HR Analysis

Project Overview

Utilized Power BI to analyze HR data by first loading and cleaning the dataset using Power Query. Created key metrics like headcount, average leave balance, and average salary using Power Pivot, while also adding custom columns like age group for better segmentation. Relationships between salary and education qualifications were analyzed, and advanced DAX calculations, such as cumulative headcount, were implemented. The final dashboard featured customized visuals and filters to highlight key insights, aiding in HR decision-making.

Objective

• How many people are in each job?

• Age spread of the staff

• Which jobs pay more?

• Top earners in each job

• Qualification vs. Salary

• Staff growth trend over time

• Leave balance analysis

Analysis Steps

Dashboard Link : PowerBI Dashboard

Following are the processes performed :

◈ Loaded data into Power BI and cleaned it with Power Query

◈ Created HR metrics like headcount, avg. leave balance, avg. salary etc. with Power Pivot

◈ Added columns to the data (like Employee's first name, age group etc.)

◈ Found relationships between salary and education qualification

◈ Used visual filters to see top / bottom paid staff in each job

◈ Customized visuals in Power BI (changing colours, axis, labels and legend)

◈ Advanced DAX calculations like cumulative headcount, leave balance more than 20 days