Jupyter notebook-based tutorials for popular use cases around transformations.
In this blueprint, we will create a transform policy to identify and redact or replace PII with fake values. We will then use the SDK to transform a dataset and examine the results.
Label and transform sensitive data locally in your environment.
In this deep dive, we will walk through some of the more advanced features to de-identify data with the Transform API, including bucketing, date shifts, masking, and entity replacements.
This notebook walks through creating a policy using the Transform API to de-identify and anonymize data in a Postgres database for test use cases.