Which combination of steps should the solutions architect take to meet these requirements?
(Choose two.)
Write the document information to an Amazon EC2 instance that runs a MySQL database.
Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.
Create an Auto Scaling group of Amazon EC2 instances to run a custom application that processes the scanned files and extracts the medical information.
Create an AWS Lambda function that runs when new documents are uploaded. Use Amazon Rekognition to convert the documents to raw text. Use Amazon Transcribe Medical to detect and extract relevant medical information from the text.
Create an AWS Lambda function that runs when new documents are uploaded. Use Amazon Textract to convert the documents to raw text. Use Amazon Comprehend Medical to detect and extract relevant medical information from the text.
Explanations:
Running a MySQL database on an EC2 instance is not scalable for a large number of documents. It also lacks the necessary integrations for automatic document analysis and medical information extraction.
Storing documents in an S3 bucket and using Amazon Athena to query data is scalable and efficient. Athena allows SQL queries on S3-stored data, meeting the scalability and operational efficiency requirements.
Creating an Auto Scaling group of EC2 instances for custom processing would be more complex and less scalable than serverless alternatives, like AWS Lambda, for the document analysis and processing.
Amazon Rekognition is designed for image and video analysis, not document text extraction. Amazon Transcribe Medical is for speech-to-text, not relevant for extracting information from scanned documents.
Using AWS Lambda with Amazon Textract (for text extraction) and Amazon Comprehend Medical (for medical information extraction) is a serverless, scalable solution that meets the requirements of processing documents and extracting medical information efficiently.
I believe the answer is:
Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.
As I see it, the answer is:
Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.