📅 2025-06-03 — Session: Comparative Analysis of Data Quality using GQM
🕒 19:50–20:35
🏷️ Labels: GQM, Data Quality, Comparative Analysis, Evaluation, Data Science
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal:
The session aimed to conduct a comparative analysis of data quality using the Goal-Question-Metric (GQM) framework, focusing on evaluating several reports and prioritizing data quality issues.
Key Activities:
- Evaluated four reports (G05, G06, G07, G08) based on their application of the GQM model and data quality.
- Conducted a comparative analysis of data quality for groups 5 to 8 and groups 9 to 17, assessing issues and the application of GQM.
- Prioritized criteria for assessing data quality within the GQM framework, emphasizing problem identification and corrective actions.
- Highlighted key data quality issues such as identifier consistency, attribute completeness, and atomicity.
Achievements:
- Completed a detailed comparative analysis of data quality for multiple groups using the GQM framework.
- Established a prioritization of data quality criteria and issues for future assessments.
Pending Tasks:
- Further exploration of corrective actions based on identified data quality issues.
- Extend the analysis to additional groups if necessary.