SAA-C03 Question 359
Single answerA company has large volumes of semi-structured data stored in Amazon S3, such as JSON and CSV files. They need to transform this data into a structured format and load it into Amazon Redshift for analytics. The data transformation process requires schema discovery, deduplication, and partitioning. Which AWS service is the most appropriate to use for this data transformation task?
- A
AWS Glue
- B
Amazon EMR
- C
AWS Data Pipeline
- D
Amazon Kinesis Data Firehose
Show answer and explanation
Correct answer: A
Explanation
AWS Glue is the most suitable service for this use case because it provides automated schema discovery, built-in ETL capabilities, and integration with Amazon Redshift. It simplifies the process of transforming semi-structured data stored in Amazon S3 into a structured format for analytics. While other services like Amazon EMR or AWS Data Pipeline can perform similar tasks, they are not as straightforward or purpose-built for this specific use case.
- A. Correct.
AWS Glue is a fully managed ETL (Extract, Transform, Load) service that is ideal for discovering schemas, deduplicating data, partitioning, and transforming semi-structured data stored in Amazon S3 into a structured format for analytics. It integrates seamlessly with Amazon Redshift.
- B. Incorrect.
Amazon EMR is a big data processing service that can also transform data, but it is better suited for large-scale data processing using distributed frameworks like Apache Spark or Hadoop. It requires more setup and management compared to AWS Glue.
- C. Incorrect.
AWS Data Pipeline is a service for orchestrating workflows and data transfer between services, but it does not provide built-in capabilities for schema discovery, deduplication, or data transformation.
- D. Incorrect.
Amazon Kinesis Data Firehose is primarily used for streaming data ingestion and transformation in real-time, not for batch transformation of large volumes of semi-structured data stored in Amazon S3.