Quick Answer
The answer is validity. Validity is the correct data quality dimension because it measures whether data conforms to its defined format, rules, or constraints—such as a ZIP code field requiring exactly five numeric digits or a recognized postal code. When an address contains letters or a non-existent code, the data fails these domain and format rules, directly violating validity rather than accuracy, completeness, or consistency. On the CompTIA Data+ DA0-001 exam, this concept often appears in scenario-based questions where you must distinguish validity from accuracy: a valid ZIP code can be correctly formatted but still be inaccurate if it doesn’t match the actual location. A common trap is confusing validity with accuracy—remember that validity checks the structure, not the truth. For a quick memory tip, think of a driver’s license: validity ensures the number has the right pattern of letters and digits, while accuracy confirms it belongs to the right person.
This DA0-001 practice question tests your understanding of comparing and contrasting data concepts. 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.
A data analyst notices that customer addresses in the database contain invalid ZIP codes. Which data quality dimension is being violated?
Validity
Validity ensures data adheres to specified formats and rules, such as valid ZIP codes.
Timeliness
Why wrong: Timeliness refers to data being available when needed, not its correctness.
Consistency
Why wrong: Consistency checks for logical conflicts, not format validity.
Completeness
Why wrong: Completeness refers to whether all required data is present, not whether data is correct.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Validity
A is correct because validity refers to the degree to which data conforms to its defined format, rules, or constraints. Invalid ZIP codes (e.g., a five-digit code containing letters or a non-existent postal code) directly violate the format and domain rules expected for that field, making this a validity issue.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Validity
Why this is correct
Validity ensures data adheres to specified formats and rules, such as valid ZIP codes.
Related concept
Read the scenario before looking for a memorised answer.
Timeliness
Why it's wrong here
Timeliness refers to data being available when needed, not its correctness.
Consistency
Why it's wrong here
Consistency checks for logical conflicts, not format validity.
Completeness
Why it's wrong here
Completeness refers to whether all required data is present, not whether data is correct.
Common exam traps
The trap here is that candidates confuse 'validity' with 'completeness' or 'consistency,' mistakenly thinking a missing or mismatched ZIP code is a completeness or consistency issue, when in fact the violation is about the data not conforming to the required format or rule set.
Detailed technical explanation
Under the hood, validity is often enforced via database constraints (e.g., CHECK constraints in SQL, regex patterns in ETL pipelines) or reference data lookups against official USPS ZIP code tables. A subtle behavior: a ZIP+4 code like '12345-6789' is valid, but '12345-678' (missing a digit) would fail a length check, illustrating that validity rules must account for exact formatting specifications.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Comparing and Contrasting Data Concepts — This question tests Comparing and Contrasting Data Concepts — Read the scenario before looking for a memorised answer..
The correct answer is: Validity — A is correct because validity refers to the degree to which data conforms to its defined format, rules, or constraints. Invalid ZIP codes (e.g., a five-digit code containing letters or a non-existent postal code) directly violate the format and domain rules expected for that field, making this a validity issue.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data analyst finds that the "Age" column contains values like "N/A", "unknown", and negative numbers. Which data quality dimension is primarily affected?
mediumWhy C: Validity refers to the degree to which data conforms to defined business rules or constraints. Invalid entries (non-numeric, negative) violate the expected data type and range.
Last reviewed: Jun 24, 2026
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