Healthcare Data Migration & Validation
A data operations case study focused on preparing client and appointment records for migration while protecting accuracy, consistency and import readiness.
Project Snapshot
Business Question
The business needed to move client and appointment records into a new system while minimizing data gaps, import errors and post-import cleanup.
My Analytical Approach
- Reviewed source client and appointment CSV structures.
- Checked required fields, missing values, duplicate rows and relationships between clients and appointments.
- Designed a source-to-target preparation and validation flow.
- Outlined pre-import and post-import quality checks.
Selected Visuals from the Analysis
Before / After Data Cleaning
Shows how messy source records can be transformed into a controlled import-ready structure.
Validation Checklist
A repeatable checklist for reviewing required fields, duplicates, date formats, relationships and post-import issues.
Key Findings
Data structure clarity
The source contained 1,000 client records and 5,790 appointment records, which required relationship checks before import.
Quality flags
Examples of useful checks included missing required fields, duplicate appointments and missing location values.
Process value
The strongest part of the case is the migration workflow: review, clean, transform, import, validate, and troubleshoot.
Recommendations / Outcome
Use a mapping sheet
Document source-to-target fields before import so assumptions are visible and reviewable.
Validate before import
Check required fields, IDs, dates and duplicates before loading data into the target system.
Run post-import QA
Compare record counts and sample records after import to confirm migration accuracy.