What involves monitoring the quality of data in the DQ lifecycle check stage?

What involves monitoring the quality of data in the DQ lifecycle check stage?

• A. Reviewing past documents
• B. Measuring against predefined requirements
• C. Eliminating non-compliant data
• D. Ignoring data quality until issues arise

Answer: (B)

Measuring against predefined requirements is a fundamental aspect of monitoring data quality in the data quality (DQ) lifecycle check stage. This stage focuses on assessing data to ensure it meets established standards and criteria for accuracy, completeness, consistency, relevancy, and timeliness. By comparing the characteristics of the data to these specific benchmarks, organizations can identify areas where the data may fall short, which is essential for making informed decisions and maintaining the integrity of the data. This process allows for systematic evaluation and enables organizations to proactively address potential data quality issues rather than waiting until problems become apparent. Setting and following predefined requirements provides a measurable way to determine whether data is fit for its intended purpose, helping to maintain high data quality throughout its lifecycle.

Measuring against predefined requirements is a fundamental aspect of monitoring data quality in the data quality (DQ) lifecycle check stage. This stage focuses on assessing data to ensure it meets established standards and criteria for accuracy, completeness, consistency, relevancy, and timeliness. By comparing the characteristics of the data to these specific benchmarks, organizations can identify areas where the data may fall short, which is essential for making informed decisions and maintaining the integrity of the data.

This process allows for systematic evaluation and enables organizations to proactively address potential data quality issues rather than waiting until problems become apparent. Setting and following predefined requirements provides a measurable way to determine whether data is fit for its intended purpose, helping to maintain high data quality throughout its lifecycle.