SAP-C02 · Question #409
A company has purchased appliances from different vendors. The appliances all have loT sensors. The sensors send status information in the vendors' proprietary formats to a legacy application that…
The correct answer is A. Connect the loT sensors to AWS loT Core. Set a rule to invoke an AWS Lambda function to parse. 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. This solution meets the requirement of…
Question
A company has purchased appliances from different vendors. The appliances all have loT 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?
Options
- AConnect the loT sensors to AWS loT Core. Set a rule to invoke an AWS Lambda function to parse
- BMigrate the application server to AWS Fargate, which will receive the information from loT
- CCreate an AWS Transfer for SFTP server. Update the loT sensor code to send the information as
- DUse AWS Snowball Edge to collect data from the loT sensors directly to perform local analysis.
How the community answered
(39 responses)- A82% (32)
- B5% (2)
- C10% (4)
- D3% (1)
Explanation
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. This solution meets the requirement of faster analysis and cost optimization by using AWS IoT Core to collect data from the IoT sensors in real-time and then using AWS Glue and Amazon Athena for efficient data analysis. This solution involves connecting the loT sensors to the AWS loT Core, setting a rule to invoke an AWS Lambda function to parse the information, and saving a .csv file to Amazon S3. AWS Glue can be used to catalog the files and Amazon Athena and Amazon QuickSight can be used for analysis. This solution will enable faster and more cost-effective data analysis. This solution is in line with the official Amazon Textbook and Resources for the AWS Certified Solutions Architect - Professional certification. In particular, the book states that: "AWS IoT Core can be used to ingest and process the data, AWS Lambda can be used to process and transform the data, and Amazon S3 can be used to store the data. AWS Glue can be used to catalog and access the data, Amazon Athena can be used to query the data, and Amazon QuickSight can be used to visualize
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