DEA-C01 Data Operations and Support Practice Question

A company has an S3 data lake with millions of objects. A data engineer needs to provide a daily report of objects that are not accessed for 90 days. The engineer must minimize cost and impact on performance. Which approach should be used?

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 S3 Storage Lens to generate a dashboard of object age and last access

S3 Storage Lens provides cost-effective analytics including last access date and object age, enabling identification of objects not accessed for 90 days without scanning all objects or incurring high costs. Option A is less suitable because S3 Inventory creates daily lists but requires additional Athena queries, adding complexity and cost. Option B is incorrect because S3 Select is designed for querying object content, not metadata; applying it to millions of objects would be highly inefficient and costly. Option C is incorrect because analyzing S3 server access logs would involve storing and querying large volumes of log data, which is costly and impacts performance, and it logs all requests rather than providing a direct last access timestamp.

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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Enable S3 Inventory and query with Athena
Why it's wrong here
S3 Inventory fails this scenario because it provides object metadata like size and storage class, but crucially, it does not include last accessed timestamps or access patterns, which are essential to identify objects not accessed for 90 days. While querying S3 Inventory with Athena is cost-effective for analysing object metadata at scale, it cannot fulfil the requirement for access-based reporting. This approach is suitable for auditing object properties or managing storage tiers based on non-access related attributes.
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Use S3 Select on each object to check last access metadata
Why it's wrong here
S3 Select is used for querying object content (e.g., CSV, JSON fields), not for checking metadata like last access time. This approach does not address the requirement.
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Analyze S3 server access logs to find objects not accessed
Why it's wrong here
S3 Server Access Logs record all requests, but analyzing them to find objects not accessed in 90 days requires processing large volumes of logs, which is costly and has performance overhead.
✓
Use S3 Storage Lens to generate a dashboard of object age and last access
Why this is correct
S3 Storage Lens provides a dashboard with free metrics such as 'Object Age' and 'Last Access Date', making it the most cost-effective and performant option for this use case.

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

DEA-C01 Data Operations and Support Practice Question

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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