- A
Amazon Kinesis Data Analytics for real-time transformation.
Why wrong: Kinesis is for streaming data, not for batch transformation of large datasets.
- B
Amazon Athena to query the source data and write results to Redshift.
Why wrong: Athena is for querying data in S3, not for ETL transformations.
- C
AWS Glue to perform extract, transform, and load (ETL) jobs.
Glue is a fully managed ETL service suitable for transforming data before loading into Redshift.
- D
AWS Database Migration Service (DMS) with transformation rules.
Why wrong: DMS is primarily for replication and offers limited transformation capabilities.
Question 550 of 1,730
DBS-C01 Deployment and Migration Practice Question
This DBS-C01 practice question tests your understanding of deployment and migration. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is planning to migrate a 5 TB Oracle data warehouse to Amazon Redshift. They need to transform the data during migration. Which AWS service should they use to perform the transformation?
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
✓
AWS Glue to perform extract, transform, and load (ETL) jobs.
AWS Glue is the correct choice because it is a fully managed ETL service designed for data transformation and loading into Amazon Redshift. It can handle the 5 TB Oracle data warehouse migration by running Spark-based ETL jobs that transform the data before writing it to Redshift, making it ideal for batch-oriented data warehouse migrations.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Kinesis Data Analytics for real-time transformation.
Why it's wrong here
Kinesis is for streaming data, not for batch transformation of large datasets.
- ✗
Amazon Athena to query the source data and write results to Redshift.
Why it's wrong here
Athena is for querying data in S3, not for ETL transformations.
- ✓
AWS Glue to perform extract, transform, and load (ETL) jobs.
Why this is correct
Glue is a fully managed ETL service suitable for transforming data before loading into Redshift.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Database Migration Service (DMS) with transformation rules.
Why it's wrong here
DMS is primarily for replication and offers limited transformation capabilities.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS DMS's transformation rules (which handle simple schema mapping) with the full ETL capabilities needed for data warehouse migration, leading them to choose DMS instead of Glue.
Detailed technical explanation
How to think about this question
AWS Glue uses Apache Spark under the hood to execute ETL jobs, allowing for complex transformations like joins, aggregations, and data cleansing. It can read from Oracle via JDBC, transform the data in memory, and write to Redshift using the Redshift Spectrum or JDBC connector, handling large volumes efficiently. In real-world scenarios, Glue's dynamic frames and built-in transforms simplify handling schema evolution and data quality issues common in legacy Oracle warehouses.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Deployment and Migration — study guide chapter
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Deployment and Migration — This question tests Deployment and Migration — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Glue to perform extract, transform, and load (ETL) jobs. — AWS Glue is the correct choice because it is a fully managed ETL service designed for data transformation and loading into Amazon Redshift. It can handle the 5 TB Oracle data warehouse migration by running Spark-based ETL jobs that transform the data before writing it to Redshift, making it ideal for batch-oriented data warehouse migrations.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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