AvinashThimmareddy/privacy-aware-data-transformation
An open-source framework for automated sensitive data classification and adaptive privacy-preserving transformations in data pipelines.
Organizations often need to share data while protecting sensitive information like customer names or health records. This tool automatically identifies sensitive data within your datasets, like customer or patient records, using metadata such as column names and descriptions. It then dynamically applies the right level of privacy protection, like masking or tokenization, based on who is receiving the data and why, outputting a modified dataset that balances privacy with usability. Data governance specialists, compliance officers, and data stewards will find this useful for managing data sharing.
Use this if you need to share data with various internal teams or external partners, but manually protecting sensitive information is too time-consuming or inconsistent, and you require dynamic privacy controls.
Not ideal if your data is not structured or if you only need a simple, static method for data masking that doesn't vary by consumer or purpose.
Stars
14
Forks
15
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 11, 2026
Commits (30d)
0
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