As privacy regulations like GDPR become increasingly relevant, organizations must ensure that Personally Identifiable Information (PII) is properly managed within their data pipelines to maintain compliance and protect consumer data. PII, which includes information like names, email addresses, and social security numbers, can inadvertently end up in places it shouldn't, such as aggregate analytics or chatbot training models. Tools like Datafold facilitate the tracking and management of PII by offering column-level lineage, allowing data engineers to trace data through upstream and downstream processes and ensure sensitive information is not improperly retained. Datafold's interface supports tagging and tracking of PII, thereby enabling teams to collaborate effectively in maintaining data privacy and security. This process is not a one-time task but part of ongoing efforts to comply with evolving privacy requirements, and Datafold's integration with tools like dbt and Snowflake aids in the seamless implementation of these best practices.