MLS-C01 Exploratory Data Analysis Practice Question
This MLS-C01 practice question tests your understanding of exploratory data analysis. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Network Topology
Refer to the exhibit. A data scientist runs the AWS CLI command shown and gets the output. The scientist wants to create an Athena table over all log files in the 'logs/2023/' prefix, including files smaller than 1000 bytes. Which approach achieves this?
Network Topology
A
Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix.
The table location covers all files regardless of size.
B
Create the table and add a WHERE clause to include small files.
Why wrong: WHERE clause filters rows after scan, does not include missing files.
C
Ask the S3 team to remove the size restriction on the bucket.
Why wrong: There is no bucket-level size restriction.
D
Modify the CLI command to remove the size filter and re-run it before creating the table.
Why wrong: The CLI command is independent of Athena table creation.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix.
Option A is correct because creating an Athena table with the LOCATION pointing to 's3://my-bucket/logs/2023/' will include all objects under that prefix, regardless of size. The CLI command's --query parameter only filters the output of the list-objects command, but does not impose any restriction on the data or the bucket. Option B is incorrect because a WHERE clause in Athena can only filter rows after the table is defined; it cannot include or exclude files from being read. Option C is incorrect because S3 does not have a built-in size restriction on a bucket; the CLI command is just a client-side query. Option D is incorrect because the CLI command is independent; the table can be created directly without needing to modify the CLI command.
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.
✓
Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix.
Why this is correct
The table location covers all files regardless of size.
Related concept
Read the scenario before looking for a memorised answer.
✗
Create the table and add a WHERE clause to include small files.
Why it's wrong here
WHERE clause filters rows after scan, does not include missing files.
✗
Ask the S3 team to remove the size restriction on the bucket.
Why it's wrong here
There is no bucket-level size restriction.
✗
Modify the CLI command to remove the size filter and re-run it before creating the table.
Why it's wrong here
The CLI command is independent of Athena table creation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Command / output trap
The CLI command is independent of Athena table creation.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create the table using LOCATION 's3://my-bucket/logs/2023/' which includes all files under that prefix. — Option A is correct because creating an Athena table with the LOCATION pointing to 's3://my-bucket/logs/2023/' will include all objects under that prefix, regardless of size. The CLI command's --query parameter only filters the output of the list-objects command, but does not impose any restriction on the data or the bucket. Option B is incorrect because a WHERE clause in Athena can only filter rows after the table is defined; it cannot include or exclude files from being read. Option C is incorrect because S3 does not have a built-in size restriction on a bucket; the CLI command is just a client-side query. Option D is incorrect because the CLI command is independent; the table can be created directly without needing to modify the CLI command.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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