DEA-C01 Data Store Management Practice Question
A company uses Amazon DynamoDB with on-demand capacity. They notice higher than expected costs due to a sudden spike in read traffic from a reporting job. The reporting job scans the entire table daily. What is the most cost-effective way to reduce costs while maintaining the same reporting output?
⚠ Common exam trap
Many exam-takers confuse DAX as a general cost-saver for all read patterns, but DAX only helps with repeated, cached reads, not with unique full-table scans that read different data each time.
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 Global Secondary Index (GSI) with a sort key that matches the reporting query pattern.
Using a Global Secondary Index (GSI) with a sort key tailored to the reporting query pattern allows the reporting job to query only the relevant items instead of scanning the entire table. This reduces the read capacity units consumed per operation, directly lowering costs under on-demand capacity, which charges per RCU consumed. The reporting output remains identical because the GSI returns the same data filtered by the query pattern.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable DynamoDB Accelerator (DAX) for caching.
Why it's wrong here
DAX adds cost and may not eliminate scans fully.
- ✓
Use a Global Secondary Index (GSI) with a sort key that matches the reporting query pattern.
Why this is correct
A GSI allows efficient querying instead of scanning, reducing read costs.
- ✗
Set a TTL attribute to automatically expire old data.
Why it's wrong here
TTL removes old data but does not optimize the reporting query.
- ✗
Reduce the read capacity units (RCU) in the table.
Why it's wrong here
On-demand capacity cannot be manually reduced; it auto-scales.
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