DEA-C01 Data Operations and Support Practice Question

A company uses Amazon Redshift for data warehousing. They notice that queries are running slowly, and the STL_LOAD_ERRORS table shows many 'Parse error' entries. The data is loaded from Amazon S3 using COPY commands. What is the MOST likely cause of the parse errors?

⚠ Common exam trap

The trap here is conflating any COPY failure with infrastructure or permissions; candidates must recognize that 'Parse error' in STL_LOAD_ERRORS specifically points to data-format/schema mismatch, not cluster capacity or IAM.

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

✓

The source data files have a different schema or delimiter than what is specified in the COPY command.

COPY loads data by parsing each source record according to the FORMAT, DELIMITER, and column definitions supplied in the command. When the actual file layout (column count, order, or delimiter) does not match those specifications, Redshift cannot map fields to columns and writes a 'Parse error' row into STL_LOAD_ERRORS. This is the classic signature of a schema/delimiter mismatch, not a resource or permission problem.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
The source data files have a different schema or delimiter than what is specified in the COPY command.
Why this is correct
COPY parses each S3 file against the declared column layout and delimiter. A mismatch between the file's actual schema or delimiter and the COPY parameters causes field parsing to fail, producing the Parse error entries in STL_LOAD_ERRORS. Aligning the COPY specification with the source files resolves it.
✗
The Redshift cluster does not have enough compute nodes to process the data.
Why it's wrong here
Insufficient compute nodes cause slow query performance and queueing, not 'Parse error' rows in STL_LOAD_ERRORS. That table records row-level load failures, so node count is irrelevant here; adding nodes would be the right response to throughput or concurrency bottlenecks, not malformed COPY input.
✗
The IAM role used by Redshift does not have permission to decrypt the S3 objects.
Why it's wrong here
Missing decrypt permission on the IAM role causes an access-denied or S3 permission failure during COPY, so no rows reach the parser and no 'Parse error' is logged. IAM policy correction is the right fix when Redshift cannot read or decrypt source objects, not when column data is malformed.
✗
The source data files are compressed using an unsupported compression format.
Why it's wrong here
An unsupported compression format makes COPY fail before parsing, producing a compression or file-format error rather than a 'Parse error'. Parse errors arise when the file's structure or data types contradict the COPY column definitions; compression mismatches would instead be resolved by specifying the correct COMPUPDATE or format option.

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

Go deeper

DEA-C01 Data Operations and Support Practice Question

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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