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Tech Industry Compensation Dataset
Data Science and Analytics
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About
This dataset contains simulated data for 400 employees within the IT industry. It provides details on each employee's gender, years of professional experience, job position, and annual salary. The data is designed to mirror realistic distributions and variations commonly observed in the IT sector, illustrating how salaries typically correlate with an individual's experience level and specific job role. The dataset was generated using the Faker library in Python, ensuring realistic yet synthetic data for various analytical purposes.
Columns
- ID: A unique identifier assigned to each employee, ranging from 1 to 400.
- Gender: Indicates the employee's gender, with values 'M' for Male and 'F' for Female.
- Experience (Years): Represents the number of years of professional experience an employee has, spanning from 0 to 20 years.
- Position: The specific job title held by the employee. This includes a variety of IT-related roles such as IT Manager, Software Engineer, Network Administrator, Systems Administrator, Database Administrator (DBA), Web Developer, IT Support Specialist, Systems Analyst, IT Security Analyst, DevOps Engineer, and Cloud Solutions Architect.
- Salary: The employee's annual salary, expressed in USD. Salaries are structured to reflect typical compensation within the IT industry, showing an increase with both job position and years of experience. Salaries range from approximately 43,600 USD to 270,000 USD.
Distribution
The dataset is provided as a data file, typically in CSV format, with a total of 400 employee records. Each record includes 5 distinct columns. The data exhibits variations across its fields; for instance, gender distribution is almost equally split between Male (51%) and Female (50%). Experience levels range from 0 to 20 years, with a mean of approximately 9.67 years. Salaries range from around 43.6k USD to 270k USD, with a mean salary of about 132k USD. The 'Position' column includes 11 unique job titles, with 'Web Developer' being the most common, accounting for 11% of the records.
Usage
This dataset is highly versatile and can be employed for a range of analytical and educational purposes, including:
- Data Analysis: To investigate salary trends based on factors like job position and years of experience within the IT industry.
- Machine Learning: For training models, particularly for salary prediction tasks.
- Human Resources: To gain insights into typical compensation structures and employee demographics in the IT sector.
- Education: As a practical resource for teaching data science and data analysis courses.
Coverage
The dataset focuses exclusively on the IT industry, providing a simulated scope of employees within this sector. It includes 400 individual employee records. Geographic coverage is not explicitly stated but implies a general, non-specific IT industry context. The time range is not specified as the data is simulated and does not represent a specific historical period. Demographic scope covers both male and female employees across a broad range of experience levels (0-20 years). Salary ranges are set to reflect typical compensation for the included IT positions.
License
CC0: Public Domain
Who Can Use It
This dataset is suitable for a wide array of users, including:
- Data Analysts: For exploring salary trends and compensation structures.
- Machine Learning Engineers: For developing predictive models related to human resources.
- HR Professionals: For benchmarking and understanding compensation in the IT industry.
- Students and Educators: For learning and teaching concepts in data science, statistics, and human resources analytics.
- Researchers: For studies on workforce dynamics and salary determinants in the technology sector.
Dataset Name Suggestions
- IT Employee Salary & Experience Data
- Simulated IT Workforce Insights
- Tech Industry Compensation Dataset
- Employee Demographics in IT
- IT Professionals Data
Attributes
Original Data Source: Tech Industry Compensation Dataset
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