Presence Insights of Employees

This project provides insightful data analysis on employee attendance and presence, including work-from-home (WFH) data, sick leave records, and presence excluding holidays. The analysis spans a three-month period (April, May, June 2022) and is visualized using Power BI to help HR managers understand trends and optimize workforce management.

Table of Contents

• Project Overview
• Data Source
• Project Structure
• Power BI Visualization
• Key Insights
• Technologies Used
• How to Run
• Learning Experience

Project Overview

This project analyzes employee presence data over three months (April, May, June 2022), with a focus on:

• Work-from-home (WFH) data
• Sick leave (SL) records
• Presence excluding holidays

The goal is to provide HR managers with valuable insights into employee attendance patterns across different days of the week, work types, and absences.

Data Source

The dataset for this project was sourced from the Codebasics YouTube channel, where I followed the steps and methodologies to perform this analysis.

Project Structure

The repository contains:

• Dataset: The CSV file includes employee attendance, WFH, and sick leave data.
• Power BI Report: A .pbix file with interactive visualizations for the data.
• README.md: The project overview and instructions.

Power BI Visualization

The Power BI report provides detailed visualizations, including:

• Overall Attendance Metrics: Showing the percentages for WFH, presence, and sick leave across all employees.
• Presence Percentage by Date: Highlighting attendance trends over the months of April, May, and June 2022.
• Work-from-Home (WFH) Percentage by Date: Displaying WFH patterns during the same period.
• Sick Leave Percentage by Date: Visualizing the trends in sick leave.
• Attendance Breakdown by Day of the Week: Offering insights into presence, WFH, and SL variations across different weekdays.

These dashboards allow HR managers to explore trends in employee presence and attendance, and they can easily filter data by date and department.

Key Insights

1. Presence Trends: The presence percentage is consistently above 90%, with minor fluctuations during weekdays.
2. WFH Trends: WFH shows a steady increase over the three months, particularly on Fridays.
3. Sick Leave: Sick leave remains low but peaks slightly on Mondays and Tuesdays.
4. Weekly Breakdown: Presence is slightly lower on Fridays, while WFH is highest on Fridays and Thursdays.

Technologies Used

• Power BI: For creating interactive visualizations and dashboards.

How to Run

1. Clone the repository:

   https://github.com/tejas-130704/DataAnalysit.git
   

Learning Experience

During this project, I gained significant experience working with Power BI, enhancing my skills in creating insightful visualizations. I learned how to efficiently analyze attendance data and generate actionable reports for HR management.