Welcome to the World Happiness Report SQL project! 🌎 In this project, we will dive into the fascinating realm of global happiness and explore the data from the World Happiness Report. We'll use SQL queries to extract valuable insights about happiness ranks, scores, economy GDP, family support, trust, and more from various countries. Additionally, we have created a Power BI report to visually represent and interact with the analysis results.
The World Happiness Report provides a comprehensive view of happiness levels and factors contributing to well-being in different countries. Our project focuses on utilizing SQL queries to perform data analysis and gain a deeper understanding of the relationships between happiness metrics. We have also enhanced the project by creating an interactive Power BI report to visualize our findings.
We begin by acquiring the World Happiness Report dataset, which contains information about happiness ranks, scores, and various contributing factors such as GDP per capita, social support, life expectancy, freedom, trust, and generosity for different countries and years.
Our analysis involves examining trends, patterns, and correlations within the dataset. We will use SQL queries to aggregate and summarize the data, enabling us to identify countries with the highest and lowest happiness scores, explore the impact of different factors on happiness, and compare happiness across regions.
The heart of our project lies in crafting SQL queries to extract valuable information from the dataset. We will write queries to:
- Calculate average happiness scores and ranks.
- Group countries by regions and analyze regional differences in happiness.
- Rank countries based on specific factors like economy GDP, family support, trust, etc.
- Identify countries with the most significant improvement or decline in happiness over time.
To enhance the project's visualization capabilities, we have created an interactive Power BI report. This report provides an engaging way to explore the analysis results through charts, graphs, filters, and dynamic visuals.
To better understand our findings, we'll visualize the results of our SQL queries using charts, graphs, and maps. Visualizations will help us communicate trends effectively and make the analysis more engaging.
In our conclusion, we'll summarize the key takeaways from our data analysis and Power BI report. We'll discuss the countries that excel in specific happiness factors, identify any interesting trends, and reflect on the overall picture of global happiness as revealed by the World Happiness Report data.
Feel free to explore the SQL scripts, Power BI report, and queries in this repository to gain insights into the World Happiness Report and the factors that contribute to happiness around the world. If you have any questions, suggestions, or ideas, please don't hesitate to reach out!
Let's journey through the data and Power BI to uncover the secrets of happiness and gain a better understanding of what makes the world a happier place! 🌟😄🌍
(Note: This project is for educational and analytical purposes only. The World Happiness Report is a serious study, and our analysis aims to contribute to understanding the data within the report.)