3 Top Tips to Take your Power BI Dashboards to the Next Level

I’m pretty far along into my data analysis journey now, having already learned Excel & SQL. After those two were out of the way, I came up against Power BI which is one of the most important tools if learning data visualisation is the/your goal (which it currently is for me).

After learning how to use Power BI to clean and organize data, write some Data Analysis Expressions (DAX) code and create basic visualisations it was time to learn some more advanced techniques to take my dashboards to the next level. Along the way I picked up some techniques which I find valuable because they add a lot of depth to your dashboards without overcomplicating anything or sacrificing usability.

I’d recommend completing your dashboards before considering adding these features in, with these being extras rather than necessities most of the time, but that’s completely up to you. Before adding these in, save a copy of your dashboard without them just in case, as sometimes it gets messy and you just want to go back to how it was before!

Below are my top 3 Power BI techniques which I use to take my Power BI dashboards to the next level.

1. Parameters to enable live scenario analysis

If you want to make your dashboards more dynamic and allow users to analyse the effect of different inputs on specific outputs, then parameters are the answer. On the modelling tab, there are two types of parameters which are available in Power BI — field parameters and numeric range parameters — but I’m going to focus on the latter.

Click new parameter on the modelling tab and select “Numeric range”.

Numeric range parameters allow users to run their own scenario analysis in real time using a simple slicer, which is a great feature that can be useful in many different scenarios.

In the example below, I was analysing the average salaries of employees in Company A and wanted to see how significant the cost to the company would be if they increased salaries across the board by X%, or what the savings would be if they did the opposite.

To do this, I used a numeric range parameter to include a slicer, allowing me to see what happens to average salaries if they were increased/decreased in 10% intervals.

This chart shows the actual average salary of employees and what these would be if they were increased by 20%.

Although this is a basic example, the applications for this are endless and can add a significant amount of value to dashboard. Consider how useful this could be to C-Suite/senior management users when making crucial business decisions in limited time frames.

2. Slicer panels to add functionality without sacrificing simplicity

While a main goal of data dashboards is to visualise key information in a simple layout, it is quite easy for them to become cluttered and overcomplicated.

The usual instinct in these cases is to remove some aspects of the dashboard. Even though this is sometimes the right call, if all the info showing on the dashboard is adding value then you don’t want to sacrifice any of this purely to save space.

This is where the slicer panel comes into play. Using a combination of buttons, bookmarks and “hidden” slicers you can enable users to analyse the data in more depth while sacrificing nothing due to these space restrictions.

Understanding how to use bookmarks here is crucial, but they are super easy to learn so don’t stress if you’re still grappling with them! Essentially, a bookmark just remembers the state of the dashboard when it is created and will return the dashboard to that state when clicked.

For example, imagine you are analysing a dataset of the best 100 tennis players of all time and you filter to only show data for Roger, Rafa and Novak (the 🐐).

If you were to create a bookmark at this point, clear all filters and then filter to show only Venus & Serena Williams’ data, you could then click on the bookmark button and it would take you back to showing data for Roger, Rafa and Novak. This can be very useful if there is a specific subset of the data you want users to look at.

Bookmarks are the fundamental concept behind the slicer panel, with at least two bookmarks required to make this work.

For the first, you create a panel on one side of the screen and place your desired filters on top of that shape. Importantly, this panel can cover any parts of the dashboard as it will be hidden at a later stage. Call this bookmark “Panel Open” or something similar.

See here how the panel covers part of the dashboard — this is okay!

For the second bookmark, you hide the slicers and the panel in the “Selection” window, and then create the bookmark. Call this one something like “Panel Closed”.

The slicer has been closed here but the data has been filtered to show married employees, between 30 and 50 years old, in Boston & Dallas.

NB — For this to work properly you need to adjust the settings of both bookmarks so that they do not affect the data displayed. If you don’t do this, then the “Panel Closed” bookmark will erase the filters which users apply in the panel.

Right click on the Bookmark and unselect the Data option.

Once these steps have been followed, you add in a couple of buttons, assign the bookmarks to them, and voila! Your dashboard will have a lot more functionality than most other dashboards due to having ‘extra space’!

3. Custom tooltips to add another layer of depth to visualisations

Custom tooltips are another way to solve the issue discussed above, where your dashboards are getting too busy and overcomplicated.

Tooltips are a great way to add contextual information about specific data points in Power BI visualisations, but the default tooltips offered by Power BI are pretty basic and don’t really offer much information further than what the visualisation itself shows. (As seen in the below screenshot.)

This is a default tooltip provided by Power BI, which provides no additional information when compared to what the user can already see from the chart.

While this is slightly annoying from Power BI, it also means that you can really step up your dashboard game by customising what your tooltips show, which is really not difficult.

The first step is to create a new blank page within your workbook. From here, go to Format, “Page Information” and set the “Page Type” to “Tooltip”. This will make the page outlines much smaller — everything you see on this smaller page will show in your tooltip!

Now you can get creative. You can go all Inception on your users and include a chart within your original chart’s tooltip if you’d like. You can add text, values, different colours. Literally whatever you want to add, you can. (Be careful not to over crowd, of course!)

This is a custom tooltip, for the exact same chart as the default tooltip shown above. Look how much more detail is available to users!

A good point to remember here is that everything you include on the tooltip page will be filtered for the specific data point which the user is looking at at that time.

I hope these tips help you to elevate your Power BI dashboards to a new level!