GIS Supports Police Analysis Through Business Intelligence


Historically police departments do a great job of recording their
crime information for analysis as well as for public record. Though how
a police department staff chooses to analyze this data once it is
collected may vary widely. For the police department of Park Ridge,
IL, they have enlisted the services of the Geographical Information
Systems (GIS) over the past few years to create maps displaying the most
current burglary locations as well as any trends that may have been
occurring over time. These maps are very beneficial and are usually
created on a monthly basis. Although this timeline seems to work, a
large amount of burglaries can happen on any given day or week making
the need for fluctuation within these maps all the more necessary.

For this reason alone, the GIS Department has upgraded the police
department’s ability to analyze the data for any select day, week, month
or year by incorporating business intelligence into the citywide
interactive mapping application. In general terms, business
intelligence can be defined as accessing live data from a source that is
actively being edited and representing that data in form that is
usable, in this case it is for mapping purposes. The data that is
actively being edited by the Park Ridge Police Department is held within
an excel file that then gets saved to a .CSV file on a citywide central
server. Because the data is in a centralized location, GIS can connect
to it in order to read the data and map it on the fly within the
interactive mapping application. Additionally, the data can also
queried with the help of Structured Query Language (SQL) in order to
allow the police department to select which police beat they want to
analyze for any given time frame. The power is now in the hands of the
Police Department to query what they want, make a map of it and export
this map to a PDF format to insert into their weekly reports.

All in all, it is easy to see that with the help of GIS the Police Department can now analyze their data more efficiently.