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Customer Analytics
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Display & Native Advertising
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Mobile App Intelligence
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Paid Search Advertising
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Social Media Sensing
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Technology and Innovation
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TV Ad Measurement and Insights
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Geo Analytics
Geo analytics combines traditional analytics with location-based information to provide greater context and perspective about the data being studied. Analytics already covers a variety of factors when generating insight and parsing data, but geo-location and other spatial information can expand intelligence by providing a new axis on which to discover insights.
The field incorporates many concepts from established fields like geographic information systems (GIS) and geo-spatial analytics. This way, data can be layered on and compared between locations, measured by cities, regions, and countries, and manipulated to offer unexpected trends and patterns.
Why should I consider Geo Analytics in my business?
Today, geo-analytics is also used in data visualization, as it can provide a much better picture of trends than a spreadsheet or chart can in many cases. Understanding a geographic distribution can be easier to comprehend when looking at a heat map or density chart as opposed to rows and columns on a table. See the full article for more details.
What is geo analysis?
Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect.
What is geospatial data used for?
Geospatial data has been used by law enforcement agencies to predict and prevent crime in several ways: Mapping. Police or other agencies can utilize data from multiple sources and visualize it on layered maps.
What are the two spatial data models?
The components of the model are spatial objects, approximating spatial entities of the real world; they are represented on the map by graphical symbols. Information is data organized to reveal patterns, and to facilitate search. description of objects and their attributes comprise spatial datasets.
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