{
  "format": "dataset-manifest/1",
  "slug": "employee-onboarding-software",
  "version": 1,
  "seed": "employee-onboarding-software:1",
  "spec": {
    "format": "dataset/1",
    "slug": "employee-onboarding-software",
    "name": "Onboarding Experience Insights",
    "tagline": "Onboarding data including employee training sessions, document submissions, background checks, and evaluations.",
    "description": "New hires navigate a structured onboarding experience designed to integrate them into the company culture and processes. This dataset models the various elements of the onboarding journey, including mandatory training modules, background checks, evaluations, and document submissions. Each table interrelates to provide a comprehensive view of employee onboarding, allowing users to analyze the efficiency and effectiveness of the onboarding process. For instance, users can explore the rate of training completion versus the timing of document submissions, and assess how these factors correlate with evaluations of candidate progress. This synthetic dataset is ideal for practicing SQL queries and ORM seeding, offering a realistic scenario for developers to work with. It covers various aspects of the onboarding process while ensuring that the data is both diverse and manageable.",
    "domain": "hr",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "onboarding",
      "employee training",
      "HR",
      "evaluations",
      "document submissions",
      "background checks"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "employees": {
        "description": "Each row represents a new hire, linking to their onboarding progress and related activities.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each employee."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the employee."
          },
          "start_date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date the employee starts at the company.",
            "trend": "growing"
          },
          "department": {
            "kind": "enum",
            "values": [
              "HR",
              "Engineering",
              "Sales",
              "Marketing"
            ],
            "description": "Department where the employee will work."
          }
        }
      },
      "training_sessions": {
        "description": "Tracks mandatory training modules each employee needs to complete during onboarding.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each training session."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.id",
            "description": "References the employee attending the training."
          },
          "session_name": {
            "kind": "sentence",
            "description": "Name of the training session."
          },
          "completion_date": {
            "kind": "date",
            "after": "employee_id.start_date",
            "withinDays": 30,
            "description": "Date the training session was completed."
          }
        }
      },
      "document_submissions": {
        "description": "Records the documents that employees must submit as part of their onboarding.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each document submission."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.id",
            "description": "References the employee who submitted the document."
          },
          "document_name": {
            "kind": "sentence",
            "description": "Name of the document submitted."
          },
          "submission_date": {
            "kind": "date",
            "after": "employee_id.start_date",
            "withinDays": 14,
            "description": "Date the document was submitted."
          }
        }
      },
      "background_checks": {
        "description": "Logs the background checks performed for each employee to ensure compliance.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each background check."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.id",
            "description": "References the employee undergoing the background check."
          },
          "check_date": {
            "kind": "date",
            "after": "employee_id.start_date",
            "withinDays": 30,
            "description": "Date the background check was performed."
          },
          "status": {
            "kind": "enum",
            "values": [
              "Pending",
              "Completed",
              "Failed"
            ],
            "description": "Outcome of the background check."
          }
        }
      },
      "evaluations": {
        "description": "Captures evaluations of employee performance during onboarding.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each evaluation."
          },
          "employee_id": {
            "kind": "fk",
            "ref": "employees.id",
            "description": "References the employee being evaluated."
          },
          "evaluation_date": {
            "kind": "date",
            "after": "employee_id.start_date",
            "withinDays": 60,
            "description": "Date of the evaluation."
          },
          "score": {
            "kind": "int",
            "min": 1,
            "max": 10,
            "description": "Score received during the evaluation."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What percentage of employees complete their training on time?",
      "How do evaluation scores correlate with the timing of document submissions?",
      "Which departments have the highest completion rates for training sessions?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Employees with Training Sessions",
        "sql": "SELECT e.full_name, t.session_name FROM employees e JOIN training_sessions t ON e.id = t.employee_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Training Completions by Department",
        "sql": "SELECT e.department, COUNT(t.id) FROM employees e LEFT JOIN training_sessions t ON e.id = t.employee_id GROUP BY e.department;",
        "dialect": "postgres"
      },
      {
        "title": "Average Evaluation Score by Department",
        "sql": "SELECT e.department, AVG(ev.score) FROM evaluations ev JOIN employees e ON ev.employee_id = e.id GROUP BY e.department;",
        "dialect": "postgres"
      },
      {
        "title": "Document Submission Timing Analysis",
        "sql": "SELECT e.full_name, ds.document_name, ds.submission_date FROM document_submissions ds JOIN employees e ON ds.employee_id = e.id WHERE ds.submission_date > e.start_date + INTERVAL '7 days';",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "HR Analytics",
        "body": "HR analysts can utilize this dataset to identify trends in employee onboarding, such as the effectiveness of training sessions and the timeliness of document submissions. By analyzing the data, they can recommend improvements to the onboarding process, ensuring a smoother experience for new hires."
      },
      {
        "title": "Training Program Evaluation",
        "body": "Training managers can leverage this dataset to evaluate the success of various training programs. By correlating training completion rates with employee evaluations, they can identify which programs yield the best results and allocate resources accordingly."
      },
      {
        "title": "Compliance Monitoring",
        "body": "Compliance officers can use this dataset to ensure that all required background checks and document submissions are conducted in a timely manner. This helps maintain organizational standards and mitigate any potential risks associated with onboarding new employees."
      }
    ]
  },
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    "background_checks": 150,
    "document_submissions": 150,
    "evaluations": 150,
    "training_sessions": 300
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