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:
Writing document information to an Amazon EC2 instance running MySQL may not be scalable, as managing EC2 instances requires more operational overhead and may not handle large volumes of new documents efficiently.
Storing document information in an Amazon S3 bucket provides scalable storage. Using Amazon Athena to query the data allows for serverless SQL queries directly on data stored in S3, maximizing operational efficiency.
Creating an Auto Scaling group of EC2 instances for a custom application adds complexity and operational overhead. It may not be the most efficient approach for processing documents continuously.
Using Amazon Rekognition for text conversion is not suitable as it is primarily designed for image and video analysis. It does not directly convert documents to text or extract medical information effectively.
AWS Lambda can trigger upon document upload, using Amazon Textract to convert documents to raw text and Amazon Comprehend Medical to extract relevant medical information, offering a scalable and efficient serverless solution.
I value that the answer is:
Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.
I infer that the answer is:
Write the document information to an Amazon S3 bucket. Use Amazon Athena to query the data.