Definition of Geospatial Analytics
What does is it mean and how is it used
What is Geospatial Analytics?
Geospatial Analytics are used to analyze data about physical objects that are linked to a geographical location. This usually means data on imagery, GPS, satellite photography and historical data, that can be used to describe exact geographic coordinates or build a picture of an area in terms of a street address, postal code or any other identifiers, as they are applied to geographic models.
Why use Geospatial Analytics?
If you can account for both time and space in analytics it enables you to see another layer of patterns and trends in data which can help build a richer and more complete picture of what you’re monitoring.
Did you know?
GPS, the source of most location data, consists of 32 satellites orbiting at a height of 12,540 miles. Most GPS systems are also able to utilize Russia’s GLONASS system which has an additional 24 satellites orbiting the globe
Latest Geospatial Analytics Insights
Research shows that over 64m prescriptions of antidepressants are dispensed per year in England. Delving deeper into the data, further information, such as geographic differences across the country, was uncovered.
With a geospatial functionality you can build maps of staggering complexity and can combine it with time-series data to get answers to a lot of “WHERE” questions. Watch our short video describing the geospatial functions available on Exasol and learn how you can work with Geography within SQL.
Big Data has the ability to shape the way we live in cities – turning them digitally interconnected to imporive the quality of life and serve its citizens better. But the data is only one half of the equation.
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