Today we spent our time analyzing government data on the Gender Pay Gap in the UK. As I learned today apparently every company above 250 employees has to report the percentage of differences between mean/median hourly pay and bonus payments.
Now three days into Dashboard Week I feel that I’m losing a bit of creativity and inspiration to think of something new every day. But of course I still tried to come up with something.
The data was a bit trickier today as the downloaded .csv file seemed to have restructured itself and some rows splitted where they shouldn’t have. Alteryx wasn’t too helpful with this but luckily we could solve the issue in Tableau Prep.
I grouped the companies in the data source by industrial sector to have another layer of granularity in my visualization. I lost some companies there which had reported more than one sector but still had more than enough to work with. I first thought of some sort of a scatter plot where each dot represents a company. I remembered that at some point in training we learned to use the RANDOM() function to randomly returns a value between zero and one. This way when I put company on the Details mark without a measure on the rows shelf it distributes the dots randomly and this way allows to have a better look at all the companies instead of receiving a straight line of dots.
I added a parameter to allow the user to switch between different payment metrics and did a bit of color coding to differentiate values above and below zero. Next to some other filters I added a small text to describe how the dashboard works and what you can see on it.
You can see the final result on my Tableau Public Profile.