- A
Assume the anomaly is real and report it
Why wrong: Assumptions without verification can lead to incorrect conclusions.
- B
Immediately alert all stakeholders
Why wrong: Alerting without validation may cause unnecessary panic.
- C
Verify the data source and extraction process
This confirms the anomaly is not due to data collection issues.
- D
Check for data entry errors or technical glitches
Common causes should be ruled out before reporting.
- E
Remove the anomaly without documentation
Why wrong: Removing data without documentation can compromise integrity and traceability.
Quick Answer
The correct actions before reporting an anomaly are to check for data entry errors or technical glitches. This is essential because anomalies often stem from pipeline issues like a misconfigured ETL job or a corrupted data feed, so verifying the data source and extraction process first ensures the anomaly reflects a genuine data problem rather than an extraction artifact. On the CompTIA Data+ DA0-001 exam, this concept tests your understanding of data integrity and the importance of root-cause validation before escalating findings; a common trap is rushing to report an outlier without confirming it isn’t a simple input mistake or system error. To remember this, think of the mnemonic “V.E.T.”—Verify Extraction before Trusting the anomaly—which reinforces that you must rule out technical glitches and entry errors as the first two diagnostic steps.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 analyst discovers an anomaly in a dataset. Which two actions should be taken before reporting? (Choose TWO.)
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
Verify the data source and extraction process
Option C is correct because before reporting an anomaly, the data analyst must verify the data source and extraction process to ensure the anomaly is not due to a pipeline error, such as a misconfigured ETL job or a corrupted data feed. This step confirms data integrity and prevents false alarms based on extraction artifacts rather than genuine data issues.
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.
- ✗
Assume the anomaly is real and report it
Why it's wrong here
Assumptions without verification can lead to incorrect conclusions.
- ✗
Immediately alert all stakeholders
Why it's wrong here
Alerting without validation may cause unnecessary panic.
- ✓
Verify the data source and extraction process
Why this is correct
This confirms the anomaly is not due to data collection issues.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Check for data entry errors or technical glitches
Why this is correct
Common causes should be ruled out before reporting.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Remove the anomaly without documentation
Why it's wrong here
Removing data without documentation can compromise integrity and traceability.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse 'immediate reporting' with proactive communication, but Cisco tests the understanding that data validation must precede any stakeholder notification to maintain data credibility.
Detailed technical explanation
How to think about this question
In practice, verifying the data source involves checking the data lineage, such as confirming the source system's timestamps, API response codes, or database transaction logs. For example, in a SQL-based ETL pipeline, an anomaly might stem from a missing JOIN condition or a WHERE clause that inadvertently filters out valid records, which can be identified by re-running the extraction with debug logging enabled. This aligns with the principle of 'trust but verify' in data quality frameworks like DAMA-DMBOK, where source-to-target reconciliation is a standard control.
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.
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Communicating Data Insights — study guide chapter
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Communicating Data Insights practice questions
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FAQ
Questions learners often ask
What does this DA0-001 question test?
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: Verify the data source and extraction process — Option C is correct because before reporting an anomaly, the data analyst must verify the data source and extraction process to ensure the anomaly is not due to a pipeline error, such as a misconfigured ETL job or a corrupted data feed. This step confirms data integrity and prevents false alarms based on extraction artifacts rather than genuine data issues.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
This DA0-001 practice question is part of Courseiva's free CompTIA 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 DA0-001 exam.
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