DEA-C01 Question 86
Select 2A retail company collects raw transactional data in an Amazon S3 bucket. They want to process this data daily to generate aggregated sales reports and store the results in another S3 bucket for downstream analytics. The company prefers a serverless solution with minimal operational overhead. Which combination of AWS services should you use to build this ETL pipeline?
- A
Amazon S3, AWS Glue, Amazon Athena
- B
Amazon S3, Amazon EMR, Amazon Redshift
- C
Amazon S3, AWS Glue, Amazon S3
- D
Amazon S3, Lambda, Amazon RDS
- E
Amazon S3, AWS Data Pipeline, Amazon DynamoDB
Show answer and explanation
Correct answers: A, C
Explanation
To build a serverless ETL pipeline with minimal operational overhead, Amazon S3 can be used for data storage, AWS Glue for processing and transforming the data, and either Amazon Athena for querying the data or another S3 bucket for storing the processed results. This combination aligns well with the company's requirements and avoids unnecessary complexity or operational burden.
- A. Correct.
Correct: Amazon S3 is used for data storage, AWS Glue for ETL processing, and Amazon Athena for querying/report generation, making this combination serverless and low-maintenance.
- B. Incorrect.
Incorrect: While Amazon EMR and Amazon Redshift are powerful, they require more operational overhead and are not fully serverless, which goes against the company's requirements.
- C. Correct.
Correct: Amazon S3 for data storage, AWS Glue for ETL, and another S3 bucket for storing the processed results align with the company's needs for a serverless ETL pipeline.
- D. Incorrect.
Incorrect: Amazon RDS adds unnecessary complexity for this use case, as it is not required for generating reports or performing ETL in a serverless manner.
- E. Incorrect.
Incorrect: AWS Data Pipeline is not the best fit here as AWS Glue is a more modern, serverless alternative for ETL pipelines. Additionally, DynamoDB is not needed for this type of analytics workload.