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DEA-C01 試験練習問題

AWS Certified Data Engineer – Associate

DEA-C01 の PDF 練習問題。資料の言語は 英語です。購入はこの試験のみで、自動更新はありません。

試験概要

DEA-C01 は「AWS Certified Data Engineer – Associate」の認定試験です。試験形式、時間、対応言語は以下をご確認ください。最新の出題範囲や受験条件は公式サイトをご参照ください。

試験コード
DEA-C01
公式の試験・資格名
AWS Certified Data Engineer – Associate
試験形式
Single-answer and multiple-response 問
試験時間
130 分
公式試験の問題数
65 問
受験可能な言語
英語、日本語、韓国語、簡体字中国語

公式試験の対応言語と練習問題ファイルの言語は異なります。試験の版と言語は公式の予約ページでご確認ください。

公式情報： 公式サイト
情報確認日：2026-10-20

対応言語

  • 英語
  • 簡体字中国語
購入前にお試し

最初の 20 問を無料プレビュー

全 366 問

題庫の元の順序で表示します。回答欄を開くと、正解と収録されている解説を確認できます。

問題の言語：英語。問題文・選択肢・正解・解説は元の題庫の言語で表示します。

免責事項：ExamPico の問題はすべてインターネット上の情報を整理したもので、学習参考用として提供しています。

問題 1

Question#1Topic1

A data engineer is configuring an AWS Glue job to read data from an Amazon S3 bucket. The data engineer has set up the necessary AWS Glue connection details and an associated IAM role. However, when the data engineer attempts to run the AWS Glue job, the data engineer receives an error message that indicates that there are problems with the Amazon S3 VPC gateway endpoint.
The data engineer must resolve the error and connect the AWS Glue job to the S3 bucket.
Which solution will meet this requirement?

  1. A. Update the AWS Glue security group to allow inbound traffic from the Amazon S3 VPC gateway endpoint.
  2. B. Configure an S3 bucket policy to explicitly grant the AWS Glue job permissions to access the S3 bucket.
  3. C. Review the AWS Glue job code to ensure that the AWS Glue connection details include a fully qualified domain name.
  4. D. Verify that the VPC's route table includes inbound and outbound routes for the Amazon S3 VPC gateway endpoint.
正解を表示

正解

D

問題 2

Question#2Topic1

A retail company has a customer data hub in an Amazon S3 bucket. Employees from many countries use the data hub to support company-wide analytics. A governance team must ensure that the company's data analysts can access data only for customers who are within the same country as the analysts.
Which solution will meet these requirements with the LEAST operational effort?

  1. A. Create a separate table for each country's customer data. Provide access to each analyst based on the country that the analyst serves.
  2. B. Register the S3 bucket as a data lake location in AWS Lake Formation. Use the Lake Formation row-level security features to enforce the company's access policies.
  3. C. Move the data to AWS Regions that are close to the countries where the customers are. Provide access to each analyst based on the country that the analyst serves.
  4. D. Load the data into Amazon Redshift. Create a view for each country. Create separate IAM roles for each country to provide access to data from each country. Assign the appropriate roles to the analysts.
正解を表示

正解

B

問題 3

Question#3Topic1

A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform.
The company wants to minimize the effort and time required to incorporate third-party datasets.
Which solution will meet these requirements with the LEAST operational overhead?

  1. A. Use API calls to access and integrate third-party datasets from AWS Data Exchange.
  2. B. Use API calls to access and integrate third-party datasets from AWS DataSync.
  3. C. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
  4. D. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).
正解と解説を表示

正解

A

解説

"You can also discover and subscribe to new third-party data sets available through AWS Data Exchange" https://docs.aws.amazon.com/data-exchange/latest/userguide/what-is.html

問題 4

Question#4Topic1

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.
Which combination of AWS services will implement a data mesh? (Choose two.)

  1. A. Use Amazon Aurora for data storage. Use an Amazon Redshift provisioned cluster for data analysis.
  2. B. Use Amazon S3 for data storage. Use Amazon Athena for data analysis.
  3. C. Use AWS Glue DataBrew for centralized data governance and access control.
  4. D. Use Amazon RDS for data storage. Use Amazon EMR for data analysis.
  5. E. Use AWS Lake Formation for centralized data governance and access control.
正解と解説を表示

正解

BE

解説

The data mesh implementation uses Amazon S3 and Athena for data storage and analysis, and AWS Lake Formation for centralized data governance and access control. When combined with AWS Glue, you can efficiently manage your data.

問題 5

Question#5Topic1

A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.
The data engineer requires a less manual way to update the Lambda functions.
Which solution will meet this requirement?

  1. A. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.
  2. B. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.
  3. C. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.
  4. D. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.
正解と解説を表示

正解

B

解説

Lambda layers allow you to centrally manage shared code and dependencies across multiple Lambda functions. By packaging the custom Python scripts into a Lambda layer, you can simply update the layer whenever changes are made to the scripts, and all the Lambda functions that use the layer will automatically inherit the updates. This approach reduces manual effort and ensures consistency across the functions.

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