DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is setting up an Amazon Kinesis Data Firehose delivery stream to load data into Amazon Redshift. The data is coming from an application that produces JSON records. The engineer needs to transform the data to match the Redshift table schema. Which approach is the MOST cost-effective and requires the least operational overhead?
⚠ Common exam trap
The trap here is that candidates often overestimate the transformation capabilities of Redshift's COPY command, mistakenly believing it can perform complex record-level transformations, when in fact it only supports basic data mapping and format parsing, not arbitrary JSON restructuring.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure a Lambda function in the Firehose delivery stream to transform records before delivery.
Kinesis Data Firehose natively supports invoking a Lambda function as a transformation step within the delivery stream. This allows the engineer to write a simple Lambda function that parses the incoming JSON records and transforms them to match the Redshift table schema, all without provisioning or managing any additional infrastructure. This approach is the most cost-effective (pay per invocation) and requires the least operational overhead since Firehose handles the orchestration, retries, and delivery to Redshift automatically.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use AWS Glue as a transformation step between Firehose and Redshift, with a trigger on S3.
Why it's wrong here
Adding Glue increases latency and cost.
- ✗
Use Kinesis Data Firehose with direct PUT to Redshift and rely on Redshift's COPY command to transform.
Why it's wrong here
Firehose cannot directly PUT to Redshift; it uses COPY, but transformation must be done upstream.
- ✓
Configure a Lambda function in the Firehose delivery stream to transform records before delivery.
Why this is correct
Firehose supports Lambda for data transformation with minimal overhead.
- ✗
Use the Kinesis Client Library (KCL) to consume the stream, transform in an EC2 instance, and then load to Redshift.
Why it's wrong here
This adds operational overhead and cost.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.