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Amazon Web Services Data-Engineer-Associate Online Access

AWS Certified Data Engineer - Associate (DEA-C01) Questions and Answers

Question 65

A global finance company needs to implement near real-time cross-Region synchronization of trading data between trading centers in the us-east-1 Region, the eu-west-2 Region, and the ap-northeast-1 Region. The company must ensure that data is encrypted in transit. The solution must ensure data ordering and consistency and must support cross-Region disaster recovery. The solution must provide data latency of less than 500 milliseconds.

Which solution will meet these requirements with the LEAST operational effort?

Options:

A.

Deploy Apache Kafka Connect in each AWS Region. Use custom-developed connectors to set up cross-Region data replication. Configure the SSL security protocol.

B.

Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) Replicator to establish fully interconnected replication relationships between MSK clusters in the three AWS Regions. Enable TLS encryption and IAM authentication. Set up cross-Region backup configurations.

C.

Deploy Apache Kafka MirrorMaker 2.0 in each AWS Region. Set up custom replication policies to handle cross-Region data synchronization. Configure the SSL security protocol.

D.

Use Amazon Kinesis Data Streams to receive trading data from each AWS Region. Use Amazon Data Firehose to replicate data between Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in each Region. Configure AWS Key Management Service (AWS KMS) encryption and IAM roles to manage access.

Question 66

A company wants to ingest streaming data into an Amazon Redshift data warehouse from an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster. A data engineer needs to develop a solution that provides low data access time and that optimizes storage costs.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Create an external schema that maps to the MSK cluster. Create a materialized view that references the external schema to consume the streaming data from the MSK topic.

B.

Develop an AWS Glue streaming extract, transform, and load (ETL) job to process the incoming data from Amazon MSK. Load the data into Amazon S3. Use Amazon Redshift Spectrum to read the data from Amazon S3.

C.

Create an external schema that maps to the streaming data source. Create a new Amazon Redshift table that references the external schema.

D.

Create an Amazon S3 bucket. Ingest the data from Amazon MSK. Create an event-driven AWS Lambda function to load the data from the S3 bucket to a new Amazon Redshift table.

Question 67

A company uses Amazon S3 buckets, AWS Glue tables, and Amazon Athena as components of a data lake. Recently, the company expanded its sales range to multiple new states. The company wants to introduce state names as a new partition to the existing S3 bucket, which is currently partitioned by date.

The company needs to ensure that additional partitions will not disrupt daily synchronization between the AWS Glue Data Catalog and the S3 buckets.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Use the AWS Glue API to manually update the Data Catalog.

B.

Run an MSCK REPAIR TABLE command in Athena.

C.

Schedule an AWS Glue crawler to periodically update the Data Catalog.

D.

Run a REFRESH TABLE command in Athena.

Question 68

A company needs to store semi-structured transactional data in a serverless database.

The application writes data infrequently but reads it frequently, with millisecond retrieval required.

Options:

A.

Store the data in an Amazon S3 Standard bucket. Enable S3 Transfer Acceleration.

B.

Store the data in an Amazon S3 Apache Iceberg table. Enable S3 Transfer Acceleration.

C.

Store the data in an Amazon RDS for MySQL cluster. Configure RDS Optimized Reads.

D.

Store the data in an Amazon DynamoDB table. Configure a DynamoDB Accelerator (DAX) cache.