Tourist Attraction Data Analysis

This project analyzes tourism trends from 2017 to 2021, focusing on visitor numbers, ratings, and attraction popularity during these years. The analysis explores how visitor behavior evolved over time, including changes in tourism patterns and key shifts in attraction visits.

Project Overview

The project includes:

• Analyzing visitor trends at famous tourist attractions.
• Exploring the relationship between attraction types, countries, and continents.
• Identifying the most popular attractions in each year.
• Understanding how global events, like the COVID-19 pandemic, impacted tourism during 2020.

Files in This Repository

• tourist_attraction_data.sql: Contains the table structure and data insertion queries.
• tourist_attraction_queries.sql: Includes queries used for data analysis and extracting insights.
• Tourist_Attraction_Data_Analysis.pdf: Documentation with analysis results, visualizations, and conclusions.
• visualizations/: Folder containing charts and graphs created using Excel to visualize key trends.

Tools Used

• SQL: To create and manage the database.
• Excel: For data visualization and chart creation.
• PDF: To present the analysis results in a structured format.

How to Use

1. Import tourist_attraction_data.sql into your SQL database to set up the schema and data.
2. Run the queries in tourist_attraction_queries.sql to analyze the data and generate insights.
3. Review the visualizations and documentation in the PDF to better understand the results.

License

This project is open-source and available under the MIT License.