📊 HR Analytics Dashboard

📌 Project Overview

Employee attrition is one of the critical challenges organizations face, leading to loss of talent, increased hiring costs, and reduced productivity.
This project provides an HR Analytics Dashboard built in Power BI to analyze employee attrition trends and identify key insights that help HR departments make data-driven decisions.

The dashboard enables HR professionals to explore attrition rates by demographics, job roles, income levels, and working conditions, and ultimately improve retention strategies.

---

🎯 Objectives

• Understand overall attrition rate within the organization.
• Identify key factors influencing employee attrition (age, department, job role, salary, overtime).
• Provide actionable insights to HR teams for improving employee retention.
• Present findings in a visually interactive dashboard for easy decision-making.

---

📂 Dataset

• Source: HR Analytics dataset (cleaned & prepared for visualization)
• Records: ~1,400 employees
• Key Columns:
  • Attrition (Yes/No)
  • Age, Gender, Department, Job Role
  • Monthly Income
  • OverTime
  • Education
  • Job Satisfaction

---

📊 Dashboard Features

✔️ Attrition Overview – Overall attrition rate with breakdown
✔️ Demographics Analysis – Attrition by Age, Gender, Education
✔️ Job Roles & Departments – Comparison of attrition across job categories
✔️ Work Conditions – Effect of overtime and job satisfaction on attrition
✔️ Compensation Insights – Relation between income and attrition

---

📸 Dashboard Screenshots

🔹 Attrition Overview

🔹 Department Insights

🔹 Human Resources

🔹 Sales

🔹 Final Dashboard

---

💡 Key Insights

• Overall Attrition Rate: ~16% of employees left the organization.
• Age Factor: Younger employees (20–30 years) show higher attrition.
• Income Influence: Employees with lower monthly income are more likely to leave.
• Overtime Effect: Attrition is significantly higher among employees working overtime.
• Departmental Impact: Sales and R&D departments have higher attrition compared to HR.
• Job Satisfaction: Employees with low job satisfaction tend to leave at higher rates.

---

🛠️ Tools Used

• Power BI → Dashboard development & visualization
• Excel / CSV → Data preparation and cleaning
• DAX – Measures & calculated columns
• GitHub → Version control & project documentation

---

📈 Business Impact

• Helps HR managers identify at-risk employees early.
• Provides data-driven support for retention strategies.
• Reduces costs related to hiring and training new employees.
• Enhances workforce stability and organizational growth.

---

🚀 How to Use

1. Clone this repository:

   git clone https://github.com/SujiPrasanth/HR-Analytics-Dashboard.git