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SmartData Collective > Business Intelligence > Location Based Business Intelligence
Business Intelligence

Location Based Business Intelligence

bharden
bharden
0 Min Read
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Business Intelligence and GIS software have both been around for many years.  More recently they have become closely integrated, with most BI offerings providing a connection to mapping layers such as MapInfo or 

Business Intelligence and GIS software have both been around for many years.  More recently they have become closely integrated, with most BI offerings providing a connection to mapping layers such as MapInfo or Google Maps.  The merger of these two tools provides a powerful visualization for data, connecting massive amounts of data with a visual that most everyone is already familiar with.  For example, a map of New York City overlaid with census data quickly shows us where to find Gotham’s ethnic neighborhoods.  Another interesting example using Google maps shows us where harassment is occurring in Cairo (and on a side note, Google Chromedoes an excellent job translating this site from Arabic to English).  Finally, an interesting take on over 300 million tweets showing when Americans are most happy.  Just think how difficult it would be to make sense of that volume of data without a map.

As more and more companies see the value of looking at their data in the context of geography this kind of mapping integration will only become easier and more common.  The enterprise is embracing this mash-up between maps and business intelligence but what about incorporating the report consumer’s location? 

Today, just about every Smartphone on the market has a built in GPS that has the capability to capture data on our location.  This new dimension of real time location data combined with GIS information, a BI tool and an enterprise data warehouse could be incredibly powerful.  Imagine an airplane mechanic being able to see the maintenance history of the aircraft that is closest to him.  Wouldn’t it be nice to have a real time map showing the location of your pizza delivery driver, with an estimated delivery time based on the driver’s location? What about a salesman who is stuck at the airport?  What if he could have a report that integrates the Twitter, FourSquare and Facebook location data of his clients within a mile of his location at the airport?  Learning that a key client is also stuck at the same airport could allow him to “bump” into them to catch up or even have an impromptu meeting.  

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These things may sound far fetched, but the reality is that we have the tools in place to make these ideas happen today.  In fact, Smartphone apps are already doing this with location based social media. For example, UrbanSpoon tells us the location of restaurants that are near us and lets us read comments on the quality of the food.  If UrbanSpoon can do it, then why can’t a fortune 500 company?  To extend these ideas to the enterprise it will require us to link our location with real time operational and analytical data.  With in memory analytics becoming more commonplace and near real-time warehouse technology available the only limitation is our imagination. 

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