DA0-002 Data Acquisition and Preparation Practice Question
A data analyst is performing data profiling on a customer dataset. Which metric would best reveal the number of distinct values in the 'state' column?
⚠ Common exam trap
The trap is that candidates might confuse cardinality with row count or null count, but cardinality specifically counts distinct values, which is the key to profiling categorical columns.
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
✓
Cardinality
Cardinality measures the number of distinct values in a column, so it directly reveals how many unique states appear in the 'state' column. This is a standard data profiling metric used to understand column variability and potential categorical encoding needs. Mean, row count, and null count do not provide distinct value counts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Mean
Why it's wrong here
The mean averages numeric values, so it cannot count distinct categories in a text column such as 'state'. It is tempting because it summarises numeric distributions, which suits profiling continuous fields like income rather than categorical cardinality.
- ✗
Row count
Why it's wrong here
Row count totals all records, including duplicates, so it reveals dataset size rather than how many distinct states appear. It is tempting because it is a basic profiling statistic, which suits completeness checks rather than measuring cardinality of a categorical column.
- ✓
Cardinality
Why this is correct
Cardinality counts the distinct values present in a column, so profiling the 'state' column returns how many unique states appear. This directly satisfies the stem's requirement to reveal the number of distinct values, distinguishing it from row count or null-count metrics.
- ✗
Null count
Why it's wrong here
Null count tallies missing entries in the column, not distinct entries, so it cannot reveal cardinality. It is tempting because it also profiles column quality, and would be correct when the analyst needs to quantify incomplete records before deciding on imputation or exclusion.
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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
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