https://github.com/riyamittal12/attrition-analysis
https://github.com/riyamittal12/attrition-analysis
analytics excel powerbi sql
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/riyamittal12/attrition-analysis
- Owner: Riyamittal12
- Created: 2025-02-18T10:13:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-18T10:30:16.000Z (over 1 year ago)
- Last Synced: 2025-11-23T01:03:43.616Z (7 months ago)
- Topics: analytics, excel, powerbi, sql
- Homepage:
- Size: 266 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Attrition Analysis
Welcome to the **Attrition Analysis Project**! This repository contains datasets and reports analyzing employee attrition across different departments. Using Power BI and data analytics, we uncover key insights into workforce trends, helping businesses make informed HR decisions.
## 📁 Repository Contents
### 🔹 Attrition Data & Reports
1. **HR.pdf** - Power BI report visualizing attrition trends in HR, Research & Development, and Sales.
2. **HR_Analytics.csv** - Dataset containing employee details and attrition factors.
### 🔹 Orders & Business Data
3. **Orders.csv** - Customer orders and transactions data for business analysis.
4. **Details.csv** - Additional information related to orders.
### 🔹 Background Image
5. **BG12.jpg** - A visually appealing background image for presentations and dashboards.
---
## 📊 Attrition Analysis Insights
### 🔍 Key Findings:
- **Total Employees Analyzed:** 1470
- **Overall Attrition Rate:** 16.1%
- **Average Employee Age:** 37 years
### 🔍 Department-wise Attrition Rates:
- **Human Resources (HR):** High attrition due to career growth limitations and job transitions.
- **Research & Development (R&D):** Moderate attrition, mostly influenced by salary expectations.
- **Sales:** Highest attrition rate, driven by high-pressure targets and job switching.
📌 *For a detailed breakdown, check out the Power BI dashboard in `HR.pdf`.*
---
## 🚀 How to Use
1. Clone the repository:
```sh
git clone https://github.com/your-username/your-repository.git
2. Open datasets in Excel, Power BI, or Python for analysis.
3. Use the `HR.pdf` report for insights and visualization.