This repository is a complete SQL-based data analysis project that demonstrates the process of designing, creating, and querying relational databases from scratch using real-world datasets. It combines employee profile data with order transaction data to perform meaningful business insights using SQL Server.
The project begins with importing two datasets from CSV files:
employee_data — containing information such as employee_id, first_name, last_name, department, salary, joining_date, and age.
orders — containing order_id, customer_id, book_id, order_date, quantity, total_amount, and a linking employee_id field to establish relationships between orders and employees.
Core activities and skills demonstrated:
1.Database Design: Creating normalized tables in SQL Server with appropriate data types and primary keys.
2.Data Import: Loading CSV data into SQL tables for analysis.
3.Data Retrieval & Filtering: Using SELECT, WHERE, ORDER BY, and GROUP BY to extract specific insights.
4.Joins & Relationships: Applying INNER JOIN, LEFT JOIN, RIGHT JOIN, and SELF JOIN to combine data across tables and within the same table.
5.Advanced Querying: Combining joins with aggregate functions (SUM, AVG, MAX, COUNT), subqueries, and conditional filtering.
6.Business Insights: Finding top-performing employees, department-wise sales totals, high-value orders, and sales trends over time.
7.Views Creation: Defining reusable SQL Views to simplify complex queries, such as high_salary_employees and it_department_orders.
8.Performance Optimization: Adding indexes to improve filtering and join performance.
9.SQL Best Practices: Writing clean, readable, and well-structured queries for maintainability.
Learning Outcomes:
1.Understanding relational database concepts and normalization.
2.Hands-on experience with SQL Server for real-world business scenarios.
3.Proficiency in writing JOIN queries to merge datasets for analytics.
4.Ability to transform raw CSV files into a relational database and extract valuable insights.
5.This project is ideal for anyone looking to strengthen their SQL skills, practice relational database design, or prepare for data analyst and business intelligence roles. The code and queries here can serve as a reference for academic purposes, portfolio building, or interview preparation.