- A
Check correlation of zero columns with other features; if low, assume zeros are missing.
Why wrong: Correlation does not imply missingness; zeros could be meaningful.
- B
Calculate the percentage of zeros and compare with other columns; if unusually high, treat as missing.
Why wrong: Statistical thresholds are arbitrary and may not reflect actual data generation process.
- C
Use AWS Glue Data Catalog to view column statistics and infer missing values.
Why wrong: Data Catalog provides basic stats like count, nulls, but cannot differentiate zeros.
- D
Consult the data source documentation or domain experts to understand the meaning of zero values.
Domain knowledge is crucial for accurate interpretation of data.
Quick Answer
The answer is to consult the data source documentation or domain experts to determine if zeros represent missing data or actual zero values. This is correct because statistical methods alone cannot distinguish between a true zero and a missing value encoded as zero—without domain context, any imputation or analysis would be based on an assumption, not evidence. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding that exploratory data analysis (EDA) must begin with data provenance, not automated heuristics; a common trap is assuming that comparing column distributions or metadata can reveal encoding intent, but only domain knowledge provides the ground truth. Remember the memory tip: “Zero without context is just a number—ask the source to know its meaning.”
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.
A data engineer is performing EDA on a dataset with 1 million rows and 200 columns. The dataset is stored in S3 as CSV files. The engineer notices that some columns have a high proportion of zeros. What is the best approach to determine if these zeros represent missing data or actual zero values?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
Consult the data source documentation or domain experts to understand the meaning of zero values.
Option D is correct because domain knowledge and documentation are the most reliable ways to understand the meaning of zeros. Option A is wrong because statistical methods cannot distinguish missing vs actual zero without context. Option B is wrong because metadata may not have this detail. Option C is wrong because comparing to other columns might be misleading.
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.
- ✗
Check correlation of zero columns with other features; if low, assume zeros are missing.
Why it's wrong here
Correlation does not imply missingness; zeros could be meaningful.
- ✗
Calculate the percentage of zeros and compare with other columns; if unusually high, treat as missing.
Why it's wrong here
Statistical thresholds are arbitrary and may not reflect actual data generation process.
- ✗
Use AWS Glue Data Catalog to view column statistics and infer missing values.
Why it's wrong here
Data Catalog provides basic stats like count, nulls, but cannot differentiate zeros.
- ✓
Consult the data source documentation or domain experts to understand the meaning of zero values.
Why this is correct
Domain knowledge is crucial for accurate interpretation of data.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
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.
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Exploratory Data Analysis — study guide chapter
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
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: Consult the data source documentation or domain experts to understand the meaning of zero values. — Option D is correct because domain knowledge and documentation are the most reliable ways to understand the meaning of zeros. Option A is wrong because statistical methods cannot distinguish missing vs actual zero without context. Option B is wrong because metadata may not have this detail. Option C is wrong because comparing to other columns might be misleading.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
This MLS-C01 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 MLS-C01 exam.
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