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HR Data Analysis

Overview

This repository contains the HR Data Analysis project . The analysis focuses on attendance data, providing insights into employee presence, work from home percentages, and sick leave percentages. The Power BI report named "HR Attendance Data Analysis" showcases various visualizations and metrics to facilitate a comprehensive understanding of the attendance patterns.

Table of Contents

  1. Project Description
  2. How to Access the Power BI Report
  3. Key Visualizations and Metrics
  4. Usage
  5. Contributing

Project Description

The HR Data Analysis project focuses on analyzing attendance data for employees in the given project. The Power BI report, named "HR Attendance Data Analysis," provides interactive visualizations and key metrics for better insights into employee attendance patterns.

How to Access the Power BI Report

  1. Clone this repository to your local machine:

    git clone https://github.com/hiteshchinu/HR-Attendance-Data-Analysis.git
    
    
  2. Open the "HR data analytics.pbix" file using Power BI Desktop.

  3. Explore the interactive report to gain insights into employee attendance data.

Key Visualizations and Metrics

  • Attendance Table: Detailed information about employee attendance, including Employee Code, Name, Date, Attendance Value, WFH Count, Month, SL Count, and Day of the Week.

  • Slicer for Months: Allows users to filter data based on selected months.

  • Attendance Percentage: Calculated percentage of attendance based on working days.

  • WFH Percentage: Calculated percentage of Work From Home (WFH) days with respect to working days.

  • Sick Leave Percentage: Calculated percentage of Sick Leave (SL) days with respect to working days.

  • Graphs for Presence %, WFH %, Sick Leave % by Date: Visual representations of attendance trends over time.

powerBI

Usage

Feel free to explore the Power BI report interactively. Utilize the slicer to analyze data for specific months and delve into key metrics and visualizations. If you have any questions or suggestions, please reach out.

Contributing

Contributions are welcome! If you have improvements or additional insights to share, please open an issue or submit a pull request.

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