Data Quality Management
The process of ensuring that data is accurate, complete, accessible, timely, and trustworthy, enabling effective decision-making and operational efficiency.
Implications
The set of practices and processes used to maintain high standards of data quality within an organization, including data cleansing, validation, and monitoring, essential for ensuring that data is fit for its intended use.
Example
Example: A financial services firm implements data quality management by regularly auditing its customer databases, identifying and correcting inconsistencies, and enforcing standards to maintain data accuracy.
Related Terms
Different from data governance, which provides the framework and policies, data quality management focuses on the specific actions taken to maintain and improve the quality of data.
Get INSTANT comprehensive market research of any industry
Chat with AII Consultant Now!
