The answer is to partition the table by date derived from timestamp and convert to Parquet. This combination is most effective because partitioning enables partition pruning, allowing Athena to skip entire directories when queries filter on timestamp, while Parquet’s columnar storage and compression drastically reduce the data scanned per query. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Athena cost optimization and data format trade-offs—a common trap is choosing only Parquet conversion, which still forces full table scans without partitioning. Remember the memory tip: “Partition first, Parquet second” to cut both scan time and cost.
MLS-C01 Exploratory Data Analysis Practice Question
This MLS-C01 practice question tests your understanding of exploratory data analysis. 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 engineer is performing EDA on a dataset containing user activity logs from a mobile app. The dataset has 10 million rows and includes columns: 'user_id', 'event_type', 'timestamp', 'device_type', and 'session_duration'. The engineer uses Amazon Athena to query the data stored in S3 as CSV files. The engineer runs a query to find the average session_duration per device_type, but the query takes over 5 minutes and scans 100 GB of data. The engineer wants to reduce query cost and improve performance for future EDA. The dataset is not partitioned, and the engineer anticipates frequent queries filtering on 'timestamp' and 'device_type'. Which action will most effectively reduce data scanned?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Partition the table by date derived from timestamp and convert to Parquet.
Option C is correct because partitioning by date (derived from timestamp) allows partition pruning when filtering by timestamp, significantly reducing data scanned. Converting to Parquet (Option A) helps but without partitioning, full scans still occur. Option B is wrong because it only partitions by device_type, but time-based filters are common. Option D is wrong because sampling loses accuracy.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Partition the table by date derived from timestamp and convert to Parquet.
Why this is correct
Combining partitioning and columnar storage maximizes reduction in scanned data.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use random sampling to query a subset of data.
Why it's wrong here
Sampling reduces accuracy and may not be acceptable for EDA.
✗
Convert the data to Parquet format and use columnar storage.
Why it's wrong here
Parquet reduces bytes scanned but without partitioning, still full scan of columns.
✗
Partition the table by device_type.
Why it's wrong here
Partitioning by device_type helps only if filtering by device_type, not timestamp.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Partition the table by date derived from timestamp and convert to Parquet. — Option C is correct because partitioning by date (derived from timestamp) allows partition pruning when filtering by timestamp, significantly reducing data scanned. Converting to Parquet (Option A) helps but without partitioning, full scans still occur. Option B is wrong because it only partitions by device_type, but time-based filters are common. Option D is wrong because sampling loses accuracy.
What should I do if I get this MLS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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