MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is exploring a dataset with a column 'transaction_date'. They want to create features for day of week and month. What is the correct AWS service to schedule a recurring ETL job for this transformation?
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
AWS Glue is a serverless ETL service that can be scheduled to run recurring jobs for data transformation, such as extracting day of week and month from a date column. Option A is wrong because Amazon Athena is an interactive query service, not an ETL scheduler. Option C is wrong because Amazon SageMaker is a machine learning platform, not an ETL service. Option D is wrong because AWS Lambda can run code on a schedule but is not a full-fledged ETL service for recurring transformations of large datasets.
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 Athena
Why it's wrong here
Athena is an interactive query service.
- ✓
AWS Glue
Why this is correct
Glue is a managed ETL service.
- ✗
Amazon SageMaker
Why it's wrong here
SageMaker is for building and training models.
- ✗
AWS Lambda
Why it's wrong here
Lambda can be used for ETL but is not a dedicated ETL service.
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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