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Dashboard Week: Wednesday- NEISS Product Injury Data in Tableau

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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Today’s challenge was to create a dashboard in Tableau using data from the NEISS which is a consumer safety agency in the United States of America. This data was tracking incidents involving products from a sample size which were weighted because of frequency of similar injuries.

My timeboxing vs actual wasn’t very linear for this project, so I’ll will just be walking through my process. I started off by transforming the data using Alteryx as the structure wasn’t ideal for comparing the different demographics and the fields were in number codes. I started by replacing the codes with the text strings, so it was more dynamic when analysing the data. Then I created tables which can be used referenced using relationships in order count values from multiple tables- eg. products, body parts, etc.

Once this was done, I started to explore the data and tried to find any interesting insights. I then noticed that the descriptions of incidents seemed to be much more severe when the patient was incarcerated vs not.
I decided this would create a very interesting dashboard to compare incarcerated vs non-incarcerated individuals across different demographics. I started by building the formatting of my dashboard then started to create the worksheets. This went pretty smoothly, and I managed to pull some very interesting insights to add context to the data.
My only issue was I got carried away with analysing and data and kept wanting to add more when I should have been more cautious of the time constraints of the project.
I managed to finish the dashboard at 8:30pm Wednesday but I could have finished earlier if I hadn’t gotten carried away with trying to do too much.
Overall, it was a very fun dashboard and there were minimal issues. feeling good for Thursday.

If you want to view the dashboard close up, it can be found here.

 

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