Today, we delved into the superannuation data of Australia, which proved to be more complex and challenging than yesterday’s data. The first reason is that the data contains 13 tables. I need to find out which table I need to use and which column.

The key challenge was the Membership demographic data was particularly difficult to wrangle due to the structure of the data fields, which included both a title and a subtitle. The subtitle, representing the age group. such as ‘<25′, ’25 to 34’, had the same field name for age group, but the measure was different. Thankfully, our coach Ross helped me solve this issue. With his guidance, I am able to adjust the structure of the data fields and create a clean, usable dataset that could be analyzed effectively in Tableau.

Moving on to the visualizations, I discovered some intriguing insights about the gender divide in superannuation. Specifically, the average account balance for males was consistently higher than that for females, regardless of whether the fund was an industry or retail type. This finding highlights the persistent gender inequality in the Australian superannuation system.

And also, in recent years, there has been a noticeable trend of Australians moving away from retail super funds and towards industry super funds. This shift is particularly pronounced among younger Australians, who are increasingly opting for industry super funds. This trend is likely due to a range of factors, such as lower fees and charges, ethical and sustainable investing options, and better long-term returns.

Overall, today was a challenging but rewarding day. We were able to gain a better understanding of the complexities of the superannuation system.

The Data School
Author: The Data School