Increasingly, companies are looking to a variety of data types and
new forms of analysis in order to remain competitive. Forward-looking
companies are developing analytics ecosystems that make
use of disparate kinds of data, including text data, social media
data, machine data, and more. Geospatial data, sometimes referred
to as location data or simply spatial data, is emerging as an
important source of information both in traditional and in big data
Geospatial data and geographic information systems (GIS) software
are being integrated with other analytics products to enable
analytics that utilize location and geographic information. Such
analytics are also moving past mapping to more sophisticated use
cases such as advanced visualization and predictive analytics.
According to a recent TDWI survey about analytics, for instance,
the number of respondents who plan to use geospatial analytics
will double between 2013 and 2016. Today, users want to better
understand the value and use cases for this technology.
Geospatial information can be extremely helpful in a variety of
analytics ranging from marketing to operations management.
This checklist introduces readers to the range of use cases where
geospatial analytics is being used today to support analysis.
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