E-commerce Data

📊 E-Commerce Analytics Dataset

This dataset simulates the backend database of an e-commerce platform. It is designed for practicing SQL, data analysis, business intelligence, and analytics workflows.

The dataset includes structured relational tables that model real-world online retail operations such as customer management, product cataloging, order processing, returns, and revenue tracking.

📁 Tables Included

1. customers - Contains customer demographic and account information. Useful for cohort analysis, repeat customer tracking, and customer lifetime value (CLV) calculations.

2. categories - Product category hierarchy for organizing inventory. Supports category-wise revenue and demand analysis.

3. products- Product details including pricing and cost information. Enables margin analysis and profitability tracking.

4. order_items - Transactional order-level data linking customers and products. Used for sales analysis, basket analysis, and order value metrics.

5. returns - Return and refund records. Supports return rate calculation, loss analysis, and product quality evaluation.

🔎 What You Can Practice

• SQL joins and subqueries
• Aggregations (SUM, AVG, COUNT)
• Window functions
• Revenue and profit analysis
• Customer segmentation
• Return rate and refund impact analysis
• Dashboard creation (Power BI / Tableau)
• Data cleaning and preprocessing