The answer is Amazon Athena Federated Query for Redshift EDA, which allows you to run SQL queries directly against Redshift and retrieve only aggregated results. This approach is the most efficient because it leverages Athena’s serverless engine to push down computation to Redshift, returning a much smaller, summarized dataset that fits easily into a pandas DataFrame on a local EC2 instance or SageMaker notebook. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of data ingestion patterns for exploratory data analysis when working with large-scale data warehouses. The common trap is assuming you must export the full dataset to S3 or load it entirely into memory, but the key insight is that EDA often only needs aggregated views, not raw rows. Remember the memory tip: “Aggregate in the warehouse, not in the notebook” — Athena Federated Query lets you reduce before you load.
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 company has a large dataset of customer transactions stored in Amazon Redshift. A data scientist wants to perform EDA using Python libraries like pandas and matplotlib. The dataset is too large to fit into memory on a single EC2 instance. What is the most efficient approach?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Amazon Athena Federated Query to run SQL queries against Redshift and retrieve aggregated results
Option C is correct because Amazon Athena allows querying Redshift data directly via federated queries, returning only aggregated results, avoiding the need to move large datasets. Option A is wrong because reading all data to a local DataFrame would exceed memory. Option B is wrong because writing to S3 and then reading with pandas still requires loading all data into memory. Option D is wrong because SageMaker notebook's local memory is still limited.
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.
✗
Launch an Amazon SageMaker notebook instance with an attached EBS volume large enough to hold the data
Why it's wrong here
Why D is wrong
✓
Use Amazon Athena Federated Query to run SQL queries against Redshift and retrieve aggregated results
Why this is correct
Why C is correct
Related concept
Read the scenario before looking for a memorised answer.
✗
Use a SQLAlchemy connection to read the entire table into a pandas DataFrame and sample it
Why it's wrong here
Why A is wrong
✗
Export the Redshift table to Amazon S3 in Parquet format, then use pandas to read the Parquet files
Why it's wrong here
Why B is wrong
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.
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.
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: Use Amazon Athena Federated Query to run SQL queries against Redshift and retrieve aggregated results — Option C is correct because Amazon Athena allows querying Redshift data directly via federated queries, returning only aggregated results, avoiding the need to move large datasets. Option A is wrong because reading all data to a local DataFrame would exceed memory. Option B is wrong because writing to S3 and then reading with pandas still requires loading all data into memory. Option D is wrong because SageMaker notebook's local memory is still limited.
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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