Organisational Demographics and Financial Data

Columns

• EmpID: Unique ID of an Employee.
• Name: Full Name of an Employee.
• Gender: Sex of an Employee (Male or Female).
• Date_of_Birth: Birth Date of an Employee.
• Age: Age of an Employee.
• Join_Date: Date of joining in company "ABC".
• Tenure_in_org_in_months: Number of months since the employee has been associated with company "ABC".
• GROSS: Salary from CTC after subtracting EPF and Gratuity.
• Net_Pay: Salary from GROSS after subtracting Income Tax and Professional tax.
• Deduction: Total Tax deduction in Amount based on Age.
• Deduction_percentage: Deduction Amount by Gross salary for each Employee.
• Designation: Job role of an Employee (e.g. Software Engineer, Senior).
• Department: Area of work (e.g. Enterprise Applications, Finance).

Distribution

• Format: CSV (Employee_monthly_salary.csv).
• Size: Approximately 227.33 kB.
• Structure: 13 columns.
• Records: 1,802 valid rows.

Usage

• Statistical Simulations: Perform predictive modelling for salary trends and tax deductions.
• Bias Detection: Analyse the relationship between gender and leadership roles, or investigate if male employees earn significantly more than female employees.
• HR Analytics: Identify departments with significantly low salaries and assess the dependency of salary on age.
• Compensation Analysis: Compare Gross versus Net pay and evaluate tax deduction percentages across different salary bands.

Coverage

• Demographic Scope: Includes employees with an age range of 21 to 56 years. The gender distribution is approximately 72% Male and 28% Female.
• Temporal Scope: Tenure ranges from 6 months to 190 months.
• Professional Scope: Covers various departments including "Enterprise Applications" and "Finance - Customer Revenue Operations G&A", with designations such as "Software Engineer.Senior." and "Software Engineer II".

License

Who Can Use It

• Data Analysts: For practicing EDA and statistical hypothesis testing on income and demographics.
• HR Professionals: To study workforce retention, pay equity, and organisational structure.
• Machine Learning Engineers: To build regression models for predicting gross or net salary based on tenure and age.
• Economists: To analyse corporate tax deduction patterns and wage distributions.

Dataset Name Suggestions

• ABC Company Employee Compensation and Demographics
• Workforce Salary, Tenure, and Diversity Metrics
• Employee Pay Grades and Tax Deduction Records
• Organisational Demographics and Financial Data
• Company ABC Staff Employment and Salary Data

Attributes