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Data EngineeringmediumMultiple SelectObjective-mapped

MLS-C01 Data Engineering Practice Question

A data engineering team is designing a data lake on AWS for machine learning workloads. The data includes structured, semi-structured, and unstructured data. The team needs to ensure that the data is cataloged, easily discoverable, and can be queried by Amazon Athena and Amazon EMR. The team also wants to enforce fine-grained access control at the column and row level for sensitive data. Which combination of AWS services should the team use? (Select TWO.)

⚠ Common exam trap

It's easy for candidates to assume IAM alone can handle fine-grained data access control, but IAM lacks the column- and row-level filtering capabilities that Lake Formation provides through its integration with the Glue Data Catalog and query engines.

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 Lake Formation

AWS Lake Formation is correct because it provides a centralized service to build, secure, and manage data lakes on AWS. It enables fine-grained access control at the column and row level for sensitive data, which directly meets the requirement for enforcing such controls. Additionally, Lake Formation integrates with Amazon Athena and Amazon EMR for querying and processing the cataloged data.

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 Lake Formation

    Why this is correct

    Lake Formation provides fine-grained access control and integrates with Glue Catalog.

  • AWS Identity and Access Management (IAM)

    Why it's wrong here

    IAM provides identity and access management but not column/row-level granularity.

  • AWS Glue Data Catalog

    Why this is correct

    Glue Data Catalog is the central metadata repository for Athena, EMR, and other services.

  • Amazon RDS for PostgreSQL

    Why it's wrong here

    RDS is a relational database, not a data catalog for the data lake.

  • Amazon DynamoDB

    Why it's wrong here

    DynamoDB is a key-value store and not used for data lake cataloging.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.