The Power of Geospatial Data Visualisation: Maps, Heatmaps, and More in Power BI
When your data has a “where” component, maps become essential. Whether you're trying to understand sales by region, customer distribution, or service coverage across suburbs, geospatial data visualisation helps you see the story your data is telling—clearly and quickly.
Power BI makes it easier than ever to transform raw location data into interactive, easy-to-read visuals. From simple pin maps to rich heatmaps and dynamic layers, Power BI offers several ways to explore geographic insights without diving into a GIS platform.
In this article, we’ll walk through the key mapping features in Power BI, explore use cases relevant to Australian organisations, and share tips to help you get the most out of your spatial data.
Why Geospatial Visualisation Matters
Location data is more than just coordinates—it provides context. When mapped effectively, it helps reveal trends, gaps, and opportunities that might otherwise go unnoticed in a spreadsheet.
Here are a few real-world examples:
A retail chain can analyse sales by store location and overlay that with demographic data to optimise where to open new outlets.
A local council might visualise service requests or maintenance jobs by suburb to better allocate their resources.
A logistics provider could identify areas with frequent delays and use that insight to reroute deliveries or improve fleet efficiency.
In short, spatial visualisation bridges the gap between data and decisions, especially when communicating with non-technical stakeholders.
Power BI Mapping Tools: An Overview
Power BI offers a range of native and custom visuals to handle geographic data. Here’s a look at the most used options:
🗺️ Map Visual
This is the most basic map type and is ideal for plotting data points using suburb, postcode, or latitude/longitude. It’s a great way to spot the spread and density of activity—like customer visits, deliveries, or support requests.
🌍 Filled Map
Filled maps shade areas based on a metric, like sales volume or incident count. They're perfect for highlighting performance across regions—think state-wide comparisons or local government area (LGA) breakdowns.
🧭 Azure Maps Visual
This more advanced option includes features like heatmaps, multiple layers, and dynamic filtering. Azure Maps supports real-time updates and custom layering, making it ideal for use cases like traffic monitoring, sensor networks, or combining public datasets with internal data.
🧩 Shape Maps
Shape Maps allow you to use custom geo-boundaries through TopoJSON files. This is particularly useful where standard maps can’t cater to more bespoke detail, like electoral boundaries and sales territories. For instance, a utilities provider might want to show network zones based on infrastructure coverage rather than political boundaries.
Use Case: Regional Australia Institute’s Good Life Guide
A standout example of spatial data in Power BI comes from one of White Box’s recent projects – Region Australia Institute’s Good Life Guide. This interactive report lets users explore how hundreds of communities across Australia perform across multiple lifestyle indicators.
What It Does:
Maps performance across key themes, such as jobs, housing, and environment.
Uses filled maps and slicers to filter data by region, state, and specific indicators.
Provides a clean, accessible interface for policymakers, researchers, developers, community leaders and the general public to compare and understand regional strengths and challenges.
Why It Works:
The use of geospatial visuals makes it easy to see which areas score highly across different indicators.
The interactivity encourages exploration, allowing users to tailor the data view to their interest or region.
It combines Power BI’s filled maps with clearly labelled filters and descriptive text—making complex data approachable.
For any organisation, this is a textbook example of how location-based insights can drive meaningful action.
Tips for Better Mapping in Power BI
To get the best results from your mapping visuals in Power BI, keep these tips in mind:
✅ Clean and standardise your location data
Inconsistent suburb or postcode naming can confuse Power BI’s geocoding engine, especially with overlapping names across Australia (e.g., multiple Springfields). Consider using consistent naming conventions or adding latitude/longitude fields.
✅ Don’t overcomplicate your visuals
While it’s tempting to layer lots of data on one map, clarity is key. Aim to highlight one or two core insights per visual and use slicers or tooltips for additional detail.
✅ Test across devices
Maps can behave differently on tablets and mobiles. If your dashboard is used on the go—by field staff, for example—check that visuals remain readable on smaller screens.
✅ Use external datasets to enrich your maps
Bring in data from sources like the ABS, Geoscape, or open government APIs. For example:
Overlay ABS population data to assess market opportunity in different suburbs.
Combine property data with sales to identify growth hotspots.
Use public transport coverage data to assess accessibility for site planning.
Unlocking the Value of Place-Based Data
Geospatial visualisation in Power BI isn’t just about making dashboards look good—it’s about making location data meaningful and actionable.
Whether you’re in healthcare, logistics, government, or retail, mapping tools help you uncover patterns, communicate clearly, and drive more informed decisions.
The best part? You don’t need to be a GIS expert to start. With Power BI’s intuitive interface and growing support for spatial analysis, you can start mapping in minutes.
We work with organisations to design dashboards that put spatial data to work. From custom map visuals to integrating third-party datasets and shaping location-aware strategies, our Sydney-based team can help you unlock your data’s full potential.
Let’s talk about how we can put maps to work in your next Power BI project.