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Vce DAS-C01 Questions Latest

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Total 207 questions
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AWS Certified Data Analytics - Specialty Questions and Answers

Question 25

A company uses Amazon Redshift as its data warehouse. The Redshift cluster is not encrypted. A data analytics specialist needs to use hardware security module (HSM) managed encryption keys to encrypt the data that is stored in the Redshift cluster.

Which combination of steps will meet these requirements? (Select THREE.)

Options:

A.

Stop all write operations on the source cluster. Unload data from the source cluster.

B.

Copy the data to a new target cluster that is encrypted with AWS Key Management Service (AWS KMS).

C.

Modify the source cluster by activating AWS CloudHSM encryption. Configure Amazon Redshift to automatically migrate data to a new encrypted cluster.

D.

Modify the source cluster by activating encryption from an external HSM. Configure Amazon Redshift to automatically migrate data to a new encrypted cluster.

E.

Copy the data to a new target cluster that is encrypted with an HSM from AWS CloudHSM.

F.

Rename the source cluster and the target cluster after the migration so that the target cluster is using the original endpoint.

Question 26

A company has a marketing department and a finance department. The departments are storing data in Amazon S3 in their own AWS accounts in AWS Organizations. Both departments use AWS Lake Formation to catalog and secure their data. The departments have some databases and tables that share common names.

The marketing department needs to securely access some tables from the finance department.

Which two steps are required for this process? (Choose two.)

Options:

A.

The finance department grants Lake Formation permissions for the tables to the external account for the marketing department.

B.

The finance department creates cross-account IAM permissions to the table for the marketing department role.

C.

The marketing department creates an IAM role that has permissions to the Lake Formation tables.

Question 27

Three teams of data analysts use Apache Hive on an Amazon EMR cluster with the EMR File System (EMRFS) to query data stored within each teams Amazon S3 bucket. The EMR cluster has Kerberos enabled and is configured to authenticate users from the corporate Active Directory. The data is highly sensitive, so access must be limited to the members of each team.

Which steps will satisfy the security requirements?

Options:

A.

For the EMR cluster Amazon EC2 instances, create a service role that grants no access to Amazon S3. Create three additional IAM roles, each granting access to each team’s specific bucket. Add the additional IAM roles to the cluster’s EMR role for the EC2 trust policy. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

B.

For the EMR cluster Amazon EC2 instances, create a service role that grants no access to Amazon S3. Create three additional IAM roles, each granting access to each team's specific bucket. Add the service role for the EMR cluster EC2 instances to the trust policies for the additional IAM roles.Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

C.

For the EMR cluster Amazon EC2 instances, create a service role that grants full access to Amazon S3. Create three additional IAM roles, each granting access to each team’s specific bucket. Add the service role for the EMR cluster EC2 instances to the trust polices for the additional IAM roles. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

D.

For the EMR cluster Amazon EC2 instances, create a service role that grants full access to Amazon S3. Create three additional IAM roles, each granting access to each team's specific bucket. Add the service role for the EMR cluster EC2 instances to the trust polices for the base IAM roles. Create a security configuration mapping for the additional IAM roles to Active Directory user groups for each team.

Question 28

A company is building a service to monitor fleets of vehicles. The company collects IoT data from a device in each vehicle and loads the data into Amazon Redshift in near-real time. Fleet owners upload .csv files containing vehicle reference data into Amazon S3 at different times throughout the day. A nightly process loads the vehicle reference data from Amazon S3 into Amazon Redshift. The company joins the IoT data from the device and the vehicle reference data to power reporting and dashboards. Fleet owners are frustrated by waiting a day for the dashboards to update.

Which solution would provide the SHORTEST delay between uploading reference data to Amazon S3 and the change showing up in the owners’ dashboards?

Options:

A.

Use S3 event notifications to trigger an AWS Lambda function to copy the vehicle reference data into Amazon Redshift immediately when the reference data is uploaded to Amazon S3.

B.

Create and schedule an AWS Glue Spark job to run every 5 minutes. The job inserts reference data into Amazon Redshift.

C.

Send reference data to Amazon Kinesis Data Streams. Configure the Kinesis data stream to directly load the reference data into Amazon Redshift in real time.

D.

Send the reference data to an Amazon Kinesis Data Firehose delivery stream. Configure Kinesis with a buffer interval of 60 seconds and to directly load the data into Amazon Redshift.

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Total 207 questions
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