This project analyzes Blinkit sales, customer, product, and delivery data using MySQL. The objective is to transform raw operational data into actionable business insights through data cleaning, database design, and analytical SQL queries.
- Analyze overall sales performance
- Identify top-performing products and categories
- Measure customer activity and purchasing behavior
- Evaluate order trends and average order value
- Examine delivery performance metrics
- Generate insights to support business decision-making
- MySQL
- SQL
- Relational Database Design
- Data Cleaning
- Business Analytics
The project uses multiple related tables:
- Customers
- Orders
- Order Items
- Products
- Delivery Performance
Primary keys and foreign keys were implemented to maintain data integrity and establish relationships between tables.
- Removed duplicate records
- Standardized text fields using TRIM()
- Converted date fields into proper date formats
- Applied primary key constraints
- Created foreign key relationships
- Filtered invalid records
- Total Revenue
- Total Orders
- Total Customers
- Average Order Value (AOV)
- Product Performance
- Category Revenue
- Customer Activity
- Delivery Performance
- Revenue is distributed across multiple products rather than being concentrated in a single item.
- Essential product categories contribute significantly to overall sales.
- Customer acquisition exceeds active ordering behavior, indicating opportunities for customer retention.
- Average Order Value (AOV) provides a benchmark for evaluating sales performance.
- Blinkit_Analysis.sql
Sumedh Patil