DA0-002 Data Governance Practice Question
Exhibit
Data Quality Check Report Table: customer_info Check: Non-null validation on email field Result: Failed - 1200 records have null email
Refer to the exhibit. A data analyst is reviewing a data quality report. Which of the following actions should the analyst take first?
⚠ Common exam trap
CompTIA often tests the principle that 'fix the source, not the symptom'—the trap here is that candidates jump to data cleansing actions (delete, fill, ignore) without first diagnosing why the nulls exist, which is a classic data quality management mistake.
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
✓
Investigate the source system to understand why emails are missing.
The first step in data quality remediation is root cause analysis. Without understanding why 1200 records have null emails (e.g., a source system bug, a failed ETL join, or a missing required field), any corrective action like deletion or placeholder insertion risks introducing bias or masking a systemic issue. Investigating the source system aligns with the data governance principle of 'fix the source, not the symptom.'
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Delete the 1200 records with null emails.
Why it's wrong here
Deleting all 1200 records destroys valid data in other columns and skews distributions before the cause is known. Deletion is tempting as immediate remediation, and it suits confirmed duplicate or corrupt rows, but null emails need profiling, source tracing and documented imputation or retention decisions first.
- ✗
Fill null emails with a placeholder.
Why it's wrong here
A placeholder such as 'unknown' fabricates a value, corrupts email validation and masks the underlying pipeline fault. Filling is tempting because it preserves row counts, and it suits categorical defaults where a sentinel is meaningful, but null emails require root-cause analysis before any documented imputation.
- ✓
Investigate the source system to understand why emails are missing.
Why this is correct
Missing emails indicate a data quality defect whose origin must be established before remediation. Investigating the source system reveals whether the cause is an optional field, a validation rule, or an extraction fault, satisfying the need to diagnose root cause first.
- ✗
Ignore the nulls as they are not critical.
Why it's wrong here
Nulls in a key contact field can break joins, notifications and downstream reporting, so dismissing them hides real defects. Ignoring is tempting when null rates look low or the field seems non-essential, and it would suit genuinely optional attributes with no analytical or operational dependency.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DA0-002 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 DA0-002 exam.