Everything in our
world is located “somewhere” and is related to other things. Spatial analysis
consists of studying these relationships to find out meaningful patterns and

Figure out, you’re
looking for the best position to open a new store. It´s not only a matter of
“where”, but also there are more implications; is the area easily accessible by
customers? Is there any parking? Is it easy to reach for suppliers? Are there
any competitors store around? What is the volume of shopping for the same
business in the area?

Here is where spatial analysis
can help us collecting, comparing and matching data to build up a framework of


Since 2008 release,
SQL Server is supporting spatial data type. Now new amazing features are
offered with the addition of R. R is shipped with a huge number of packages for
performing spatial analysis, mapping, geocoding, etc . There virtually anything
you can’t do with R: finding relationships, measuring spatial autocorrelation,
interpolating point data, mapping point data, …

And, last but not least,
we have Power BI that offers a full range of mapping capabilities. Not only
bubble or choropleth maps, but visual for performing spatial analysis like
ArcGIS, or for creating custom shape maps. And R scripts naturally.


In the session, we
will show how the joint use of these three tools empowers us to analyze and
query the spatial properties of data.

We’ll showcase a
real-world example for a better understanding of the endless possibilities that
are now offered to us.

Come, have fun and
discover a world of information inside your data with Spatial Analytics!
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