DA0-002 Data Concepts and Environments Practice Question
A data analyst is profiling a dataset of customer records and discovers that 12% of the rows have missing values in the "postal_code" column, while the "customer_id" column is fully populated. The analyst needs to document this finding for a data quality report. Which data quality dimension does the missing postal code values primarily violate?
⚠ Common exam trap
The trap here is conflating missing values with incorrect values, which leads to selecting accuracy instead of recognizing that absence of data is a completeness issue.
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
✓
Completeness
Completeness assesses whether all required values are present. The postal_code column has 12% missing entries, meaning the dataset does not fully capture that attribute for all customers, which is the defining characteristic of a completeness violation. Accuracy, consistency, and uniqueness address correctness, agreement, and duplication respectively, none of which describe absent values.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Uniqueness
Why it's wrong here
Uniqueness measures whether records or key values appear only once without duplication. The scenario notes that customer_id is fully populated and does not mention duplicate rows. Missing postal codes relate to absent values, not repeated ones, so uniqueness is not the dimension violated.
- ✓
Completeness
Why this is correct
Completeness measures the extent to which required data is present without missing values. With 12% of postal codes absent, the column fails to fully represent all customer records, directly violating completeness. Documenting this gap helps downstream processes assess whether imputation or source correction is needed before analysis.
- ✗
Accuracy
Why it's wrong here
Accuracy measures whether values correctly represent the real-world entities they describe. Missing postal codes are absent rather than incorrect, so the issue is not accuracy. A record with a wrong postal code would violate accuracy, but blank values fall under a different dimension. Therefore, accuracy is not the primary dimension violated here.
- ✗
Consistency
Why it's wrong here
Consistency refers to whether data values agree across systems, formats, or time. Missing values do not inherently indicate contradictory information; they indicate absence. The scenario describes blanks in a single column rather than conflicting records, so consistency is not the dimension primarily affected.
Go deeper
Related to this question
About these practice questions
This DA0-002 question is part of Courseiva's 1,004-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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.