{
  "format": "dataset-manifest/1",
  "slug": "workforce-insights",
  "version": 1,
  "seed": "workforce-insights:1",
  "spec": {
    "format": "dataset/1",
    "slug": "workforce-insights",
    "name": "Workforce Insights",
    "tagline": "Employee records detailing leave allocations, payroll, performance evaluations, and benefits for a diverse workforce.",
    "description": "Organizations actively manage their workforce, focusing on employee development, compensation, and overall satisfaction. Employees navigate a structured environment where leave allocations, payroll details, performance evaluations, and employee benefits play significant roles in shaping their work experience. This data provides a detailed view of the workforce ecosystem, illuminating patterns of growth and engagement among employees. Most employees feature typical salary and attendance records, while insights into bonuses and higher performance ratings reveal a concentration among top performers who actively participate in training and development programs.\n\nThe employee_records table serves as the core of this dataset, with each row representing an individual employee's journey within the organization. It holds vital information such as employee ID, name, role, salary, leave balances, performance ratings, and benefits enrollment. By examining the various attributes within this table, users can explore relationships between employee satisfaction and performance metrics, analyze trends in leave usage, and assess the effectiveness of training initiatives.\n\nPracticing with this data allows developers to answer questions about workforce dynamics, such as how employee engagement correlates with performance outcomes or the impact of different benefit offerings on employee retention. Additionally, it can illuminate the distribution of compensation and leave across various demographics within the workforce. This dataset is synthetic, designed to offer a realistic yet fictional landscape of HR operations without revealing any real-world information.",
    "domain": "hr",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "employee data",
      "performance evaluation",
      "compensation",
      "leave allocation",
      "HR analytics"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "employee_records": {
        "description": "Each row represents an employee's profile, including their performance ratings, compensation details, and leave balances. The data links performance metrics to compensation and benefits, providing insights into workforce trends.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each employee."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Employee's full name."
          },
          "department": {
            "kind": "enum",
            "values": [
              "HR",
              "Engineering",
              "Sales",
              "Marketing",
              "Finance"
            ],
            "description": "Department the employee belongs to."
          },
          "salary": {
            "kind": "decimal",
            "min": 30000,
            "max": 120000,
            "scale": 2,
            "description": "Annual salary of the employee."
          },
          "bonus": {
            "kind": "decimal",
            "min": 0,
            "max": 20000,
            "scale": 2,
            "nullable": true,
            "nullRate": 0.5,
            "description": "Annual bonus awarded to the employee, if applicable."
          },
          "performance_rating": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Performance rating of the employee, on a scale of 1 to 5."
          },
          "leave_balance": {
            "kind": "int",
            "min": 0,
            "max": 30,
            "description": "Remaining leave days available for the employee."
          },
          "training_completed": {
            "kind": "bool",
            "trueRate": 0.6,
            "description": "Indicates if the employee has completed any training programs."
          },
          "date_of_joining": {
            "kind": "date",
            "from": "2010-01-01",
            "to": "2023-12-31",
            "description": "Date when the employee joined the organization.",
            "trend": "growing"
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "categorical",
      "monetary",
      "nullable"
    ],
    "analysisQuestions": [
      "What is the average salary across different departments?",
      "How do performance ratings correlate with bonuses?",
      "Which departments have the highest leave balances?",
      "What percentage of employees have completed training programs?",
      "How does employee tenure affect salary levels?"
    ],
    "suggestedQueries": [
      {
        "title": "Select All Employees",
        "sql": "SELECT * FROM employee_records;",
        "dialect": "postgres"
      },
      {
        "title": "Average Salary by Department",
        "sql": "SELECT department, AVG(salary) AS average_salary FROM employee_records GROUP BY department;",
        "dialect": "postgres"
      },
      {
        "title": "Performance Rating Distribution",
        "sql": "SELECT performance_rating, COUNT(*) FROM employee_records GROUP BY performance_rating;",
        "dialect": "postgres"
      },
      {
        "title": "Leave Balance Comparison",
        "sql": "SELECT department, AVG(leave_balance) AS average_leave FROM employee_records GROUP BY department;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "HR Analytics Dashboard",
        "body": "HR analysts can use the Workforce Insights dataset to develop dashboards that visualize employee performance, compensation trends, and leave balances across departments. By analyzing this data, organizations can identify top performers and areas for improvement in workforce management."
      },
      {
        "title": "Performance Management System",
        "body": "Developers can utilize this dataset to seed a performance management system with realistic employee data, enabling them to test features such as performance evaluations, bonus calculations, and training program tracking without needing real employee information."
      },
      {
        "title": "Employee Retention Analysis",
        "body": "Business analysts can leverage the dataset to conduct retention analysis by examining the correlation between employee training and performance ratings. Insights gained from this analysis can inform retention strategies, helping to reduce turnover in high-performing departments."
      }
    ]
  },
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