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Dashboard Week Day 2: Customize your processor

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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On the second day of Dashboard Week, we were given a dataset containing performance indicators of CPU and GPU products from the year 2000 to 2021. Our task was to build a dashboard to analyse the development of chip and provide product suggestions for those looking to choose a processor.

Fortunately, the data was clear, clean, and well-organized, which minimized the work required for data preparation. After understanding the meaning of all the performance indicators, I began creating charts for the dashboard. The dataset includes five performance indicators: frequency, TDP, process size, die size, and transistors, each representing a different aspect of a chip’s performance.

To effectively compare these five performance indicators in a single chart, I decided against using the commonly used bar or line charts. Instead, I opted for a radar chart. In the following section, I will explain how to create a radar chart in Tableau.

In the radar chart, each performance indicator is represented by a dot on the chart’s axes, with the angle corresponding to the indicator and the distance from the center indicating its value. Before creating the radar chart, I organized the data into the format required for it. I generated a set of performance ratios and pivoted the data as shown in the picture.

Next, I created two calculated fields, x and y, to determine the coordinates of the dots on the radar chart, as depicted.

The final step involved dragging the calculated fields x and y into rows and columns and adjusting the marks area. I chose the Polygon mark type and used the field names in the path. By following these steps, a radar chart for the product’s performance was built, allowing users to quickly assess the overall performance of a specific product.

                  

In this dashboard, I practiced Level of Detail (LOD) calculation a lot, which enables analyzing different levels of detail in a single view.

Dashboard Week proved to be an intense and challenging experience, but it undoubtedly sharpened my skills as data analysts.

If you are curious about what the dashboard week is and how you should organize all the process, I hope this video will be helpful to you.

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