Location-based and geographic services produce $100 billion per year in global, gross value added (GVA).
As demand for geospatial data (and for the systems to manage and maintain such data) grows, it’s not hard to see why.
As consumers, social media, smartphones and satnavs have made us all aware of the power and prevalence of location data … for better and for worse. Where would we be without Google Maps?
In business, geospatial data is everywhere. Add to social media and smartphones, data from Internet of Things sensors, from utility smart meters and insurance companies’ in-car black boxes and you can see how quickly the volume of data builds.
Even in supposedly traditional organisations like city councils, every department relies on location data: traffic flows, public facilities, the location of field staff and of client-citizens. Data centres are brimming with disparate sets of spatial data.
Combining data – both spatial and non-spatial – from multiple sources multiplies the insight available: preventative maintenance can be planned more effectively; customer service can become more usefully targeted and emergency services can be more accurately deployed.
However, an abundance of different and disparate data sets, nestled in siloes across the organisation presents challenges, too.
The data was collected over different periods, at different frequencies, to different levels of accuracy and for different purposes. It is stored in different formats and at different and/or unknown levels of quality and completeness.
Integrating that data to support a valid, single point decision is hard.
Managing and maintaining it for regular interrogation is even harder.
The potential time and cost involved can appear unmanageable.
Many experienced integrators of complex geospatial data – like Ordnance Survey, Northumbrian Water or the US Federal Highways Administration – use data management processes and tools that automate validation and integration. This reduces the cost and time involved in data stewardship.
Rules-based automation preserves organisational knowledge and frees your experts up to innovate.
It’s an approach that we recommend.
Over the next few weeks, we’ll be looking at how the automation of spatial data management can help businesses seize the location opportunity.
To learn more, download our Little Book of Spatial Data Management, here. https://1spatial.com/solutions/little-book-spatial-data-management/