DEA-C01 Data Ingestion and Transformation Practice Question
A company is using AWS DMS to replicate data from an on-premises Oracle database to Amazon RDS for MySQL. The replication is working, but the target table has a different schema. Which DMS feature should be used to transform the source schema to match the target?
⚠ Common exam trap
Candidates often confuse AWS Schema Conversion Tool (SCT) with DMS transformation rules, assuming SCT handles runtime schema mapping, whereas SCT is a separate pre-migration assessment and conversion tool, not a DMS feature for ongoing replication transformations.
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
✓
Use DMS transformation rules
AWS DMS transformation rules allow you to modify the schema, table, or column names and data types during the migration process. This feature is specifically designed to handle schema transformations within the DMS task itself, enabling you to map the source Oracle schema to the target MySQL schema without external tools or services.
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 Schema Conversion Tool (SCT)
Why it's wrong here
SCT is for converting schema before migration, not during ongoing replication.
- ✗
Use AWS Glue ETL jobs
Why it's wrong here
Glue is not directly integrated with DMS for ongoing replication.
- ✓
Use DMS transformation rules
Why this is correct
DMS transformation rules allow renaming tables, schemas, and columns during replication.
- ✗
Use AWS Lambda triggers
Why it's wrong here
AWS Lambda triggers operate outside the DMS replication engine and cannot intercept or modify the schema mapping during the ongoing CDC or full-load transfer from Oracle to RDS for MySQL. The temptation arises because Lambda is a general-purpose compute service that can transform data after it lands, but the requirement is for DMS to apply schema transformations *during* replication — a task handled by DMS’s built-in transformation rules, not by post-replication triggers.
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Same concept, more angles
1 more way this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company wants to ingest data from an on-premises SQL Server database into Amazon Redshift. They need to transform the data during ingestion, such as masking PII columns. Which approach meets these requirements with minimal operational overhead?
medium- A.Use AWS Glue ETL jobs to extract data from SQL Server, transform it, and load into Redshift
- B.Use a custom application on EC2 to extract, transform, and load
- C.Use Kinesis Data Firehose to stream data from SQL Server to Redshift
- ✓ D.Use AWS Database Migration Service (DMS) with transformation rules
Why D: AWS DMS can perform transformations, such as data masking, during the migration process and can load data directly into Amazon Redshift, minimizing operational overhead. Option A (AWS Glue ETL) adds an extra step and overhead compared to DMS. Option B (custom application on EC2) introduces high operational overhead for management and scaling. Option C (Kinesis Data Firehose) is designed for streaming data and is not suitable for batch ingestion from an on-premises SQL Server database.
JA
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.