PL-300 Model the data Practice Question
You are modeling data in Power BI that includes a table named SurveyResponses with columns: ResponseID, QuestionID, RespondentID, and AnswerText. Each respondent answers multiple questions. You need to create a measure that counts the number of unique respondents who answered a specific question. Which DAX measure should you use?
⚠ Common exam trap
Candidates often confuse COUNTROWS (which counts all rows) with DISTINCTCOUNT (which counts unique values), or they assume COUNT or COUNTA will automatically deduplicate, leading them to pick a wrong option that counts total responses instead of unique respondents.
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
✓
DISTINCTCOUNT(SurveyResponses[RespondentID])
DISTINCTCOUNT(SurveyResponses[RespondentID]) counts the number of unique RespondentID values in the table, which directly gives the count of unique respondents who answered a specific question when used in a filter context (e.g., with a slicer or visual grouping by QuestionID). This is the standard DAX pattern for counting distinct entities in a column.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
DISTINCTCOUNT(SurveyResponses[RespondentID])
Why this is correct
DISTINCTCOUNT(SurveyResponses[RespondentID]) is correct because it evaluates the unique values in the RespondentID column, ignoring blanks and returning the number of distinct respondents. In a table where each row is a survey response, a single respondent may appear multiple times; distinct counting on the respondent identifier isolates each unique individual, which is exactly the measure needed. This function is designed for counting unique non-blank values and is the standard way to count distinct entities in DAX.
- ✗
COUNT(SurveyResponses[RespondentID])
Why it's wrong here
COUNT(SurveyResponses[RespondentID]) is incorrect because the COUNT function in DAX counts only numeric values in a column; it ignores text, logicals, and blanks. RespondentID is typically a text-based identifier (e.g., a GUID or alphanumeric code), so COUNT would return a blank or an error, not a meaningful count. Even if the ID were stored as a number, COUNT counts all non-blank occurrences in the column, including duplicates from multiple responses, so it would overcount rather than provide distinct respondents.
- ✗
COUNTROWS(SurveyResponses)
Why it's wrong here
COUNTROWS(SurveyResponses) counts the number of rows in the table, which corresponds to the total number of survey responses recorded, not the number of unique respondents. Since a respondent can submit multiple responses, the table grain is responses, and each row represents one submission. Therefore, COUNTROWS returns a higher number than the distinct respondent count and fails to answer the intended question of 'how many unique customers' took the survey.
- ✗
COUNTA(SurveyResponses[RespondentID])
Why it's wrong here
COUNTA(SurveyResponses[RespondentID]) counts all non-blank values in the RespondentID column, which includes every occurrence of every ID across all rows. If the RespondentID is populated for each response, COUNTA returns the total number of responses, counting the same respondent multiple times. Unlike DISTINCTCOUNT, it does not deduplicate values, so it overstates the number of unique respondents; moreover, if some IDs are blank, it would exclude them, but it still does not provide distinct counts.
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