AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are designing a knowledge mining solution that must handle sensitive customer data. The solution must ensure that personally identifiable information (PII) is not returned in search results. What should you do?
⚠ Common exam trap
AI-102 often tests the confusion between access control (RBAC) and data minimization (redaction) — candidates pick RBAC thinking 'restricting access' satisfies 'not returned in results,' but the requirement is about the data itself, not who can see it.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a custom skill in the skillset to detect and redact PII before indexing
A custom skill in the Azure AI Search skillset lets you invoke a custom function (e.g., Azure Function calling Azure AI Language's PII detection or a regex-based redactor) during the enrichment pipeline, before documents are indexed. This ensures PII is detected and redacted/removed at ingestion time, so it never appears in the search index or query results.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure AI Search with encryption at rest
Why it's wrong here
Encryption at rest protects stored data from physical or disk-level compromise, but decrypted documents are still returned to any authorised query, so PII would surface in results. It is tempting because encryption is a core compliance control, and it is the right choice when the threat is storage media theft rather than result filtering.
- ✗
Implement role-based access control on the search index
Why it's wrong here
RBAC governs who may query the index, not which fields a permitted user receives; an authorised user still gets PII columns. It is tempting because access control is a standard security layer, and it is correct when the requirement is restricting whole-index or document-level access to specific identities.
- ✓
Use a custom skill in the skillset to detect and redact PII before indexing
Why this is correct
A custom skill runs PII detection and redaction during enrichment, so sensitive values are removed before documents reach the index. Because the index never stores the PII, search results cannot return it, satisfying the requirement.
- ✗
Configure field mappings to exclude PII fields
Why it's wrong here
Field mappings control how source content is routed into index fields during indexing; they do not detect or redact PII, and mapped fields remain searchable. It is tempting because mappings shape the index schema, and they are correct when you need to project source paths into specific fields or transform field names.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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