Data Quality Management (DQM) refers to the processes and practices that ensure the accuracy, consistency, and reliability of data within an organization. It involves identifying and correcting errors, standardizing data formats, and implementing policies to maintain high data quality over time. DQM is essential for making informed decisions, as poor data quality can lead to incorrect conclusions and ineffective strategies. Effective DQM typically includes several key components, such as data profiling, data cleansing, and data governance. These components work together to monitor data quality metrics, establish data standards, and ensure compliance with regulations. By prioritizing DQM, organizations can enhance their operational efficiency and improve overall performance.