These are well known, for instance 36°51’50”S, 174°45’43’E defines the iStart office in Grafton Auckland as a specific point on the Earth’s round surface.

However, the Earth is not round.

It is an oblate spheroid. Using a sextant and chronometer might have been good enough for Cook to map the South Pacific 225 years ago. But, with today’s modern + 2cm accuracies, derived from GPS (global positioning system), the old lat/long system falls short.

GPS uses a more realistic model of the Earth’s ellipsoid shape as a standard.

Geographers built the model as the distance from the centre of the planet to the surface for a geocentric datum. Called the WGS84 (World Geodetic System – 1984), it is globally consistent within ±1 m. GPS data consists of multi-digit x,y coordinates – stored as either GEOMETRY data types or GEOGRAPHY data types.

In digital GPS terms the coordinate above becomes -36.86397, 174.762005.

You can also use descriptive fields to assign location. For instance, you can take street addresses or postcodes and then ‘geo-code’ them to assign x,y coordinates.

This places them on the map. However, geo-coding has it’s own set of challenges.

Addresses have to be unique. They have to be spelt correctly, and many businesses use a building as their address, say iStart House instead of 44 Khyber Pass Road.

Address scrubbing is a major undertaking, especially if databases are large or encompass a wide area. Again, location intelligence gives end-users a powerful tool to analyse information in a geographical context, but setting up the spatially-aware databases in the background can be a laborious and time-consuming task.

Once you have accurate point data (i.e. the exact location of a point, which has no length or surface area), you can build accurate lines. And once you have lines, you can make polygons, or spaces completely enclosed by a series of connected location-aware lines. You can then assign values or attributes to them. Point A could be a customer, complete with sales history. Line B is the road they live on.

And Polygon C could be a sales rep region or shopping mall catchment area. As above, it takes specialist knowledge and more advanced technology to create polygons that drive the embedded location intelligence modules. But once the basemaps have been created and the location and attribute data has been scrubbed, the possibilities are endless.

Today’s smart databases are being developed with spatial data in mind. Microsoft’s SQL Server 2008 is a perfect example. SQL Server has been set up so that you can store location coordinates as well as polygons. These are the basic building blocks of spatial analysis and can now be supported.

SQL Server 2008 also supports Geographic Markup Language (GML) and is compatible with Open Geospatial Consortium (OGC) standards for geometric data types. So if you can capture location data as you build your customer or event profiles, you can also build spatial capabilities into your business intelligence applications.

The beauty is that as technology advances, and data sources are consolidated and maintained more efficiently, the majority of us don’t need to worry that the earth is, in fact, not round.

Instead we can focus on what the maps are telling us.

Thankfully.





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