Data quality management involves processes and techniques to ensure the accuracy, consistency, reliability, and completeness of data within an organization. This includes activities such as data profiling, cleansing, validation, and monitoring to address issues like duplicates, errors, and inconsistencies. Implementing data quality management helps organizations make informed decisions, improve operational efficiency, and enhance overall data-driven processes.