Elastic and parallel✑ The results of the analytic processing should be persisted for data miningWhich architecture outlined below win meet the initial requirements for the collection platform?

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Your company is in the process of developing a next generation pet collar that collects biometric information to assist families with promoting healthy lifestyles for their pets.Each collar will push 30kb of biometric data in JSON format every 2 seconds to a collection platform that will process and analyze the data providing health trending information back to the pet owners and veterinarians via a web portal.Management has tasked you to architect the collection platform ensuring the following requirements are met.✑ Provide the ability for real-time analytics of the inbound biometric data✑ Ensure processing of the biometric data is highly durable.

Elastic and parallel✑ The results of the analytic processing should be persisted for data miningWhich architecture outlined below win meet the initial requirements for the collection platform?

Utilize S3 to collect the inbound sensor data analyze the data from S3 with a daily scheduled Data Pipeline and save the results to a Redshift Cluster.

Utilize Amazon Kinesis to collect the inbound sensor data, analyze the data with Kinesis clients and save the results to a Redshift cluster using EMR.

Utilize SQS to collect the inbound sensor data analyze the data from SQS with Amazon Kinesis and save the results to a Microsoft SQL Server RDS instance.

Utilize EMR to collect the inbound sensor data, analyze the data from EUR with Amazon Kinesis and save me results to DynamoDB.

Explanations:

While S3 is durable for storage, it does not support real-time analytics effectively and relies on a daily scheduled job, failing to meet the real-time requirement.

Amazon Kinesis provides real-time data collection and processing, and using EMR allows for elastic and parallel processing, meeting all specified requirements.

SQS is primarily for message queuing and does not support real-time analytics. Additionally, using Microsoft SQL Server may not provide the durability and scalability needed for large data volumes.

EMR is used for processing but not for data collection. Moreover, DynamoDB is not optimal for analytic processing as required in the scenario.

2026-03-23

2 Comments

  1. Lori
    Author

    I deduce that the answer is:
    Utilize Amazon Kinesis to collect the inbound sensor data, analyze the data with Kinesis clients and save the results to a Redshift cluster using EMR.

  2. Sophia
    Author

    I arrange that the answer is:
    Utilize Amazon Kinesis to collect the inbound sensor data, analyze the data with Kinesis clients and save the results to a Redshift cluster using EMR.

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