Walmart Sales Data Analysis Using SQL

This project involves an in-depth analysis of Walmart's sales data using SQL. The primary objective is to extract actionable insights to enhance business strategies, optimize sales performance, and understand customer behavior.

Table of Contents

• Introduction
• Dataset Description
• Project Objectives
• Tools and Technologies
• Setup and Installation
• Data Analysis Process
  • Data Cleaning
  • Feature Engineering
  • Exploratory Data Analysis (EDA)
• Key Findings
• Contributing
• License

Introduction

Analyzing sales data is crucial for large retail chains like Walmart to make informed decisions. This project utilizes SQL to delve into Walmart's sales transactions, aiming to identify trends, patterns, and insights that can drive business improvements.

Dataset Description

The dataset comprises sales transactions from three Walmart branches located in Mandalay, Yangon, and Naypyitaw. It includes 1,000 rows and 17 columns, detailing information such as:

• Invoice ID: Unique identifier for each transaction
• Branch: Branch where the sale occurred
• City: City of the branch
• Customer Type: Type of customer (e.g., Member, Normal)
• Gender: Gender of the customer
• Product Line: Category of the product sold
• Unit Price: Price per unit of the product
• Quantity: Number of units sold
• Tax (5%): Tax amount for the purchase
• Total: Total amount including tax
• Date: Date of the transaction
• Time: Time of the transaction
• Payment: Payment method used
• COGS: Cost of goods sold
• Gross Margin Percentage: Gross margin percentage
• Gross Income: Gross income from the sale
• Rating: Customer rating of the purchase

Project Objectives

The main goals of this analysis are to:

• Identify top-performing branches and products
• Analyze sales trends across different product categories
• Understand customer demographics and purchasing behavior
• Evaluate the effectiveness of various payment methods
• Provide actionable recommendations to optimize sales strategies

Tools and Technologies

• Database Management System: MySQL
• Query Language: SQL
• Data Visualization: (Optional) Tools like Tableau or Power BI for visual representation of findings

Setup and Installation

1. Clone the Repository:

   git clone https://github.com/erfan-seifi/WalmartDataAnalysis_SQL.git
   

2. Import the Dataset:: Use the provided CSV file in the Dataset directory. Import the data into your MySQL database. Ensure the table schema matches the dataset structure.

3. Execute SQL Scripts::

   Open the main.sql file. Run the scripts in your SQL environment to perform data cleaning, feature engineering, and analysis.