Powerful map visualizations and location-based analytics for both Qlik Sense and QlikView.
Qlik GeoAnalytics not only provides comprehensive mapping capabilities but also moves beyond visualization with built-in spatial analysis support for a broad range of advanced geoanalytic use cases to help reveal crucial geospatial information and expose hidden geographic relationships.
With on-the-fly location lookup, you can automatically populate and update dashboards and maps with data about specific places and areas for use in spatial analysis. Search by city, county, zip code, place names or airport codes. For example, if you want to analyze police activity in a specific region, you can quickly include that data on your map without knowing any geographic coordinates.
Clustering lets you view the geographic density of points or events, showing groupings of high or low values that stand out in your data. For example, by analyzing how many people live within a 15-minute drive time from existing stores, a retailer can determine the best possible locations for a new shop.
Formatting and Annotating
Colors, lines and shapes can help you more easily make sense of your data. When analyzing customer buying behavior, for instance, you can use colors to represent the shops and zip codes in which people are buying, as well as shapes to differentiate between shop locations and customer data.
Geospatial analysis tools allow you to perform visual mapping, which helps you view and analyze multiple data sets by displaying them on maps in different layers. The layers are overlaid on background maps and can include area, bubble, chart, geodata, heatmap and line layers. Data for background maps and layers can come from both internal and external sources, such as CAD files from traffic or weather warning systems.
Your analytics solution should allow you to select any type and combination of data on any layer, whether you select from a bar graph, or directly on the map using lasso selections or pan and zoom. For example, you could combine road geographies with traffic conditions to analyze traffic flow in a certain area, or overlay real-time weather with weather warnings data to understand how those patterns affect airport traffic in a particular region.