I’ve been a data analyst for a year and I’ve learned it’s rare to get things perfect on the first try. Projects often go through multiple revisions before they reach their final state. Below is a recent experience I had with this and how feedback played an important role in the final product.
The Stages
A few days ago, I shared an example of a heatmap to show why other charts besides the basic line graphs and bar charts, may be needed. This first version had some issues, but thanks to some constructive feedback and my revisions, it became a more effective visualization.
Original Version
Randomized numbers resulted in random colors.
Purple to yellow gradient affected chart readability
![](https://static.wixstatic.com/media/bc9ec1_25c0102a9dfe4ae29ee89daa6ea8d91d~mv2.png/v1/fill/w_980,h_1027,al_c,q_90,usm_0.66_1.00_0.01,enc_auto/bc9ec1_25c0102a9dfe4ae29ee89daa6ea8d91d~mv2.png)
Revised Version
Numbers were made more realistic with the help of ChatGPT.
Kept the same palette, which improved readability but still delayed insights
![](https://static.wixstatic.com/media/bc9ec1_81185cb0e80f4b7cbd67b37fd2c02da7~mv2.png/v1/fill/w_980,h_1027,al_c,q_90,usm_0.66_1.00_0.01,enc_auto/bc9ec1_81185cb0e80f4b7cbd67b37fd2c02da7~mv2.png)
Final Version
Kept realistic numbers.
Switched to a single color and removed the legend for quicker, clearer insights.
![](https://static.wixstatic.com/media/bc9ec1_2bf06fca33d24a6ca49d0d248dc2f53a~mv2.png/v1/fill/w_980,h_1027,al_c,q_90,usm_0.66_1.00_0.01,enc_auto/bc9ec1_2bf06fca33d24a6ca49d0d248dc2f53a~mv2.png)
The Importance of Constructive Feedback
One of the key factors in improving the heatmap was the specific and actionable feedback I received. Jasmin Jusufbegovic, was especially helpful, he offered detailed suggestions and explained his reasoning. This feedback not only improved the visualization but also my understanding of effective (and simple) charts.
How I Used This at Work
While this heatmap was made to be a general example (all the numbers and data are made up), it is based on a real heatmap for work. With this feedback, I was able to revise the heatmap I made for a stakeholder, and we used it to gain insights for a project and determine the next actionable steps.
Key Lessons and Insights
Here are some other takeaways:
It's okay not to know everything. - We’re all human, and our focus should be on continuous learning and improvement.
Revisions are a natural part of data projects. - Your first draft might not be perfect, and that’s okay. Iteration is key to refining your work.
The power of specific and constructive feedback. - Feedback that is focused on helping you learn and improve is incredibly valuable.
Embrace the Process
Understanding that your first draft won’t be perfect can be freeing. It allows you to focus on learning and improving rather than aiming for unrealistic perfection from the start. Embrace feedback and the process of revising your work. It will lead to better projects and a deeper understanding of your work.
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