This dashboard provides a general overview of key HR metrics, including total employees, attrition rate, average salary, and workforce distribution.
The analysis was conducted using SQL for data cleaning and transformation and Power BI for interactive data visualization.
Employee attrition is a critical challenge that affects organizational performance, productivity, and cost.
This project explores workforce data to understand patterns behind employee turnover and provide actionable insights for improving employee retention.
- Total employees analyzed: 1,470
- Attrition rate: 16%
The dataset includes:
- Age
- Department
- Job Role
- Monthly Income
- Job Satisfaction
- Overtime Status
- Training Hours
- Performance Rating
- SQL Server (Data Cleaning & Transformation)
- Power BI (Dashboard & Visualization)
- CSV Files (Data Source)
Data cleaning was performed using SQL to ensure data quality and consistency.
Key steps included:
- Imported data using SQL Server Import Flat File Wizard
- Merged multiple datasets using SQL JOIN
- Handled missing values
- Renamed columns for clarity
- Converted numerical values (0/1) into categorical values (Yes/No)
- Filtered dataset to ensure data quality
The Final dataset contained 1470 clean and valid employee records.
Explortary Data Analysis (EDA) was conducted to understand the structure and patterns in the dataset before building the dashboard.
Key metrics analyzed:
- Attrition distribution
- Employee distribution by department
- Job role analysis
- Overtime patterns
An intractive dashboard was bulit using Power BI to present insights clearly.
This section focuses on employee atrrition patterns across departments, job roles, and overtime status, helping identify areas with higher turnover.
This dashboard shows the distribution of employees across departments, job roles, and salary levels, providing insights into workforce structure.
This section highlights employee training hours and performance ratings, and explores their relationship with employee satisfaction and retention.
- Attrition is concentrated in specific job roles
- Research & Development has the highest attrition
- Overtime is associated with higher employee turnover
- Employees aged 29–31 show higher resignation trends
- Manager roles have the highest average salary
- Improve career development in high-attrition roles
- Reduce excessive overtime
- Strengthen employee training programs
- Enhance employee engagement strategies
- SQL Data Cleaning
- SQL JOIN & Data Merging
- Data Transformation
- Exploratory Data Analysis
- Power BI Dashboard Design
- Analytical Thinking
HR-Employee-Attrition-Analysis │ ├── README.md ├── HR_Employee_Attrition_Report.pdf │ ├── sql │ └── data_cleaning_queries.sql │ ├── dashboard │ └── attrition_dashboard.pbix │ └── images ├── overview.png ├── attrition.png ├── workforce.png └── training.png
Author: Mohammed Elmojtaba
I’m currently open to entry-level data analyst opportunities.
If you have any feedback, questions, or collaboration opportunities, feel free to reach out:
- 💼 LinkedIn: https://www.linkedin.com/in/mohamedelmojtaba
- 📧 Email: mohammed.elmojtaba@hotmail.com
- 💻 GitHub: https://github.com/M-elmojtaba-code
Your feedback is highly appreciated and will help me continue improving my skills in data analytics.