![]() ![]() This puts the data into further context and makes it really easy for managers to spot specific key points. Take a look at the bubble chart that we created using the data from the first Excel 3D example: Chart 3 – A quadrant bubble chart This is useful if you want to categorize your data a little further by using a common layout like it is used in a SWOT or market attractiveness analysis. In Cognos 10, we can also turn any bubble chart into a quadrant chart. The traditional 3D bar chart was useless. Also notice how this chart allows me to combine three measures with different types scales: percentages and absolute values. Or, I could first focus on the size of business that we do with each carrier by picking out the large bubbles. Depending on the problem that I am trying to solve, I could simple look at the top right area to find the black sheep that are super later and also careless. Notice how easy it is to read this chart (which vendor has the best performance?). The shipping costs, however, are visualized via the size of the bubble. The first two measures are obvious – they are represented by the x and y axis. Let’s have a look at an example: This is a classic bubble chart that displays three different measures: Late shipments, damaged shipments and shipping cost for different carriers. And not only that: they are easy to read and they allow us to make critical associations between these measures. Bubble charts allow us to visualize three different measures at the same time. My boys loves this chart type: Bubble charts (all kids love bubbles!). There is a better way to display this type of data. Analyzing numbers would also be more difficult in that setup as we have to shift our view from one chart to the next. But that requires a lot of space – and space is tight in a good dashboard. The other option is to break this out into multiple charts. I could not, would not make a decision based on this chart. And let’s be honest – this looks super ugly. There are a lot of obvious problems with these type of charts: The dimension have different scales and it is therefore impossible to decipher. Many people are tempted to simply create a 3D bar-chart like the one below: Chart 1 – Is this useful? Let’s say we want to analyze market size, market share & margin. For example: Once we reach more than 2 dimensions, many people reach out for 3D charts. There are a lot of complicated and useless charts out in dashboards. The objective of charts is to visualize data in the most effective and easy way. Especially when we look at multi-dimensional data-sets. ![]()
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