MLS-C01 Exploratory Data Analysis Practice Question

A data scientist is working with a dataset containing customer transactions. The dataset has a column named 'transaction_date' with timestamp values. The scientist wants to create new features such as day of week, hour, and whether the transaction occurred on a weekend. Which AWS service provides built-in feature engineering capabilities for datetime columns?

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

✓

Amazon SageMaker Data Wrangler

Amazon SageMaker Data Wrangler includes built-in transformations for datetime features like extracting day, month, hour, etc. Option B (Amazon Athena) can extract parts but not as a feature engineering step. Option C (AWS Glue ETL) requires custom code. Option D (Amazon EMR) requires more manual effort.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Amazon SageMaker Data Wrangler
Why this is correct
Amazon SageMaker Data Wrangler includes built-in transformations for datetime features.
✗
Amazon Athena
Why it's wrong here
Amazon Athena can extract parts but not as a dedicated feature engineering step.
✗
AWS Glue ETL
Why it's wrong here
AWS Glue ETL requires custom code for feature engineering.
✗
Amazon EMR
Why it's wrong here
Amazon EMR requires more manual effort.

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Last reviewed: Jun 20, 2026

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