Databricks-GenAI-Assoc Governance Practice Question
A generative AI engineer trains a model on a Delta table that contains customer support transcripts. Before registering the model, security requires that the training data be classified so that policies can be applied consistently across the lakehouse. The engineer wants to attach a governed label to the transcript column indicating it contains sensitive personal data. Which Unity Catalog feature should be used?
⚠ Common exam trap
The trap here is treating descriptive comments or access grants as classification, when only governed tags provide enforceable labels.
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
✓
A governed tag applied to the column
Governed tags provide a structured, searchable classification layer in Unity Catalog that can be attached to columns and referenced by policy and discovery tooling. Applying a sensitivity tag to the transcript column gives security a consistent label for the training data, enabling uniform policy enforcement and auditability rather than relying on informal comments or access mechanisms.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A governed tag applied to the column
Why this is correct
Governed tags in Unity Catalog attach classification metadata to securable objects, including individual columns, and can be used to drive policy decisions and discovery. Tagging the transcript column as sensitive personal data gives security a consistent label that downstream policies and audits can reference, which is exactly the classification requirement described.
- ✗
A storage credential scoped to the transcript path
Why it's wrong here
Storage credentials authorize access to cloud storage locations; they convey no classification meaning about column contents. Creating one for the transcript path would not label the data as sensitive and would not feed any policy engine, so it fails to satisfy the classification objective entirely.
- ✗
A comment added to the column definition
Why it's wrong here
Comments describe a column for human readers but are free text with no governed semantics. They cannot be reliably used by policy engines or searched as classification labels, so a comment would not provide the consistent, enforceable classification that security requires across the lakehouse.
- ✗
A row filter that excludes rows containing personal data
Why it's wrong here
A row filter restricts which rows a caller can read, but it does not classify a column. Using one here would also remove training rows rather than label them, degrading the dataset while leaving the classification requirement unmet, so it is the wrong tool for attaching a governed sensitivity label.
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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 Databricks exam blueprint
This Databricks-GenAI-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-GenAI-Assoc exam.