Data Catalyst - EnergyWe’ve got a lot of projects on the go here at Data Catalyst, but once in a while, we also take some time to play with and explore tools and techniques that might help inform our future work.

Recently, colleagues in the cleantech cluster at MaRS were trying to understand where their clients are located, specifically looking at the concentration of cleantech clients in Ontario and Quebec. This kind of information is useful not only in their decision-making, but also in telling the story about the cleantech cluster and the work it does.

We saw this as an opportunity to test out some of the new tools and techniques we’ve been exploring over the past few months.

To help create these visualizations, we turned to Tableau because it has built-in geocoding. Tableau automatically recognized the first three digits of clients’ postal codes (known as the Forward Sortation Area or FSA) and placed the clients on a map based on the location of their postal codes. This was a much faster and simpler solution than getting an exact latitude and longitude from the street address, and it also gave a sense of hot spots where a number of firms were clustered in a single location.

The preliminary maps below show MaRS clients from Kingston to Montreal. Clearly, quite a few clients are in the Ottawa area.

Data Catalyst - Behind The Scenes - Mapping Cleantech Clients - Visualizing Clients by Geography

We also wanted to take this work a little further, so we decided to explore client density. By increasing the size of the dots where there is a higher density of firms, we noticed that the K2K FSA in Kanata, ON, has an especially high density of cleantech clients.

Data Catalyst - Behind The Scenes - Mapping Cleantech Clients - Visualizing Clients by Density

How does this compare to the larger MaRS portfolio in the same geographic area? We added all MaRS clients to the map and colour-coded them to identify their sectors.

Data Catalyst - Behind The Scenes - Mapping Cleantech Clients - Visualizing Clients by Type
These kinds of visualizations give us a good way to explore our impact and reach, and they help MaRS advisors make better decisions about where and how to target their services. We’re convinced that this kind of data can help all kinds of organizations working in the innovation support ecosystem.

Dr. Adam Jacobs

Adam is an analyst, statistician and data designer for the innovation economy team at Data Catalyst. He is interested in new data visualization tools and open source tools for research. Adam joined MaRS in 2013 after working in data development at a geographic information systems (GIS) software company in Toronto. See more…