Power BI Blog: Azure Map Data Bound Reference Layers

Welcome back to this week’s edition of the Power BI blog series.  This week, we look at how Azure Map has now brought a powerful enhancement to its data visualisation.

Until recently, the Azure Maps reference layer was limited to static shapes without the ability to conditionally format or bind geometries to customers’ business data.  Additionally, the static nature of the reference layers limited user interaction, preventing actions such as selecting, filtering, clicking or accessing ToolTips for polygons and points, unlike other visual components.

With the data bound reference layer, this limitation is now addressed by allowing integration between the reference layers and customer business data.  Reference layers may now be dynamically bound with the spatial fields used, allowing you to visualise your business data in context with geographic or spatial elements.  Users may now update their visuals in real time, interact with their data through Power BI’s standard features such as filtering, cross-highlighting and ToolTips, greatly enhancing the flexibility and interactivity of the Azure Map visual.

Making your reference layers data bound is easy to do.  Power BI will automatically map the shapes in your reference layer to values of the field in the ‘Location’ bucket in the Build pane based upon the name property you provide in your reference layer file.

This update also allows you to customise the colours of your shapes as well, using features like conditional formatting or through tying their colour to a legend colour.

Shapes that aren’t tied to a value in your model are considered unmapped.  You may format them to use custom colours or hide them completely from your map.  As cross-highlighting is a temporary filter on the map, the treatment you apply here is also what will happen to unselected shapes when cross-highlighting from another visual.

That’s it for this week.  In the meantime, please remember we offer training in Power BI which you can find out more about here.  If you wish to catch up on past articles, you can find all of our past Power BI blogs here.