COUNT and DISTINCTCOUNT in Power BI - Cell-by-Cell Formula Trace

Sample Data

This table shows sales transactions with SalesID, CustomerID, and Amount.

Cell	Value
A1	SalesID
A2	101
A3	102
A4	103
A5	104
A6	105
B1	CustomerID
B2	C001
B3	C002
B4	C001
B5	C003
B6	C002
C1	Amount
C2	250
C3	450
C4	300
C5	150
C6	500

Formula Trace

COUNT(Sales[CustomerID]) and DISTINCTCOUNT(Sales[CustomerID])

Step 1: COUNT(Sales[CustomerID])

Step 2: DISTINCTCOUNT(Sales[CustomerID])

Cell Reference Map

    A        B          C
1 SalesID  CustomerID  Amount
2  101      C001       250
3  102      C002       450
4  103      C001       300
5  104      C003       150
6  105      C002       500

Arrows: COUNT and DISTINCTCOUNT use column B (CustomerID) values from rows 2 to 6.

The formula references the CustomerID column (cells B2 to B6) to count total and distinct customers.

Result

    A        B          C          D               E
1 SalesID  CustomerID  Amount    COUNT_CustID  DISTINCTCOUNT_CustID
2  101      C001       250          5                 3
3  102      C002       450
4  103      C001       300
5  104      C003       150
6  105      C002       500

Column D shows COUNT of CustomerID as 5 (all rows counted). Column E shows DISTINCTCOUNT as 3 (unique customers).

Sheet Trace Quiz - 3 Questions

What does COUNT(Sales[CustomerID]) return in this data?

A 5

B 3

C 6

D 4

Key Result

COUNT counts all non-blank values; DISTINCTCOUNT counts unique values in a column.

Practice

1.

What does the DISTINCTCOUNT function do in Power BI?

easy

A. Counts all values including empty ones in a column

B. Counts the total number of rows in a table

C. Counts only empty values in a column

D. Counts the number of unique non-empty values in a column

Solution

1. Step 1: Understand DISTINCTCOUNT purpose

   DISTINCTCOUNT counts unique non-empty values in a column, ignoring duplicates and blanks.

2. Step 2: Compare with other options

   Other options describe counting all values, empty values, or rows, which are incorrect for DISTINCTCOUNT.

3. Final Answer:

   Counts the number of unique non-empty values in a column -> Option D

4. Quick Check:

   DISTINCTCOUNT = unique non-empty count [OK]

Hint: DISTINCTCOUNT counts unique values only, ignoring blanks [OK]

Common Mistakes:

• Confusing DISTINCTCOUNT with COUNT
• Thinking it counts empty or blank values
• Assuming it counts total rows

2.

Which of the following is the correct syntax to count all non-empty values in the Sales[OrderID] column?

?

easy

A. DISTINCTCOUNT(Sales[OrderID])

B. COUNT(Sales[OrderID])

C. COUNTROWS(Sales[OrderID])

D. COUNTBLANK(Sales[OrderID])

Solution

1. Step 1: Identify COUNT syntax

   COUNT(column) counts all non-empty values in the specified column.

2. Step 2: Eliminate incorrect options

   DISTINCTCOUNT counts unique values, COUNTROWS requires a table, COUNTBLANK counts blanks, so only COUNT is correct here.

3. Final Answer:

   COUNT(Sales[OrderID]) -> Option B

4. Quick Check:

   COUNT(column) counts non-empty values [OK]

Hint: Use COUNT(column) to count non-empty values [OK]

Common Mistakes:

• Using COUNTROWS on a column instead of a table
• Confusing DISTINCTCOUNT with COUNT
• Using COUNTBLANK instead of COUNT

3.

Given the table Products with the Category column containing values: {"Fruit", "Fruit", "Vegetable", "Fruit", "Vegetable", "Grain"}, what is the result of DISTINCTCOUNT(Products[Category])?

medium

A. 3

B. 6

C. 5

D. 1

Solution

1. Step 1: Identify unique categories

   The unique values in Category are "Fruit", "Vegetable", and "Grain" which totals 3.

2. Step 2: Apply DISTINCTCOUNT

   DISTINCTCOUNT counts these unique non-empty values, so the result is 3.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   DISTINCTCOUNT = 3 unique categories [OK]

Hint: Count unique values, ignore duplicates [OK]

Common Mistakes:

• Counting total rows instead of unique values
• Confusing DISTINCTCOUNT with COUNT
• Including duplicates in count

4.

Consider this DAX measure:
UniqueCustomers = COUNT(Customer[CustomerID])
Why might this measure give an incorrect count of unique customers?

medium

A. Because CustomerID column is not numeric

B. Because COUNT only counts blank values

C. Because COUNT counts all non-empty values, including duplicates

D. Because COUNT counts unique values only

Solution

1. Step 1: Understand COUNT behavior

   COUNT counts all non-empty values, including duplicates, so it does not count unique customers.

2. Step 2: Identify correct function for unique count

   To count unique customers, DISTINCTCOUNT should be used instead of COUNT.

3. Final Answer:

   Because COUNT counts all non-empty values, including duplicates -> Option C

4. Quick Check:

   COUNT counts duplicates, use DISTINCTCOUNT for unique [OK]

Hint: Use DISTINCTCOUNT for unique counts, not COUNT [OK]

Common Mistakes:

• Assuming COUNT counts unique values
• Thinking COUNT counts blanks
• Believing CustomerID must be numeric for COUNT

5.

You have a sales table with 1000 rows. The CustomerID column has 900 non-empty values, but only 850 unique customers. Which DAX measure correctly returns the number of unique customers who made a purchase?

hard

A. DISTINCTCOUNT(Sales[CustomerID])

B. COUNTROWS(Sales)

C. COUNT(Sales[CustomerID])

D. COUNTBLANK(Sales[CustomerID])

Solution

1. Step 1: Understand the data counts

   There are 900 non-empty CustomerID values but only 850 unique customers.

2. Step 2: Choose measure for unique count

   DISTINCTCOUNT returns the count of unique non-empty values, which is 850, the correct unique customer count.

3. Final Answer:

   DISTINCTCOUNT(Sales[CustomerID]) -> Option A

4. Quick Check:

   Use DISTINCTCOUNT for unique customer count [OK]

Hint: Use DISTINCTCOUNT to get unique counts, not COUNT [OK]

Common Mistakes:

• Using COUNT which counts duplicates
• Using COUNTROWS which counts all rows
• Using COUNTBLANK which counts blanks