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Exam Code: AWS Certified Cloud Practitioner CLF-C02

Exam Name AWS Certified Cloud Practitioner CLF-C02

Certification Provider: Amazon

Corresponding Certification: AWS Certified Cloud Practitioner

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Amazon AWS Certified Cloud Practitioner CLF-C02 Practice Test 43

Question 420

Which service-to-requirement explanation best fits this situation: An organization wants to migrate and replicate database data to AWS with minimal service interruption?

  1. Amazon Athena — queries object data through serverless SQL
  2. AWS Glue — supports managed ETL and data catalog workflows
  3. AWS Schema Conversion Tool — AWS SCT assists in assessing and converting database schemas and related code across supported engines
  4. AWS Database Migration Service — AWS DMS helps migrate databases and perform ongoing replication between supported data stores

Explanation

Correct Answer

D:

AWS DMS helps migrate databases and perform ongoing replication between supported data stores. This fits the situation: An organization wants to migrate and replicate database data to AWS with minimal service interruption.

Incorrect Answers

A:

Amazon Athena: Queries object data through serverless SQL. This does not address the need for An organization wants to migrate and replicate database data to AWS with minimal service interruption. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

B:

AWS Glue: Supports managed ETL and data catalog workflows. This does not address the need for An organization wants to migrate and replicate database data to AWS with minimal service interruption. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

C:

AWS Schema Conversion Tool: AWS SCT assists in assessing and converting database schemas and related code across supported engines. This does not address the need for An organization wants to migrate and replicate database data to AWS with minimal service interruption. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

Question 421

A firm needs ongoing change replication while transferring production database data. Which option is the best fit?

  1. AWS Database Migration Service
  2. AWS Glue
  3. AWS Schema Conversion Tool
  4. Amazon Athena

Explanation

Correct Answer

A:

AWS DMS helps migrate databases and perform ongoing replication between supported data stores. This fits the case: A firm needs ongoing change replication while transferring production database data.

Incorrect Answers

B:

AWS Glue: Supports managed ETL and data catalog workflows. That does not meet the requirement: A firm needs ongoing change replication while transferring production database data.

C:

AWS Schema Conversion Tool: AWS SCT assists in assessing and converting database schemas and related code across supported engines. That does not meet the requirement: A firm needs ongoing change replication while transferring production database data.

D:

Amazon Athena: Queries object data through serverless SQL. That does not meet the requirement: A firm needs ongoing change replication while transferring production database data.

Question 422

A firm needs ongoing change replication while transferring production database data. Which justification most accurately supports the recommended choice?

  1. AWS Schema Conversion Tool — AWS SCT assists in assessing and converting database schemas and related code across supported engines
  2. AWS Database Migration Service — AWS DMS helps migrate databases and perform ongoing replication between supported data stores
  3. AWS Glue — supports managed ETL and data catalog workflows
  4. Amazon Athena — queries object data through serverless SQL

Explanation

Correct Answer

B:

AWS DMS helps migrate databases and perform ongoing replication between supported data stores. This fits the situation: A firm needs ongoing change replication while transferring production database data.

Incorrect Answers

A:

AWS Schema Conversion Tool: AWS SCT assists in assessing and converting database schemas and related code across supported engines. This does not address the need for A firm needs ongoing change replication while transferring production database data. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

C:

AWS Glue: Supports managed ETL and data catalog workflows. This does not address the need for A firm needs ongoing change replication while transferring production database data. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

D:

Amazon Athena: Queries object data through serverless SQL. This does not address the need for A firm needs ongoing change replication while transferring production database data. The appropriate AWS Database Migration Service applies because AWS DMS helps migrate databases and perform ongoing replication between supported data stores.

Question 423

Consider this AWS requirement: A legacy database migration requires converting SQL schema definitions between unlike database engines. What should the team select?

  1. Amazon Athena
  2. AWS DataSync
  3. AWS Schema Conversion Tool
  4. AWS Database Migration Service

Explanation

Correct Answer

C:

AWS SCT assists in assessing and converting database schemas and related code across supported engines. This fits the case: A legacy database migration requires converting SQL schema definitions between unlike database engines.

Incorrect Answers

A:

Amazon Athena: Queries object data through serverless SQL. That does not meet the requirement: Consider this AWS requirement: A legacy database migration requires converting SQL schema definitions between unlike database engines.

B:

AWS DataSync: Moves and synchronizes data among supported file and object storage locations. That does not meet the requirement: Consider this AWS requirement: A legacy database migration requires converting SQL schema definitions between unlike database engines.

D:

AWS Database Migration Service: AWS DMS helps migrate databases and perform ongoing replication between supported data stores. That does not meet the requirement: Consider this AWS requirement: A legacy database migration requires converting SQL schema definitions between unlike database engines.

Question 424

A review board wants evidence for this choice: A legacy database migration requires converting SQL schema definitions between unlike database engines. Which reasoning is best aligned with the requirement?

  1. Amazon Athena — queries object data through serverless SQL
  2. AWS DataSync — moves and synchronizes data among supported file and object storage locations
  3. AWS Database Migration Service — AWS DMS helps migrate databases and perform ongoing replication between supported data stores
  4. AWS Schema Conversion Tool — AWS SCT assists in assessing and converting database schemas and related code across supported engines

Explanation

Correct Answer

D:

AWS SCT assists in assessing and converting database schemas and related code across supported engines. This fits the situation: A legacy database migration requires converting SQL schema definitions between unlike database engines.

Incorrect Answers

A:

Amazon Athena: Queries object data through serverless SQL. This does not address the need for A legacy database migration requires converting SQL schema definitions between unlike database engines. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

B:

AWS DataSync: Moves and synchronizes data among supported file and object storage locations. This does not address the need for A legacy database migration requires converting SQL schema definitions between unlike database engines. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

C:

AWS Database Migration Service: AWS DMS helps migrate databases and perform ongoing replication between supported data stores. This does not address the need for A legacy database migration requires converting SQL schema definitions between unlike database engines. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

Question 425

A company changes relational engine technology and needs help analyzing and converting database schema objects. Which cloud capability or service directly addresses the requirement?

  1. AWS Schema Conversion Tool
  2. Amazon Athena
  3. AWS DataSync
  4. AWS Database Migration Service

Explanation

Correct Answer

A:

AWS SCT assists in assessing and converting database schemas and related code across supported engines. This fits the case: A company changes relational engine technology and needs help analyzing and converting database schema objects.

Incorrect Answers

B:

Amazon Athena: Queries object data through serverless SQL. That does not meet the requirement: A company changes relational engine technology and needs help analyzing and converting database schema objects.

C:

AWS DataSync: Moves and synchronizes data among supported file and object storage locations. That does not meet the requirement: A company changes relational engine technology and needs help analyzing and converting database schema objects.

D:

AWS Database Migration Service: AWS DMS helps migrate databases and perform ongoing replication between supported data stores. That does not meet the requirement: A company changes relational engine technology and needs help analyzing and converting database schema objects.

Question 426

A company changes relational engine technology and needs help analyzing and converting database schema objects. Which explanation correctly distinguishes the appropriate approach from the alternatives?

  1. AWS Database Migration Service — AWS DMS helps migrate databases and perform ongoing replication between supported data stores
  2. AWS Schema Conversion Tool — AWS SCT assists in assessing and converting database schemas and related code across supported engines
  3. AWS DataSync — moves and synchronizes data among supported file and object storage locations
  4. Amazon Athena — queries object data through serverless SQL

Explanation

Correct Answer

B:

AWS SCT assists in assessing and converting database schemas and related code across supported engines. This fits the situation: A company changes relational engine technology and needs help analyzing and converting database schema objects.

Incorrect Answers

A:

AWS Database Migration Service: AWS DMS helps migrate databases and perform ongoing replication between supported data stores. This does not address the need for A company changes relational engine technology and needs help analyzing and converting database schema objects. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

C:

AWS DataSync: Moves and synchronizes data among supported file and object storage locations. This does not address the need for A company changes relational engine technology and needs help analyzing and converting database schema objects. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

D:

Amazon Athena: Queries object data through serverless SQL. This does not address the need for A company changes relational engine technology and needs help analyzing and converting database schema objects. The appropriate AWS Schema Conversion Tool applies because AWS SCT assists in assessing and converting database schemas and related code across supported engines.

Question 427

A technical reviewer evaluates this need: Analysts need a managed warehouse for complex SQL analysis over large datasets. Which choice is most appropriate?

  1. Amazon RDS
  2. Amazon DynamoDB
  3. Amazon Redshift
  4. Amazon ElastiCache

Explanation

Correct Answer

C:

Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads. This fits the case: Analysts need a managed warehouse for complex SQL analysis over large datasets.

Incorrect Answers

A:

Amazon RDS provides managed relational database engines. That does not meet the requirement: A technical reviewer evaluates this need: Analysts need a managed warehouse for complex SQL analysis over large datasets.

B:

Amazon DynamoDB provides managed key-value and document NoSQL storage. That does not meet the requirement: A technical reviewer evaluates this need: Analysts need a managed warehouse for complex SQL analysis over large datasets.

D:

Amazon ElastiCache: ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data. That does not meet the requirement: A technical reviewer evaluates this need: Analysts need a managed warehouse for complex SQL analysis over large datasets.

Question 428

For the following need, select the most defensible technical rationale: Analysts need a managed warehouse for complex SQL analysis over large datasets.

  1. Amazon DynamoDB — provides managed key-value and document NoSQL storage
  2. Amazon ElastiCache — ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data
  3. Amazon RDS — provides managed relational database engines
  4. Amazon Redshift — Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads

Explanation

Correct Answer

D:

Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads. This fits the situation: Analysts need a managed warehouse for complex SQL analysis over large datasets.

Incorrect Answers

A:

Amazon DynamoDB provides managed key-value and document NoSQL storage. This does not address the need for Analysts need a managed warehouse for complex SQL analysis over large datasets. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.

B:

Amazon ElastiCache: ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data. This does not address the need for Analysts need a managed warehouse for complex SQL analysis over large datasets. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.

C:

Amazon RDS provides managed relational database engines. This does not address the need for Analysts need a managed warehouse for complex SQL analysis over large datasets. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.

Question 429

A business intelligence team wants to run large-scale structured analytical queries on consolidated data. Identify the AWS approach that most directly meets the stated goal.

  1. Amazon Redshift
  2. Amazon RDS
  3. Amazon ElastiCache
  4. Amazon DynamoDB

Explanation

Correct Answer

A:

Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads. This fits the case: A business intelligence team wants to run large-scale structured analytical queries on consolidated data.

Incorrect Answers

B:

Amazon RDS provides managed relational database engines. That does not meet the requirement: A business intelligence team wants to run large-scale structured analytical queries on consolidated data.

C:

Amazon ElastiCache: ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data. That does not meet the requirement: A business intelligence team wants to run large-scale structured analytical queries on consolidated data.

D:

Amazon DynamoDB provides managed key-value and document NoSQL storage. That does not meet the requirement: A business intelligence team wants to run large-scale structured analytical queries on consolidated data.

Question 430

Which service-to-requirement explanation best fits this situation: A business intelligence team wants to run large-scale structured analytical queries on consolidated data?

  1. Amazon RDS — provides managed relational database engines
  2. Amazon Redshift — Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads
  3. Amazon ElastiCache — ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data
  4. Amazon DynamoDB — provides managed key-value and document NoSQL storage

Explanation

Correct Answer

B:

Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads. This fits the situation: A business intelligence team wants to run large-scale structured analytical queries on consolidated data.

Incorrect Answers

A:

Amazon RDS provides managed relational database engines. This does not address the need for A business intelligence team wants to run large-scale structured analytical queries on consolidated data. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.

C:

Amazon ElastiCache: ElastiCache supplies managed in-memory caching engines for high-speed access to frequently used data. This does not address the need for A business intelligence team wants to run large-scale structured analytical queries on consolidated data. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.

D:

Amazon DynamoDB provides managed key-value and document NoSQL storage. This does not address the need for A business intelligence team wants to run large-scale structured analytical queries on consolidated data. The appropriate Amazon Redshift applies because Redshift is designed for scalable analytic SQL warehousing rather than primary transactional OLTP workloads.