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Amazon Data-Engineer-Associate Exam Syllabus Topics:

Section	Weight	Objectives
Data Operations and Support	22%	- Monitor and maintain data pipelines - Troubleshoot data workflow issues
Data Store Management	26%	- Select appropriate data storage solutions - Optimize storage performance and cost
Data Ingestion and Transformation	34%	- Ingest and transform data using AWS services - Build and manage data pipelines
Data Security and Governance	18%	- Apply governance and compliance best practices - Implement data security controls

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Data-Engineer-Associate Testantworten & Data-Engineer-Associate Demotesten

Es ist uns allen bekannt, dass IT-Branche eine neue Branche und auch eine Kette ist, die die wirtschaftliche Entwicklung fördert. So ist ihre Position nicht zu ignorieren. Die Amazon Data-Engineer-Associate IT-Zertifizierung ist eine Methode für den Wettbewerb. Durch die Amazon Data-Engineer-Associate Zertifizierung werden Sie sich in allen Aspekten verbessern. Aber es ist nicht so einfach, die Prüfung zu bestehen. So empfehle ich Ihnen unsere originale Fragen. Wenn Sie die Schulungsressourcen wählen, ist Pass4Test die erste Wahl. Seine Erfolgsquote beträgt 100%. Und Sie können die Amazon Data-Engineer-Associate Prüfung sicher bestehen.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate Prüfungsfragen mit Lösungen (Q261-Q266):

261. Frage
A company needs to optimize storage for an Amazon S3 bucket. Objects older than 1 year must be accessible within 5 hours. All versions of the objects must be retained and immutable for 7 years. All versions of the objects must use the write-once-read-many (WORM) model.
Which solution will meet these requirements?

A. Configure S3 Object Lock on the bucket and use the S3 Intelligent-Tiering storage class. Configure a lifecycle policy for the bucket to transition objects that are older than 1 year to S3 Glacier Deep Archive. Configure the policy to delete objects that are older than 7 years.
B. Configure S3 Versioning on the bucket and use the S3 Intelligent-Tiering storage class. Configure a lifecycle policy for the bucket to transition objects that are older than 1 year to S3 Glacier Flexible Retrieval. Configure the policy to delete objects that are older than 7 years.
C. Configure S3 Object Lock on the bucket and use the S3 Intelligent-Tiering storage class. Configure a lifecycle policy for the bucket to transition objects that are older than 1 year to S3 Glacier Flexible Retrieval. Configure the policy to delete objects that are older than 7 years.
D. Configure S3 Versioning on the bucket and use the S3 Intelligent-Tiering storage class. Configure a lifecycle policy for the bucket to transition objects that are older than 1 year to S3 Glacier Deep Archive. Configure the policy to delete objects that are older than 7 years.

Antwort: C

Begründung:
The requirement to retain immutable object versions using a WORM model mandates the use of S3 Object Lock, not just S3 Versioning. Object Lock enforces immutability by preventing deletion or modification of objects for a specified retention period, which is required for compliance scenarios such as regulatory data retention.
To meet the access requirement of retrieving data within 5 hours, the appropriate archival storage class is S3 Glacier Flexible Retrieval, which supports expedited and standard retrieval within minutes to hours. S3 Glacier Deep Archive does not meet this requirement because retrieval times are typically 12 hours or longer.
Using S3 Intelligent-Tiering for active data optimizes storage costs automatically before transitioning older objects. A lifecycle policy can then transition objects older than 1 year to Glacier Flexible Retrieval and delete them after the 7-year retention period expires.
Options that rely only on S3 Versioning do not provide immutability guarantees. Options using Glacier Deep Archive fail the access-time requirement. Therefore, Option C is the only solution that satisfies WORM compliance, retrieval-time constraints, and cost optimization.

262. Frage
A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wants to scale read and write capacity to meet demand. A data engineer needs to identify a solution that will turn on concurrency scaling.
Which solution will meet this requirement?

A. Turn on concurrency scaling at the workload management (WLM) queue level in the Redshift cluster.
B. Turn on concurrency scaling in workload management (WLM) for Redshift Serverless workgroups.
C. Turn on concurrency scaling for the daily usage quota for the Redshift cluster.
D. Turn on concurrency scaling in the settings during the creation of and new Redshift cluster.

Antwort: B

263. Frage
A company is planning to upgrade its Amazon Elastic Block Store (Amazon EBS) General Purpose SSD storage from gp2 to gp3. The company wants to prevent any interruptions in its Amazon EC2 instances that will cause data loss during the migration to the upgraded storage.
Which solution will meet these requirements with the LEAST operational overhead?

A. Change the volume type of the existing gp2 volumes to gp3. Enter new values for volume size, IOPS, and throughput.
B. Create snapshots of the gp2 volumes. Create new gp3 volumes from the snapshots. Attach the new gp3 volumes to the EC2 instances.
C. Use AWS DataSync to create new gp3 volumes. Transfer the data from the original gp2 volumes to the new gp3 volumes.
D. Create new gp3 volumes. Gradually transfer the data to the new gp3 volumes. When the transfer is complete, mount the new gp3 volumes to the EC2 instances to replace the gp2 volumes.

Antwort: A

Begründung:
Changing the volume type of the existing gp2 volumes to gp3 is the easiest and fastest way to migrate to the new storage type without any downtime or data loss. You can use the AWS Management Console, the AWS CLI, or the Amazon EC2 API to modify the volume type, size, IOPS, and throughput of your gp2 volumes.
The modification takes effect immediately, and you can monitor the progress of the modification using CloudWatch. The other options are either more complex or require additional steps, such as creating snapshots, transferring data, or attaching new volumes, which can increase the operational overhead and the risk of errors. References:
Migrating Amazon EBS volumes from gp2 to gp3 and save up to 20% on costs (Section: How to migrate from gp2 to gp3) Switching from gp2 Volumes to gp3 Volumes to Lower AWS EBS Costs (Section: How to Switch from GP2 Volumes to GP3 Volumes) Modifying the volume type, IOPS, or size of an EBS volume - Amazon Elastic Compute Cloud (Section:
Modifying the volume type)

264. Frage
A company has an application that is deployed on AWS. The application uses Amazon Simple Notification Service (Amazon SNS) with multiple topics. The company's security team needs to be able to audit all Publish and PublishBatch API actions for all the SNS topics. The company ' s application team and security team must also be able to query the audit data. The company has already established an event data store in AWS CloudTrail Lake to collect all events.
Which solution will meet these requirements with the LEAST operational overhead?

A. Enable data events for the SNS topics. Create a table in AWS Glue Data Catalog. Query the data by using Amazon Athena.
B. Enable management events for the SNS topics. Create a table in AWS Glue Data Catalog. Query the data by using Amazon Athena.
C. Enable data events for the SNS topics. Use CloudTrail Lake to query the audit data.
D. Enable management events for the SNS topics. Use CloudTrail Lake to query the audit data.

Antwort: C

Begründung:
The correct answer is C because SNS Publish and PublishBatch operations are data-plane operations, not ordinary management events. AWS CloudTrail documentation specifically lists Amazon SNS Publish and PublishBatch API operations on topics as supported data events. Because the company already has a CloudTrail Lake event data store, the lowest-operational-overhead approach is to enable the relevant SNS data events and query them directly in CloudTrail Lake. Creating Glue Data Catalog tables and querying with Athena adds unnecessary cataloging and query infrastructure. Management events would not satisfy the requirement to audit the requested SNS publishing actions. Therefore, the precise configuration is SNS data events plus CloudTrail Lake querying.

265. Frage
A company receives .csv files that contain physical address data. The data is in columns that have the following names: Door_No, Street_Name, City, and Zip_Code. The company wants to create a single column to store these values in the following format:

Which solution will meet this requirement with the LEAST coding effort?

A. Write a Lambda function in Python to read the files. Use the Python data dictionary type to create the new column.
B. Use AWS Glue DataBrew to read the files. Use the PIVOT transformation to create the new column.
C. Use AWS Glue DataBrew to read the files. Use the NEST TO MAP transformation to create the new column.
D. Use AWS Glue DataBrew to read the files. Use the NEST TO ARRAY transformation to create the new column.

Antwort: C

Begründung:
The NEST TO MAP transformation allows you to combine multiple columns into a single column that contains a JSON object with key-value pairs. This is the easiest way to achieve the desired format for the physical address data, as you can simply select the columns to nest and specify the keys for each column. The NEST TO ARRAY transformation creates a single column that contains an array of values, which is not the same as the JSON object format. The PIVOT transformation reshapes the data by creating new columns from unique values in a selected column, which is not applicable for this use case. Writing a Lambda function in Python requires more coding effort than using AWS Glue DataBrew, which provides a visual and interactive interface for data transformations. References:
7 most common data preparation transformations in AWS Glue DataBrew (Section: Nesting and unnesting columns) NEST TO MAP - AWS Glue DataBrew (Section: Syntax)

266. Frage
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Die Examfragen zur Amazon Data-Engineer-Associate Zertifizierungsprüfung von Pass4Test ist von den IT-Experten verifiziert und überprüft. Die Fragen und Antworten zur Amazon Data-Engineer-Associate Zertifizierungsprüfung sind die von der Praxis überprüfte Software und die Schulungsinstrumente. In Pass4Test werden Sie die besten Zertifizierungsmaterialien finden, die originale Fragen und Antworten enthalten. Unsere Materialien bieten Ihnen die Chance, die echten Übungen zu machen. Endlich werden Sie Ihr Ziel, nämlich die Amazon Data-Engineer-Associate Zertifizierungsprüfung zu bestehen, erreichen.

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