📊 Amazon Sales Report Analysis
📝 Project Overview This project analyzes Amazon sales data to extract meaningful insights that can help in business decision-making, sales trend identification, and customer behavior understanding. The analysis focuses on identifying top-performing products, seasonal demand patterns, and sales growth opportunities.
🎯 Objectives Clean and preprocess raw sales data for analysis.
Identify top-selling products and categories.
Detect seasonal trends and monthly performance patterns.
Calculate revenue, profit margins, and discount impacts.
Create visual dashboards for quick insights.
🛠️ Tools & Technologies Python: Data cleaning & analysis (Pandas, NumPy)
Power BI: Interactive dashboards & visualizations
Excel: Initial data exploration & calculations
Matplotlib & Seaborn: Data visualization in Python
📈 Key Insights Top 5 products contributed to over 40% of total revenue.
Sales spiked during festive seasons and holiday months.
Discounts increased sales volume but reduced profit margins.
Certain categories showed consistent year-round demand.
📂 Project Structure bash Copy Edit
Amazon_Sales_Report/
│── data/ # Raw & cleaned datasets
│── notebooks/ # Jupyter notebooks for analysis
│── visuals/ # Charts & graphs generated
│── dashboard/ # Power BI dashboard file
│── README.md # Project documentation
📊 Dashboard Snapshot
🚀 How to Use Clone the repository:
bash Copy Edit git clone https://github.com/ifuriouscoder/Amazon Sales.git
View the Power BI .pbix file for the interactive dashboard.
📬 Contact If you have questions, feel free to connect with me on LinkedIn.