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AWS Certified Data Engineer – Associate Exam (DEA-C01) - AWS Exam Questions
Last updated on June 20, 2026
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294
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1
Question
A company has a data processing pipeline that runs multiple SQL queries in sequence against an Amazon Redshift cluster. After a merger, a query joining two large sales tables becomes slow. Table S1 has 10 billion records, Table S2 has 900 million records. The query performance must improve.
Select 2
Options
A
Use the KEY distribution style for both sales tables. Select a low cardinality column to use for the join.
B
Use the EVEN distribution style for Table S1. Use the ALL distribution style for Table S2.
C
Use the KEY distribution style for both sales tables. Select a high cardinality column to use for the join.
D
Use the Amazon Redshift query optimizer to review and select optimizations to implement.
E
Use Amazon Redshift Advisor to review and select optimizations to implement.
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2
Question
A company runs multiple applications on AWS. The company configured each application to output logs. The company wants to query and visualize the application logs in near real time.
Which solution will meet these requirements?
Which solution will meet these requirements?
Options
A
Configure the applications to output logs to Amazon CloudWatch Logs log groups. Use CloudWatch log anomaly detection to query and visualize the log data.
B
Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an Amazon S3 bucket. Create an AWS Lambda function that runs on a schedule to export the required log groups to the S3 bucket. Use Amazon Athena to query the log data in the S3 bucket.
C
Create an Amazon OpenSearch Service domain. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an OpenSearch Service subscription filter for each log group to stream the data to OpenSearch. Create the required queries and dashboards in OpenSearch
Service to analyze and visualize the data.
Service to analyze and visualize the data.
D
Update the application code to send the log data to Amazon QuickSight by using Super-fast,
Parallel, In-memory Calculation Engine (SPICE). Create the required analyses and dashboards in QuickSight.
Parallel, In-memory Calculation Engine (SPICE). Create the required analyses and dashboards in QuickSight.
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3
Question
A retail company is expanding its operations globally. The company needs to use Amazon QuickSight to accurately calculate currency exchange rates for financial reports. The company has an existing dashboard that includes a visual that is based on an analysis of a dataset that contains global currency values and exchange rates. A data engineer needs to ensure that exchange rates are calculated with a precision of four decimal places. The calculations must be precomputed. The data engineer must materialize results in QuickSight super-fast, parallel, in-memory calculation engine (SPICE).
Which solution will meet these requirements?
Which solution will meet these requirements?
Options
A
Define and create the calculated field in the visual.
B
Define and create the calculated field in the dataset.
C
Define and create the calculated field in the analysis.
D
Define and create the calculated field in the dashboard.
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4
Question
A data engineer is configuring an AWS Glue Apache Spark extract, transform, and load (ETL) job. The job contains a sort-merge join of two large and equally sized DataFrames. The job is failing with the following error: No space left on device.
Which solution will resolve the error?
Which solution will resolve the error?
Options
A
Convert the sort-merge join in the job to be a broadcast join.
B
Use the AWS Glue Spark shuffle manager.
C
Deploy an Amazon Elastic Block Store (Amazon EBS) volume for the job to use.
D
Convert the DataFrames to DynamicFrames, and perform a DynamicFrame join in the job.
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5
Question
A company has a data processing pipeline that includes several dozen steps. The data processing pipeline needs to send alerts in real time when a step fails or succeeds. The data processing pipeline uses a combination of Amazon S3 buckets, AWS Lambda functions, and AWS Step Functions state machines. A data engineer needs to create a solution to monitor the entire pipeline.
Which solution will meet these requirements?
Which solution will meet these requirements?
Options
A
Use AWS CloudTrail to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications when a state machine fails to run or succeeds to run.
B
Configure the Step Functions state machines to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.
C
Configure the AWS Lambda functions to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.
D
Configure an Amazon EventBridge rule to react when the execution status of a state machine changes. Configure the rule to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications.
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