Decomposition tree in Power BI - Step-by-Step Guide

Introduction

A decomposition tree helps you explore data by breaking it down into smaller parts. It shows how different categories contribute to a total, making it easier to find patterns or causes in your data.

When you want to see which product categories contribute most to total sales.

When you need to analyze customer complaints by region and then by issue type.

When your manager asks why revenue dropped in a specific quarter.

When you want to explore employee performance by department and then by individual.

When you want to understand which marketing channels drive the most website visits.

Steps

Step 1: Click

- Visualizations pane

The list of available visuals expands

💡 Look for the icon that looks like a branching tree

Step 2: Select

- Decomposition tree visual

A blank decomposition tree visual appears on the report canvas

Step 3: Drag

- Measure or numeric field from Fields pane to 'Analyze' well in the visual

The total value appears at the top of the tree

Step 4: Drag

- Category fields from Fields pane to 'Explain by' well in the visual

These categories become options to break down the total value

Step 5: Click

- Plus (+) icon next to the total or any branch in the decomposition tree

The tree expands showing the breakdown by one of the category fields

Step 6: Select

- Different category from the list that appears after clicking plus (+)

The tree updates to show the breakdown by the selected category

Step 7: Use

- Search box in the decomposition tree

You can quickly find a specific category to expand

Before vs After

Before

The report shows a single total sales number: 100,000

After

The decomposition tree shows total sales 100,000 broken down by Region, then by Product Category, with each branch showing sales amounts

Settings Reference

Explain by fields

📍 Visualizations pane under 'Explain by'

These fields define how the total value is broken down in the tree

Default: None

Analyze field

📍 Visualizations pane under 'Analyze'

This is the main value that the tree breaks down

Default: None

Expand mode

📍 Format pane under 'Expand controls'

Controls if the tree expands only when you click or automatically

Default: Manual

Data labels

📍 Format pane under 'Data labels'

Shows or hides the numeric values on the tree branches

Default: On

Common Mistakes

Not adding any 'Explain by' fields

Without categories to break down by, the tree cannot expand and explore data

Add one or more categorical fields to the 'Explain by' well to enable breakdown

Using a non-numeric field in the 'Analyze' well

The tree needs a number to show totals and breakdowns

Use a numeric measure or field like sales amount or count

Expecting the tree to expand automatically without clicking

By default, expansion is manual to avoid clutter

Click the plus (+) icons to expand branches or change expand mode in settings

Summary

The decomposition tree helps break down a total value into parts using categories.

You add a numeric field to analyze and one or more categories to explain by.

Remember to click plus (+) icons to explore deeper levels unless automatic expand is enabled.

Practice

1. What is the main purpose of a Decomposition tree visual in Power BI?

easy

A. To combine multiple unrelated datasets

B. To create a static summary table of data

C. To display data as a simple bar chart

D. To break down a measure into parts for detailed analysis

Solution

1. Step 1: Understand the function of a decomposition tree

   A decomposition tree helps explore a measure by breaking it down into smaller parts or categories.

2. Step 2: Compare options with this function

   Only To break down a measure into parts for detailed analysis describes breaking down a measure for detailed analysis, which matches the decomposition tree's purpose.

3. Final Answer:

   To break down a measure into parts for detailed analysis -> Option D

4. Quick Check:

   Decomposition tree = Break down measure [OK]

Hint: Think: decomposition means breaking down [OK]

Common Mistakes:

• Confusing decomposition tree with simple charts
• Thinking it creates static tables
• Assuming it merges unrelated data

2. Which of the following is the correct way to add a category to a Decomposition tree visual in Power BI?

easy

A. Drag a field to the 'Explain by' bucket

B. Drag a field to the 'Analyze' bucket

C. Drag a field to the 'Values' bucket

D. Drag a field to the 'Filters' pane

Solution

1. Step 1: Recall Decomposition tree buckets

   The 'Explain by' bucket is where you add categories to break down the measure in the decomposition tree.

2. Step 2: Match options to buckets

   Only Drag a field to the 'Explain by' bucket correctly identifies 'Explain by' as the place to add categories for decomposition.

3. Final Answer:

   Drag a field to the 'Explain by' bucket -> Option A

4. Quick Check:

   'Explain by' = categories in decomposition tree [OK]

Hint: Categories go in 'Explain by' bucket [OK]

Common Mistakes:

• Putting categories in 'Analyze' or 'Values' buckets
• Confusing 'Filters' pane with category placement
• Not knowing bucket names

3. Given a Decomposition tree analyzing total sales by Region and Product Category, what happens when you click on a Region node?

medium

A. It shows a tooltip with total sales for all Regions

B. It filters the entire report to only that Region

C. It drills down to show sales breakdown by Product Category within that Region

D. It resets the tree to show all Regions again

Solution

1. Step 1: Understand interaction in decomposition tree

   Clicking a node drills down to the next category level within that node's context.

2. Step 2: Apply to Region and Product Category

   Clicking a Region shows sales broken down by Product Category inside that Region.

3. Final Answer:

   It drills down to show sales breakdown by Product Category within that Region -> Option C

4. Quick Check:

   Click node = drill down next category [OK]

Hint: Click node to drill down next level [OK]

Common Mistakes:

• Thinking it filters whole report
• Assuming it resets the tree
• Confusing tooltip with drill down

4. You added a Decomposition tree visual but it shows no breakdown when clicking nodes. What is the most likely cause?

medium

A. No categories were added to the 'Explain by' field well

B. The measure used is not numeric

C. The visual is not connected to any data source

D. The report page is filtered to zero rows

Solution

1. Step 1: Check category setup in decomposition tree

   If no categories are in 'Explain by', the tree cannot break down the measure further.

2. Step 2: Evaluate other options

   While measure type and filters matter, the main reason for no breakdown is missing categories.

3. Final Answer:

   No categories were added to the 'Explain by' field well -> Option A

4. Quick Check:

   Missing 'Explain by' categories = no breakdown [OK]

Hint: Always add categories to 'Explain by' [OK]

Common Mistakes:

• Ignoring missing categories
• Blaming measure type first
• Not checking filters

5. You want to analyze sales by Region, then by Product Category, but only for the top 3 Regions by sales. How can you set this up using a Decomposition tree?

hard

A. Add Product Category to 'Explain by' and Region to 'Values' with a slicer for top 3

B. Add Region and Product Category to 'Explain by' and apply a Top N filter on Region by sales

C. Add Region to 'Analyze' and Product Category to 'Explain by' without filters

D. Add Region and Product Category to 'Explain by' and use a measure that sums only top 3 Regions

Solution

1. Step 1: Set categories in 'Explain by'

   Both Region and Product Category should be in 'Explain by' to allow drilling down.

2. Step 2: Apply Top N filter on Region by sales

   Use a Top N filter on Region to limit to top 3 Regions by sales before drilling down.

3. Final Answer:

   Add Region and Product Category to 'Explain by' and apply a Top N filter on Region by sales -> Option B

4. Quick Check:

   Top N filter + categories in 'Explain by' = correct setup [OK]

Hint: Use Top N filter on first category in 'Explain by' [OK]

Common Mistakes:

• Putting categories in wrong buckets
• Not applying Top N filter correctly
• Using measures instead of filters for top N