Quick Answer

The answer is to enable S3 compression in Firehose, use a Lambda function for data transformation within the Firehose stream, and deliver the stream directly to S3 via Firehose. This combination works because Kinesis Data Firehose is purpose-built to load streaming data into S3 with minimal overhead, handling buffering, compression, and partitioning automatically. Adding a Lambda transformation allows you to parse or enrich the raw clickstream data before it lands in S3, while enabling GZIP compression reduces storage costs and improves downstream query performance—all without managing servers. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of managed ingestion patterns versus custom coding; a common trap is overcomplicating the solution by building a custom consumer with Lambda and PutRecord when Firehose already handles the heavy lifting. Remember the mnemonic “Firehose First, Lambda for Logic, Compress for Cost” to quickly recall the three steps for near real-time delivery with minimal operational burden.