{
  "format": "dataset-manifest/1",
  "slug": "employee-management-system",
  "version": 1,
  "seed": "employee-management-system:1",
  "spec": {
    "format": "dataset/1",
    "slug": "employee-management-system",
    "name": "Employee Lifecycle Insight",
    "tagline": "Employee attributes, job roles, performance reviews, training sessions, leave requests, and department details.",
    "description": "Employees participate in a structured environment where they engage in various job roles, undergo performance reviews, and attend training sessions to enhance their skills. Human resources professionals manage these activities, ensuring that individuals are properly supported and recognized for their contributions within the organization. This operational flow is critical for building a productive workforce and adapting training programs to enhance employee performance. \n\nThe data consists of several interrelated tables: employees, job_roles, performance_reviews, training_sessions, leave_requests, and departments. Each employee record represents an individual within the organization, containing vital information about their job roles and leave requests. Job roles connect to employees, indicating the various functions they perform and the departments they belong to. Performance reviews capture the quality of work and progress through evaluations tied to each employee, while training sessions document the professional development efforts undertaken by them. Leave requests track the time employees take off, providing insight into work-life balance and attendance patterns. \n\nBy examining these tables, users can answer questions about workforce dynamics, such as which job roles are most frequently associated with high performance or which training sessions yield significant improvements in employee reviews. Analyzing leave requests can also highlight patterns in absenteeism or the impact of specific training sessions on attendance. This makes the dataset particularly valuable for practice in data analysis and reporting, providing insights into employee lifecycle management. \n\nIt’s important to note that the data is synthetic, designed to reflect realistic scenarios within HR without compromising real-world privacy.",
    "domain": "hr",
    "shape": "slowly-changing",
    "useCases": [
      "etl-pipelines",
      "teaching"
    ],
    "keywords": [
      "employee",
      "HR",
      "performance",
      "training",
      "leave",
      "job role"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "employees": {
        "description": "Each row represents an employee in the organization, linking to their job roles and performance reviews.",
        "rows": 300,
        "columns": {
          "employee_id": {
            "kind": "pk",
            "description": "Unique identifier for each employee."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the employee.",
            "nullable": true
          },
          "date_hired": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The date the employee was hired.",
            "trend": "growing"
          },
          "job_role_id": {
            "kind": "fk",
            "ref": "job_roles.role_id",
            "description": "The job role this employee occupies.",
            "nullable": true
          }
        }
      },
      "job_roles": {
        "description": "This table contains information about various job roles within the organization, linked to employees.",
        "rows": 50,
        "columns": {
          "role_id": {
            "kind": "pk",
            "description": "Unique identifier for each job role."
          },
          "title": {
            "kind": "enum",
            "values": [
              "Software Engineer",
              "HR Manager",
              "Sales Representative",
              "Data Analyst"
            ],
            "description": "The title of the job role.",
            "nullable": true,
            "when": {
              "column": "department",
              "in": [
                "Engineering",
                "Human Resources"
              ]
            }
          },
          "department": {
            "kind": "enum",
            "values": [
              "Engineering",
              "Human Resources",
              "Sales",
              "Analytics"
            ],
            "description": "The department for the job role."
          }
        }
      },
      "performance_reviews": {
        "description": "Records performance evaluations for employees, linked to their job roles.",
        "rows": 600,
        "columns": {
          "review_id": {
            "kind": "pk",
            "description": "Unique identifier for each performance review."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.employee_id",
            "description": "The employee being reviewed."
          },
          "review_date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The date of the performance review.",
            "trend": "seasonal"
          },
          "rating": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "The performance rating given to the employee.",
            "nullable": true
          }
        }
      },
      "training_sessions": {
        "description": "This table captures training sessions attended by employees, linked to their records.",
        "rows": 400,
        "columns": {
          "session_id": {
            "kind": "pk",
            "description": "Unique identifier for each training session."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.employee_id",
            "description": "The employee who attended the training."
          },
          "training_date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The date of the training session.",
            "nullable": true,
            "when": {
              "column": "training_topic",
              "in": [
                "Leadership",
                "Technical Skills"
              ]
            },
            "trend": "growing"
          },
          "training_topic": {
            "kind": "enum",
            "values": [
              "Leadership",
              "Technical Skills",
              "Compliance",
              "Customer Service"
            ],
            "description": "The topic of the training session.",
            "nullable": true
          }
        }
      },
      "leave_requests": {
        "description": "Records of leave requests made by employees, linked to their job roles.",
        "rows": 300,
        "columns": {
          "request_id": {
            "kind": "pk",
            "description": "Unique identifier for each leave request."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.employee_id",
            "description": "The employee requesting leave."
          },
          "leave_start": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The start date of the leave."
          },
          "leave_end": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The end date of the leave.",
            "nullable": true
          }
        }
      },
      "departments": {
        "description": "This table contains a list of departments within the organization, linked to job roles.",
        "rows": 10,
        "columns": {
          "department_id": {
            "kind": "pk",
            "description": "Unique identifier for each department."
          },
          "name": {
            "kind": "enum",
            "values": [
              "Engineering",
              "Human Resources",
              "Sales",
              "Analytics"
            ],
            "description": "The name of the department."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most common job roles in the organization?",
      "How does employee performance correlate with training attendance?",
      "What trends can be observed from the leave requests over the year?",
      "How do different departments compare in terms of employee performance ratings?",
      "What is the average duration of leave taken by employees?"
    ],
    "suggestedQueries": [
      {
        "title": "List all employees and their job roles",
        "sql": "SELECT e.full_name, j.title FROM employees e JOIN job_roles j ON e.job_role_id = j.role_id",
        "dialect": "postgres"
      },
      {
        "title": "Get performance ratings by department",
        "sql": "SELECT d.name, AVG(p.rating) as avg_rating FROM performance_reviews p JOIN employees e ON p.employee_id = e.employee_id JOIN job_roles j ON e.job_role_id = j.role_id JOIN departments d ON j.department = d.name GROUP BY d.name",
        "dialect": "postgres"
      },
      {
        "title": "Count training sessions per employee",
        "sql": "SELECT e.full_name, COUNT(ts.session_id) as training_count FROM employees e LEFT JOIN training_sessions ts ON e.employee_id = ts.employee_id GROUP BY e.full_name",
        "dialect": "postgres"
      },
      {
        "title": "Analyze leave requests over time",
        "sql": "SELECT EXTRACT(MONTH FROM lr.leave_start) as month, COUNT(*) as leave_count FROM leave_requests lr GROUP BY month ORDER BY month",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "HR Analytics",
        "body": "Human resource analysts can use this dataset to explore employee performance metrics, training impact, and leave patterns. This analysis can help inform strategic decisions around employee development and resource allocation."
      },
      {
        "title": "Teaching HR Concepts",
        "body": "Educators can leverage this dataset in classrooms to teach concepts related to employee management, performance appraisal, and workforce analytics. The variety of data allows students to engage in practical exercises and real-world scenarios."
      },
      {
        "title": "ETL Process Development",
        "body": "Data engineers can utilize this dataset to design and test ETL pipelines that aggregate, transform, and load employee data into data warehouses. This practical application aids in honing their skills in data pipeline creation."
      }
    ]
  },
  "counts": {
    "departments": 10,
    "job_roles": 50,
    "employees": 300,
    "leave_requests": 300,
    "performance_reviews": 600,
    "training_sessions": 400
  },
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