DataCamp-Project

Python + Tableau project analyzing retail sales, profitability, and discount impact.

Retail Sales Analysis Project

Overview

This project was completed as part of the MetBrains 7-Day DataCamp. My role was to analyze the dataset using Tableau to create meaningful dashboards, perform data exploration using Python to uncover deeper insights, and build a machine learning model to predict sales trends. It explores retail sales data using Python for data cleaning and analysis, and Tableau for interactive dashboard visualization.

Tools Used

• Python (Pandas, Matplotlib, Seaborn, sklearn)
• Tableau (for dashboards and storytelling)

Key Insights

• Discounts above 20% often lead to negative profit.
• Consumer segment dominates online sales.
• Regional differences in category profitability.

Repository Contents

• Sales Data EDA & Predictive Analysis (1).ipynb → Python notebook with data cleaning and analysis
• Tableau.png → Link to Tableau dashboard
• README.md → Project documentation