Research Institution · Data Cleaning & QA
Longitudinal Dataset Cleanup
Cleaned and standardized a 5-year longitudinal education dataset for a regional think tank.
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Problem
Inconsistent variable labels and missing metadata made the dataset unreliable for analysis.
Approach
- Unified variable naming conventions
- Created a reproducible cleaning pipeline
- Delivered audit-ready QA logs
Deliverables
- Clean dataset
- Updated codebook
- QA documentation
Outcomes
- Increased usable records by 24%
- Enabled cross-year analysis
Impact metrics
- 4 waves cleaned
- 180 variables standardized
Sample visuals
Snapshots from the engagement
Mock visuals demonstrate how insights were surfaced for stakeholders.
Data quality scorecard
Pipeline overview
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