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Andrea Martorana Tusa

BI Specialist working at Widex, a danish manifacturing company producing hearing aids.? 
My task is collecting data from every branch of the company (Production, CRM, Marketing, Finance, etc.) and put it togheter with exposure towards the end-user. All through a full integrated BI solution based on Microsoft’s tools; SSIS, SSAS, SSRS, Power BI.? 
 
Formerly worked for 15 years in an italian bank as BI developer.? 
 
Common speaker as events and conferences around Europe (SQL Saturdays, SQL Nexus, SQL Konferenz, SQL Day Poland, etc). Speaker for DW/BI and Italian Virtual Chapters.? 
Author for sqlservercentral.com, sqlshack.com, UGISS (User Group Italiano SQL Server). 





Presenting

Spatial Analytics with SQL Server, R and Power BI

LINK TO FEEDBACK

 

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 behaviors.
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 possibilities.

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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