A company will use Amazon Kinesis Data Firehose to deliver data to Amazon S3. The incoming files are 2 MB CSV files. The company must convert the CSV files to JSON and store them in Apache Parquet format in S3. Which approach requires the least development effort?

The correct approach leverages Kinesis Data Firehose's native capabilities for format conversion and S3 delivery, combined with a Lambda function for the initial CSV to JSON transformation. Kinesis Data Firehose can directly invoke a Lambda function to transform incoming data. In this scenario, the Lambda function handles the CSV to JSON conversion. After the Lambda transformation, Firehose receives the JSON data and can then natively convert it to Apache Parquet format before delivering it to S3. This minimizes development effort because Firehose handles the Parquet conversion and S3 delivery without requiring additional custom code. Incorrect options: Using Lambda for Parquet conversion after Firehose converts to JSON adds unnecessary development complexity, as Firehose can do this natively. Relying solely on Firehose to convert CSV to JSON and then to Parquet is not directly supported in a single native step; Firehose needs a pre-processing step for the initial CSV to JSON. Using Lambda for both transformations and storage bypasses Firehose's native capabilities for Parquet conversion and S3 delivery, increasing development and operational overhead.