A company uses a legacy application to produce data in CSV format. The legacy application stores the output data in Amazon S3. The company is deploying a new commercial off-the-shelf (COTS) application that can perform complex SQL queries to analyze data that is stored in Amazon Redshift and Amazon S3 only. However, the COTS application cannot process the .csv files that the legacy application produces. The company cannot update the legacy application to produce data in another format. The company needs to implement a solution so that the COTS application can use the data that the legacy application produces. Which solution will meet these requirements with the LEAST operational overhead?
Select one answer.
Marked answer: A
Community Discussion
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Chose A23
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
Chose A4
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)
3
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
