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The Perfect Use Case for Decomposition Trees

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Decomposition trees or dendrograms are a powerful and easy-to-implement visualisation in Microsoft Power BI. It offers a way to break down your data into further categories within a limited dashboard space while maintaining interactivity by giving users the ability to choose what categories they’d like to view. As decomposition trees can break off into multiple branches, it becomes tempting to fit in as much data as possible. This can make composition trees complicated as it breaks off into multiple branches and can make it hard to visualise data. This blog takes you through the perfect use case for decomposition trees to maximise how effectively we use this visualisation in Power BI.

On day 3 of dashboard week, we were challenged to create a Power BI dashboard. While creating my dashboard, I came across the issue of creating dynamic slicers to show a different categories and subcategories within it. To solve this issue, I opted to use a decomposition tree to show the breakdown of the categories and sub-categories. A screenshot of my dashboard utilising the decomposition tree can be found here:

Decomposition trees are a great way to show a breakdown of sub-categories within categories and details within this such as a count of items for a sub-category. To add to another layer of interactivity to the dashboard, you can use the decomposition tree as a diagram to filter other charts. This allows you to maximise the limited space within the dashboard without sacrificing dashboard interactivity.

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