Databricks-GenAI-Assoc Governance Practice Question
Which Unity Catalog object is used to link a specific cloud storage path to a catalog, schema, or table, allowing users to create tables without managing individual storage credentials?
⚠ Common exam trap
Candidates often confuse 'External Location' with 'Storage Credential', failing to distinguish between the object that maps a path and the object that holds the authentication secret.
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
✓
External Location
An External Location in Unity Catalog acts as a secure bridge between Databricks and a specific path in cloud storage (e.g., S3 or ADLS). By using a Storage Credential, the external location allows data engineers to manage storage access at a high level. This simplifies data governance by abstracting cloud-specific permissions into Databricks-native access controls.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Storage Credential
Why it's wrong here
A storage credential is the long-term secret (like an IAM role ARN or Service Principal) used by Databricks to access cloud storage. While it is associated with an external location, it is not the object used to map the specific storage path to the Unity Catalog hierarchy.
- ✓
External Location
Why this is correct
The external location object defines the specific path in cloud storage and associates it with a storage credential. It is the primary mechanism for accessing data in Unity Catalog that is stored in user-managed cloud accounts, providing a governed interface for data engineers to register data assets.
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Managed Table
Why it's wrong here
Managed tables are created within the metastore's root storage location. While Unity Catalog manages the lifecycle and lifecycle of the underlying files, the object itself is the table, not the mechanism used to link disparate external storage paths to the governance model.
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Unity Catalog Volume
Why it's wrong here
Volumes are used to manage non-tabular data (files) in cloud storage. While they do map storage paths, they are intended for unstructured or semi-structured data files rather than acting as the primary registration point for tabular data governance and cataloging within the metastore's hierarchy.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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.