Data quality metrics and frameworks: A comprehensive study for ensuring reliable information systems

In today's data driven enterprise environments, the quality of data plays a pivotal role in ensuring operational efficiency, informed decision making, regulatory compliance, and customer satisfaction. However, despite the exponential growth in data generation, ensuring its accuracy, completeness, and reliability remains a persistent challenge. This paper explores the dimensions of data quality, the key metrics used to measure it, and prominent frameworks adopted by organizations to maintain high data quality standards. Through case studies and comparative analysis, we propose an integrated Data Quality Management (DQM) framework that aligns with modern enterprise needs, especially in the context of big data, data warehousing, and real time analytics.