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Geospatial Analysis is immensely valuable as maps are something that we all have grown up seeing around the place. It gives an instant frame of reference to data that is overlayed geographically.

It is said that a picture can tell a thousand words and ultimately too much of what we do in the Business Intelligence World is just that – say thousands of words with our pretty charts and pictures. No matter how much we want it to come across differently – that is the unfortunate reality.   

The challenge facing so many businesses is to tell a story with their data, or rather have the data make sense in a defined context. These “stories” are so much easier when a shared context is made available, something that often just is not there within raw charts. Maps have a shared context – after all you know where you are, and you can no doubt (at least) find the nearest city to you on a map. So, to know that “Hey! 27% of our sales came from that same city” has context to you, you can apply a raft of contextual information to that, from the “Hm, that’s an affluent city…” to “Wow, those godless heathens bought that much?”  We can clearly see that we are applying a shared context to the data. That is why Geospatial analysis is so powerful. 

Looking at Average Taxi Fares we are automatically overlaying context to the data… “Of course, Manhattan fares are lower, there are more journeys, and they probably mostly go around Manhattan, while Staten Island fares will no doubt be less frequent and go into another borough across a bridge.” This is a clear example of why maps are so vital. However average fares are a great reason to use Shape Maps, as specific point maps can make “Average Fare” difficult. Plotting the data points and using a Heat Map works for “Count of Journeys”, but a heat map that averages fares is more challenging. I’m sure we can all agree that the map on the right is easier to understand than the map on the left, even if a heat map could apply colour correctly! 

 Another takeaway from this is that Shape Maps– for all they have less detail due to being line outlines– pack an awful lot more detail in. However, you must know the location they are covering – New York in our case.  So, Shape Maps bring a lot to the table if the audience can bring the shared context.  

A strategy we recommend is to use a combination of Shape Maps for high level data and regular maps for lower–level detail. This means that you have must be aware of the level that your data is at, as all low-level reports require you to have Latitude and Longitude. If that is not present you will struggle to complete the objective. Shape Maps have a similar challenge if the granularity gets too high, as each “shape” within the map, must be rendered and the value that it will receive must be calculated before the shape colour can be defined, so 10 shapes will be far quicker than 1000. The New York Taxi dataset has around 300 Zones and is approaching the maximum number of shapes you should realistically use for a shape map.  

This brings us to performance. “Maps” have two ways of working, lookup or direct placement, direct placement is the mechanism used by Shape Maps and the majority of other visuals in Power BI. A context is know for example Colour = “Blue” and the cross tab query is executed within DAX to determine Total Sales – £5,000,000. A direct result of “placement” being part of the visual means these are as quick as they can be, determined by the number of “placements” required. Lookup on the other hand means that while the same start point of Zone = “Union Sq” then cross tab to total passengers = 9,368,080, the visual also has to trigger a lookup against either Bing or Azure Maps (depending on visual used). Those lookups are always relatively slow although results can be cached to speed up subsequent runs (within the caching window). The result is that while you would not see a huge difference in performance across the ~300 items in the Taxi dataset if a lookup was attempted for the Food Hygiene data that would be prohibitively slow, so when details are wanted it is always better to make them direct by using Latitude and Longitude. This whole “Should I use Shapes or common locations to populate my maps or Latitude and Longitude” means that geography is almost as important as Dates from an reporting perspective and is something that must always be considered and revisited over time to ensure success not just now but always. 

Geordie Consulting, a dedicated consultancy, has partnered with numerous companies to tackle this challenge. We are committed to sharing our expertise and experience with clients by supporting your Centre of Excellence. Our consultants and their knowledge will be available to foster the growth and development of this function within your organisation. Our team will oversee your Power Platform estate, ensuring consistent refresh cycles. Additionally, we will mentor your team or facilitate knowledge-sharing events to promote a new Data Culture within your business. As a Microsoft Partner, we ensure our team stays current with platform updates. We can simplify the upskilling process for your internal team by guiding and supporting their learning and demonstrating solutions implemented during your engagement. To optimise your return on investment, consider enrolling your organisation in our Centre of Excellence as a Service offering.