- A
Store data in JSON format for flexibility.
Why wrong: JSON is row-based and increases scan size.
- B
Compress data using Snappy or Gzip compression.
Compression reduces storage and scan costs.
- C
Use columnar storage formats such as Parquet or ORC.
Columnar formats reduce scan and improve compression.
- D
Store data in many small files to improve parallel processing.
Why wrong: Many small files increase overhead; use larger files.
- E
Partition the data by date and other high-cardinality columns.
Partition pruning reduces data scanned.
Question 1,324 of 1,746
SAP-C02 Design for New Solutions Practice Question
This SAP-C02 practice question tests your understanding of design for new solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 company is designing a new data lake on AWS. The data lake will store raw data from various sources in Amazon S3. The data will be processed using AWS Glue ETL jobs and queried using Amazon Athena. To optimize costs and performance, which three practices should the solutions architect implement?
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
✓
Compress data using Snappy or Gzip compression.
Compressing data with Snappy or Gzip reduces storage costs in Amazon S3 and decreases the amount of data scanned by Athena, which charges per TB scanned. Snappy offers faster decompression for ETL workloads, while Gzip provides higher compression ratios. Both are natively supported by AWS Glue and Athena, making them optimal for cost and performance.
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.
- ✗
Store data in JSON format for flexibility.
Why it's wrong here
JSON is row-based and increases scan size.
- ✓
Compress data using Snappy or Gzip compression.
Why this is correct
Compression reduces storage and scan costs.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use columnar storage formats such as Parquet or ORC.
Why this is correct
Columnar formats reduce scan and improve compression.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Store data in many small files to improve parallel processing.
Why it's wrong here
Many small files increase overhead; use larger files.
- ✓
Partition the data by date and other high-cardinality columns.
Why this is correct
Partition pruning reduces data scanned.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose JSON for its flexibility without realizing its severe cost and performance penalties in analytics workloads, or they mistakenly believe many small files improve parallelism, when in fact they cause S3 request throttling and increased Athena query overhead.
Detailed technical explanation
How to think about this question
Parquet and ORC store data column-wise, enabling predicate pushdown and projection pruning in Athena, which only reads the necessary columns. Partitioning by date (e.g., year/month/day) leverages S3 prefix-based filtering, but high-cardinality columns (e.g., user_id) should be avoided as partitions because they create too many S3 prefixes, overwhelming the Glue Data Catalog and slowing query planning. Snappy compression is splittable in Parquet, allowing parallel reads across workers without decompressing the entire file.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Design for New Solutions — study guide chapter
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FAQ
Questions learners often ask
What does this SAP-C02 question test?
Design for New Solutions — This question tests Design for New Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Compress data using Snappy or Gzip compression. — Compressing data with Snappy or Gzip reduces storage costs in Amazon S3 and decreases the amount of data scanned by Athena, which charges per TB scanned. Snappy offers faster decompression for ETL workloads, while Gzip provides higher compression ratios. Both are natively supported by AWS Glue and Athena, making them optimal for cost and performance.
What should I do if I get this SAP-C02 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
This SAP-C02 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 SAP-C02 exam.
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