MLS-C01 Exploratory Data Analysis Practice Question
A machine learning engineer is performing exploratory data analysis on a dataset containing customer transaction records. The dataset includes a column 'transaction_date' with timestamps. The engineer wants to derive features such as day of the week, hour, and month for modeling. Which AWS service can be used directly to extract these features without writing custom code?
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
✓
AWS Glue ETL with built-in timestamp transforms
AWS Glue ETL provides built-in transforms like `ExtractTimestamp` that can parse timestamps and extract date/time components (e.g., day of week, hour, month) without writing custom code. Option B is wrong because Amazon Athena requires writing SQL queries to extract date parts, which constitutes custom code. Option C is wrong because Amazon QuickSight is a BI visualization tool, not designed for feature engineering. Option D is wrong because Amazon SageMaker Data Wrangler, while offering visual transformations, requires an active SageMaker Studio environment and is not a serverless ETL service like AWS Glue.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AWS Glue ETL with built-in timestamp transforms
Why this is correct
AWS Glue provides transforms like 'ExtractTimestamp' to derive date components without custom code.
- ✗
Amazon Athena with SQL date functions
Why it's wrong here
Athena requires writing SQL queries, which is not 'without writing custom code'.
- ✗
Amazon QuickSight
Why it's wrong here
QuickSight is for visualization and dashboards, not for feature extraction.
- ✗
Amazon SageMaker Data Wrangler
Why it's wrong here
Data Wrangler is a visual tool but still requires user interaction to configure transformations.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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