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A company has a podcast platform that has thousands of users.

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A company has a podcast platform that has thousands of users. The company implemented an algorithm to detect low podcast engagement based on a 10-minute running window of user events such as listening to. pausing, and closing the podcast. A machine learning (ML) specialist is designing the ingestion process for these events. The ML specialist needs to transform the data to prepare the data for inference.

How should the ML specialist design the transformation step to meet these requirements with the LEAST operational effort?

A.

Use an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster to ingest event data. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to transform the most recent 10 minutes of data before inference.

B.

Use Amazon Kinesis Data Streams to ingest event data. Store the data in Amazon S3 by using Amazon Data Firehose. Use AWS Lambda to transform the most recent 10 minutes of data before inference.

C.

Use Amazon Kinesis Data Streams to ingest event data. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to transform the most recent 10 minutes of data before inference.

D.

Use an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster to ingest event data. Use AWS Lambda to transform the most recent 10 minutes of data before inference.

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Amazon Web Services MLS-C01 Summary

  • Vendor: Amazon Web Services
  • Product: MLS-C01
  • Update on: Jul 28, 2025
  • Questions: 330
Price: $52.5  $149.99
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