You are an AWS solutions architect in an IT company. Your company has a big data product that analyzes data from various sources like transactions, web servers, surveys, and social media. You need to design a new solution in AWS that can extract data from the source in S3 and transform the data to match the target schema automatically. Moreover, the transformed data can be analyzed using standard SQL. Which combination of solutions would meet these requirements in the best way? (Select TWO.)

Answer options:

A.Set up an AWS ECS cluster to manage the extract, transform, and load (ETL) service to prepare and load the data in S3 for analytics.
B.Configure an AWS EMR cluster to transform the data to a target format for downstream. Execute the EMR tasks on a schedule.
C.Create an AWS Glue ETL to run on schedule to scan the data in S3 and populate the Glue data catalog accordingly.
D.Configure AWS QuickSight to analyze the data using standard SQL commands.
E.Use AWS Athena to query the data using standard SQL.

Correct Answer – C, E
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.
AWS Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a metadata repository across various services.
AWS Glue and AWS Athena, when used together, can meet the requirements for this case.
Option A is incorrect:Although the ECS cluster may work, it is not fully managed by AWS. By AWS Glue, you can create and run an ETL job with a few clicks in the AWS Management Console.
Option B is incorrect: Similar reason as
Option A. AWS Glue should be considered as the first choice when an extract, transform, and load (ETL) service is required in AWS.
Option C is correct because AWS Glue generates Scala or PySpark (the Python API for Apache Spark) scripts with AWS Glue extensions. You can use and modify these scripts to perform various ETL operations. You can extract, clean, and transform raw data, and then store the result in a different repository, where it can be queried and analyzed.
Option D is incorrect: Because AWS QuickSight is a service to deliver insights rather than perform SQL queries.
Option E is CORRECT: Because AWS Athena can directly query the data in AWS Glue Data Catalog with SQL commands. No additional step is needed.