Data Collection Quality: How to Ensure Data Quality

This article shares actionable steps and best practices for ensuring data quality during digital data collection, including real-time checks and enumerator training. It discusses the importance of training data collectors to follow standardized procedures for data entry and ensuring that data is validated at the point of collection. The article also emphasizes the need for real-time data validation checks to catch errors early and prevent inaccurate data from being entered into the system. By following these best practices, organizations can ensure that their digital data collection efforts yield high-quality data that is reliable and useful for decision-making and program evaluation.

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Marta Costa

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Data Science for social impact

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