Free DAS-C01 Web TestEngine Demo

Q42 Single choice

A company wants find ways to expand its website business by analyzing customer orders and purchasing

trends. To perform data analysis, a pipeline must support daily data ingestion from the production databases into a data lake that is built on Amazon S3. The website uses Amazon DynamoDB to store product details and Amazon Aurora PostgreSQL to store order details in production.

Which solution can be used to accomplish these goals with LEAST operational overhead?

A
Leverage AWS Database Migration Service (AWS DMS) to run two continuous data replication jobs from both Aurora PostgreSQL and DynamoDB into Amazon S3. Leverage AWS Glue for data cataloging.
B
Set up an AWS Lake Formation workflow with blueprints for Aurora PostgreSQL and an AWS Glue ETLjob for DynamoDB to ingest data into Amazon S3. Leverage AWS Glue for data cataloging.
C
Create a custom Python script to ingest data from both Aurora PostgreSQL and Amazon DynamoDB into Amazon S3 using the AWS SDK for Python (Boto3) library. Deploy the script on an Amazon EC2 instance and schedule the job to run daily using a cron job. Leverage AWS Glue for data cataloging.
D
Use Amazon EMR to ingest data from both Aurora PostgreSQL and DynamoDB into Amazon S3.
Leverage Apache Hive on the same EMR cluster for data cataloging.

DAS-C01 Web TestEngine demo