And it’s finally the last day of the Dashboard Week, in which every day we had the task to create one dashboard. 


Today we had to use the OECD Better Life Index data set to find out which country suits us best to live in, based on some criteria that we could preselect. 

The data set had different indicators with its corresponding values for each country and the biggest challenge today was to finish by 2 pm and be ready to present by 3 pm. This was good on one side, as I wouldn’t have to work late, but also gave me less time to get a satisfactory result. 


Step 1

Before anything, I decided to normalise the data, so that the measures are more comparable. I used the formula (x – min(x)) / (max(x) – min(x)) and then multiplied by 10 each variable to have that scale. I also pivoted my data from a long to a wide table, so I have one column for each indicator – the layout I needed for Tableau. To perform these actions I use Alteryx, and this was my workflow:


Step 2

Once I imported the data into Tableau:

  1. I created different parameters, so a user can specify the importance/weight of each indicator.
  2. Multiplied each parameter by the value of each indicator
  3. Summed up all numbers 
  4. Created a bar chart for each country and ordered them in descending order by the sum of those ‘weighted’ numbers. 


Step 3

I was curious to see if the ‘Life Satisfaction’ indicator had any relationship with the indicators I selected, so I created some scatterplots. 




I brought my graphs in one dashboard, searched for some icons to give colour to my dashboard, and prepared for the presentation. This was the result (looks like I should move to Denmark):

Dana Voroshchuk
Author: Dana Voroshchuk