Data Quality Fundamentals, June 2025
Instructor: Mary Pat Selvaggio and Kris Eale
Data is a critical asset for any program, organization, or business. Poor-quality data degrades knowledge, leading to negative consequences in understanding the world, situations, systems, or events, and poor decision-making that negatively affects all aspects of life (health, social, economics, etc.).
Various factors influence data quality, and shortcomings in these factors will contribute to poor-quality data. As M&E practitioners, we must ensure that the data collected is of the highest possible quality–whether in routine monitoring or evaluations–so that follow-on actions and decisions based on the data are true and correct.
This three-module course will introduce participants to core concepts of data quality and how to structure data management systems for collecting and reporting data, as well as how to assess the quality of data collected and reported.
At the end of this course, participants should understand:
Why data quality is important
The concepts and terminologies used in data quality
The elements of strong data management systems to enhance data quality
The components, tools, and processes of a Data Quality Assessment/Audit
This course is intended for:
Researchers and evaluators
Program Managers
M&E Managers
Any persons working with data.
Read more about each of the modules below. Classes will take place online via Zoom. Certificates of completion will be provided at the end of the course to all participants who successfully complete the three modules.
Module 1: Introduction to Data Quality
June 3, 9 a.m.-12 p.m. EDT
This module presents the rationale for enhancing data quality and introduces core data quality terminology, criteria, and common data quality issues and risks.
Module 2: Data Management Systems
June 5, 9 a.m.-12 p.m. EDT
The second module focuses on the data management systems (DMS) that produce and report data. We will discuss how to structure the DMS for routine reporting and research/evaluation to enhance data quality. We will look at data management concepts and best practices and introduce approaches to correcting errors in M&E data sets.
Module 3: Data Quality Assessments/Audits (DQAs)
June 10, 9 a.m.-12 p.m. EDT
The final module presents the methodology for data quality assessments/audits (DQAs) – whether internal or external – including how to verify the accuracy/precision of data and how to assess the data management system for structural risks that may compromise data quality.
We hope to see you online soon! Please contact us with any questions at learningcenter@encompassworld.com