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?
Select one answer.
Marked answer: A
Community Discussion
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Chose A1
Answer is A — this is the most efficient and scalable solution. Why? AWS IoT Core connects IoT sensors securely and in real-time. An IoT Rule sends data to a Lambda function to parse vendor-specific formats. Parsed data is saved in S3, cataloged by Glue, queried with Athena, and visualized in QuickSight. It's serverless, real-time, and cost-effective, unlike the batch-processing legacy system.
1
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.
