A company has purchased appliances from different vendors. The appliances all have IoT sensors. The sensors send status information in the vendors' proprietary formats to a legacy application that parses the information into JSON. The parsing is simple, but each vendor has a unique format. Once daily, the application parses all the JSON records and stores the records in a relational database for analysis. The company needs to design a new data analysis solution that can deliver faster and optimize costs. Which solution will meet these requirements? A. Connect the IoT sensors to AWS IoT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon. S3 Use AWS Glue to catalog the files. Use Amazon Athena and Amazon QuickSight for analysis. B. Migrate the application server to AWS Fargate, which will receive the information from IoT sensors and parse the information into a relational format. Save the parsed information to Amazon Redshlft for analysis. C. Create an AWS Transfer for SFTP server. Update the IoT sensor code to send the information as a .csv file through SFTP to the server. Use AWS Glue to catalog the files. Use Amazon Athena for analysis. D. Use AWS Snowball Edge to collect data from the IoT sensors directly to perform local analysis. Periodically collect the data into Amazon Redshift to perform global analysis.