Welcome to Day 3 of Dashboard Week for DSAU 17!

Today’s challenge was involving the Victorian Census data from the ABS. You can find a bit more about that here.

Using that data set, the challenge was to build a dashboard that told a story, that was specific to a topic. A very open-ended task to be sure.

The restriction imposed was that we were not able to use Alteryx for any data preparation, instead we were to make use of other tools. In my case, I chose to make use of Tableau Prep as an alternative to Alteryx.

After initial indecision about what direction to go, thanks to some inspiration from the ABC who published an article about population trends in Australia, I decided to investigate what has actually made up the current changes in population, how that’s affected different groups of people based on gender, religion via migration and natural changes within Victoria, then potentially break that down further based on any findings. After quickly preparing this in Tableau Prep, and having an investigation into the data, I wasn’t able to find something that was worth pursuing.

It was getting late in the day, so instead I quickly pivoted to comparing the income statistics between states, to find what state I should be living in at different ages if I wanted to have the highest likelihood of earning the most money.

Tableau Prep – The Flow

Tableau – Dashboarding

As the day was drawing to the end, I set about making an extremely simple dashboard that I could use to understand what state I should live in during my working years, and then where I should retire based on some income stats.

Firstly, I wanted to know what state has the highest % of high income population, meaning where I’d have the highest chance of earning the most money.

While ugly at the moment, we can then filter it to look at one category at a time. Based on this, the ACT looks like it is trending downwards in low earners and trending higher in earners above $1000/week.

I then looked at the median income per state, to see if this hypothesis continued to be supported.

We can see that there’s a very dark blue spot where the ACT is, and I included a filter to allow us to progress throughout the years. Based on this, I would want to live & work in the ACT during my working years. But where to retire?

Based on the pension spend per state, it looks like NSW at the top is a steady contributor as the highest spender, while VIC in 2nd place is trending downwards. This could mean I would want to live in NSW, but it may be due to being the most populous state that the spend is high. I would need to explore this further in phase 2.

The Final Product

The first draft looked like this. It allowed us to explore the data a little bit, but further exploration must be done in phase 2 regarding pension spend per capita to realise actual insight into where I should retire. Based on the information however, it looks like working in the ACT would give me the best chance of being a high earner.

That concludes the challenge for day 3. This certainly proved to be my most difficult in finding something to explore, but I’ll be posting about our last challenge soon.

The Data School
Author: The Data School