BackBRAJESH KUMAR
01 — Case Study
HR Analytics Dashboard
Understanding why employees leave — and what the data says about keeping them.
Power BIExcel
Dashboard Preview
[ADD INFORMATION: Upload dashboard screenshot here]
01
The Problem
HR teams often sit on large amounts of employee data but struggle to translate it into meaningful patterns around attrition, demographics, and performance. This project builds an interactive Power BI dashboard to surface those patterns and support strategic workforce decisions.
02
The Dataset
Source
[ADD INFORMATION: Dataset source — e.g., Kaggle HR Analytics Dataset / Internal HR records]
Type
Structured employee records (Excel/CSV)
Approximate Size
[ADD INFORMATION: Number of rows — e.g., ~1,400 employee records]
Key Fields
Employee IDAgeGenderDepartmentJob RoleAttritionYears at Company[ADD INFORMATION: Additional fields]
03
Objectives
- 01Understand the overall attrition rate across the organization
- 02Identify which age groups and departments have the highest attrition
- 03Analyze gender distribution across roles and departments
- 04Surface patterns in employee tenure and retention
- 05[ADD INFORMATION: Additional business questions explored]
04
Data Cleaning
- ◆Handled missing values in key fields
- ◆Standardized categorical fields (e.g., department names, job roles)
- ◆Created calculated columns for attrition rate and age groups
- ◆[ADD INFORMATION: Specific transformations performed]
05
Key Insights
01
[ADD INFORMATION: Key attrition finding]
[ADD INFORMATION: Supporting detail and what it means for the business]
02
[ADD INFORMATION: Age group pattern]
[ADD INFORMATION: Which age groups showed highest/lowest attrition and why this matters]
03
[ADD INFORMATION: Gender ratio insight]
[ADD INFORMATION: Gender distribution finding across roles or departments]
06
Business Recommendations
- 01[ADD INFORMATION: Business recommendation based on attrition analysis]
- 02[ADD INFORMATION: Suggested HR intervention based on demographic findings]