The answer is to investigate the source data to understand why 'Region' is missing. This is correct because missing data in a critical field like 'Region' signals a potential data quality issue that demands root cause analysis rather than a quick fix; the analyst must determine whether the absence stems from a collection error, a transformation bug, or a legitimate null, adhering to the principle of data provenance. On the CompTIA Data+ DA0-001 exam, this scenario tests your ability to prioritize traceability over assumptions—common traps include choosing to delete rows or fill in a default value, which can corrupt downstream analytics. When investigating missing data in critical fields, always trace back to the source system before taking action. Memory tip: think "Source First, Not Default"—if a field is critical, never guess; always ask where the data went.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
Exhibit
2025-03-15 14:32:01 ERROR [TransformJob] Failed to transform row 4521: Missing value for field 'Region'
2025-03-15 14:32:02 WARN [TransformJob] Defaulting missing 'Region' to 'Unknown'
Refer to the exhibit. What is the best course of action for the data analyst?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
2025-03-15 14:32:01 ERROR [TransformJob] Failed to transform row 4521: Missing value for field 'Region'
2025-03-15 14:32:02 WARN [TransformJob] Defaulting missing 'Region' to 'Unknown'
A
Change the default value to 'NA'
Why wrong: Changing default does not address the root cause.
B
Delete rows with missing 'Region'
Why wrong: Deleting rows reduces data integrity and may not be acceptable.
C
Investigate source data to understand why 'Region' is missing
Root cause analysis helps improve data quality at the source.
D
Ignore the warning as it is handled
Why wrong: The default handling may mask underlying data quality problems.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Investigate source data to understand why 'Region' is missing
Option C is correct because missing data in a critical field like 'Region' indicates a potential data quality issue that requires root cause analysis. The data analyst should investigate the source system to determine whether the missing values result from a collection error, a transformation bug, or a legitimate null, rather than making assumptions by deleting rows or filling defaults. This aligns with the principle of data provenance and ensures that downstream insights are based on accurate, traceable 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.
✗
Change the default value to 'NA'
Why it's wrong here
Changing default does not address the root cause.
✗
Delete rows with missing 'Region'
Why it's wrong here
Deleting rows reduces data integrity and may not be acceptable.
✓
Investigate source data to understand why 'Region' is missing
Why this is correct
Root cause analysis helps improve data quality at the source.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Ignore the warning as it is handled
Why it's wrong here
The default handling may mask underlying data quality problems.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume missing data should be immediately cleaned by deletion or default values, but Cisco tests the understanding that a data analyst's first responsibility is to investigate the source of the anomaly before applying any transformation.
Detailed technical explanation
How to think about this question
In data warehousing and ETL processes, missing values in dimension attributes (like 'Region') often arise from referential integrity failures, such as a missing lookup key in a star schema. A proper investigation involves querying source logs, checking for NULL constraints, and validating the extract phase—for example, using SQL COALESCE or CASE statements to trace the origin. In a real-world scenario, a retail analyst might find that missing region codes are caused by a recent API change that dropped the field, and fixing the source prevents recurring data loss across all historical and incremental loads.
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 practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
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.
Communicating Data Insights — This question tests Communicating Data Insights — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Investigate source data to understand why 'Region' is missing — Option C is correct because missing data in a critical field like 'Region' indicates a potential data quality issue that requires root cause analysis. The data analyst should investigate the source system to determine whether the missing values result from a collection error, a transformation bug, or a legitimate null, rather than making assumptions by deleting rows or filling defaults. This aligns with the principle of data provenance and ensures that downstream insights are based on accurate, traceable data.
What should I do if I get this DA0-001 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: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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