- A
Query the data directly in Athena without any preprocessing
For a one-time query, scanning 5 TB at $5 per TB is $25, which is minimal compared to preprocessing costs.
- B
Create an S3 Select query to filter data before Athena
Why wrong: S3 Select is for object-level filtering, not for full SQL queries across many objects.
- C
Use Amazon Redshift Spectrum to query the data
Why wrong: Redshift Spectrum requires a provisioned Redshift cluster, adding cost for a one-time query.
- D
Use AWS Glue to convert the data to Parquet format and repartition by date
Why wrong: Conversion costs time and money; for a one-time query, it's cheaper to just query as-is.
Question 1,621 of 1,755
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data scientist needs to run a one-time query on 10 TB of data stored in S3 using Amazon Athena. The query scans 5 TB and returns a small result set. Which approach minimizes cost?
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
✓
Query the data directly in Athena without any preprocessing
Athena charges based on the amount of data scanned per query. Since this is a one-time query on 10 TB of data that scans only 5 TB, querying directly in Athena without preprocessing is the most cost-effective approach because you pay only for the 5 TB scanned, with no additional costs for data conversion, storage, or cluster provisioning.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Query the data directly in Athena without any preprocessing
Why this is correct
For a one-time query, scanning 5 TB at $5 per TB is $25, which is minimal compared to preprocessing costs.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create an S3 Select query to filter data before Athena
Why it's wrong here
S3 Select is for object-level filtering, not for full SQL queries across many objects.
- ✗
Use Amazon Redshift Spectrum to query the data
Why it's wrong here
Redshift Spectrum requires a provisioned Redshift cluster, adding cost for a one-time query.
- ✗
Use AWS Glue to convert the data to Parquet format and repartition by date
Why it's wrong here
Conversion costs time and money; for a one-time query, it's cheaper to just query as-is.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume data must be converted to a columnar format (like Parquet) to reduce costs, ignoring that for a one-time query, the cost of conversion and storage outweighs the savings from reduced scan size.
Detailed technical explanation
How to think about this question
Athena uses Presto under the hood and charges $5.00 per TB of data scanned (in us-east-1). For a 5 TB scan, the cost is approximately $25.00. Parquet conversion reduces scan size (e.g., columnar pruning) but for a one-time query, the cost of running an AWS Glue job (e.g., DPU-hours) and storing the converted data often exceeds the direct scan cost, especially when the query scans only half the data. The trap is that candidates over-optimize for future queries without considering the one-time nature of the task.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Query the data directly in Athena without any preprocessing — Athena charges based on the amount of data scanned per query. Since this is a one-time query on 10 TB of data that scans only 5 TB, querying directly in Athena without preprocessing is the most cost-effective approach because you pay only for the 5 TB scanned, with no additional costs for data conversion, storage, or cluster provisioning.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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