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Amazon Web Services DBS-C01 Exam Sample Questions


Question # 1

A company is migrating a mission-critical 2-TB Oracle database from on premises to
Amazon Aurora. The cost for the database migration must be kept to a minimum, and both
the on-premises Oracle database and the Aurora DB cluster must remain open for write
traffic until the company is ready to completely cut over to Aurora.
Which combination of actions should a database specialist take to accomplish this
migration as quickly as possible? (Choose two.)

A.

Use the AWS Schema Conversion Tool (AWS SCT) to convert the source database
schema. Then restore the converted schema to the target Aurora DB cluster.

B.

Use Oracle’s Data Pump tool to export a copy of the source database schema and
manually edit the schema in a text editor to make it compatible with Aurora.

C.

Create an AWS DMS task to migrate data from the Oracle database to the Aurora DB
cluster. Select the migration type to replicate ongoing changes to keep the source and
target databases in sync until the company is ready to move all user traffic to the Aurora
DB cluster.

D.

Create an AWS DMS task to migrate data from the Oracle database to the Aurora DB
cluster. Once the initial load is complete, create an AWS Kinesis Data Firehose stream to
perform change data capture (CDC) until the company is ready to move all user traffic to
the Aurora DB cluster.

E.

Create an AWS Glue job and related resources to migrate data from the Oracle
database to the Aurora DB cluster. Once the initial load is complete, create an AWS DMS
task to perform change data capture (CDC) until the company is ready to move all user
traffic to the Aurora DB cluster.



A.

Use the AWS Schema Conversion Tool (AWS SCT) to convert the source database
schema. Then restore the converted schema to the target Aurora DB cluster.


C.

Create an AWS DMS task to migrate data from the Oracle database to the Aurora DB
cluster. Select the migration type to replicate ongoing changes to keep the source and
target databases in sync until the company is ready to move all user traffic to the Aurora
DB cluster.





Question # 2

A global digital advertising company captures browsing metadata to contextually display relevant
images,pages, and links to targeted users. A single page load can generate multiple events that need to be
storedindividually. The maximum size of an event is 200 KB and the average size is 10 KB. Each page load
mustquery the user’s browsing history to provide targeting recommendations. The advertising company
expectsover 1 billion page visits per day from users in the United States, Europe, Hong Kong, and India. The
structureof the metadata varies depending on the event. Additionally, the browsing metadata must be written
and readwith very low latency to ensure a good viewing experience for the users.
Which database solution meets these requirements?

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 # 3

A retail company manages a web application that stores data in an Amazon DynamoDB
table. The company is undergoing account consolidation efforts. A database engineer
needs to migrate the DynamoDB table from the current AWS account to a new AWS
account.
Which strategy meets these requirements with the LEAST amount of administrative work?

A.

Use AWS Glue to crawl the data in the DynamoDB table. Create a job using an
available blueprint to export the data to Amazon S3. Import the data from the S3 file to a
DynamoDB table in the new account.

B.

Create an AWS Lambda function to scan the items of the DynamoDB table in the
current account and write to a file in Amazon S3. Create another Lambda function to read
the S3 file and restore the items of a DynamoDB table in the new account.

C.

Use AWS Data Pipeline in the current account to export the data from the DynamoDB
table to a file in Amazon S3. Use Data Pipeline to import the data from the S3 file to a
DynamoDB table in the new account.

D.

Configure Amazon DynamoDB Streams for the DynamoDB table in the current account.
Create an AWS Lambda function to read from the stream and write to a file in Amazon S3.
Create another Lambda function
to read the S3 file and restore the items to a DynamoDB table in the new account.



C.

Use AWS Data Pipeline in the current account to export the data from the DynamoDB
table to a file in Amazon S3. Use Data Pipeline to import the data from the S3 file to a
DynamoDB table in the new account.


Explanation:
https://aws.amazon.com/premiumsupport/knowledge-center/dynamodb-cross-accountmigration/
https://aws.amazon.com/premiumsupport/knowledge-center/data-pipeline-account-accessdynamodb-
s3/




Question # 4

A database professional maintains a fleet of Amazon RDS database instances that are
configured to utilize the default database parameter group. A database expert must
connect a custom parameter group with certain database instances.
When will the instances be allocated to this new parameter group once the database
specialist performs this change?

A.

Instantaneously after the change is made to the parameter group

B.

In the next scheduled maintenance window of the DB instances

C.

After the DB instances are manually rebooted

D.

Within 24 hours after the change is made to the parameter group



C.

After the DB instances are manually rebooted





Question # 5

A retail company is about to migrate its online and mobile store to AWS. The company’s CEO has strategic
plans to grow the brand globally. A Database Specialist has been challenged to provide predictable read and
write database performance with minimal operational overhead.
What should the Database Specialist do to meet these requirements?

A.

Use Amazon DynamoDB global tables to synchronize transactions

B.

Use Amazon EMR to copy the orders table data across Regions

C.

Use Amazon Aurora Global Database to synchronize all transactions

D.

Use Amazon DynamoDB Streams to replicate all DynamoDB transactions and sync them



A.

Use Amazon DynamoDB global tables to synchronize transactions




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