What type of online dashboard will work best for your data? This post reviews eight types of online dashboards to assist you in choosing the right approach for your next dashboard. Note that there may well be more than eight types of dashboards, I am sure I will miss a few. If so, please tell me in the comments section of this post.
KPI Online Dashboards
The classic dashboards are designed to report key performance indicators (KPIs). Think of the dashboard of a car or the cockpit of an airplane. The KPI dashboard is all about dials and numbers. Typically, these dashboards are live and show the latest numbers. In a business context, they typically show trend data as well.
A very simple example of a KPI Dashboard is below. Such dashboards can, of course, be huge. Huge dashboards have lots of pages crammed with numbers and charts, looking at all manner of operational and strategic data.
Geographic Online Dashboards
The most attractive dashboards are often geographic. The example below was created by Iaroslava Mizai in Tableau. Due to people being inspired by such dashboards, I imagine that a lot of money has been spent on Tableau licenses.
While visually attractive, such dashboards tend to make up a tiny proportion of the dashboards in widespread use. Outside of sales, geography, and demography, few people spend much time exploring geographic data.
Catalog Online Dashboards
A catalog online dashboard is based around a menu. The viewer can select the results they are interested in from that menu. It is a much more general dashboard used for displaying data rather than geography. Here, you can also use any variable to cut the data. For example, the Catalog Dashboard below gives the viewer a choice of country to investigate.
The dashboard below has the same basic idea, except the user navigates by clicking the control box on the right-side of the heading. In this example of a brand health dashboard, the control box is currently set to IGA (but you could click on it to change it to another supermarket).
The PowerPoint Alternative Dashboard
A story dashboard consists of a series of pages specifically ordered for the reader. This type of online dashboard is used as a powerful alternative to PowerPoint, with the additional benefits of being interactive, updatable and live. Typically, a user either navigates through such a dashboard using navigation buttons (i.e., forward and backward). Alternatively, they use the navigation bar on the left, as shown in the online dashboard example below.
Drill-Down Online Dashboards
A drill-down is an online dashboard (or dashboard control) where the viewer can "drill" into the data to get more information. The whole dashboard is organized in in hierarchical fashion.
There are five common ways of facilitating drill-downs in dashboards: zoom, graphical filtering, control-based, filtering, and landing pages. The choice of which to use is partly technological and partly related to the structure of the data.
1. Zoom
Zooming is perhaps the most widely used technique for permitting users to drill-down. The user can typically achieve the zoom via mouse, touch, + buttons, and draggers. For example, the earlier Microsoft KPI dashboard permitted the viewer to change the time series window by dragging on the bottom of each chart.
While zooming is the most aesthetically pleasing way of drilling into data, it is also the least general. This approach to dashboarding only works when there is a strong and obvious ordering of the data. This is typically only the case with geographic and time series data, although sometimes data is forced into a hierarchy to make zooming possible. This is the case in the Zooming example below, which shows survival rates for the Titanic (double-click on it to zoom).
Unless writing everything from scratch, the ability to add zoom to a dashboard will depend on the components being used (i.e. whether the components support zoom).
2. Graphical filtering
Graphical filtering allows the user to explore data by clicking on graphical elements of the dashboard. For example, in this QLik dashboard, I clicked on the Ontario pie slice (on the right of the screen) and all the other elements on the page automatically updated to show data relating to Ontario.
Graphical filtering is cool. However, it both requires highly structured data and quite a bit of time figuring out how to design and implement the user interface. They are also the most challenging to build. The most amazing examples tend to be bespoke websites created by data journalists (e.g., http://www.poppyfield.org/). The most straightforward way of creating such dashboards with graphical filtering tends to be using business intelligence tools, like Qlik and Tableau. Typically, there is a lot of effort required to structure the data up front. You then get the graphical filtering "for free". If you are more the DIY-type, wanting to build your own dashboards and pay nothing, RStudio's Shiny is probably the most straightforward option.
3. Control-based drill-downs
A quicker and easier way of implementing drill-downs is to give the user controls that they can use to select data. From a user interface perspective, the appearance is essentially the same as with the Supermarket Brand Health dashboard (example a few dashboards above). Here, a user chooses from the available options (or uses sliders, radio buttons, etc.).
4. Filtered drill-downs
When drilling-down involves restricting the data to a subset of the observations (e.g., to a subset of respondents in a survey), users can zoom in using filtering tools. For example, you can filter the Supermarket Brand Health dashboard by various demographic groups. While using filters to zoom is the least sexy of the ways of permitting users to drill into data, it is usually the most straightforward to implement. Furthermore, it is also a lot more general than any of the other styles of drill-downs considered so far. For example, the picture below illustrates drilling into the data of women aged 35 or more (using the Filters drop-down menu on the top right corner).
5. Hyperlink drill-downs
The most general approach for creating drill-downs is to link together multiple pages with hyperlinks. While all of the other approaches involve some aspect of filtering. On the other hand, hyperlinks enable the user to drill into qualitatively different data. Typically, there is a landing page that contains a summary of key data. So the user clicks on the data of interest to drill down and get more information. In the example of a hyperlinked dashboard below, the landing page shows the performance of different departments in a supermarket. The viewer clicks on the result for a department (e.g.: CHECK OUT) which takes them to a screen showing more detailed results.
Interactive Infographic Dashboard
Infographic dashboards present viewers with a series of closely related charts, text, and images. Here is an example of an interactive infographic on Gamers, where the user can change the country at the top and the dashboard automatically updates.
Visual Confections Dashboard
A visual confection is an online dashboard that layers multiple visual elements. On the other hand, a series of related visualizations is an infographic. The dashboard below overlays time series information, with exercise and diet information.
Simulator Dashboards
The final type of dashboard that I can think of is a simulator. The simulator dashboard example below is from a latent class logit choice model of the egg market. The user can select different properties for each of the competitors and the dashboard predicts market share.
Create your own Online Dashboards
I have mentioned a few specific apps for creating online dashboards, including Tableau, QLik, and Shiny. All the other online dashboards in this post used R from within Displayr (you can even just use Displayr to see the underlying R code for each online dashboard). To explore or replicate the Displayr dashboards, just follow the links below for Edit mode for each respective dashboard, and then click on each of the visual elements.
Microsoft KPI
Overview: A one-page dashboard showing stock price and Google Trends data for Microsoft.
Interesting features: Automatically updated every 24 hours, pulling in data from Yahoo Finance and Google Trends.
Edit mode: Click here to see the underlying document.
View mode: Click here to see the dashboard.
Europe and Immigration
Overview: Attitudes of Europeans to Immigration
Interesting features: Based on 213,308 survey responses collected over 13 years. Custom navigation via images and hyperlinks.
Edit mode: Click here to see the underlying document.
View mode: Click here to see the online dashboard.
Supermarket Brand Health
Overview: Usage and attitudes towards supermarkets
Interesting features: Uses a control (combo box) to update the calculations for the chosen supermarket brand.
Edit mode: Click here to see the underlying document.
View mode: Click here to see the online dashboard.
Supermarket Department NPS
Overview: Performance by department of supermarkets.
Interesting features: Color-coding of circles based on underlying data (they change when the data is filtered using the Filters menu in the top right). Custom navigation, whereby the user clicks on the circle for a department and gets more information about that department.
Edit mode: Click here to see the underlying document.
View mode: Click here to see the dashboard.
Blood Glucose Confection
Overview: Blood glucose measurements and food diary.
Interesting features: The fully automated underlying charts that integrate data from a wearable blood glucose implant and a food diary. See Layered Data Visualizations Using R, Plotly, and Displayr for more about this dashboard.
Edit mode: Click here to see the underlying document.
View mode: Click here to see the online dashboards.
Interactive infographic
Overview: An infographic that updates based on the viewer's selection of country.
Interesting features: Based on an infographic created in Canva. The data is pasted in from a spreadsheet (i.e., no hookup to a database).
Edit mode: Click here to see the dashboard.
View mode: Click here to see the underlying document.
Presidential MaxDiff
Overview: A story-style dashboard showing an analysis of what Americans desire in their Commander-in-Chief.
Interesting features: A revised data file can be used to automatically update the visualizations, text, and the underlying analysis (a MaxDiff model)(i.e., it is an automated report).
Edit mode: Click here to see the underlying document.
View mode: Click here to see the dashboard.
Or...
Create your own MaxDiff DesignChoice Simulator
Overview: A decision-support system
Interesting features: The simulator is hooked up directly to an underlying latent class model. See How to Create an Online Choice Simulator for more about this dashboard.
Edit mode: Click here to see the dashboard.
View mode: Click here to see the underlying document.