Data Profiling Workflow
A workflow that profiles the "shape" of a dataset before handing it to AI — share structure and summary statistics without exposing raw records. PDPA-safe by design.
Lets the team get AI help on real data without exposing personal information.
You want AI to help analyze real data — but real data usually contains personal information you can't share directly under PDPA. That's the gap this workflow fills.
The idea
Instead of sending raw records, profile the dataset first and send only the summary for AI to work with:
- Table structure — column names and types
- Summary statistics — ranges, missing values, distinct counts
- The shape of the data, without any identifying records
AI sees enough of the data's shape to reason about it, while personal data never leaves.
Why it matters
Working with organizational data always has to respect PDPA. This workflow lets the team get AI help without choosing between speed and safety — it's repeatable across new datasets, and it's auditable: you can see exactly what was shared.
Written in Python · full source via the button above.