MLA-C01 Question 73
Select 3You are building a real-time machine learning pipeline to process and transform streaming data from IoT devices. The transformed data will be used to make predictions and stored in Amazon S3 for further analysis. Which of the following services can you use to process and transform the streaming data before storing it in Amazon S3?
- A
AWS Lambda
- B
Amazon Kinesis Data Analytics
- C
AWS Glue
- D
Amazon SageMaker
- E
Apache Spark on Amazon EMR
Show answer and explanation
Correct answers: A, B, E
Explanation
To process and transform streaming data, AWS Lambda, Amazon Kinesis Data Analytics, and Apache Spark on Amazon EMR are suitable services. AWS Lambda allows you to execute custom code for real-time transformation, Kinesis Data Analytics provides a managed solution for analyzing streams, and Spark on EMR enables large-scale stream processing. AWS Glue and SageMaker are not designed for real-time streaming transformations.
- A. Correct.
AWS Lambda can process and transform streaming data by executing custom code in response to streaming events from sources like Kinesis or DynamoDB Streams.
- B. Correct.
Amazon Kinesis Data Analytics is designed to process and transform streaming data using SQL, Java, or Python in real-time.
- C. Incorrect.
AWS Glue is primarily used for ETL (Extract, Transform, Load) operations on batch data, not for real-time streaming data transformation.
- D. Incorrect.
Amazon SageMaker is designed for building, training, and deploying machine learning models, but it does not natively process or transform streaming data.
- E. Correct.
Apache Spark on Amazon EMR can be used to process and transform streaming data in real-time using Spark Streaming.