World Mapping File For Qlik Sense Maps (KML Shape and Point)

    When building mapping visualizations in Qlik Sense, you will need either Lat & Long data to plot points on a map, or shape data to plot areas. For the latter, Qlik Sense will recognize KML files as a data format and load those natively. But shapes are merely a series of lat & long points that when plotted will connect up into a shape, such as a state or a sales region. When multiple shapes are plotted they can connect to form a country, or even a map of the world.


    When plotting either points on a map or a series of shapes, you will need either the relevant Lat and Long data or shape data in your data model. It must also be associated the relevant field in your data model to allow you to plot the relationships. For example, to plot a series of bubbles on a world map to indicate population, you will need lat & long data for each country and you will need it linked to your population data on say country code.


    UPDATE (8/7/2017): The new mapping object in Qlik Sense allows you to render maps without actually having the shape or point data in your data model. This is because the map object leverages a geospatial engine that recognizes country, state and town names dynamically. For more information refer to our help:


    But where can you get such a data set? Well, there are many free location based data sets on the web, but often they are a bit fragmented and incomplete. To save you all a bit of time I have joined together a few files into a single world based location set, which contains the following for each country:

    - Latitude & Longitude

    - Country Shape data

    - 2 char ISO code

    - 3 char ISO code

    - Short Name

    - Full ISO Name

    These are contained in the attached QVD file which I hope you find useful. When I get a chance I will also upload a Qlik Sense app with a few examples using the data. If you need some info on how to use the mapping object check out this great video from Mike TaralloQlik Sense - Creating a Map Visualization