Employee SQL Analysis Project

Prepared by: Nazish Khalid

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🧠 Project Overview

This project demonstrates how to use SQL to analyze employee and department data using a variety of SQL concepts — from basic queries to advanced window functions.

The goal is to strengthen practical SQL skills while answering real-world business questions.

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📂 Dataset Description

We used two tables:

• Employees Table: Contains details like First Name, Last Name, Hire Date, Department ID, and Salary.
• Departments Table: Contains Department ID and Department Name (e.g., Sales, IT, Marketing).

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📌 What This Project Covers

🔹 Basic SELECT & WHERE

• Filter employees by department, hire date, and salary range.

🔹 ORDER BY Practice

• Sort employees by hire date and salary.

🔹 DISTINCT & Aggregates

• Count employees and calculate average salaries.

🔹 GROUP BY & HAVING

• Group salary data by department and apply filters.

🔹 JOINS

• Combine employee and department data using INNER and LEFT JOINs.

🔹 WINDOW FUNCTIONS (Advanced)

• Use RANK and MAX to analyze salary rankings and department-level insights.

🔹 Challenge Tasks

• Get top-paid employees per department, detect duplicate names, and extract year from hire dates.

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🛠️ Tools Used

• SQL (T-SQL / Azure Data Studio / Synapse)
• GitHub for version control and sharing
• Azure or local SQL environment

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📁 Files Included

• Zingo_Database_project.ipynb – Main SQL notebook
• SQL Project: Analyse Employee Data- Project Report
• SQLQuery_.sql – SQL Queries file
• README.md – This documentation file

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📬 Contact

If you have questions or suggestions, feel free to open an issue or contact me via GitHub.

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