- A
Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries
S3 provides cost-effective storage with lifecycle management, and Athena can query data directly.
- B
Store data in S3 with lifecycle policies to transition to Glacier, and use S3 Select for queries
Why wrong: S3 Select works on S3 objects, but Glacier requires restoration before querying.
- C
Store data in Amazon EMR on EC2 and query with Hive
Why wrong: EMR requires cluster management and is not cost-effective for occasional queries.
- D
Store data in Amazon Redshift and query with Redshift Spectrum
Why wrong: Redshift is a data warehouse, not a cost-effective data lake for petabyte-scale diverse data.
Question 1,155 of 1,746
SAP-C02 Design for New Solutions Practice Question
This SAP-C02 practice question tests your understanding of design for new solutions. 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 company is designing a new data lake on AWS. The data lake will store petabytes of data from various sources, including IoT devices, application logs, and streaming data. The data must be stored cost-effectively, and access patterns vary from frequently accessed recent data to rarely accessed historical data. The company also needs to run SQL queries on the data. Which solution should the architect recommend?
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
✓
Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries
Amazon S3 lifecycle policies allow automatic transition of objects between storage classes (e.g., S3 Standard to S3 Standard-IA to S3 Glacier Deep Archive) based on age, optimizing cost for varying access patterns. Amazon Athena enables serverless SQL querying directly on data stored in S3, making it ideal for a petabyte-scale data lake without managing infrastructure.
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 S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries
Why this is correct
S3 provides cost-effective storage with lifecycle management, and Athena can query data directly.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Store data in S3 with lifecycle policies to transition to Glacier, and use S3 Select for queries
Why it's wrong here
S3 Select works on S3 objects, but Glacier requires restoration before querying.
- ✗
Store data in Amazon EMR on EC2 and query with Hive
Why it's wrong here
EMR requires cluster management and is not cost-effective for occasional queries.
- ✗
Store data in Amazon Redshift and query with Redshift Spectrum
Why it's wrong here
Redshift is a data warehouse, not a cost-effective data lake for petabyte-scale diverse data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse S3 Select with Athena, not realizing S3 Select is limited to single-object filtering and cannot perform joins or aggregations across multiple files, which is required for SQL queries on a data lake.
Detailed technical explanation
How to think about this question
S3 lifecycle policies support transitions to S3 Glacier Instant Retrieval, S3 Glacier Flexible Retrieval, and S3 Glacier Deep Archive, with minimum storage durations (e.g., 30 days for Standard-IA) to avoid early deletion fees. Athena uses Presto under the hood and charges per TB scanned, making it cost-effective when data is partitioned and compressed (e.g., Parquet or ORC). A real-world scenario: a company storing IoT sensor data in S3 with a lifecycle rule moving data older than 90 days to Glacier Deep Archive can still query recent data via Athena while historical data remains accessible but at minimal cost.
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.
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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: Store data in S3 with lifecycle policies to transition between storage classes, and use Amazon Athena for queries — Amazon S3 lifecycle policies allow automatic transition of objects between storage classes (e.g., S3 Standard to S3 Standard-IA to S3 Glacier Deep Archive) based on age, optimizing cost for varying access patterns. Amazon Athena enables serverless SQL querying directly on data stored in S3, making it ideal for a petabyte-scale data lake without managing infrastructure.
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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