{
  "format": "dataset-manifest/1",
  "slug": "hostel-management-system",
  "version": 1,
  "seed": "hostel-management-system:1",
  "spec": {
    "format": "dataset/1",
    "slug": "hostel-management-system",
    "name": "Hostel Operations Insight",
    "tagline": "Hostel operations data including bookings, room types, guest check-ins, meal subscriptions, and complaint updates.",
    "description": "Hostels manage bookings and guest experiences that revolve around shared accommodations, dining, and communal facilities. Guests book various room types and have access to meal subscriptions through a mess menu, creating a dynamic environment where short-term visitors intermingle with long-term residents. The operations team handles guest check-ins and check-outs, ensuring that facilities run smoothly. Complaints are tracked and addressed, while asset management and staff shifts are organized to maintain high service standards. This dataset provides a comprehensive look at hostel operations, enabling users to analyze booking patterns, guest demographics, and service efficiency. Being synthetic, it allows for various testing and development scenarios without the complexities of real-world data privacy concerns.",
    "domain": "hospitality",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "hostel",
      "operations",
      "guest management",
      "bookings",
      "complaints",
      "meal subscriptions"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "hostel_operations": {
        "description": "This table contains records of hostel operations, with each row representing a unique guest booking or transaction. It tracks essential details such as room types, guest check-in and check-out dates, meal subscriptions, and any complaints raised during the stay.",
        "rows": 250,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each booking or transaction."
          },
          "guest_name": {
            "kind": "fullName",
            "description": "Full name of the guest making the booking.",
            "nullable": true
          },
          "room_type": {
            "kind": "enum",
            "values": [
              "shared",
              "private",
              "dormitory"
            ],
            "description": "Type of room booked by the guest."
          },
          "check_in_date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date when the guest checks in."
          },
          "check_out_date": {
            "kind": "date",
            "after": "check_in_date",
            "withinDays": 60,
            "description": "Date when the guest checks out."
          },
          "meal_subscription": {
            "kind": "enum",
            "values": [
              "none",
              "breakfast",
              "full board"
            ],
            "description": "Meal plan chosen by the guest.",
            "nullable": true,
            "when": {
              "column": "room_type",
              "in": [
                "private",
                "dormitory"
              ]
            }
          },
          "complaint_status": {
            "kind": "enum",
            "values": [
              "none",
              "resolved",
              "pending"
            ],
            "description": "Status of any complaints raised by the guest."
          },
          "length_of_stay": {
            "kind": "int",
            "min": 1,
            "max": 30,
            "description": "Total number of nights the guest stays.",
            "nullable": true
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most common room types booked by guests?",
      "How does the length of stay vary among different meal subscription plans?",
      "What percentage of complaints are resolved before check-out?",
      "Which months see the highest number of guest bookings?",
      "What trends can we observe in meal subscription choices over time?"
    ],
    "suggestedQueries": [
      {
        "title": "List all guest bookings",
        "sql": "SELECT * FROM hostel_operations;",
        "dialect": "postgres"
      },
      {
        "title": "Count bookings by room type",
        "sql": "SELECT room_type, COUNT(*) FROM hostel_operations GROUP BY room_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average length of stay for resolved complaints",
        "sql": "SELECT AVG(length_of_stay) FROM hostel_operations WHERE complaint_status = 'resolved';",
        "dialect": "postgres"
      },
      {
        "title": "Booking trends by month",
        "sql": "SELECT DATE_TRUNC('month', check_in_date) AS month, COUNT(*) FROM hostel_operations GROUP BY month ORDER BY month;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Training for hospitality staff",
        "body": "Hospitality management programs can use this dataset to train staff on handling guest bookings, managing complaints, and understanding meal subscriptions. By practicing with this data, students can simulate real-world scenarios and improve their operational skills."
      },
      {
        "title": "Data analysis for hostel management",
        "body": "Hostel managers can leverage this dataset to analyze booking trends, assess guest satisfaction through complaint resolution rates, and optimize meal offerings based on guest preferences. This insight can lead to improved service delivery and operational efficiency."
      },
      {
        "title": "ORM development for booking systems",
        "body": "Developers creating booking management systems can use this dataset to seed their databases with realistic data. This allows for thorough testing of features like booking transactions, guest check-ins, and complaint handling before deploying the system."
      }
    ]
  },
  "counts": {
    "hostel_operations": 250
  },
  "stats": {
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      "columns": {
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          "nulls": 0,
          "distinct": 250,
          "min": 1,
          "max": 250
        },
        "guest_name": {
          "nulls": 21,
          "distinct": 228,
          "min": "Alice Nakamura",
          "max": "Zoe Bennett"
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        "room_type": {
          "nulls": 0,
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          "min": "dormitory",
          "max": "shared"
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          "nulls": 0,
          "distinct": 183,
          "min": "2023-01-01",
          "max": "2023-12-31"
        },
        "check_out_date": {
          "nulls": 0,
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          "min": "2023-01-21",
          "max": "2024-02-16"
        },
        "meal_subscription": {
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          "min": "breakfast",
          "max": "none"
        },
        "complaint_status": {
          "nulls": 0,
          "distinct": 3,
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          "max": "resolved"
        },
        "length_of_stay": {
          "nulls": 32,
          "distinct": 30,
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          "max": 30
        }
      }
    }
  },
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