Overview
The CSV Anonymizer project focuses on processing sensitive tabular data locally. It demonstrates a practical approach to configurable anonymization, repeatable profiles, and traceable processing results.
Python · Data privacy · CSV processing
CSV Anonymizer
A configurable tool concept for anonymizing CSV files using profiles, masking, pseudonymization, and audit logging.
Planned / implemented concepts
- Column-based masking and pseudonymization.
- YAML-style processing profiles.
- Audit log for what was processed and how.
- CLI/headless workflow for reproducible batch runs.
- Privacy-aware on-premise processing concept.
What this demonstrates
This project is relevant for application development roles because it combines data processing, privacy requirements, configuration design, and documentation around operational use.