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Dashboard Week – Day 3 – Accidents in Victoria

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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Dashboard Week – Day Three started with data sets on accidents in Victoria with more than 15 files. One of the challenges was to clean the data without using alteryx. Instead, we have to clean and prepared data by using Tableau Prep.

Firstly, we discussed the business objective for the dashboard of this sad but true reality of Victorian roads. Secondly, we understood all the fields in the available data files which we have joined to make our final data set.

The final data set had 60+ fields. So, we selected the relevant fields to move forward.

Key factors I explored are the hotspots of road accidents by suburb/postcode followed by specific roads.

Another view created was based on age, gender and severity of accident.


 

Assuming time of the day and day of the year also could be an important factor, so I have created one more view where a two-dimensional heat map was used as a source and time of the day as target dashboard connecting using action filter. Using this dashboard, you can figure out the hot spots using postcode road name, gender, age, day of week, time of week.

On lighter note, one thing is clear that women are actually better drivers than their male counterpart.  

Link for Viz : https://public.tableau.com/profile/babita.dalal#!/vizhome/AccidentsinVictoria2006-2017/1_HeatMap

 

 

 

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