- A
Pattern analysis (e.g., format consistency)
Why wrong: Pattern analysis is typically for string columns, not date columns.
- B
Count of null values
Null count is a standard profiling check for any column.
- C
Variance
Why wrong: Variance is a statistical measure for numeric data, not applicable to dates.
- D
Cardinality (number of unique values)
Why wrong: Cardinality is more useful for categorical columns; for dates, range is often more informative.
- E
Data type verification
Verifying that the column is stored as a date type is an important quality check.
Question 736 of 1,000
DA0-001 Mining Data Practice Question
This DA0-001 practice question tests your understanding of mining data. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 is reviewing a dataset of customer transactions and wants to assess data quality by profiling the 'order_date' column. Which TWO profiling tasks are most appropriate for this date column? (Select TWO).
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
✓
Count of null values
Profiling a date column typically includes checking for null values and verifying the data type. Cardinality and pattern analysis are more relevant for categorical or string columns; variance is for numeric data.
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.
- ✗
Pattern analysis (e.g., format consistency)
Why it's wrong here
Pattern analysis is typically for string columns, not date columns.
- ✓
Count of null values
Why this is correct
Null count is a standard profiling check for any column.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Variance
Why it's wrong here
Variance is a statistical measure for numeric data, not applicable to dates.
- ✗
Cardinality (number of unique values)
Why it's wrong here
Cardinality is more useful for categorical columns; for dates, range is often more informative.
- ✓
Data type verification
Why this is correct
Verifying that the column is stored as a date type is an important quality check.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 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
Got this wrong? Here's your next step.
Identify which DA0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this DA0-001 question test?
Mining Data — This question tests Mining Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Count of null values — Profiling a date column typically includes checking for null values and verifying the data type. Cardinality and pattern analysis are more relevant for categorical or string columns; variance is for numeric data.
What should I do if I get this DA0-001 question wrong?
Identify which DA0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 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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