This project demonstrates SQL-based data analysis using a relational database designed for a logistics and delivery management system.
The goal of this project is to extract business insights from operational data using structured SQL queries.
The database includes the following key entities:
- Customer
- Orders
- Shipment
- Package
- Invoice
- Payment
- Branch
- Employee
- Delivery_Segment
- Route
- Vehicle
The schema is fully normalised to Third Normal Form (3NF) and implemented in MySQL.
This project answers analytical questions such as:
- How many shipments are processed per branch?
- What is the total revenue generated?
- Which invoices remain unpaid?
- Which customers generate the highest revenue?
- What is the average shipment value?
- MySQL
- SQL (Joins, Aggregation, Group By, Filtering)
- phpMyAdmin
- Relational Database Design
- Relational database querying
- Multi-table joins
- Aggregation functions
- Data summarisation
- Business insight extraction
- Identified total shipments handled per branch
- Calculated total revenue generated
- Detected unpaid invoices for financial monitoring
- Analyzed shipment status distribution This project forms part of my journey toward becoming a Data Analyst.
- Add data visualisation using Python (Matplotlib / Seaborn)
- Implement dashboard using Power BI or Tableau
- Optimise queries using indexing strategies
- Deploy database to cloud environment