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Amazon Web Services DBS-C01 Exam Sample Questions


Question # 1

A company is hosting critical business data in an Amazon Redshift cluster. Due to the sensitive nature of the
data, the cluster is encrypted at rest using AWS KMS. As a part of disaster recovery requirements, the
company needs to copy the Amazon Redshift snapshots to another Region.
Which steps should be taken in the AWS Management Console to meet the disaster recovery requirements?

A.

Create a new KMS customer master key in the source Region. Switch to the destination Region, enable
Amazon Redshift cross-Region snapshots, and use the KMS key of the source Region.

B.

Create a new IAM role with access to the KMS key. Enable Amazon Redshift cross-Region replication
using the new IAM role, and use the KMS key of the source Region

C.

Enable Amazon Redshift cross-Region snapshots in the source Region, and create a snapshot copy grant
and use a KMS key in the destination Region.

D.

Create a new KMS customer master key in the destination Region and create a new IAM role with
access to the new KMS key. Enable Amazon Redshift cross-Region replication in the source Region and
use the KMS key of the destination Region



A.

Create a new KMS customer master key in the source Region. Switch to the destination Region, enable
Amazon Redshift cross-Region snapshots, and use the KMS key of the source Region.






Question # 2

A single MySQL database was moved to Amazon Aurora by a business. The production
data is stored in a database cluster in VPC PROD, whereas 12 testing environments are
hosted in VPC TEST with the same AWS account. Testing has a negligible effect on the test data. The development team requires that each environment be updated nightly to
ensure that each test database has daily production data.
Which migration strategy will be the quickest and least expensive to implement?

A.

Run the master in Amazon Aurora MySQL. Create 12 clones in VPC_TEST, and script
the clones to be deleted and re-created nightly.

B.

Run the master in Amazon Aurora MySQL. Take a nightly snapshot, and restore it into
12 databases in VPC_TEST using Aurora Serverless.

C.

Run the master in Amazon Aurora MySQL. Create 12 Aurora Replicas in VPC_TEST,
and script the replicas to be deleted and re-created nightly.

D.

Run the master in Amazon Aurora MySQL using Aurora Serverless. Create 12 clones in
VPC_TEST, and script the clones to be deleted and re-created nightly.



A.

Run the master in Amazon Aurora MySQL. Create 12 clones in VPC_TEST, and script
the clones to be deleted and re-created nightly.






Question # 3

A worldwide digital advertising corporation collects browser information in order to provide
targeted visitors with contextually relevant pictures, websites, and connections. A single
page load may create many events, each of which must be kept separately. A single event
may have a maximum size of 200 KB and an average size of 10 KB. Each page load
requires a query of the user's browsing history in order to deliver suggestions for targeted
advertising. The advertising corporation anticipates daily page views of more than 1 billion
from people in the United States, Europe, Hong Kong, and India. The information structure
differs according to the event. Additionally, browsing information must be written and read
with a very low latency to guarantee that consumers have a positive viewing experience.
Which database solution satisfies these criteria?

A.

Amazon DocumentDB

B.

Amazon RDS Multi-AZ deployment

C.

Amazon DynamoDB global table

D.

Amazon Aurora Global Database



C.

Amazon DynamoDB global table






Question # 4

A company is running its customer feedback application on Amazon Aurora MySQL. The
company runs a report every day to extract customer feedback, and a team reads the
feedback to determine if the customer comments are positive or negative. It sometimes
takes days before the company can contact unhappy customers and take corrective
measures. The company wants to use machine learning to automate this workflow.
Which solution meets this requirement with the LEAST amount of effort?

A.

Export the Aurora MySQL database to Amazon S3 by using AWS Database Migration
Service (AWS DMS). Use Amazon Comprehend to run sentiment analysis on the exported
files.

B.

Export the Aurora MySQL database to Amazon S3 by using AWS Database Migration
Service (AWS DMS). Use Amazon SageMaker to run sentiment analysis on the exported
files.

C.

Set up Aurora native integration with Amazon Comprehend. Use SQL functions to extract sentiment analysis

D.

Set up Aurora native integration with Amazon SageMaker. Use SQL functions to extract
sentiment analysis



C.

Set up Aurora native integration with Amazon Comprehend. Use SQL functions to extract sentiment analysis


For details about using Aurora and Amazon Comprehend together,
see Using Amazon Comprehend for sentiment detection. Aurora machine learning uses a
highly optimized integration between the Aurora database and the AWS machine learning
(ML) services SageMaker and Amazon Comprehend.
https://www.stackovercloud.com/2019/11/27/new-for-amazon-aurora-use-machinelearning-
directly-from-your-databases/





Question # 5

An ecommerce company is using Amazon DynamoDB as the backend for its order-processing application.
The steady increase in the number of orders is resulting in increased DynamoDB costs. Order verification and
reporting perform many repeated GetItem functions that pull similar datasets, and this read activity is
contributing to the increased costs. The company wants to control these costs without significant development
efforts.
How should a Database Specialist address these requirements?

A.

Use AWS DMS to migrate data from DynamoDB to Amazon DocumentDB

B.

Use Amazon DynamoDB Streams and Amazon Kinesis Data Firehose to push the data into
AmazonRedshift

C.

Use an Amazon ElastiCache for Redis in front of DynamoDB to boost read performance

D.

Use DynamoDB Accelerator to offload the reads



B.

Use Amazon DynamoDB Streams and Amazon Kinesis Data Firehose to push the data into
AmazonRedshift





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