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Answer: Use Amazon S3 for data storage, Amazon Kinesis for data ingestion, and AWS Lambda for data processing and analysis
In this scenario, using Amazon S3 for data storage, Amazon Kinesis for data ingestion, and AWS Lambda for data processing and analysis would be the most appropriate choice. Amazon S3 provides a scalable and durable storage solution for the healthcare application. Amazon Kinesis can handle data ingestion from various medical devices and sensors, while AWS Lambda can process and analyze the data in real-time. By using AWS Key Management Service (KMS) and AWS Identity and Access Management (IAM), you can ensure data privacy and security. This combination of services meets the requirements of the healthcare application's data ingestion pipeline.
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Your company is building a data ingestion pipeline for a healthcare application that requires data to be ingested from various medical devices and sensors. The pipeline should be able to handle high data volumes, ensure data privacy and security, and support data processing and analysis. Which AWS service would you recommend for this scenario, and how would you design the data ingestion pipeline to meet the requirements?
A
Use Amazon S3 for data storage, Amazon Kinesis for data ingestion, and AWS Lambda for data processing and analysis
B
Use Amazon DynamoDB for data storage, AWS IoT Core for data ingestion from medical devices, and AWS Lambda for data processing and analysis
C
Use Amazon Redshift for data storage, Amazon Kinesis for data ingestion, and Amazon SageMaker for data processing and analysis
D
Use Amazon RDS for data storage, AWS IoT Core for data ingestion from medical devices, and Amazon SageMaker for data processing and analysis
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