Project Overview

The Employee Attrition Insights Dashboard analyzes workforce trends using data from 10,000 employees sourced from Kaggle - Employee Attrition Prediction Dataset. Built with Power BI, it offers dynamic filters to explore attrition patterns by Department, Job Role, and Gender, transforming raw data into actionable insights.

Key Insights:
- Attrition Rate: 19.97% of employees left the company.
- Average Age: 39.56 years, showing attrition impacts mid-career professionals.
- Average Tenure: 14.94 years, highlighting turnover among long-term employees.
- By Department: Highest attrition in Finance & Marketing, lowest in HR.
- By Job Role: Assistants & Analysts face the highest attrition; Managers the lowest.
- By Gender: Similar attrition rates for Males (1,005) and Females (992), indicating gender is not a key driver.
- Work Environment Satisfaction: Employees who left had slightly lower satisfaction (2.46) vs. those who stayed (2.49).
- Job Involvement: Surprisingly, those who left had higher involvement (2.53) than those who stayed (2.49), suggesting engagement alone doesn’t guarantee retention.

Business Impact:
- Targeted Retention Strategies: Focus on high-risk roles/departments like Finance & Marketing.
- Beyond Engagement: High involvement doesn’t prevent attrition—factors like growth opportunities and workload matter.
- Data-Driven Decisions: Gender-neutral attrition shifts focus to other influential factors.

Tech Stack:
- Power BI for visualization
- CSV Data Wrangling for data preparation
- Interactive Slicers for dynamic analysis

🔗 Dataset Link: https://www.kaggle.com/datasets/ziya07/employee-attrition-prediction-dataset
🔗 View the Dashboard: https://www.youtube.com/watch?v=smQMs_kf-3Y