VALUES and DISTINCT in Power BI - Dashboard Guide

Dashboard Mode - VALUES and DISTINCT

Business Question

Which unique product categories and their sales amounts are in our sales data? We want to see distinct categories and total sales per category.

Sample Data

OrderID	ProductCategory	SalesAmount
1001	Electronics	200
1002	Furniture	450
1003	Electronics	300
1004	Clothing	150
1005	Furniture	200
1006	Clothing	100

Dashboard Components

• KPI Card: Total Sales
  Formula: Total Sales = SUM(Sales[SalesAmount])
  Result: 1400
• Table Visual 1: Distinct Product Categories
  Formula: Distinct Categories = DISTINCT(Sales[ProductCategory])
  Shows unique categories: Electronics, Furniture, Clothing
• Table Visual 2: Product Categories with Total Sales
  Formula: Total Sales by Category = SUM(Sales[SalesAmount]) grouped by ProductCategory
  Results:
  - Electronics: 500
  - Furniture: 650
  - Clothing: 250
• Table Visual 3: VALUES function output
  Formula: VALUES(Sales[ProductCategory])
  Shows unique categories same as DISTINCT

Dashboard Layout

+----------------------+---------------------------+
|      Total Sales      |   Distinct Categories      |
|       (KPI Card)      |       (Table Visual 1)     |
+----------------------+---------------------------+
|       Sales by Category Table (Table Visual 2)       |
+-----------------------------------------------------+
|       VALUES Output Table (Table Visual 3)           |
+-----------------------------------------------------+

Interactivity

Applying a slicer filter on ProductCategory updates all tables and the KPI card to show data only for the selected categories. For example, selecting 'Electronics' filters the sales and recalculates totals accordingly.

Self Check

If you add a filter to show only Furniture category, which components update and what results do they show?

• Total Sales KPI: Updates to 650
• Distinct Categories Table: Shows only 'Furniture'
• Sales by Category Table: Shows 'Furniture' with 650 sales
• VALUES Output Table: Shows only 'Furniture'

Key Result

Dashboard showing unique product categories and their total sales using VALUES and DISTINCT functions.

Practice

1. What is the main difference between the DAX functions VALUES and DISTINCT?

easy

A. VALUES returns unique values including blanks, DISTINCT returns unique values excluding blanks.

B. VALUES returns unique values and blanks, DISTINCT returns unique values including blanks.

C. VALUES returns unique values excluding blanks, DISTINCT excludes blanks.

D. VALUES and DISTINCT are exactly the same in all cases.

Solution

1. Step 1: Understand VALUES behavior

   VALUES returns unique values from a column and includes blank values if they exist.

2. Step 2: Understand DISTINCT behavior

   DISTINCT returns unique values but excludes blank values from the result.

3. Final Answer:

   VALUES includes blanks, DISTINCT excludes blanks -> Option A

4. Quick Check:

   VALUES includes blanks, DISTINCT excludes blanks [OK]

Hint: Remember: VALUES keeps blanks, DISTINCT drops them [OK]

Common Mistakes:

• Thinking VALUES and DISTINCT always return the same results
• Assuming DISTINCT includes blanks
• Confusing the behavior of blank values in both functions

2. Which of the following is the correct syntax to get unique values from the column Product[Category] using DISTINCT?

easy

A. DISTINCT(Product[Category])

B. DISTINCT(Product.Category)

C. VALUES(Product[Category])

D. VALUES(Product.Category)

Solution

1. Step 1: Check correct column reference syntax

   In DAX, columns are referenced with table name and column name inside square brackets, like Product[Category].

2. Step 2: Check function syntax

   Both VALUES and DISTINCT take a column reference in parentheses. The correct syntax is DISTINCT(Product[Category]).

3. Final Answer:

   DISTINCT(Product[Category]) -> Option A

4. Quick Check:

   Correct syntax uses square brackets and function call [OK]

Hint: Use square brackets for columns inside functions [OK]

Common Mistakes:

• Using dot notation instead of square brackets
• Missing parentheses after function name
• Using incorrect column references

3. Given a table Sales with a column CustomerID containing values [1, 2, 2, 3, BLANK, 3], what will be the result of COUNTROWS(VALUES(Sales[CustomerID]))?

medium

A. 6

B. 3

C. 4

D. 5

Solution

1. Step 1: Identify unique values including blanks

   The unique values in CustomerID are 1, 2, 3, and BLANK. That is 4 unique values.

2. Step 2: Apply COUNTROWS on VALUES

   VALUES returns unique values including blanks, so COUNTROWS counts 4 rows.

3. Final Answer:

   4 -> Option C

4. Quick Check:

   Unique values including blank = 4 [OK]

Hint: VALUES includes blanks, so count them too [OK]

Common Mistakes:

• Ignoring blank values in count
• Counting duplicates multiple times
• Confusing DISTINCT behavior here

4. You wrote this DAX measure: UniqueProducts = DISTINCT(Product[ProductName]). When you use it in a card visual, it shows an error. What is the problem?

medium

A. The column name is incorrect; it should be ProductName[Product].

B. DISTINCT returns a table, but card visuals need a single value.

C. DISTINCT cannot be used in measures, only in calculated columns.

D. You need to wrap DISTINCT with SUM to get a number.

Solution

1. Step 1: Understand what DISTINCT returns

   DISTINCT returns a table of unique values, not a single number or scalar value.

2. Step 2: Understand card visual requirements

   Card visuals require a single scalar value, like a number or text, not a table.

3. Final Answer:

   DISTINCT returns a table, but card visuals need a single value. -> Option B

4. Quick Check:

   DISTINCT returns table, card needs scalar [OK]

Hint: DISTINCT returns tables; use aggregation for single values [OK]

Common Mistakes:

• Using DISTINCT directly in measures for visuals needing scalars
• Incorrect column references
• Thinking DISTINCT returns a number

5. You want to create a slicer that shows only unique non-blank customer names from the Customers[Name] column. Which DAX expression should you use to create a calculated table for this slicer?

hard

A. CustomerNames = FILTER(DISTINCT(Customers[Name]), NOT(ISBLANK(Customers[Name])))

B. CustomerNames = VALUES(Customers[Name])

C. CustomerNames = FILTER(VALUES(Customers[Name]), NOT(ISBLANK(Customers[Name])))

D. CustomerNames = DISTINCT(Customers[Name])

Solution

1. Step 1: Understand the need to exclude blanks

   Both VALUES and DISTINCT return unique values, but VALUES includes blanks while DISTINCT excludes them.

2. Step 2: Choose function and filter blanks

   DISTINCT returns unique values excluding blanks, which is perfect for a slicer.

3. Step 3: Compare options

   CustomerNames = DISTINCT(Customers[Name]) directly provides unique non-blank names without needing extra filtering.

4. Final Answer:

   CustomerNames = DISTINCT(Customers[Name]) -> Option D

5. Quick Check:

   DISTINCT excludes blanks for clean slicer [OK]

Hint: DISTINCT excludes blanks automatically [OK]

Common Mistakes:

• Using VALUES without filtering blanks
• Assuming DISTINCT includes blanks
• Using incorrect column references in FILTER conditions