Today’s challenge was centered around World Happiness Data and Power BI. The data provided was a good starting point, but I felt it was essential to look for additional data sources to contribute to the analysis. After conducting some research, I discovered fascinating datasets on tertiary education levels per country and the number of individuals living in urban areas. To determine the percentage of the population living in cities, I included the population data in my analysis.

The primary objective of creating this dashboard was to:

  1. Identify if there is a correlation between urbanization and the happiness index.
  2. Determine if there is a correlation between the percentage of individuals with tertiary education and the happiness index.

To achieve these goals, I created an Alteryx workflow, which I then loaded into Power BI. After analyzing the data, I established the following metrics:

  • Average percentage of the urban population.
  • The correlation between urban population and the happiness index.
  • Scatter plot depicting the relationship between urban population percentage and the happiness index.
  • Dynamics of urban population changes.
  • Average percentage of individuals with tertiary education.
  • Correlation between tertiary education level and happiness index.
  • Scatter plot depicting the relationship between education percentage and happiness index.

In conclusion, it is evident that education and urbanization are significant factors that can predict a country’s happiness index. Countries with a higher percentage of individuals who complete tertiary education tend to have a higher happiness index. Similarly, countries with a higher urban population also exhibit a higher happiness index. The dashboard I created shows the correlation between these factors and the happiness index, which can be useful in making informed decisions that promote well-being.

Veronika Varaksina
Author: Veronika Varaksina

Meet Veronika, a dynamic and adaptable individual with a diverse background in economics, accounting, finance, and data analytics. Veronika pursued a Bachelor’s degree in Economics and gained valuable experience in financial analysis, budgeting, and forecasting while working for five years in accounting and finance. However, she soon realized her passion for data analytics and decided to pursue a postgraduate degree in Analytics at Victoria University. Throughout her academic journey, Veronika honed her skills in data visualization, statistical modeling, and machine learning. Her expertise earned her a spot in the highly competitive Data School program, where she further continues to expand her skills in data analysis.