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The May 2020 update is a good one! The decomposition tree is a seriously good new visual, drop shadows are a nice idea well-implemented, and there are lots of improvements to the way buttons look and work.
- New features introduced in the May 2020 Power BI Update
- Visuals can now have drop shadows
- Buttons can have fill images
- The new Decomposition Tree visual (this blog)
- Improvements to page navigation buttons
- The drill-through action is out of preview, and enhanced
Posted by Andy Brown on 24 May 2020
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The new Decomposition Tree visual
This has been in preview for yonks, but now sees the cold hard light of day:
A warm welcome, please, for the new Decomposition Tree visual.
This is one of the more complex visuals, and as a consequence this is going to be a longer than usual blog page!
"Decomposition" is not only a long word to type in, but also makes me think of decay. I'll therefore refer to the visual as the DT visual (although that acronym also has some negative connotations - you can't have everything).
An outline of what the DT visual does
Suppose you're looking at a value - here it's the total quantity of goods sold in our portfolio of Construct-a-Creature stores:
You can choose to break down your chosen statistic or measure by any of the dimensions you've attached to the visual, in any order.
Note that you may well see two additional options with light bulbs next to them, saying High value and Low value - I'll explain these AI options further down this page.
Here I've chosen to break sales down firstly by region, then by the environment in which each animal lives and finally by the type of retail centre:
Viewing by region, environment and centre type.
I've also locked the first two dimensions, to stop anyone making changes to them (hence the padlocks next to their titles).
Creating a DT visual
The field well for the DT visual is deceptively simple:
You can choose to analyse any single statistic (here I've gone for the quantity of goods sold) by one or more dimensions.
Note that it doesn't really matter in which order you put the explanation fields, as you can choose in which order to apply them within the DT visual. The above choices would give you this visual initially:
I've changed the default formatting, but otherwise this is pretty much what you'll see initially.
Hover over the tiny + symbol and you'll see this:
You can choose how to explain this single figure.
Here I've chosen to expand firstly by region:
I can remove any level by clicking on the cross shown, or click on any + symbol to choose another explanation field.
I can keep expanding levels to get to the visual shown at the top of this page (although initially the formatting will be simpler).
That's pretty much it with a Decomposition Tree visual, but there are many additional options to control how it displays and how it works. Read on!
Formatting your title
The top of my visual looks like this:
My visual is showing the titles and subtitles for each level.
Here are the relevant formatting settings:
You can give different colours to your titles and subtitles (and also hide your subtitles, if you don't want to show the currently selected item at each level).
Formatting your tree
There are a host of options for this:
The Density can be Dense, Default or (as here) Sparse. As you might imagine, the Sparse setting requires most space on screen.
Instead of using the default connector shape, you could choose Round instead (the only other option):
Spot the difference? There isn't much.
Changing the default action to collapse
When you click on a node of the tree, what should happen? One option would be to tell Power BI to collapse the node instead of just selecting it:
If you choose this option, when you click on a node it will collapse or expand.
So clicking here will collapse the Air environment node:
Click to hide/display the centre type dimension breakdown.
Formatting the data bars
You can set what colours Power BI uses to display the data bars:
These are the settings I've used. I've made my bars a bit wider than they would be normally - 123% of normal, in fact - and set them to scale to the parent node.
Here are the 3 scaling options:
The options are explained below.
To illustrate how these work, consider the Water environment node below:
The percentage of the Water node which is coloured pink is 1331/12731 (that is, the proportion of the total figure for the parent node).
Here are the 3 options:
|Option||What it would show|
|Top node||1331 / 74415 (ie the proportion of the overall total figure)|
|Parent node||1331 / 12731 (the proportion of the parent node, North West)|
|Level maximum||1331 / 10384 (since 10384 is the sales for Land, the highest figure at this level)|
Conditional formatting data bar colours
You can even tell Power BI to colour data bars proportional to the number they show (or to some other measure):
Turn conditional formatting on for the data bar colours, then click on the link shown.
This is what you'd see if you set the colour scale to go from a minimum of 0 to a maximum of 20,000 for our example, and didn't choose the colours wisely:
The bigger the number, the darker the bar.
Sometimes you'll want to freeze the top levels, but let people play about with ones further down the tree. Here's how to do this:
Hover over the title of a level and the padlock symbol will appear. Click on this to lock the level.
You can't remove a locked level without first unlocking it:
The Region level is locked, so we can't remove it.
Standard features supported by DT visuals
A decomposition tree visual supports sorting:
You can sort by any level.
It also supports drill-through, if you've set it up:
If you've set up drill-through, this will work when you right-click on a DT visual node.
As if all of the above weren't enough, you can choose to apply Artificial Intelligence (well, ish) when choosing how to break down a node. This is a feature that you can turn on or off:
I've turned the feature to Enable AI splits back on.
When you click to expand a node, you can choose one of the options with a light bulb next to it:
The extra two options you'll see for AI splits.
Here I've chosen Low value, so Power BI has automatically selected the environment or centre type with the lowest sales:
Power BI decides which dimension to show next based on your choice, and selects the node within it.
Using absolute or relative analysis
Suppose that I expand this:
I want to show the breakdown of sales for the Shopping Centre centre type, and choose Low value.
Here's what this would normally give:
Out of all of the environment and region dimension values, the one which gives the lowest sales is East Anglia, at 2,135 - so that's what Power BI selects.
However, you could make a case that this isn't actually that low a value. There are lots of regions, and the sales for East Anglia aren't actually that much lower than those for the next lowest region by sales (East Midlands, at 3,745). Let's change the Analysis type to Relative:
I've changed the analysis type from absolute to relative.
If I now choose to show the lowest value for the Shopping Centre node, I see this:
The sales for the Air environment (at 4411) are higher than those for the East Anglia region (at 2135), so shouldn't really appear. However, the Air environment's sales of 4411 as a proportion of average environment sales at this level (60576/3) is lower than the proportion of East Anglia sales 2135) to average region sales at this level (60576/9).
If all this is blowing your mind a bit, just leave the analysis type as Absolute (or even turn AI levels off completely).
I've been waiting to blog on the Decomposition Tree visual until it emerged from preview. I'm really impressed with it - what do you think?