Geocoding has emerged as a priority for companies that want to exploit customer and other data by visually representing it on a map to inform their decision-making. Geocodes provide precise location data, expressed as latitude and longitude co-ordinates, allowing information like customer data to be plotted visually.
This data can then be combined with other data such as customer demographics or the risk profile of an area. One example is a short-term insurer using spatial data from geocoding to assess whether a customer lives in an area with a high-risk profile for crime or flooding. Another might be a freight and logistics company using this data for route-planning.
Geocoding is not new, but is becoming more useful with the introduction of spatial business intelligence tools, Gary Allemann, MD, Master Data Management.
Geocoding is not new, but is becoming more useful with the introduction of spatial business intelligence tools, says Gary Allemann, MD of Master Data Management. But the challenge most companies face is that the data they need to exploit these tools is dirty.
Inconsistent addressing is at the heart of the problem. Many companies will be drawing on data sets where something as simple as the street name 'Seventh Avenue' could be represented in a number of different ways, for example, 'Sewende Laan', '7th Avenue' and 'Seventh Ave'. In a real-life data set, it's not uncommon to find hundreds of spellings of even a simple town name, like East London, says Allemann.
That means most companies will need to invest substantially in data cleansing and matching tools to make the most of spatial BI tools, he adds. Building common addressing standards for their own data sets and those they get from other sources, deduplicating data and correcting errors is essential before geocoding can deliver the benefits hoped for by organisations.
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