- A
Patient
Why wrong: Incorrect. Each row is per visit, not per patient.
- B
Visit
Correct. Each record captures one visit.
- C
Day
Why wrong: Incorrect. Day would imply one aggregate per day, but the data has multiple visits per day.
- D
Hospital
Why wrong: Incorrect. The data is about visits, not hospital-level aggregates.
Quick Answer
The answer is Visit. This is correct because data granularity refers to the level of detail or the finest grain captured in a dataset, and here each row represents a single patient visit event, not a patient or a day. Since the data contains daily patient visits, the smallest unique record is the visit occurrence itself, making "Visit" the precise granularity. On the CompTIA Data+ DA0-001 exam, this concept tests your ability to identify the atomic unit of data—a common trap is confusing granularity with the entity being analyzed (like "patient") or the time period (like "day"), but the key is to look at what each row actually describes. A helpful memory tip: think of granularity as the "one row equals one what?" question—if each row is one visit, the granularity is visit, not the patient or the date.
DA0-001 Comparing and Contrasting Data Concepts Practice Question
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.
A hospital wants to analyze patient readmission rates. The data contains daily patient visits. What is the level of granularity?
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
Visit
The level of granularity refers to the finest detail captured in the dataset. Since the data contains daily patient visits, each record represents a single visit event, not the patient or the day itself. Therefore, 'Visit' is the correct granularity because each row corresponds to one visit occurrence.
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.
- ✗
Patient
Why it's wrong here
Incorrect. Each row is per visit, not per patient.
- ✓
Visit
Why this is correct
Correct. Each record captures one visit.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Day
Why it's wrong here
Incorrect. Day would imply one aggregate per day, but the data has multiple visits per day.
- ✗
Hospital
Why it's wrong here
Incorrect. The data is about visits, not hospital-level aggregates.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing the subject of analysis (patient readmission rates) with the actual data granularity (each row is a visit), leading candidates to incorrectly select 'Patient' instead of 'Visit'.
Detailed technical explanation
How to think about this question
Granularity determines the level of detail in a dataset; finer granularity (e.g., per visit) allows more precise analysis but increases data volume. In healthcare analytics, visit-level data enables tracking of individual patient readmissions within specific time windows, such as 30-day readmission rates, which is critical for CMS reporting. Coarser granularity (e.g., per day) would lose the ability to link visits to the same patient.
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 small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
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Comparing and Contrasting Data Concepts — study guide chapter
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FAQ
Questions learners often ask
What does this DA0-001 question test?
Comparing and Contrasting Data Concepts — This question tests Comparing and Contrasting Data Concepts — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Visit — The level of granularity refers to the finest detail captured in the dataset. Since the data contains daily patient visits, each record represents a single visit event, not the patient or the day itself. Therefore, 'Visit' is the correct granularity because each row corresponds to one visit occurrence.
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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