Free AWS-CERTIFIED-DATA-ENGINEER-ASSOCIATE-DEA-C01 Amazon AWS-CERTIFIED-DATA-ENGINEER-ASSOCIATE-DEA-C01 Practice Test Question - Page 5

Question 13 (Topic 1)

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? (Choose two.)

Select an option, then click Submit answer.

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

Reference / correct answer:

Add the S3 bucket as a resource that the QuickSight service role can access.

Most accepted answer: B. Add the S3 bucket as a resource that the QuickSight service role can access.

Community votes: B=6, D=3, E=3

Selected Answer: E D & E S3 bucket policy is already updated from the question. Hence KMS key policy and IAM policy need to be altered to allow QuickSight service account to access KMS key. upvoted 6 times

Answer : DE upvoted 5 times

Selected Answer: B B & D. use chat gpt it will give you correct answer upvoted 1 times

Selected Answer: D BD: Answer would be B and D Add the S3 bucket as a resource that the QuickSight service role can access: In the BI-Account (where QuickSight is located), you must explicitly register the Hub-Account's S3 bucket within the QuickSight settings. This is done by navigating to Manage QuickSight > Security & permissions and adding the specific cross-account bucket name under the S3 bucket selection. Add an IAM policy to the QuickSight service role to grant access to the KMS key: Because the bucket is encrypted with an AWS KMS key in another account, the QuickSight service role in the BI-Account requires explicit permission to use that key for decryption. This is achieved by attaching an IAM policy to the aws-quicksight-service-role-v0 in the BI-Account that allows kms:Decrypt and kms:DescribeKey on the Hub-Account's KMS key ARN upvoted 3 times

Selected Answer: D Answer: B and D. B explicitly states adding S3 as a resource to the QuickSight role's IAM policy (s3:GetObject, s3:ListBucket permissions needed in BI-Account) D explicitly states adding KMS permissions to the role's IAM policy (kms:Decrypt needed) E is vague—"add KMS key as a resource" could mean UI config or policy, but doesn't specify the IAM policy on the role. upvoted 1 times

Question 14 (Topic 1)

A retail company is using an Amazon Redshift cluster to support real-time inventory management. The company has deployed an ML model on a real-time endpoint in Amazon SageMaker. The company wants to make real-time inventory recommendations. The company also wants to make predictions about future inventory needs. Which solutions will meet these requirements? (Choose two.)

Select an option, then click Submit answer.

○ Use Amazon Redshift ML to generate inventory recommendations.
○ Use SQL to invoke a remote SageMaker endpoint for prediction.
○ Use Amazon Redshift ML to schedule regular data exports for offline model training.
○ Use SageMaker Autopilot to create inventory management dashboards in Amazon Redshift.
○ Use Amazon Redshift as a file storage system to archive old inventory management reports.

Question 15 (Topic 1)

A company stores CSV files in an Amazon S3 bucket. A data engineer needs to process the data in the CSV files and store the processed data in a new S3 bucket. The process needs to rename a column, remove specific columns, ignore the second row of each file, create a new column based on the values of the first row of the data, and filter the results by a numeric value of a column. Which solution will meet these requirements with the LEAST development effort?

Select an option, then click Submit answer.

○ Use AWS Glue Python jobs to read and transform the CSV files.
○ Use an AWS Glue custom crawler to read and transform the CSV files.
○ Use an AWS Glue workflow to build a set of jobs to crawl and transform the CSV files.
○ Use AWS Glue DataBrew recipes to read and transform the CSV files.

Free AWS-CERTIFIED-DATA-ENGINEER-ASSOCIATE-DEA-C01 – Amazon AWS-CERTIFIED-DATA-ENGINEER-ASSOCIATE-DEA-C01 Practice Test Question