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Throughout my blog entries, we have taken a tour through the catalog of charts that Qlik has to offer. We have covered bar charts, line charts, pie and Sankeys, today we’re going to be diving into one of the lesser known, but still powerful, charts: Scatter Plots.
Scatter plots are used to show the relationship between two quantitative variables. The scatter plot is usually made of three elements, the X axis, the Y axis, and a point to show a data point shared between the two axes. Additional information can be shown on the chart in the form of the size of the data points, in Qlik Sense these data points are called ‘bubbles'.
How can you use a Scatter plot chart to visualize your data?
To demonstrate the capabilities of a scatter plot, we’ll look to an example found in the CRM app. This app was developed to showcase data including sales, numbers of customers and opportunities. This app would help a manager of a company see what parts of their business are doing well, and which need improvement.
Above we have the scatter plot built for this app, as well as the view of the ‘Advanced options’ of the chart to give a clearer view of which data is being shown and how. Beginning with our X axis, # of Customers and the Y axis which is Opportunity Amount. With the interaction of these axes, we’re shown that the higher and more to the right that a data point would be, the better for the company that data point would be (more money, more customers), and the opposite for down and to the left (less money, less customers). Additionally, the name of the Sales Person is assigned to the ‘Bubbles’ in this chart. Finally, the size of the bubbles shows the Amount of Opportunities won.
What information can we gain from this example?
A manager looking at this chart would quickly be able to determine who are the top and bottom performers and in which way. At a glance, the manager could see two outliers, Gonzalo Geary and Val Conforto, for two different reasons. According to our chart Gonzalo is adept at gaining customers, close to around 230 (double that of their closest competitor), with a larger number of opportunities won compared to his fellow salespeople. Val conversely shows that while she does not have as many customers as Gonzalo does, she makes the most out of the customers she does have, ranking highest in the amount of her opportunities.
That is the power of the scatter plot giving users insight into data points between two metrics. If the manager had only looked at Opportunity Amount, they might think Gonzalo as an average salesperson, while the same could be said for Val if looked at through the lens of # of Customers. Instead, the scatter plot allows for the manager to see how these individuals excel, and where they require additional assistance or training.
Hopefully this blog entry has led to a few ideas of how you can use scatter plots to visualize your own data. How can you use scatter plots to help you or your company? Is there something I might have missed? Leave it in a comment down below.