What is Geo-Analytics
Geo-coded, or location-based data integrated with analytics results in powerful GeoAnalytics. GeoAnalytics provides hidden insights into geographical aspect of data extracting crucial information of geospatial system. It provides accurate data as geo-codes of a location or in simple terms latitude and longitudes, and a broader data as postal code, street name, house number along with other details which are subject to change.
GeoAnalytics largely helps in understanding the aspects of geospatial analysis include climate change monitoring, sales analysis, human population insight, precision farming, agricultural maps and many others. There are various modeling techniques followed in geospatial analytics. The first GIS (geographical information system) was founded for creating a manageable inventory of natural resources. Roger Tomlinson created design for automated computing to store bulk of data and deriving buried information from it for Canadian Government. He also gave GIS its name.
How Does Geo-Analytics Work
Although there has been advancement in GeoAnalytics, most of the systems are yet not apt to moderate and analyze huge chunk of data. This is especially true for geospatial data that deals with complex issues as spatial dependence. Spatial dependence is the tendency of nearby locations to influence each other and exhibit similar attributes. Spatial analysis systems were majorly designed to compute finite datasets. Large spatial data meant greater analytics to calculate spatial dependencies and thus parallel computing, where multiple processes are carried out mutually exclusively, couldn’t perform to its utmost efficiency.
In order to deal with large geospatial datasets, GeoAnalytics uses coding and scripting to create new systems. These systems are powerful enough to deal with satellite data and perform super-modern calculations emulating supercomputers where parallel computing could also be included. This is a huge migration from the rudimentary practices of geospatial analytics.
The wave of GeoAnalytics is further drifting towards Predictive Analytics now i.e. predicting future aspects based on the trends and statistics that have been recorded. Organizations having geospatial predictive analytics have a competitive edge over those that don’t. This enables businesses to have better visualization and analysis of data thus giving them the ability to aim for blueprint of a familiar structure.
Implementation of Geo-Analytics
GeoAnalytics can also be used to study behavioral pattern of demography. For instance, say there is epidemic disease in an area, the doctors can analyze the Census Data to view the major affected areas and perform GeoAnalytics determining the factors what is the root cause of the disease. They can launch campaigns hosting health-checkups, analyze eating habits, hold surveys and analyze the root cause of disease, start preventive measures in the area and take other actions.
This data can be stored in the GeoAnalytics system and further used for Predictive Analysis and taking precautionary measures. By extending the capabilities of GeoAnalytics in this era, it has become available on your fingertips. Whether you want to perform Spatial Analysis, Predictive Analysis, Sales Person Performance Analysis, Tracking POS (point of sale) data or others, you can just turn to GeoAnalytics. The advancement has happened at a lightning speed in few decades and is still growing.
There are many other reporting tools available that allow number-crunching but being able to visualize data based on location and do a visual analysis on the map is incredibly powerful. GeoAnalytics is key in defining the ‘Where’ element of data, that where is the data coming from and what is its business significance. It is adapted by major organizations and is instrumental in their growth.
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