Which of the following is NOT a principle of data quality (DQ)?

Which of the following is NOT a principle of data quality (DQ)?

• A. Lifecycle management
• B. Information overload prevention
• C. Governance
• D. Object measurement

Answer: (B)

Information overload prevention is not considered a principle of data quality. Data quality principles are typically focused on ensuring that data is accurate, consistent, complete, timely, and relevant for its intended use. Lifecycle management involves managing the various stages of data, from creation to disposal, ensuring data remains usable and relevant throughout its life. Governance pertains to the frameworks and policies that guide data management practices, ensuring accountability and compliance with standards. Object measurement focuses on defining metrics and criteria for assessing the quality of data. In contrast, while preventing information overload can be a beneficial practice in data management, it is not a fundamental principle of data quality itself. Data quality principles aim to enhance the intrinsic characteristics of data rather than manage the external challenges related to data utilization and consumption.

Information overload prevention is not considered a principle of data quality. Data quality principles are typically focused on ensuring that data is accurate, consistent, complete, timely, and relevant for its intended use.

Lifecycle management involves managing the various stages of data, from creation to disposal, ensuring data remains usable and relevant throughout its life. Governance pertains to the frameworks and policies that guide data management practices, ensuring accountability and compliance with standards. Object measurement focuses on defining metrics and criteria for assessing the quality of data.

In contrast, while preventing information overload can be a beneficial practice in data management, it is not a fundamental principle of data quality itself. Data quality principles aim to enhance the intrinsic characteristics of data rather than manage the external challenges related to data utilization and consumption.