Qlik offers a powerful tool that enables users to create insightful analyses using a map. All the way from finding the best possible routes to aggregating volumes of data into bins to finding travel areas for logistic optimization, Geo Analytics provides a solution for all your problems!
This article will help you grasp the essential functionalities of Geo Analytics, from an industry-level perspective! Get ready to dive right in!
Geo Analytics can be performed using either of the following,
The Visualization Extension
The Geo Analytics Connector (This is the focus of the article!)
There are two components of the Geo Analytics:
The Map displays the geography.
The Dimensions and Measures that connect to a layer in the Map.
Qlik Sense uses one of two ways to pinpoint the location of a data point on a map:
Location IDs also known as geo-keys are names or codes of countries, regions, etc.
Lat-long data of each row with the data model. Generally, the GEOMAKEPOINT function converts the user lat-long data to Qlik-supported data.
The below image represents the categories of Geo Analytics:
Now that we have covered the basics, let's delve into the intricacies!
Of course, the first step is to navigate to the Geo Analytics Connector and this section will be your faithful guide 😁
Open the Data Load Editor, and click on Create new connection.
In the Analytics sources column, find Qlik GeoOperations, and click on it.
A pop-up appears, click Create, and you should see this in the Connections.
Geometric Operations perform operations on map geometries, enabling users to make custom map areas, aggregate points into a bin, simplify detailed lines on a map (for performance optimization), etc.
Here’s a comprehensive representation of the various functionalities in Geometric Operations:
This function compares a point (source) in one dataset to several points (destination) in another and finds the closest set of destination points. It returns the distance between the source and closest destination points.
Question:
There is a scenario where a truck travels from the Team Bricks plant or warehouse to deliver bricks to a client. However, another Team Bricks Plant could be located near that client. If such loopholes are identified, this company can save a lot of money by making wise decisions by aligning deliveries from plants close to their customers.
Solution:
Open the Connector and provide the following inputs.
Now, fill in the details of both your datasets accordingly.
In my case, the source and destination data are separated. However, both could be in the same table, in which case the table name is the same for both datasets while the key field and location will differ.
Generate the script and load the data. Check out the results below!
This function is useful if you are required to make a custom map by merging several small map units such as municipalities, zip codes, streets, etc.
Question:
A particular company has to plan the budget for three regions in Vermont. However, these regions are custom-made. They are based on the stores present in each county. Make a custom map where these counties are merged to form one of the three regions.
Solution:
Open the Connector and provide the following inputs.
Add the following in the Dataset section.
Generate the script and load the script. Check out the results below.
To summarize, Geometric Operators are used to perform operations of map geometries.
Aggregation Operations are used to aggregate multiple points within a given. This enables users to better visualize the data rather than looking at a clutter of data points as represented below.
Below are the types of Aggregation Operations that can be applied to your dataset.
The Binning Operator takes all points and adds them to a bin! Take a look at the example below!
Question:
Aggregate all crimes within a certain radius, bin them, and represent the magnitude of crime within that bin using color gradients.
Solution:
Open the Connector and provide the following inputs.
Input the following info into the Dataset section.
Generate the script and load the data. Check out the results below.
This section summarizes the Aggregation Operators which help simplify concentrated data on a map, consequently facilitating an insightful map.
As the name suggests, these operations help in determining the routes between the source and destination whilst taking into account the mode of transport.
This operator simply finds the optimized route for a particular journey along its duration of completion. Below is its real-life illustration
Question:
Visualize freight transported from a plant or warehouse to clients more than 230 km away in red. Represent clients within 230kms in green.
Solution:
Open the Connector and provide the following inputs.
Add the following inputs in the Dataset section.
Generate the script and load the data. Below is the result.
The Route Operator returns the field distance. It can be used in the color by expression for conditional coloring.
Travel Area is an excellent way to identify areas that can be reached from an origin within a certain time or a certain distance!
Question:
Determine how many customers are living within a 6-hour drive radius.
Solution:
Open the Connector and provide the following inputs.
Add the following inputs in the Dataset section.
Generate the script and load the data. Below is the result.
The points within the radius (green circle) can be reached via the specified transportation medium (car in this case) within the stipulated time (15 minutes in this case).
In conclusion, Qlik's Geo Analytics, particularly the Geo Analytics Connector, empowers users to unlock the full potential of spatial data by understanding the basics of map visualization to dive into intricate operations such as geometric, aggregation, and route-based tasks, this tool offers a comprehensive solution.
