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Cover image for IBM HR Analytics Dashboard — Power BI + Python Project
Nivesh Bansal
Nivesh Bansal

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IBM HR Analytics Dashboard — Power BI + Python Project

Author: Nivesh Bansal
Tech Stack: Power BI | Python (Pandas, Matplotlib) | Power Query | DAX | Excel

🔗 Explore the project on GitHub: IBM HR Dashboard Repo

🔗 Explore the project on LinkedIn: IBM HR Dashboard Post


📊 Project Overview

I'm excited to share my latest IBM HR Analytics Dashboard, built to explore and visualize insights from the IBM HR Analytics Dataset (Kaggle).

This project focuses on understanding key human resource trends — including attrition, job satisfaction, salary distribution, employee engagement, and performance.

The dashboard is designed to help HR professionals and data analysts uncover insights that drive data-informed decisions.

Dashboard

Dashboard

🧠 Objectives

  • Analyze employee attrition and performance trends
  • Understand salary distribution by department and job role
  • Visualize travel frequency and demographic patterns
  • Monitor key HR KPIs like job satisfaction, training, and promotions
  • Highlight the relationship between employee involvement and retention

💡 Key Features

Department-wise Analysis — Breakdown of Research, Sales, and HR departments
Travel Frequency Insights — Compare frequent vs. rare travelers
Salary & Income Visualization — Hourly, Monthly, and Annual income tracking
Attrition & Performance Dashboard — Identify high-performing roles and retention risks
Gender Distribution — Insights into diversity within the organization


⚙️ Tools & Technologies

  • Power BI — Interactive visual dashboard creation
  • Python (Pandas, Matplotlib) — Data preprocessing and visualization
  • Power Query & DAX — Data transformation and calculated measures
  • Excel — Data cleaning and structure setup

📂 Dataset Source

Dataset: IBM HR Analytics Employee Attrition & Performance – Kaggle


📈 Insights Discovered

  • Research & Development department has the highest employee count
  • Rare Travelers form the largest segment of the workforce
  • Average Employee Age: 36 years
  • Average Performance Rating: 3 / 4
  • Most employees have 0 previous companies worked (low external mobility)

🧩 Conclusion

This project demonstrates how data analytics empowers HR management to make evidence-based decisions.
By analyzing workforce data visually, HR teams can improve retention, engagement, and overall productivity.

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