Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 317 discussion

Time to sell some Glue. I believe these kind of questions are there to indoctrinate us into acknowledging how blessed we are to have managed services like AWS Glue when you look at other horrible and painful options

A, AWS Glue is a fully managed ETL service that can extract data from various sources, transform it into the required format, and load it into a target data store. In this case, the ETL job can be configured to read the CSV files from Amazon S3, transform the data into a format that can be loaded into Amazon Redshift, and load it into an Amazon Redshift table. B requires the development of a custom script to convert the CSV files to SQL files, which could be time-consuming and introduce additional operational overhead. C, while using serverless technology, requires the additional use of DynamoDB to store the processed data, which may not be necessary if the data is only needed in Amazon Redshift. D, while an option, is not the most efficient solution as it requires the creation of an EMR cluster, which can be costly and complex to manage.

B - Developing a script is surely not minimizing operational effort C - Stores data in DynamoDB where the new app cannot use it D - Could work but is total overkill (EMR is for Big Data analysis, not for simple ETL)

A-ETL is serverless & best suited with the requirement who primary job is ETL B-Usage of Ec2 adds operational overhead & incur costs C-DynamoDB(NoSql) does suit the requirement as company is performing SQL queries D-EMR adds operational overhead & incur costs

A-ETL is serverless & best suited with the requirement who primary job is ETL B-Usage of Ec2 adds operational overhead & incur costs C-DynamoDB(NoSql) does suit the requirement as company is performing SQL queries D-EMR adds operational overhead & incur costs

Data transformation = AWS Glue

Create an AWS Glue ETL job to process the CSV files Configure the job to run on a schedule Output the transformed data to Amazon Redshift The key points: Legacy app generates CSV files in S3 New app requires data in Redshift or S3 Need to transform CSV to support new app with minimal ops overhead

Glue is server less and has less operational head than EMR so A.

o meet the requirement with the least operational overhead, a serverless approach should be used. Among the options provided, option C provides a serverless solution using AWS Lambda, S3, and DynamoDB. Therefore, the solution should be to create an AWS Lambda function and an Amazon DynamoDB table. Use an S3 event to invoke the Lambda function. Configure the Lambda function to perform an extract, transform, and load (ETL) job to process the .csv files and store the processed data in the DynamoDB table. Option A is also a valid solution, but it may involve more operational overhead than Option C. With Option A, you would need to set up and manage an AWS Glue job, which would require more setup time than creating an AWS Lambda function. Additionally, AWS Glue jobs have a minimum execution time of 10 minutes, which may not be necessary or desirable for this use case. However, if the data processing is particularly complex or requires a lot of data transformation, AWS Glue may be a more appropriate solution.

A would be the best solution as it involves the least operational overhead. With this solution, an AWS Glue ETL job is created to process the .csv files and store the processed data directly in Amazon Redshift. This is a serverless approach that does not require any infrastructure to be provisioned, configured, or maintained. AWS Glue provides a fully managed, pay-as-you-go ETL service that can be easily configured to process data from S3 and load it into Amazon Redshift. This approach allows the legacy application to continue to produce data in the CSV format that it currently uses, while providing the new COTS application with the ability to analyze the data using complex SQL queries.

A https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-format-csv-home.html I AGREE AFTER READING LINK

A: https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-format.html