Quick Answer
The answer is customer feedback comments. This is the correct choice because qualitative data consists of non-numerical, descriptive information that captures opinions, sentiments, or experiences, exactly like written feedback from customers. Unlike quantitative data, which can be measured or counted, qualitative data is categorical and requires thematic analysis to derive insights. On the CompTIA Data+ DA0-001 exam, this concept tests your ability to distinguish between data types, often appearing in scenario-based questions where a common trap is confusing structured survey ratings (quantitative) with open-ended comments (qualitative). A useful memory tip is to think of the word “quality” in qualitative—it describes the quality or characteristics of something, not its quantity.
This DA0-001 practice question tests your understanding of comparing and contrasting data concepts. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
Which of the following is an example of qualitative data?
Stock price
Why wrong: Stock price is numeric, quantitative data.
Customer feedback comments
Comments are text, non-numeric, qualitative data.
Number of website visitors
Why wrong: Visitors count is numeric, quantitative data.
Product weight in grams
Why wrong: Weight is numeric, quantitative data.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Customer feedback comments
Customer feedback comments are qualitative data because they consist of non-numerical, descriptive text that captures opinions, sentiments, or experiences. Unlike quantitative data, which can be measured or counted, qualitative data is categorical and often requires thematic analysis to derive insights.
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.
Stock price
Why it's wrong here
Stock price is numeric, quantitative data.
Customer feedback comments
Why this is correct
Comments are text, non-numeric, qualitative data.
Related concept
Read the scenario before looking for a memorised answer.
Number of website visitors
Why it's wrong here
Visitors count is numeric, quantitative data.
Product weight in grams
Why it's wrong here
Weight is numeric, quantitative data.
Common exam traps
The trap here is that candidates often confuse 'qualitative' with 'quantifiable' and may incorrectly select a numeric option like stock price or website visitors, not realizing that qualitative data is inherently non-numeric and descriptive.
Detailed technical explanation
In data analytics, qualitative data is often stored as strings or text fields in databases (e.g., VARCHAR in SQL) and requires natural language processing (NLP) or manual coding for analysis. This contrasts with quantitative data, which is stored as numeric types (e.g., INT, FLOAT) and supports direct mathematical operations like averaging or summing. A real-world scenario: analyzing customer feedback comments to identify common themes (e.g., 'slow service') requires qualitative methods, while measuring the average stock price over time uses quantitative techniques.
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
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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: Customer feedback comments — Customer feedback comments are qualitative data because they consist of non-numerical, descriptive text that captures opinions, sentiments, or experiences. Unlike quantitative data, which can be measured or counted, qualitative data is categorical and often requires thematic analysis to derive insights.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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. Refer to the exhibit. Which type of data is the field "region"?
mediumWhy A: The field 'region' contains categorical labels (e.g., 'North', 'South', 'East', 'West') that represent distinct groups or categories, not numerical measurements. Qualitative data (also called categorical data) describes attributes or characteristics that can be named but not meaningfully ordered or measured on a numeric scale. Since 'region' assigns a name to a geographic area without any inherent numeric value or order, it is a classic example of qualitative data.
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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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