Lesson 4.3: Data Quality Assurance
Description: In this lesson, you will explore common data quality issues – the “seven sins of data quality” – and learn practical solutions and best practices for ensuring high-quality data.
By the end of this lesson, you will be able to:
- Explain the importance of data quality for the ACQF QCP.
- Define and apply core data quality dimensions (accuracy, completeness, consistency, timeliness, validity, integrity, uniqueness) to qualification data.
- Identify common data quality issues, including the “seven sins of data quality,” and their impact in a qualifications context.
- Describe practical data quality assurance processes, including validation techniques and checklists.
Data entry checklist (during and after submission of data)
The following data entry checklist helps you ensure that qualification data uploaded to the QCP is complete, accurate, consistent, and aligned with the African Learning Model (ALM).
This checklist guides personnel through a structured process of verification, validation, and quality assurance at each stage of data handling. By following this checklist, teams can avoid common errors, inconsistencies, and misalignments with national or international frameworks.
Keep in mind that this is a generic checklist – tailor it to fit the national data structure of your qualification (for example,. to include notes on how the mapping process is done to the ALM), the work organisation and roles within your team, and the data storage method that you currently use.
References
QCP Training Unit 3: Mapping and Standardising Qualifications Data