What is the purpose of data quality management according to DAMA-DMBOK?

The purpose of data quality management, as outlined in the DAMA-DMBOK, focuses on ensuring that data is accurate, complete, consistent, and reliable. This is fundamental to the integrity of any data-driven decision-making process. Data quality management involves establishing processes and standards to regularly assess and improve data, ensuring that it meets the necessary criteria for its intended use.

By placing an emphasis on the accuracy and completeness of data, organizations can make informed decisions based on reliable information. Consistency ensures that data can be compared and analyzed universally across different systems and over time, while reliability reflects the trustworthiness of the data. Together, these attributes contribute to better outcomes, operational efficiencies, and enhanced analytics capabilities.

The other options do not pertain directly to the core focus of data quality management. For example, increasing data storage capacity or improving data visualization serves different purposes within data management frameworks, and analyzing socio-economic impacts is a specific application of data, rather than a component of managing its quality.