resources to make meaningful improvements in data quality. This includes defining roles and responsibilities, creating data quality metrics, and ensuring compliance with policies that support the overall integrity of the data. The other options do not align with the core functions of data governance. For instance, eliminating the need for data policies would likely lead to inconsistencies and potential data quality issues. Prioritizing financial investments over quality undermines the goal of improving data integrity, while simplifying data access does not directly address the standards and practices necessary for ensuring high data quality.

Data governance plays a crucial role in enhancing data quality efforts by setting priorities and developing standards that guide how data is managed, maintained, and utilized across an organization. Establishing a framework for data governance ensures that there are clear guidelines and protocols in place that dictate what constitutes high-quality data, how to assess and improve that quality, and who is responsible for various aspects of data management.

By prioritizing the strategic elements of data management, data governance helps organizations determine where to focus their efforts and resources to make meaningful improvements in data quality. This includes defining roles and responsibilities, creating data quality metrics, and ensuring compliance with policies that support the overall integrity of the data.

The other options do not align with the core functions of data governance. For instance, eliminating the need for data policies would likely lead to inconsistencies and potential data quality issues. Prioritizing financial investments over quality undermines the goal of improving data integrity, while simplifying data access does not directly address the standards and practices necessary for ensuring high data quality.