DEA-C01 Data Operations and Support Practice Question
A company is using AWS Glue to catalog data stored in Amazon S3. The data is partitioned by year, month, and day. A data analyst reports that new partitions are not automatically discovered by the Glue crawler. The crawler runs on a schedule every hour. What is the MOST likely reason for the missing partitions?
⚠ Common exam trap
DEA-C01 often tests the misconception that crawler scheduling or catalog limits cause missing partitions, when the most common root cause is insufficient S3 ListBucket permission on the crawler's IAM role.
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
✓
The IAM role used by the crawler does not have permission to list the S3 bucket.
For a Glue crawler to discover new partitions in S3, its IAM role must have s3:ListBucket (and GetObject) permissions on the bucket and prefix. If the role lacks ListBucket, the crawler cannot enumerate the partition folders and will silently miss new partitions even though it runs on schedule. This is the most common cause of 'crawler runs but doesn't find new data' issues.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The IAM role used by the crawler does not have permission to list the S3 bucket.
Why this is correct
Without s3:ListBucket permission, the crawler cannot enumerate prefixes under the bucket, so newly written year/month/day partitions remain invisible even though the hourly schedule runs. The missing IAM action is the specific cause of undiscovered partitions.
- ✗
The Glue Data Catalog is not configured to use a Hive metastore.
Why it's wrong here
The Glue Data Catalog is itself a Hive-compatible metastore, so no external Hive metastore configuration is required for crawlers to register partitions. This option would matter only when integrating an existing self-managed Hive metastore with Glue, which is unrelated to S3 partition discovery.
- ✗
The number of partitions exceeds the Glue catalog limit of 100,000.
Why it's wrong here
The Glue Data Catalog supports millions of partitions per table, far beyond 100,000, so this limit is not the cause. Partition-count limits become relevant only at extreme scale, whereas the stem describes a routine year/month/day layout with hourly crawls.
- ✗
The crawler schedule is set to run too frequently.
Why it's wrong here
A frequent hourly schedule discovers partitions faster, not slower; crawler frequency does not prevent new partitions from being catalogued. Hourly scheduling is appropriate for rapidly arriving data, so this cannot explain missing partitions under a year/month/day prefix layout.
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 |
Go deeper
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services 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 DEA-C01 exam.