Name: Employee Attrition And Factors
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Employee Attrition And Factors

Employee Attrition and Factors

Examining Performance, Financials, and Job Role for Impact on Retention

By [source]

About this dataset

This dataset offers a comprehensive and varied analysis of an organization's employees, focusing on areas such as employee attrition, personal and job-related factors, and financials. Included are numerous parameters such as Age, Gender, Marital Status, Business Travel Frequency, Daily Rate of Pay, Departmental Information such as Distance From Home Office or Education Level Obtained by the employee in question. Also included is a variant series of parameters related to the job being performed such as Job Involvement (level), Job Level (relative to similar roles within the same organization), Job Role specifically meant for that individual(function/task), total working hours in a week/month/year be it overtime or standard hours for a given role. Furthermore detailed aspects include Percent Salary Hike during their tenure with the company from promotion or otherwise , Performance Rating based on specific criteria established by leadership , Relationship Satisfaction among peers at workplace but also taking into account outside family members that can influence stress levels in varying capacities ,Monthly Income considered at its starting point once hired then compared against their monthly payrate with overtime hours included if applicable along with Number Companies Worked before if any. Lastly the Retirement Status commonly known as Attrition is highlighted; covering whether there was an intent to stay with one employer through retirement age or if attrition took place for reasons beyond ones control earlier than expected . Through this dataset you can get an insight into various major aspect regarding today's workforce management philosphies which have changed drastically over time due to advancements in technology

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How to use the dataset

Understand the variables that make up this dataset. The dataset includes several personal and job-related variables such as Age, Gender, Marital Status, Business Travel, Daily Rate, Department, Distance From Home, Education, Education Field, Employee Count, Employee Number, Environment Satisfaction Hoursly Rate and so on. Knowing what each variable is individuallly will help when exploring employee attrition as a whole.

Analyze the data for patterns as well as outliers or anomalies either at an individual level or across all of the data points together. Identifying these patterns or discrepancies can offer insight into factors that are related to employee attrition.

Visualize the data using charts and graphs to allow for easy understanding of which relationships might be causing higher levels of employees leaving the organization over time dimensions like age or job role can be key factors in employee attrition rates visually displaying how they relate to one another can provide clarity into what needs to change within an organization in order to reduce attrition rates

Explore relationships between pairs of variables through correlation analysis correlations are measures of how strongly two variables are related when looking at employment retention it’s important to analyze correlations at both an individual level and for all variables together showing which pairings have more influence than others when it comes to influencing employee decisions
5 Use descriptive analytics methods such as scatter plots histograms boxplots etc with aggregated values from each field like average age average monthly income etc These analytics help gain a deeper understanding about where changes need to be made internally
6 Utilize predictive analytics with more advanced techniques such as regressions clustering decision trees in order identify trendsfrom past data points then build models on those insights from different perspectives helping further prepare organizations against potential high levelsinvolving employees departing ?

Research Ideas

Identifying performance profiles of employees at risk for attrition through predictive analytics and using this insight to create personalized development plans or retention strategies.

Using the data to assess the impact of different financial incentives or variations in job role/structure on employee attitudes, satisfaction and ultimately attrition rates.

Analyzing different age groups' responses to various perks or turnover patterns in order to understand how organizations can better engage different demographic segments

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: HR_Analytics.csv.csv

Column name	Description
Age	The age of the employee. (Numerical)
Attrition	Whether or not the employee has left the organization. (Categorical)
BusinessTravel	The frequency of business travel for the employee. (Categorical)
DailyRate	The daily rate of pay for the employee. (Numerical)
Department	The department the employee works in. (Categorical)
DistanceFromHome	The distance from home in miles for the employee. (Numerical)
Education	The level of education achieved by the employee. (Categorical)
EducationField	The field of study for the employee's education. (Categorical)
EmployeeCount	The total number of employees in the organization. (Numerical)
EmployeeNumber	A unique identifier for each employee profile. (Numerical)
EnvironmentSatisfaction	The employee's satisfaction with their work environment. (Categorical)
Gender	The gender of the employee. (Categorical)
HourlyRate	The hourly rate of pay for the employee. (Numerical)
JobInvolvement	The level of involvement required for the employee's job. (Categorical)
JobLevel	The job level of the employee. (Categorical)
JobRole	The role of the employee in the organization. (Categorical)
JobSatisfaction	The employee's satisfaction with their job. (Categorical)
MaritalStatus	The marital status of the employee. (Categorical)
MonthlyIncome	The monthly income of the employee. (Numerical)
MonthlyRate	The monthly rate of pay for the employee. (Numerical)
NumCompaniesWorked	The number of companies the employee has worked for. (Numerical)
Over18	Whether or not the employee is over 18. (Categorical)
OverTime	Whether or not the employee works overtime. (Categorical)
PercentSalaryHike	The percentage of salary hike for the employee. (Numerical)
PerformanceRating	The performance rating of the employee. (Categorical)
RelationshipSatisfaction	The employee's satisfaction with their relationships. (Categorical)
StandardHours	The standard hours of work for the employee. (Numerical)
StockOptionLevel	The stock option level of the employee. (Numerical)
TotalWorkingYears	The total number of years the employee has worked. (Numerical)
TrainingTimesLastYear	The number of times the employee was taken for training in the last year. (Numerical)
WorkLifeBalance	The employee's perception of their work-life balance. (Categorical)
YearsAtCompany	The number of years the employee has been with the company. (Numerical)
YearsInCurrentRole	The number of years the employee has been in their current role. (Numerical)
YearsSinceLastPromotion	The number of years since the employee's last promotion. (Numerical)
YearsWithCurrManager	The number of years the employee has been with their current manager. (Numerical)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Hr Analytics

@kaggle.thedevastator_employee_attrition_and_factors.hr_analytics

71.09 KB
1470 rows
35 columns


CREATE TABLE hr_analytics (
  "age" BIGINT,
  "attrition" VARCHAR,
  "businesstravel" VARCHAR,
  "dailyrate" BIGINT,
  "department" VARCHAR,
  "distancefromhome" BIGINT,
  "education" BIGINT,
  "educationfield" VARCHAR,
  "employeecount" BIGINT,
  "employeenumber" BIGINT,
  "environmentsatisfaction" BIGINT,
  "gender" VARCHAR,
  "hourlyrate" BIGINT,
  "jobinvolvement" BIGINT,
  "joblevel" BIGINT,
  "jobrole" VARCHAR,
  "jobsatisfaction" BIGINT,
  "maritalstatus" VARCHAR,
  "monthlyincome" BIGINT,
  "monthlyrate" BIGINT,
  "numcompaniesworked" BIGINT,
  "over18" VARCHAR,
  "overtime" VARCHAR,
  "percentsalaryhike" BIGINT,
  "performancerating" BIGINT,
  "relationshipsatisfaction" BIGINT,
  "standardhours" BIGINT,
  "stockoptionlevel" BIGINT,
  "totalworkingyears" BIGINT,
  "trainingtimeslastyear" BIGINT,
  "worklifebalance" BIGINT,
  "yearsatcompany" BIGINT,
  "yearsincurrentrole" BIGINT,
  "yearssincelastpromotion" BIGINT,
  "yearswithcurrmanager" BIGINT
);