MLS-C01 Question 59
Single answerYou are working as a Machine Learning Engineer for an e-commerce company. The company wants to analyze customer purchasing trends in near real-time by processing and transforming clickstream data as it flows into their data lake. The solution must be serverless, scalable, and capable of handling schema evolution automatically. Which AWS service should you choose to perform this data transformation?
- A
AWS Glue
- B
Amazon EMR
- C
AWS Batch
- D
Amazon Kinesis Data Analytics
Show answer and explanation
Correct answer: A
Explanation
AWS Glue is the most appropriate choice for this scenario because it is a serverless ETL service that can process data in transit, handle schema evolution, and integrate seamlessly with the data lake. The other services, such as Amazon EMR, AWS Batch, and Amazon Kinesis Data Analytics, are either not serverless or not designed for the specific requirements of near real-time ETL and schema evolution.
- A. Correct.
AWS Glue is a serverless ETL service that can process and transform data in transit or in batch mode, and it handles schema evolution automatically, making it suitable for this use case.
- B. Incorrect.
Amazon EMR is a managed Hadoop and Spark service that is primarily designed for big data batch processing and does not handle near real-time data in a serverless manner.
- C. Incorrect.
AWS Batch is used for batch processing workloads and is not suitable for near real-time data transformation or streaming data pipelines.
- D. Incorrect.
Amazon Kinesis Data Analytics is used for real-time analytics on streaming data but is not focused on ETL tasks or handling schema evolution automatically.