DEA-C01 Data Operations and Support Practice Question
A data engineer is using Amazon Athena to query data stored in Amazon S3. The engineer notices that queries are returning incorrect results, specifically missing some rows that are known to exist in the underlying data. The data is stored in Parquet format and is partitioned by date. The engineer runs a query with a WHERE clause on the date partition and finds that some dates are missing from the results. The S3 bucket contains folders for each date, but some folders are empty. What is the MOST likely cause of the missing rows?
⚠ Common exam trap
The trap here is assuming that Athena is malfunctioning when the underlying data is simply absent, leading to unnecessary troubleshooting of Athena settings.
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 empty folders in S3 indicate that the data for those dates was never written or was deleted, so Athena correctly returns no rows for those dates.
The missing rows correspond to dates for which the S3 folders are empty. Athena queries data directly from S3, so if there are no files in a partition folder, no rows will be returned for that partition. This is not an Athena misconfiguration; it is a data availability issue. The engineer should check the upstream processes that write data to those partitions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Athena is using a stale metadata cache and needs to be refreshed.
Why it's wrong here
Athena does not have a persistent metadata cache that would cause it to miss data. It queries the AWS Glue Data Catalog for table metadata and then reads data directly from S3. If new partitions are added, you may need to update the catalog, but the scenario mentions empty folders, which are a data issue, not a metadata caching issue. Refreshing metadata would not populate empty folders.
- ✗
The Parquet files are corrupted, causing Athena to skip them.
Why it's wrong here
Corrupted Parquet files would typically cause Athena to return an error, not silently skip rows. Athena would fail the query or log an error. The scenario states that some folders are empty; if files were corrupted, the folders would contain files. The absence of files is the more likely cause of missing rows.
- ✗
The Athena table is not configured with the correct partition projection settings.
Why it's wrong here
Partition projection is used to avoid manually adding partitions to the AWS Glue Data Catalog. If not configured, Athena might not see new partitions until they are added via MSCK REPAIR TABLE or ALTER TABLE ADD PARTITION. However, the scenario states that some folders are empty, which suggests the data itself is missing, not that partitions are not registered. Partition projection would affect all partitions, not just empty ones.
- ✓
The empty folders in S3 indicate that the data for those dates was never written or was deleted, so Athena correctly returns no rows for those dates.
Why this is correct
If the S3 folders for certain dates are empty, there is no data for Athena to query. Athena reads files from S3; empty folders contain no files, so queries for those dates return no rows. This is expected behavior. The missing rows are due to missing data files, not an Athena configuration issue. The engineer should investigate why those folders are empty, possibly due to upstream ETL failures.
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
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