Amazon-DEA-C01 practice materials Questions Answers

Exam Code:
Amazon-DEA-C01
Exam Name:
AWS Certified Data Engineer – Associate Exam
Last Update:
Jun 01,2026

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Amazon-DEA-C01 Questions for AWS Certified Data Engineer Associate Certification Exam 2026

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Page: 1 / 26
Total Questions: 130

Questions & Answers PDF

• Question 1

  

  A data engineer needs to debug an AWS Glue job that reads from Amazon S3 and writes to Amazon Redshift. The data engineer enabled the bookmark feature for the AWS Glue job. The data engineer has set the maximum concurrency for the AWS Glue job to 1.The AWS Glue job is successfully writing the output to Amazon Redshift. However, the Amazon S3 files that were loaded during previous runs of the AWS Glue job are being reprocessed by subsequent runs.What is the likely reason the AWS Glue job is reprocessing the files?

  • The AWS Glue job does not have the s3:GetObjectAcl permission that is required for bookmarks to work correctly.
  • The maximum concurrency for the AWS Glue job is set to 1.
  • The data engineer incorrectly specified an older version of AWS Glue for the Glue job.
  • The AWS Glue job does not have a required commit statement.

  Reveal Answer Answer: A Next Question

• Question 2

  

  A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR.Which solution will meet these requirements with the LEAST operational overhead?

  • Use Amazon S3 for data lake storage. Use S3 access policies to restrict data access by rows and columns. Provide data access through Amazon S3.
  • Use Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR to restrict data access by rows and columns. Provide data access by using Apache Pig.
  • Use Amazon Redshift for data lake storage. Use Redshift security policies to restrict data access by rows and columns. Provide data access by using Apache Spark and Amazon Athena federated queries.
  • Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.

  Reveal Answer Answer: D Next Question

• Question 3

  

  A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.Which solution will meet these requirements with the LEAST operational overhead?

  • Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.
  • Create an AWS Lambda Python function with provisioned concurrency.
  • Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).
  • Create an AWS Lambda function. Ensure that the function is warm by scheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by using mock events.

  Reveal Answer Answer: B Next Question

• Question 4

  

  A marketing company uses Amazon S3 to store marketing datThe company uses versioning in some buckets. The company runs several jobs to read and load data into the buckets.To help cost-optimize its storage, the company wants to gather information about incomplete multipart uploads and outdated versions that are present in the S3 buckets.Which solution will meet these requirements with the LEAST operational effort?

  • Use AWS CLI to gather the information.
  • Use Amazon S3 Inventory configurations reports to gather the information.
  • Use the Amazon S3 Storage Lens dashboard to gather the information.
  • Use AWS usage reports for Amazon S3 to gather the information.

  Reveal Answer Answer: B Next Question

• Question 5

  

  A company maintains a data warehouse in an on-premises Oracle database. The company wants to build a data lake on AWS. The company wants to load data warehouse tables into Amazon S3 and synchronize the tables with incremental data that arrives from the data warehouse every day.Each table has a column that contains monotonically increasing values. The size of each table is less than 50 GB. The data warehouse tables are refreshed every night between 1 AM and 2 AM. A business intelligence team queries the tables between 10 AM and 8 PM every day.Which solution will meet these requirements in the MOST operationally efficient way?

  • Use an AWS Database Migration Service (AWS DMS) full load plus CDC job to load tables that contain monotonically increasing data columns from the on-premises data warehouse to Amazon S3. Use custom logic in AWS Glue to append the daily incremental data to a full-load copy that is in Amazon S3.
  • Use an AWS Glue Java Database Connectivity (JDBC) connection. Configure a job bookmark for a column that contains monotonically increasing values. Write custom logic to append the daily incremental data to a full-load copy that is in Amazon S3.
  • Use an AWS Database Migration Service (AWS DMS) full load migration to load the data warehouse tables into Amazon S3 every day Overwrite the previous day's full-load copy every day.
  • Use AWS Glue to load a full copy of the data warehouse tables into Amazon S3 every day. Overwrite the previous day's full-load copy every day.

  Reveal Answer Answer: A Next Question

• Question 6

  

  A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket.The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.Which solution will meet these requirements with the LOWEST latency?

  • Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.
  • Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard.
  • Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Create a new Data Firehose delivery stream to publish data directly to an Amazon Timestream database. Use the Timestream database as a source to create an Amazon QuickSight dashboard.
  • Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.

  Reveal Answer Answer: C Next Question

• Question 7

  

  A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes.A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake.Which solution will capture the changed data MOST cost-effectively?

  • Create an AWS Lambda function to identify the changes between the previous data and the current data. Configure the Lambda function to ingest the changes into the data lake.
  • Ingest the data into Amazon RDS for MySQL. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
  • Use an open source data lake format to merge the data source with the S3 data lake to insert the new data and update the existing data.
  • Ingest the data into an Amazon Aurora MySQL DB instance that runs Aurora Serverless. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.

  Reveal Answer Answer: C Next Question

• Question 8

  

  A data engineer needs to maintain a central metadata repository that users access through Amazon EMR and Amazon Athena queries. The repository needs to provide the schema and properties of many tables. Some of the metadata is stored in Apache Hive. The data engineer needs to import the metadata from Hive into the central metadata repository.Which solution will meet these requirements with the LEAST development effort?

  • Use Amazon EMR and Apache Ranger.
  • Use a Hive metastore on an EMR cluster.
  • Use the AWS Glue Data Catalog.
  • Use a metastore on an Amazon RDS for MySQL DB instance.

  Reveal Answer Answer: C Next Question

• Question 9

  

  A company has five offices in different AWS Regions. Each office has its own human resources (HR) department that uses a unique IAM role. The company stores employee records in a data lake that is based on Amazon S3 storage.A data engineering team needs to limit access to the records. Each HR department should be able to access records for only employees who are within the HR department's Region.Which combination of steps should the data engineering team take to meet this requirement with the LEAST operational overhead? (Choose two.)

  • Use data filters for each Region to register the S3 paths as data locations.
  • Register the S3 path as an AWS Lake Formation location.
  • Modify the IAM roles of the HR departments to add a data filter for each department's Region.
  • Enable fine-grained access control in AWS Lake Formation. Add a data filter for each Region.
  • Create a separate S3 bucket for each Region. Configure an IAM policy to allow S3 access. Restrict access based on Region.

  Reveal Answer Answer: B, ,D Next Question

• Question 10

  

  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?

  • Use API calls to access and integrate third-party datasets from AWS Data Exchange.
  • Use API calls to access and integrate third-party datasets from AWS
  • Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
  • Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

  Reveal Answer Answer: A Next Question

Page: 1 / 26
Total Questions: 130

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