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Amazon Data-Engineer-Associate Exam Syllabus Topics:

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

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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q262-Q267):

NEW QUESTION # 262
A company uses Amazon DataZone as a data governance and business catalog solution. The company stores data in an Amazon S3 data lake. The company uses AWS Glue with an AWS Glue Data Catalog.
A data engineer needs to publish AWS Glue Data Quality scores to the Amazon DataZone portal.
Which solution will meet this requirement?

A. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an Amazon Redshift data source.Enable the data quality configuration for the data source.
B. Create a data quality ruleset with Data Quality Definition Language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.
C. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.
D. Create a data quality ruleset with Data Quality Definition Language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.

Answer: B

Explanation:
Publishing AWS Glue data quality scores to Amazon DataZone requires creating aDQDL ruleset, scheduling it to run regularly, and then linking the corresponding AWS Glue table as a data source in the DataZone project. The setup ensures that data quality scores from Glue are correctly published and accessible within Amazon DataZone:
"You can define DQDL rulesets for Glue tables and publish the data quality results to DataZone when the project is configured with an AWS Glue data source and the rulesets are scheduled."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf OptionCfollows the expected flow without unnecessary complexity and aligns perfectly with theintegration flow supported by AWS.

NEW QUESTION # 263
A company uses Amazon S3 to store data and Amazon QuickSight to create visualizations.
The company has an S3 bucket in an AWS account named Hub-Account. The S3 bucket is encrypted by an AWS Key Management Service (AWS KMS) key. The company's QuickSight instance is in a separate account named BI-Account The company updates the S3 bucket policy to grant access to the QuickSight service role. The company wants to enable cross-account access to allow QuickSight to interact with the S3 bucket.
Which combination of steps will meet this requirement? (Select TWO.)

A. Use the existing AWS KMS key to encrypt connections from QuickSight to the S3 bucket.
B. Add the 53 bucket as a resource that the QuickSight service role can access.
C. Add an IAM policy to the QuickSight service role to give QuickSight access to the KMS key that encrypts the S3 bucket.
D. Use AWS Resource Access Manager (AWS RAM) to share the S3 bucket with the Bl-Account account.
E. Add the KMS key as a resource that the QuickSight service role can access.

Answer: C,E

Explanation:
* Problem Analysis:
* The company needscross-account accessto allow QuickSight inBI-Accountto interact with anS3 bucket in Hub-Account.
* The bucket is encrypted with anAWS KMS key.
* Appropriate permissions must be set for bothS3 accessandKMS decryption.
* Key Considerations:
* QuickSight requiresIAM permissionsto access S3 data and decrypt files using the KMS key.
* Both S3 and KMS permissions need to be properly configured across accounts.
* Solution Analysis:
* Option A: Use Existing KMS Key for Encryption
* While the existing KMS key is used for encryption, it must also grant decryption permissions to QuickSight.
* Option B: Add S3 Bucket to QuickSight Role
* Granting S3 bucket access to the QuickSight service role is necessary for cross-account access.
* Option C: AWS RAM for Bucket Sharing
* AWS RAM is not required; bucket policies and IAM roles suffice for granting cross- account access.
* Option D: IAM Policy for KMS Access
* QuickSight's service role in BI-Account needs explicit permissions to use the KMS key for decryption.
* Option E: Add KMS Key as Resource for Role
* The KMS key must explicitly list the QuickSight role as an entity that can access it.
* Implementation Steps:
* S3 Bucket Policy in Hub-Account:Add a policy to the S3 bucket granting the QuickSight service role access:
json
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": { "AWS": "arn:aws:iam::<BI-Account-ID>:role/service-role/QuickSightRole" },
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::<Bucket-Name>/*"
}
]
}
* KMS Key Policy in Hub-Account:Add permissions for the QuickSight role:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": { "AWS": "arn:aws:iam::<BI-Account-ID>:role/service-role/QuickSightRole" },
"Action": [
"kms:Decrypt",
"kms:DescribeKey"
],
"Resource": "*"
}
]
}
* IAM Policy for QuickSight Role in BI-Account:Attach the following policy to the QuickSight service role:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:GetObject",
"kms:Decrypt"
],
"Resource": [
"arn:aws:s3:::<Bucket-Name>/*",
"arn:aws:kms:<region>:<Hub-Account-ID>:key/<KMS-Key-ID>"
]
}
]
}
:
Setting Up Cross-Account S3 Access
AWS KMS Key Policy Examples
Amazon QuickSight Cross-Account Access

NEW QUESTION # 264
A data engineer is configuring Amazon SageMaker Studio to use AWS Glue interactive sessions to prepare data for machine learning (ML) models.
The data engineer receives an access denied error when the data engineer tries to prepare the data by using SageMaker Studio.
Which change should the engineer make to gain access to SageMaker Studio?

A. Add the AWSGlueServiceRole managed policy to the data engineer's IAM user.
B. Add the AmazonSageMakerFullAccess managed policy to the data engineer's IAM user.
C. Add a policy to the data engineer's IAM user that allows the sts:AddAssociation action for the AWS Glue and SageMaker service principals in the trust policy.
D. Add a policy to the data engineer's IAM user that includes the sts:AssumeRole action for the AWS Glue and SageMaker service principals in the trust policy.

Answer: D

Explanation:
This solution meets the requirement of gaining access to SageMaker Studio to use AWS Glue interactive sessions. AWS Glue interactive sessions are a way to use AWS Glue DataBrew and AWS Glue Data Catalog from within SageMaker Studio. To use AWS Glue interactive sessions, the data engineer's IAM user needs to have permissions to assume the AWS Glue service role and the SageMaker execution role. By adding a policy to the data engineer's IAM user that includes the sts:AssumeRole action for the AWS Glue and SageMaker service principals in the trust policy, the data engineer can grant these permissions and avoid the access denied error. The other options are not sufficient or necessary to resolve the error. Reference:
Get started with data integration from Amazon S3 to Amazon Redshift using AWS Glue interactive sessions Troubleshoot Errors - Amazon SageMaker AccessDeniedException on sagemaker:CreateDomain in AWS SageMaker Studio, despite having SageMakerFullAccess

NEW QUESTION # 265
A data engineer needs to onboard a new data producer into AWS. The data producer needs to migrate data products to AWS.
The data producer maintains many data pipelines that support a business application. Each pipeline must have service accounts and their corresponding credentials. The data engineer must establish a secure connection from the data producer's on-premises data center to AWS. The data engineer must not use the public internet to transfer data from an on-premises data center to AWS.
Which solution will meet these requirements?

A. Instruct the new data producer to create Amazon Machine Images (AMIs) on Amazon Elastic Container Service (Amazon ECS) to store the code base of the application. Create security groups in a public subnet that allow connections only to the on-premises data center.
B. Create an AWS Direct Connect connection to the on-premises data center. Store the service account credentials in AWS Secrets manager.
C. Create a security group in a public subnet. Configure the security group to allow only connections from the CIDR blocks that correspond to the data producer. Create Amazon S3 buckets than contain presigned URLS that have one-day expiration dates.
D. Create an AWS Direct Connect connection to the on-premises data center. Store the application keys in AWS Secrets Manager. Create Amazon S3 buckets that contain resigned URLS that have one-day expiration dates.

Answer: B

Explanation:
For secure migration of data from an on-premises data center to AWS without using the public internet,AWS Direct Connectis the most secure and reliable method. UsingSecrets Managerto store service account credentials ensures that the credentials are managed securely with automatic rotation.
* AWS Direct Connect:
* Direct Connect establishes adedicated, private connectionbetween the on-premises data center and AWS, avoiding the public internet. This is ideal for secure, high-speed data transfers.
Reference:AWS Direct Connect
AWS Secrets Manager:
Secrets Manager securely stores and rotatesservice account credentials, reducing operational overhead while ensuring security.
Reference:AWS Secrets Manager
Alternatives Considered:
A (ECS with security groups): This does not address the need for a secure, private connection from the on- premises data center.
C (Public subnet with presigned URLs): This involves using the public internet, which does not meet the requirement.
D (Direct Connect with presigned URLs): While Direct Connect is correct, presigned URLs with short expiration dates are unnecessary for this use case.
References:
AWS Direct Connect Documentation
AWS Secrets Manager Documentation

NEW QUESTION # 266
A company has a production AWS account that runs company workloads. The company's security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs.
The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.
Which solution will meet these requirements?

A. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.
B. Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.
C. Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
D. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account.

Answer: D

Explanation:
Amazon Kinesis Data Streams is a service that enables you to collect, process, and analyze real-time streaming data. You can use Kinesis Data Streams to ingest data from various sources, such as Amazon CloudWatch Logs, and deliver it to different destinations, such as Amazon S3 or Amazon Redshift. To use Kinesis Data Streams to deliver the security logs from the production AWS account to the security AWS account, you need to create a destination data stream in the security AWS account. This data stream will receive the log data from the CloudWatch Logs service in the production AWS account. To enable this cross- account data delivery, you need to create an IAM role and a trust policy in the security AWS account. The IAM role defines the permissions that the CloudWatch Logs service needs to put data into the destination data stream. The trust policy allows the production AWS account to assume the IAM role. Finally, you need to create a subscription filter in the production AWS account. A subscription filter defines the pattern to match log events and the destination to send the matching events. In this case, the destination is the destination data stream in the security AWS account. This solution meets the requirements of using Kinesis Data Streams to deliver the security logs to the security AWS account. The other options are either not possible or not optimal.
You cannot create a destination data stream in the production AWS account, as this would not deliver the data to the security AWS account. You cannot create a subscription filter in the security AWS account, as this would not capture the log events from the production AWS account. References:
* Using Amazon Kinesis Data Streams with Amazon CloudWatch Logs
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.3: Amazon Kinesis Data Streams

NEW QUESTION # 267
......

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