Sales Data Analysis & Forecasting — Sample Superstore

Internship Project — Algonive

📌 Overview

This project analyzes the Sample Superstore dataset to gain business insights and forecast future sales.
It includes data cleaning, exploratory data analysis (EDA), and sales forecasting using Prophet.

🔹 Steps Covered

• Import & clean dataset
• Exploratory Data Analysis (EDA)
  • Sales by Category, Sub-Category, Region, and State
  • Profitability analysis
  • Discount vs Profit impact
• Time series aggregation of monthly sales
• Forecasting using Facebook Prophet
• Evaluation with RMSE & MAPE
• Insights & business recommendations

📊 Tools & Libraries

• Python (Pandas, NumPy)
• Visualization: Matplotlib, Plotly
• Forecasting: Prophet
• Evaluation: Scikit-learn metrics

🚀 Results

• Analyzed 9,994 sales records
• Identified top categories, regions, and products by sales & profit
• Prophet model built to forecast monthly sales
• Achieved evaluation metrics (RMSE & MAPE) on last 6 months test data
• Visual dashboards for better decision-making

👨‍💻 Developed by: Akshat Singh
• Internship Project - Algonive