DEA-C01 Question 30
Select 2You are designing a batch data ingestion pipeline for a retail company that collects sales data every night from multiple stores. The data needs to be ingested into an Amazon S3 bucket for further processing. The ingestion process should scale based on the size of the incoming data and must ensure high availability. Which combination of AWS services and features would be the most appropriate for this use case?
- A
Amazon S3 for storing the ingested data
- B
AWS Glue for scheduling and orchestrating the batch ingestion process
- C
Amazon Kinesis Data Firehose for ingesting batch data into Amazon S3
- D
AWS Lambda for automatically scaling the batch ingestion process
- E
Amazon SQS for decoupling and buffering the incoming batch data
Show answer and explanation
Correct answers: A, B
Explanation
For this batch data ingestion scenario, Amazon S3 is the most appropriate storage solution for its scalability and durability. AWS Glue is well-suited for orchestrating and scheduling ETL jobs required for batch processing. While services like Amazon Kinesis Data Firehose, AWS Lambda, and Amazon SQS have their use cases, they are not the ideal tools for handling batch data ingestion in this specific context.
- A. Correct.
Correct: Amazon S3 is an optimal choice for storing the ingested data due to its scalability, durability, and cost-effectiveness.
- B. Correct.
Correct: AWS Glue can be used to create and schedule ETL jobs that handle the batch ingestion process in a scalable and reliable manner.
- C. Incorrect.
Incorrect: Amazon Kinesis Data Firehose is designed for streaming data ingestion, not batch data ingestion, so it is not the ideal choice for this scenario.
- D. Incorrect.
Incorrect: AWS Lambda is better suited for event-driven, serverless processing and is not ideal for handling large-scale batch data ingestion processes.
- E. Incorrect.
Incorrect: Amazon SQS is used for decoupling and buffering messages in event-driven architectures but does not directly support batch ingestion into Amazon S3.