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Employee SQL Analysis Project

Prepared by: Nazish Khalid

🧠 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.

📂 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).

📌 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.

🛠️ Tools Used

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

📁 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

📬 Contact

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