Sales Data Analysis – Customer & Product Insights (v1.0.0)

🚀 Initial Release – Sales Data Analysis: Customer & Product Insights

This release includes:

• ✅ Cleaned Superstore dataset (Cleaned_Superstore.csv)
• ✅ Data cleaning & preprocessing (data_cleaning_processing.ipynb)
• ✅ Exploratory Data Analysis with visualizations (EDA.ipynb)
• ✅ SQL-based insights for business decisions (SQLqury(project02).ipynb)
• ✅ Final presentation slides (masai_project_presentation.pptx)

🔍 Key Features:

• Data cleaning (date conversion, null/duplicate removal, new features)
• EDA with Pandas, Matplotlib, Seaborn
• SQL queries for customer, product, and regional insights
• Business insights on profitability, discounts, and seasonal sales

💡 Highlights:

• Technology category is the most profitable
• West region leads in sales & profits
• Central region shows lowest profit margins
• High discounts often cause negative profits
• Peak sales observed during Nov–Dec