Which of the following is an example of DQ technique?

Which of the following is an example of DQ technique?

• A. Setting economic goals
• B. Preventative actions
• C. Developing data policies
• D. Implementing data governance

Answer: (B)

The choice of preventative actions as an example of a data quality (DQ) technique is particularly relevant because it involves proactive measures to identify and address potential data issues before they escalate. In the realm of data management, preventative actions can include implementing checks and balances, conducting regular data audits, and establishing monitoring systems to catch discrepancies early on. By focusing on preventative measures, organizations can ensure the integrity, accuracy, and reliability of their data over time, thus enhancing overall data quality. In the context of data quality, the other options, while important in the broader field of data management, do not directly exemplify DQ techniques as clearly. Setting economic goals relates more to the overarching objectives of an organization, rather than specific data quality measures. Developing data policies establishes guidelines but does not inherently involve actions to ensure data quality. Implementing data governance is a strategic initiative that includes broader organizational structures and processes which, while essential for maintaining data quality, do not constitute a specific technique that directly addresses data quality issues in the same immediate way that preventative actions do.

The choice of preventative actions as an example of a data quality (DQ) technique is particularly relevant because it involves proactive measures to identify and address potential data issues before they escalate. In the realm of data management, preventative actions can include implementing checks and balances, conducting regular data audits, and establishing monitoring systems to catch discrepancies early on. By focusing on preventative measures, organizations can ensure the integrity, accuracy, and reliability of their data over time, thus enhancing overall data quality.

In the context of data quality, the other options, while important in the broader field of data management, do not directly exemplify DQ techniques as clearly. Setting economic goals relates more to the overarching objectives of an organization, rather than specific data quality measures. Developing data policies establishes guidelines but does not inherently involve actions to ensure data quality. Implementing data governance is a strategic initiative that includes broader organizational structures and processes which, while essential for maintaining data quality, do not constitute a specific technique that directly addresses data quality issues in the same immediate way that preventative actions do.