20+ practice questions focused on Data Operations and Support — one of the most tested topics on the AWS Certified Data Engineer Associate DEA-C01 exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Data Operations and Support PracticeAn Amazon Kinesis Data Streams application is lagging behind. The data records are small (1 KB) and the shard count is 10. The consumer uses the KCL with default configuration. Which action will MOST effectively reduce the consumer lag?
Explanation: Enhanced Fan-Out provides each consumer with dedicated throughput (2 MB/s per shard) and eliminates the need for polling, which reduces latency and lag. Given that the consumer is lagging with default configuration and small records, Enhanced Fan-Out directly addresses the consumer-side bottleneck by providing dedicated read throughput, making it the most effective option. Option A is incorrect because the KCL does not support multiple workers per shard; each shard is processed by a single worker in a single-threaded manner. Option C may help if the shard is saturated with incoming data, but the problem is consumer lag, not data ingestion. Option D reduces data size but does not address the consumer processing speed.
A data engineer is troubleshooting a failed AWS Glue ETL job that reads from a JDBC source. The error log shows 'java.sql.SQLException: Connection timed out'. The job previously ran successfully. Which of the following is the MOST likely cause?
Explanation: The error 'Connection timed out' indicates a network-level failure, not an authentication or schema issue. Since the job previously ran successfully, the most likely cause is that the security group for the source database no longer allows inbound traffic from the Glue job's IP range. AWS Glue ETL jobs run in a VPC with elastic network interfaces, and the security group rules must permit traffic on the JDBC port (e.g., 5432 for PostgreSQL, 3306 for MySQL).
A data engineer is designing a solution to move data from an on-premises Oracle database to Amazon S3 using AWS DMS. The engineer needs to ensure that data changes are replicated continuously with minimal latency. Which DMS configuration is most appropriate?
Explanation: DMS with continuous replication (CDC) captures ongoing changes with low latency. Option A is wrong because AWS SCT is used for schema conversion, not data movement; DMS with full load only does an initial copy. Option C is wrong because a daily full-load task does not provide continuous replication or low latency. Option D is wrong because it describes Kinesis Data Streams, which is not a DMS configuration—DMS itself supports CDC to S3.
Refer to the exhibit. A data engineer runs this CloudWatch Logs Insights query on a log group but gets no results. What is the most likely reason?
Explanation: The query 'fields @timestamp, @message | filter @message like /ERROR/ | sort @timestamp desc | limit 20' is syntactically correct (so option A is wrong). The limit of 20 would still return results if matching log events existed (so B is wrong). Although CloudWatch Logs Insights defaults to the last 15 minutes, that alone doesn't explain zero results—if errors occurred in that window, they would appear; the lack of results suggests no 'ERROR' events exist in the scanned logs (so C is wrong). The most likely reason is that the log group contains no log events with the string 'ERROR', making option D correct.
A data engineer notices that an AWS Glue ETL job is failing with an OutOfMemory error when processing a large dataset. The job uses a Standard worker type. Which action is MOST effective to resolve this issue without changing the job script?
Explanation: The most effective action is to switch to the G.2X worker type (Option C). In AWS Glue, worker types determine the DPU and memory allocated per worker. Standard workers provide 0.25 DPU (4 GB memory). An OutOfMemory error indicates insufficient memory per worker. Changing to G.2X allocates 2 DPU (16 GB memory) per worker, directly resolving the issue without modifying the script. Option A (increasing workers) does not increase per-worker memory. Option B (G.1X) provides 1 DPU (8 GB), which may help but is less effective than G.2X. Option D is invalid because DPU per worker is not a configurable parameter; it is defined by the worker type.
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Practice all Data Operations and Support questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Data Operations and Support. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Data Operations and Support questions on the DEA-C01 frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Data Operations and Support is tested as part of the AWS Certified Data Engineer Associate DEA-C01 blueprint. Practicing with targeted Data Operations and Support questions ensures you can handle any format or difficulty that appears.
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Difficulty is subjective, but Data Operations and Support is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
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