Data-driven analysis of employee attrition using HR analytics techniques to support retention strategies and workforce planning.

This project presents a comprehensive HR Analytics Dashboard built using Tableau. It visualizes key workforce metrics such as employee attrition, department-wise and education-wise trends, age distribution, gender-based attrition, and job satisfaction across various roles.

HR analytics & machine learning project predicting employee attrition using the IBM HR dataset

This repo contains HR Analytics project to analyze what factors impact employee attrition using dataset for Atlas Labs Company.

This project presents a comprehensive **HR Analytics Dashboard** built with **Power BI**. The dashboard visualizes employee attrition across various departments, job roles, education levels, salary slabs, and more. It provides actionable insights into workforce trends using real company data.

Working on Project related to Workforce Analytics wherein we need to understand and help the organization with its HR and workforce analytics for sustaining the business. Trying to understand the factors/ variables related to employee attrition and retention along with ensuring the business does not gets effected. Performing EDA on the features selected. Checking for correlation. Visualizing using Seaborn and plotly for various insights on the data. Checking for the survival of an employee in the organisation to determine the duration an Employee would attrite after.

Business-focused HR analytics project leveraging SQL (CTE, Window Functions, Subqueries) to uncover attrition patterns and high-risk employee segments.

Minor project on employee attrition using HR analytics and EDA

This project is a Power BI-based HR Analytics dashboard designed to provide insights into employee demographics, attrition trends, job satisfaction, performance, and other key HR metrics.

This project features an interactive Power BI HR Analytics dashboard that visualizes employee hiring trends, attrition rates, salary group distribution, overtime analysis, and dynamic slicers using bookmarks and buttons. It is designed for HR decision-making and analytics practice.

A Power BI-driven HR analytics project that visualizes employee attrition trends, performance metrics, and demographic insights. Includes data cleaning, modeling, and dashboard development using Power Query and DAX. Offers actionable recommendations to support HR strategies for employee retention, diversity, and satisfaction across departments.

Result of final project with a topic of HR analytics using classification method to predict employee attrition (employee leaving the company) and to find the most important factors that affects employee attrition. This project is conducted in order to meet the final requirements to pass the Data Science and Machine Learning program at Purwadhika Digital Technology School.

Using the IBM HR Analytics Employee Attrition Dataset, this project predicts employee turnover with machine learning. It analyzes features like job satisfaction and income using Random Forest and XGBoost, addressing class imbalance with SMOTE. The study provides insights to enhance retention strategies.

A comprehensive HR Analytics dashboard built using Power BI, analyzing employee attrition, demographics, job satisfaction, performance, and compensation trends. This project helps organizations identify workforce patterns and make data-driven decisions to improve retention and engagement.

The HR Analytics Dashboard project is a visual exploration of key HR metrics and workforce trends using Power BI. Designed as part of an academic initiative, this dashboard aims to support data-driven decision-making within human resource management, highlighting employee demographics, attrition patterns, performance indicators, and hiring trends.

A large company named XYZ, employs, at any given point of time, around 4000 employees. However, every year, around 15% of its employees leave the company and need to be replaced with the talent pool available in the job market. The management believes that this level of attrition (employees leaving, either on their own or because they got fired) is bad for the company, because of the following reasons - The former employees’ projects get delayed, which makes it difficult to meet timelines, resulting in a reputation loss among consumers and partners A sizeable department has to be maintained, for the purposes of recruiting new talent More often than not, the new employees have to be trained for the job and/or given time to acclimatise themselves to the company Hence, the management has contracted an HR analytics firm to understand what factors they should focus on, in order to curb attrition. In other words, they want to know what changes they should make to their workplace, in order to get most of their employees to stay. Also, they want to know which of these variables is most important and needs to be addressed right away.

IBM HR Analytics Employee Attrition & Performance Project

Explore our HR Analytics Dashboard, a powerful Power BI project designed for HR managers and leaders. Analyzed essential KPIs such as Employee Count, Attrition Rate, and Job Satisfaction across various demographics. Our intuitive visualizations, including Lollipop, Pie, Bar, and Donut charts, empower targeted decision-making.

PowerBI Project HR Analytics & Employee Attrition,Retention,Churn

This project focuses on predicting employee attrition using machine learning models based on HR analytics data. The goal is to help organizations identify key factors that lead to employee turnover and take proactive measures to improve retention.

The project “HR Analytics – Employee Attrition Prediction” aims to predict employee attrition based on various work-related factors using the IBM HR Analytics Dataset.

Machine learning project to predict employee attrition using HR analytics

Excel HR analytics project analyzing employee attrition through KPIs, dashboards, and insights across demographics, satisfaction, salary, and experience.

This is a Data Science project to uncover factors that lead to employee attrition.

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A machine learning project to predict employee attrition using HR analytics data.

HR Analytics project identifying factors for employee attrition using SQL and Excel.

This repo contains HR Analytics project to analyze what factors impact employees attrition using dataset of employee attrition rate

HR Analytics project to predict employee attrition using ML and Power BI

This project aims to analyze and predict employee attrition using HR analytics data. It involves data exploration, statistical testing, machine learning modeling, and visualization to uncover patterns in employee turnover and identify key factors influencing attrition.