End-to-end SQL analysis focused on revenue distribution, customer retention, and structural risk in an e-commerce business.

📊 Project Overview

This project explores how revenue is distributed across customers and product categories in an e-commerce marketplace, with a focus on identifying structural risks and retention dynamics.

Using SQL, the analysis uncovers key patterns that impact long-term business sustainability.

🎯 Business Problem

E-commerce companies often grow revenue without understanding:

• How concentrated their revenue really is
• Whether they depend on a small group of customers
• The impact of customer churn
• Risks associated with product category dependency

This project addresses these challenges through a structured, data-driven approach.

📂 Dataset

• Source: Olist Brazilian E-commerce Dataset
• Type: Transactional relational data

Tables used:

• orders
• order_items
• customers
• products

⚙️ Analytical Approach