The answer is to use a SageMaker Spark processing job with PySpark to aggregate and detect duplicate transactions. This approach is correct because Spark’s distributed computing framework efficiently handles the 5-million-row dataset by partitioning the data across worker nodes, allowing you to group by customer_id, transaction_date, and transaction_amount to identify duplicates without exhausting memory, unlike pandas which would fail on an ml.t3.medium instance. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of scaling EDA tasks within SageMaker’s ecosystem—a common trap is assuming Athena or DataBrew suffice, but Athena requires SQL and external table setup while DataBrew lacks custom aggregation logic. Remember the memory tip: when data exceeds a single instance’s RAM, think Spark for distributed deduplication.
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 scientist is performing EDA on a dataset containing customer transaction records. The dataset includes columns: 'transaction_id', 'customer_id', 'transaction_amount', 'transaction_date', and 'product_category'. The data scientist wants to check for duplicate transactions and identify any suspicious patterns, such as multiple transactions from the same customer on the same day with the same amount. The dataset has 5 million rows. The data scientist is using a SageMaker Studio notebook with a ml.t3.medium instance. The data is stored in S3. What is the most efficient way to perform this analysis?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a SageMaker Spark processing job with PySpark to aggregate and detect duplicates.
Using Spark on SageMaker allows distributed processing of large data. Option A is wrong because pandas may run out of memory. Option B is wrong because Athena requires SQL queries and external setup. Option D is wrong because DataBrew is for profiling but not custom duplicate analysis.
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.
✓
Use a SageMaker Spark processing job with PySpark to aggregate and detect duplicates.
Why this is correct
Spark can handle large data efficiently.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use Amazon Athena to run SQL queries to find duplicates.
Why it's wrong here
Athena is query-only, not for interactive EDA with custom logic.
✗
Load the entire dataset into a pandas DataFrame and use groupby operations.
Why it's wrong here
Memory may be insufficient.
✗
Use AWS Glue DataBrew to create a profile and manually inspect.
Why it's wrong here
DataBrew may not support custom duplicate detection logic.
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 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.
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: Use a SageMaker Spark processing job with PySpark to aggregate and detect duplicates. — Using Spark on SageMaker allows distributed processing of large data. Option A is wrong because pandas may run out of memory. Option B is wrong because Athena requires SQL queries and external setup. Option D is wrong because DataBrew is for profiling but not custom duplicate analysis.
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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