The Decomposition Tree visual in Power BI helps users analyze a measure by breaking it down into multiple dimensions and hierarchies. It includes built-in AI capabilities that automatically identify the highest and lowest contributors, making it easier to explore data and discover insights interactively.
In the below blog post will guide through the process of creating Decomposition Tree in Power BI.
How to Proceed?
Step 1
Launch power BI desktop app and open the new report page and import the data required.
Step 2
In “visualizations” pane click on “Decomposition Tree” which is highlighted in the given figure.
Step 3
Drag the data fields into “Build visual pane“ that we want to and analyze.
Analyze: The measure or KPI to analyze (Count of Medal).
Explain by: One or more dimensions used to break down the measure (Region, Gender).
Tooltips: Add additional fields to display more information when hovering over the visual.
Step 4 Features of Decomposition Tree
Each time you expand a node, Power BI allows you to choose one of the following:
High value – Displays the category with the highest contribution.
Low value – Displays the category with the lowest contribution.
AI split – Automatically selects the next best category based on AI analysis.
Any field added under Explain by.
AI Splits is the feature of decomposition Tree which has the ability to find out the highest and lowest value of our data.
When we hover on the bulb icon it also displays an explanation as a tooltip.
To make use of this AI features we should Enable AI splits on under Format visual pane.
The selected branch expands to display the chosen category, while AI splits automatically identify the most significant contributors based on the data.
Step 5
Filters in the chart are like special tools that allow us to focus on specific parts of the data, making it easier to understand. In this visual we Excluded the “No Medal” count.
Step 6
Customizing the appearance of Decomposition Tree
You can customize the appearance of the visual.
Gave suitable title for the visual and customize the font size, colour and position of the title.
We can customize the space related settings for the tree nodes under Tree settings.
Here in the Tree, the bars representing the categorical data. We can adjust the nodes bar by using this bar settings
Likewise, we can customize the colors of the bar represented in the tree, their background etc.
We have an option “Conditional Formatting” where can customize the data bar color
Click on the More options (...) on the header icon of the visual to export the data or to sort the data based on the requirements
Report creator can lock the particular levels where it can’t be removed or changed. Hence users can explore different level of hierarchies but they can’t change or move the levels
Step 7 Save the visual
Finally, your Decomposition Tree visual is ready. Click Save to save the report.
When to use Decomposition Tree?
Decomposition tree can be used when we need to analyze the metrics which can be broken down into multiple categories also, we can use this when we need to understand the KPI’s.
Pros
- Interactive and easy to explore.
- AI-assisted analysis helps identify key contributors.
- Supports hierarchical drill-down.
- Useful for root cause analysis.
- Makes complex data easier to understand.
Cons
- Best suited for hierarchical analysis.
- Large numbers of levels can make the visual difficult to read.
- AI insights depend on the quality of the underlying data.
Conclusion
The Decomposition Tree visual is a powerful analytical tool for exploring hierarchical data and identifying the factors that contribute to a measure. Its built-in AI capabilities make it easier to perform root cause analysis and uncover insights with minimal effort.
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