AWS Data Engineer Associate Practice Exam
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Official Name: AWS Certified Data Engineer - Associate
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Start NowAbout the AWS Data Engineer Associate Certification
The AWS Data Engineer Associate certification is designed for professionals who build and maintain data pipelines, integrate data sources, and optimize data processing workflows using IBM data engineering tools. As technology evolves and industry demands grow more complex; this credential validates your ability to apply real-world skills and knowledge using AWS tools and frameworks. Earning the certification positions you as a trusted expert, capable of solving high-impact challenges and contributing to secure, scalable, and efficient systems.
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Test Your Knowledge of AWS Data Engineer Associate
Question #1
The company wants to automate ETL pipelines.
What is the best starting point?
A) Use a managed ETL service with scheduling and monitoring.
B) Only run ETL jobs manually.
C) Disable scheduling.
D) Ignore job failures.
Solution
Correct answers: A – Explanation:
Managed/scheduled ETL is reliable. Manual/disabling/ignoring is risky.
Question #2
The team needs to ensure data quality.
What is the recommended practice?
A) Implement data validation and cleansing steps in pipelines.
B) Only check quality at the end.
C) Disable validation.
D) Ignore bad data.
Solution
Correct answers: A – Explanation:
Validation/cleansing catch errors early. End/disabling/ignoring is insufficient.
Question #3
The business must secure sensitive data in transit.
What should they do?
A) Enable encryption for all data transfers between systems.
B) Only encrypt some transfers.
C) Disable encryption.
D) Ignore transfer security.
Solution
Correct answers: A – Explanation:
Encryption in transit prevents leaks. Some/disabling/ignoring is unsafe.
Question #4
The company wants to optimize data storage costs.
What is the best solution?
A) Tier data by access frequency and use lifecycle policies.
B) Only store on premium disks.
C) Disable lifecycle management.
D) Ignore storage costs.
Solution
Correct answers: A – Explanation:
Tiering/policies control costs. Premium/disabling/ignoring is expensive.
Question #5
The team must support real-time analytics.
What is the first step?
A) Deploy a streaming data platform for ingest and processing.
B) Only batch process data.
C) Disable streaming.
D) Ignore latency.
Solution
Correct answers: A – Explanation:
Streaming enables real-time. Batch/disabling/ignoring is slow.
Question #6
The business wants to automate data lineage tracking.
What is the best approach?
A) Integrate data lineage tools in ETL workflows.
B) Only track lineage manually.
C) Disable tracking.
D) Ignore data flows.
Solution
Correct answers: A – Explanation:
Automated tools ensure accuracy. Manual/disabling/ignoring is incomplete.
Question #7
The company must comply with data retention policies.
What should they do?
A) Configure automated data retention and deletion in storage systems.
B) Only delete data manually.
C) Disable retention rules.
D) Ignore job failures.
Solution
Correct answers: A – Explanation:
Automation ensures compliance. Manual/disabling/ignoring is unreliable.
Question #8
The team needs to support schema evolution.
What is a good solution?
A) Use schema registry and versioning in pipelines.
B) Only allow static schemas.
C) Disable registry.
D) Ignore schema changes.
Solution
Correct answers: A – Explanation:
Managed/scheduled ETL is reliable. Manual/disabling/ignoring is risky.
Question #9
The business wants to scale data pipelines.
What is the recommended method?
A) Use auto-scaling clusters and distributed processing.
B) Only run on single server.
C) Disable scaling.
D) Ignore workload peaks.
Solution
Correct answers: A – Explanation:
Auto-scaling/distributed scale easily. Single/disabling/ignoring is limiting.
Question #10
The company must monitor data pipeline health.
What is the best practice?
A) Deploy end-to-end monitoring with alerting for failures.
B) Only check logs after issues.
C) Disable monitoring.
D) Ignore alerts.
Solution
Correct answers: A – Explanation:
Monitoring/alerts detect problems fast. After/disabling/ignoring is too late.
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