Overview
Sound decisions rely on high-quality data, which is why it's crucial to ensure the data are of good quality. The Data Quality Review (DQR) protocol is designed to evaluate the quality of the data produced by Monitoring and Evaluation Systems. It establishes a system to evaluate data quality by conducting regular data monitoring, yearly independent data quality reviews, and periodic comprehensive program assessments. The goal is to identify weaknesses in the data management system and implement measures for system strengthening, as well as track data quality performance over time and the capacity to produce high-quality data. The six primary factors we utilize to gauge Data quality are: accuracy, completeness, consistency, timeliness, validity, and uniqueness.
Other Solutions
Overview
Sound decisions rely on high-quality data, which is why it's crucial to ensure the data are of good quality. The Data Quality Review (DQR) protocol is designed to evaluate the quality of the data produced by Monitoring and Evaluation Systems. It establishes a system to evaluate data quality by conducting regular data monitoring, yearly independent data quality reviews, and periodic comprehensive program assessments. The goal is to identify weaknesses in the data management system and implement measures for system strengthening, as well as track data quality performance over time and the capacity to produce high-quality data. The six primary factors we utilize to gauge Data quality are: accuracy, completeness, consistency, timeliness, validity, and uniqueness.
