HR Dashboard Project

Welcome to the HR Dashboard Project repository! 🚀
This project showcases the end-to-end process of generating, transforming, and analyzing HR data through a fully functional dashboard.

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📖 Project Overview

This project involves:

1. Synthetic Data Generation — Creating a realistic HR dataset of 8,950 employees using Python and Faker.

2. Data Transformation & Cleansing — Validating and standardizing employee details (dates, salaries, demographics).

3. Dashboard Development — Building a Tableau dashboard to visualize key HR insights.

🎯 Core Focus Areas:

• Python Data Generation

• Data Cleansing and Transformation

• Data Modeling for Analytics

• HR Metrics Visualisation

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🚀 Project Requirements

Objective

To provide HR managers with a comprehensive analytical dashboard for workforce insights — combining summary-level metrics and individual employee records.

📊 Dashboard Design

Summary View

Divided into three main analytical sections:

🧾 Overview

• Total number of hired, active, and terminated employees

• Trends of hires vs terminations over the years

• Department- and job title-wise employee count

• Comparison of HQ (New York) vs branch offices

• Distribution of employees across cities and states

👥 Demographics

• Gender ratio visualization

• Age and education level distributions

• Employee count by age group and education level

• Correlation between education level and performance ratings

💰 Income Analysis

• Salary comparisons across education levels and genders

• Correlation between age and salary within departments

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📂 Repository Structure

HR-Dashboard-project/
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├── mockups.drawio/                     # Draw.io file for dashboard layout
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├── generate_data.ipynb/                # Python script to generate dataset
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├── README.md                           # Project overview and instructions
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├── LICENSE                             # License information for the repository

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🛡️ License

This project is licensed under the MIT License. You are free to use, modify, and share this project with proper attribution.

🌟 About Me

Hi there! I'm Ankit Khareshiya. I’m a student who likes working with data.

Feel free to connect with me on the following platforms: