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Making Simple Privacy Transformations Easier in dbt

Today we published a new dbt package to make it easier to pseudonymize data in your data warehouse

At Privacy Dynamics, our mission is to empower innovative and ethical data teams. Our SaaS product applies state-of-the-art anonymization techniques to data in your data warehouse, so that it can be used and shared more broadly in your organization.

However, sometimes simpler transformations are called for, and we want to support data teams in helping them keep customer data safe and robust to their use cases, whether or not they choose to use our SaaS product.

To that end, today we published a new dbt package to make it easier to pseudonymize data in your data warehouse. You can find it on the dbt Package Hub or on GitHub. The first version of the package has several macros to make it easier to hash and redact fields in your dbt project. The macros use your warehouse’s native functions, and do not require you to use Privacy Dynamics.

We have many more features planned, and we would love to hear from you about how you pseudonymize data and how we can help — issues and pull requests are more than welcome. Please reach out to us through GitHub or in the dbt Slack.