Victoria Census Data – Dashboard Week Day 3

January 5, 2023

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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Hello, I’m back with Dashboard week – Day 3 Challenge: Victoria Census Data

Requirement:

Build a dashboard from the provided dataset Victoria | Region summary | Data by region | Australian Bureau of Statistics (abs.gov.au)
Be specific with a chosen topic and we could supplement the analysis with additional data if we wish
No Alteryx

So, we were not allowed to use Alteryx for this project. We could use Tableau Prep instead, which was good for practicing Tableau Prep. It is also a nice data prepping tool although it is not as powerful as Alteryx in my opinion.

DATA EXPLORING

After getting the dataset from our coach, I went on exploring the data as usual. It has clear content and explanation of each tab. There are 9 topics/ angles that I could choose from. I was first drawn into migration, data about persons born oversea, as I can relate to it. Still, I spent some more time exploring the rest of the data set out of curiosity and I did not want to miss any better insight from other angle if there was one.

I ended up getting lost in the data set, hoping I could see a good story. However, it was hard to see any pattern or outlier by reading numbers in Excel. I wanted to visualize them all, but recalled I was warned from my coach not to visualize all the data and be specific about the topic. The clock kept ticking, I had to decide. I settled with my first point of interest in the data set – immigrants!

DATA PREPPING

The data is at a high level, so it is not much to clean. I performed couple steps in Tableau Prep to spit out the information I need.

Clean and Spit

Pivot the years into tall data format

DATA VISUALISATION

I started to build all the charts I could to see what story the data brings me. Well, it did not go so well.

Limitations of the main data set:

The data is at a high level, there is not much to break down.
No linking that I can find to perform spatial analysis
There are only 2 points of time: 2016 & 2021.
Some interesting angles like level of highest education, occupations, labour force status, have only data for 2016.

My visualization mostly was comparing the 2 years to see the change in different areas.

After having my charts, I went on to look for more detailed census data for immigrants for 2021 as I am interested in that year after my findings, but no luck.

Below is my finished dashboard.

My Reflection on this project:

I think I did not do so well with this project in delivering an interesting story.

In terms of data visualization, I am a bit happier as it was a good chance for me to find different ways to visualize data, rather than using bars for every chart.

Lesson learnt:

When given a data at high level, try to get a more granular data as soon as possible to analyze. It was too late for me for this project after visualizing data from the main data set, so I just went with what I got.

Yes, that’s it for day 3, scored a new lesson.

Thanks for reading, see you next time.

Thao