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Data Ingestion and Transformation →mediumMultiple ChoiceObjective-mapped

DEA-C01 Data Ingestion and Transformation Practice Question

This DEA-C01 practice question tests your understanding of data ingestion and transformation. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 data engineer is building a data ingestion pipeline that reads JSON files from Amazon S3 and loads them into an Amazon Redshift table using COPY commands. The files are gzip compressed and contain nested JSON. The engineer wants to minimize transformation steps. Which approach should the engineer use?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

A
Use Amazon Athena to query the JSON and INSERT INTO Redshift.
Why wrong: Athena is not optimized for bulk load; COPY is better.
B
Use Kinesis Data Firehose to transform and load into Redshift.
Why wrong: Firehose is for streaming, not batch S3 files.
C
Use the COPY command with the 'auto' option to ingest JSON directly.
COPY with 'auto' automatically parses JSON.
D
Use AWS Glue ETL to flatten the JSON and write to S3 as CSV, then COPY from CSV.
Why wrong: Adds complexity; COPY can handle JSON directly.

Full breakdown with real-world context →

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 the COPY command with the 'auto' option to ingest JSON directly.

Option C is correct because the COPY command with the 'auto' option can directly ingest gzip-compressed JSON files from S3 into Redshift, automatically inferring the schema and handling nested structures without requiring intermediate transformation steps. This minimizes transformation steps by leveraging Redshift's native JSON parsing capability, which supports both 'auto' and 'jsonpaths' options for nested data.

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.

✗
Use Amazon Athena to query the JSON and INSERT INTO Redshift.
Why it's wrong here
Athena is not optimized for bulk load; COPY is better.
✗
Use Kinesis Data Firehose to transform and load into Redshift.
Why it's wrong here
Firehose is for streaming, not batch S3 files.
✓
Use the COPY command with the 'auto' option to ingest JSON directly.
Why this is correct
COPY with 'auto' automatically parses JSON.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use AWS Glue ETL to flatten the JSON and write to S3 as CSV, then COPY from CSV.
Why it's wrong here
Adds complexity; COPY can handle JSON directly.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often overcomplicate the solution by assuming nested JSON requires an ETL tool like Glue or Athena, when Redshift's COPY command with 'auto' or 'jsonpaths' can handle nested structures natively, minimizing transformation steps as explicitly requested.

Detailed technical explanation

How to think about this question

The COPY command's 'auto' option uses the 'auto' schema inference to map JSON keys to Redshift column names, and it automatically decompresses gzip files during ingestion. For deeply nested JSON, the 'jsonpaths' option can be used to specify explicit mapping, but 'auto' works well for flat or moderately nested structures by treating nested objects as super columns or using the 'noshred' option to store them as VARCHAR. A real-world scenario is ingesting IoT sensor data where JSON contains nested readings; using COPY with 'auto' avoids the overhead of ETL jobs while maintaining performance.

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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

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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FAQ

Questions learners often ask

What does this DEA-C01 question test?

Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use the COPY command with the 'auto' option to ingest JSON directly. — Option C is correct because the COPY command with the 'auto' option can directly ingest gzip-compressed JSON files from S3 into Redshift, automatically inferring the schema and handling nested structures without requiring intermediate transformation steps. This minimizes transformation steps by leveraging Redshift's native JSON parsing capability, which supports both 'auto' and 'jsonpaths' options for nested data.

What should I do if I get this DEA-C01 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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