Protect information with Microsoft Purview information protection: Review

Creating the custom SIT (Sensitive Information Type) was the most useful part. Walking through the XML file and regex for a transaction pattern, then seeing it light up in the sandbox, connected a lot of dots. But the verification steps were a letdown—just screenshots asking 'Does your screen look like this?' This is a common weakness in these modules; they can go stale the moment the UI team ships a minor redesign.

The content is fresh, which I appreciate. The explicit tie-in to Microsoft 365 Copilot grounding is timely and addresses a key concern for any organization activating genAI features. It correctly frames information protection not as a compliance checkbox, but as a prerequisite for safely using large language models with internal data. The module clearly differentiates between SITs, trainable classifiers, and Exact Data Match, a distinction many of my own company's technical documents blur.

I was hoping for more depth, though, especially with the 'advanced' tag. The section on trainable classifiers, for instance, describes what they do but not how they work. There's no mention of the underlying models, the sample size requirements for robust training, or the statistical confidence of the results. As a data scientist, I'm left wondering about the false positive and false negative rates. The module treats it as a black box you feed documents to. It’s an admin’s view, not a builder’s.