IBM Employee Attrition Data with Education and Job Satisfaction Metrics

IBM Employee Attrition Data is a human resources analytics dataset originally sourced from Kaggle. It contains data on employees who stay and leave, including metrics such as education level, job satisfaction, and commute distance. The dataset was obtained from an IBM GitHub repository and is available under the Open Database License.

Use Cases

• Predict employee attrition based on job satisfaction and commute distance metrics.
• Analyze the relationship between education level and employee retention.
• Model workforce dynamics using HR analytics data on employees who stay and leave.

Strengths

• Dataset includes specific HR metrics such as education level, job satisfaction, and commute distance.
• Data originates from a known source, IBM's GitHub repository for AI fairness tools.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The columns 'Attrition' and 'PercentSalaryHike' have been removed, limiting analysis on those specific features.

Provenance

Source

Kaggle, via IBM's employee-attrition-aif360 GitHub repository.

Collection Method

Supplied for use in a code pattern; original collection method is not specified.