Introduction

In this project, a comprehensive analysis of the Zomato dataset was conducted using SQL. The aim was to gain insights into various aspects of the restaurant industry, customer preferences, and regional restaurant distribution.

Dataset Overview

The Zomato dataset comprises a wealth of information, including details about restaurants, cuisines, user reviews, locations, and more. Understanding the dataset’s structure and the available variables is the first step in the analysis.

Data Exploration

In this phase, the dataset was explored to identify key patterns and trends. SQL queries were employed to retrieve basic statistics, such as the total number of restaurants, cuisines, and user reviews.

Popular Cuisines

One of the primary objectives of the analysis was to identify the most popular cuisines among restaurants. SQL queries were used to determine the cuisines that appeared most frequently in the dataset.

Customer Preferences

The dataset provided valuable information about customer reviews and ratings. SQL queries were applied to uncover customer preferences by examining the highest-rated restaurants, the distribution of ratings, and common factors contributing to positive reviews.

Geographic Insights

Understanding the regional distribution of restaurants is essential. SQL queries were used to determine which areas had the highest concentration of restaurants, helping to identify potential market opportunities.

Conclusion

The analysis of the Zomato dataset using SQL has provided valuable insights into the restaurant industry. These insights encompass popular cuisines, customer preferences, and regional variations, which can be leveraged for strategic decision-making and understanding the dynamics of the restaurant business.