Shopping Trends Analysis Project

Overview

This project involves the analysis of consumer behavior and shopping habits using a dataset obtained from Kaggle. The project includes SQL scripts for creating tables, triggers, and answering specific business questions based on the dataset.

Files

• table_creation.sql: Script for creating tables and importing data.
• business_questions.sql: Script for answering business questions.
• shopping_trends.csv: CSV file with shopping data (Note: The file used with the database is "shopping_trends.csv" not "shopping_trends_updated.csv" included in the Kaggle download).

How to Use

1. Setting up the Database:

   • Create SQLite database
   • Execute table_creation.sql in an SQLite environment to create tables and import data for the database.

2. Answering Business Questions:

   • Execute business_questions.sql to run SQL queries answering specific business questions.
   • View the results directly or uncomment specific sections to view intermediate results.

Dataset Source

The dataset used in this project is sourced from Kaggle. You can find it here. The CSV file included in this project is "shopping_trends.csv."

Details

table_creation.sql

• Creates tables for storing customer information, purchase history, item details, order information, and units sold.
• Defines triggers for updating the units sold table.
• Inserts data from the CSV file into the created tables.

business_questions.sql

Question 1

• Creates a view (subscriber_item_revenue) that identifies orders for accessories with promo codes or discounts made by subscribed customers.
• Orders the view by total revenue.

Question 2

• Identifies the top 10 most sold items among male customers.
• Displays total revenue produced from these items.
• Explores the correlation between the count of orders and total revenue.

Question 3

• Uses Common Table Expressions (CTE) to find the most used payment method by young adults in each season.
• Compares the most used payment method overall with the most used payment method in each season.

Conclusion

This README provides an overview of the project structure, files, and how to use the scripts to set up the database and answer business questions.