Geospatial Analysis: Making Complex Data Consumable
Everybody knows how to read a map (well, maybe not everyone, but you get what I mean!). Not everybody, however, enjoys sifting and sorting through complex information to draw conclusions. Geospatial analytics take location-specific data and presents it in familiar maps. It is effective because the human eye can pick up trends and patterns on a map much easier than on a spreadsheet. In other words, this is presenting information linked to maps and presenting it in a way that the average user can easily identify the message.
Examples of geospatial analysis
Geospatial analytics impacts our daily lives. When Google Maps gives you a shorter route to get to work one morning, you can thank geospatial analytics. When Netflix draws insights on its global users to create shows catering to local tastes, geospatial analytics play a part. Airlines use real-time data to track flight operations to make sure planes land on time and cost effectively. You can thank geospatial analytics for those fantastic airfares on your next holiday.
But it doesn’t have to be massive scale like these examples. It could be as simple as what product sell well by suburb. Or which workstations have the most errors or accidents in a production line.
Geo analysis – Not just big data
Billions of devices generate massive amounts of geospatial data every day. Using mapping for analysis can add a rich dimension of awareness for decision makers within a business. It has a wide range of applications from simple market segmentation to refine marketing plans to more complex analysis such as helping a telecom network prioritise equipment repairs based on customer density.
Why geospatial analytics?
There are a few reasons using mapping for analysis can give you a significant business edge:
- Make complex relationships understandable. When shifts in data are visualised on recognisable maps, they’re easier to understand, draw insights from, and make decisions.
- Illuminate past, present, and future. Geospatial analytics helps organisations see changes in location-based events. These could be in the past as well as the present, and can be used to anticipate and prepare for changes in the future.
- Get local. Visualising location-based analysis helps organisations understand why certain solutions that work in one place might not work in another.
Considering organisations already collect huge amounts of location-specific data that often goes under-utilised. Tools like IBM’s Cognos Analytics can help to transpose a wide range of information onto easy-to-interpret maps.
With location-based analysis evolving alongside the leaps and bounds made in machine learning and AI, companies who have yet to integrate some form of mapping for analysis may be missing out. Mapping for analysis is a powerful, simple approach to help unearth information that may not be obvious or expected.
The next couple of posts in this series will give you interesting applications of geospatial analysis. You’ll also get tips on how to integrate maps into your business analytics, so stay tuned by joining our spam-free email community!
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