MLA-C01 Question 34
Select 3A company wants to build a machine learning pipeline that processes real-time streaming data from IoT sensors. The data should be ingested into the pipeline, transformed, and then stored for downstream analysis. Which combination of AWS services can be used to accomplish this?
- A
Amazon Kinesis Data Streams for ingesting the streaming data
- B
Apache Flink on Amazon Kinesis Data Analytics for transforming the data
- C
Amazon S3 for storing the transformed data
- D
AWS Glue for real-time data ingestion
- E
Amazon Redshift for ingesting streaming data directly
Show answer and explanation
Correct answers: A, B, C
Explanation
To process real-time streaming data from IoT sensors, Amazon Kinesis Data Streams can be used to ingest the data into the pipeline. Apache Flink on Amazon Kinesis Data Analytics is well-suited for real-time transformation of the data. The transformed data can then be stored in Amazon S3 for long-term storage and downstream analysis. AWS Glue is not used for real-time ingestion, and Amazon Redshift is not suitable for directly ingesting streaming data, making them incorrect choices for this scenario.
- A. Correct.
Correct: Amazon Kinesis Data Streams is a managed service designed for real-time ingestion and processing of streaming data, making it suitable for this use case.
- B. Correct.
Correct: Apache Flink on Amazon Kinesis Data Analytics can be used to perform real-time data transformation and processing on streaming data.
- C. Correct.
Correct: Amazon S3 is a cost-effective storage solution that can be used to store the transformed data for downstream analysis.
- D. Incorrect.
Incorrect: AWS Glue is primarily used for batch data processing, not real-time ingestion of streaming data.
- E. Incorrect.
Incorrect: Amazon Redshift is a data warehousing service and is not designed to directly ingest streaming data. It is better suited for analytics on structured data.