Objective

The objective of this project is to analyze the Olympics 2024 dataset to extract meaningful insights and trends that provide a comprehensive understanding of country-wise performance, athlete achievements, and participation patterns. This analysis aims to predict outcomes, identify key performance indicators, and present the findings through an interactive Power BI dashboard for easy interpretation and decision-making.

Key Findings & Analysis

1 . Data Collection :

• Method : Data was collected using web scraping, leveraging Python libraries such as BeautifulSoup and Selenium to extract relevant information from publicly available sources.
• Challenges : Ensuring the scraping script handled dynamic web pages and large data volumes efficiently. I also implemented checks to avoid duplicate or incomplete records.

2 . Data Cleaning and Preprocessing :

• Removed inconsistent or missing values to ensure data accuracy.
• Standardized formats for dates, numerical values, and country codes.
• Filtered irrelevant information to focus on data essential for the analysis.
• Applied transformations to normalize the dataset for better compatibility with Power BI.

3 . Data Analysis and Insights :

• Medal Distribution : Visualized the total medal tally by countries and sports to identify top-performing nations.
• Athlete Performance Trends : Analyzed individual performances over time to highlight standout athletes.
• Participation Overview : Explored the number of participants across countries, highlighting growth or decline in representation.
• Historical Context : Compared data from previous Olympics to identify trends and predict possible outcomes for 2024.

4 . Dashboard Features :

The interactive Power BI dashboard is the core of this project. Features include :

• Dynamic Filtering : Allows users to view data by sport, country, or medal type.
• Custom Visualizations : Charts, maps, and tables were designed to simplify complex data trends.
• Predictive Analytics : Implemented to provide a forecast of potential medal counts based on historical trends.

5 . Tools and Technologies Used :

• Web Scraping and Preprocessing : Python (BeautifulSoup, Pandas, NumPy)
• Visualization : Power BI and DAX for advanced calculations.
• Data Transformation : Power Query for data reshaping and integration.

Conclusion

This project successfully provides a data-driven perspective on the Olympics 2024, highlighting valuable insights into medal distribution, athlete performance, and country-wise participation. The interactive Power BI dashboard enables users to explore the data dynamically, offering an intuitive way to uncover trends and forecasts. This end-to-end project demonstrates my skills in data collection, cleaning, analysis, and visualization, reinforcing the importance of data analytics in understanding large-scale events like the Olympics.

Code link :

Click here to access the code

Live Dashboard :

Click here to access dashboard