Power BI Employee Analysis Dashboard
Budget: $15 – $25 USD
Employee Data Analysis Dashboard – Power BI Project
In this project, I analyzed an Employee Dataset using Power BI to uncover key insights about workforce trends, salaries, diversity, and turnover rates.
The goal of this dashboard was to provide a clear overview of employee distribution, performance metrics, and HR-related indicators to support better decision-making within the company.
- Key Insights:
1. Turnover Rate Analysis:
Compared turnover rates by department, age group, and ethnicity to identify where employee turnover is highest.
2. Geographical Distribution:
Found the country with the highest number of jobs across all job roles.
3. Salary Insights:
Analyzed the total annual salary by age group.
Calculated the average annual salary by age and department.
Explored the sum, average, maximum, and minimum of annual salaries across all employees.
4. Workforce Composition:
Compared job titles across departments to understand workforce structure.
Analyzed employee status (active vs. exited).
Examined gender distribution to highlight diversity insights.
5. Age and Job Relationship:
Compared age variations across different job titles.
6. Hiring Trends:
Identified the month with the highest hiring rate.
7. Ethnicity Insights:
Compared ethnicity distribution across departments to assess diversity and inclusion.
In this project, I analyzed an Employee Dataset using Power BI to uncover key insights about workforce trends, salaries, diversity, and turnover rates.
The goal of this dashboard was to provide a clear overview of employee distribution, performance metrics, and HR-related indicators to support better decision-making within the company.
- Key Insights:
1. Turnover Rate Analysis:
Compared turnover rates by department, age group, and ethnicity to identify where employee turnover is highest.
2. Geographical Distribution:
Found the country with the highest number of jobs across all job roles.
3. Salary Insights:
Analyzed the total annual salary by age group.
Calculated the average annual salary by age and department.
Explored the sum, average, maximum, and minimum of annual salaries across all employees.
4. Workforce Composition:
Compared job titles across departments to understand workforce structure.
Analyzed employee status (active vs. exited).
Examined gender distribution to highlight diversity insights.
5. Age and Job Relationship:
Compared age variations across different job titles.
6. Hiring Trends:
Identified the month with the highest hiring rate.
7. Ethnicity Insights:
Compared ethnicity distribution across departments to assess diversity and inclusion.