We are on day 4 of the dashboard week, more than halfway over. Must reiterate that I am loving it.
We had to use any dataset from the Gapminder website. This is going it be very different from all our previous dashboard day’s, as Gapminder has data on various metrics and we could choose any of the available as our base dataset. On previously days, all of us mostly build dashboards from the same dataset. So, it is going to be interesting as to what datasets my fellow Data Schoolers were to choose.
The brief was not over yet, the curve-ball today was, we could not use Alteryx to prep our data. This meant we had to use Tableau Prep. Though Tableau Prep is not nearly as good as Alteryx but it had some strong functionality and really good recent updates. Also, I did not miss Alteryx much as the data set was fairly clean.
I kept exploring the website, until I decided to pick Electricity data. I imagined it will be great to see correlation with some key metrics on the data available. So, I started downloading data on other key metrics like Income per capita, Life Expectancy, etc. I then used Tableau prep to pivot, rename and join the data. Electricity generated per capita was my base dataset, and I have left-joined all other data.
With the dashboard I initially went with a separate scatter plot correlating each of the factors, with population on Size. However, it felt a bit squished and details were hard to read unless I increased the size of my dashboard. So, I decided to fix Electricity generated on Y axis and parameterised other factors. Currently the data on my scatter plot was filtered for a single year. I also wanted to capture the trend overtime, So I went with sparklines for each of the factors.
Click on the picture to go to the dashboard.
