{
  "format": "dataset-manifest/1",
  "slug": "vehicle-rental-operations",
  "version": 1,
  "seed": "vehicle-rental-operations:1",
  "spec": {
    "format": "dataset/1",
    "slug": "vehicle-rental-operations",
    "name": "Vehicle Rental Operations",
    "tagline": "Customers, vehicles, rentals, payments, and maintenance details from car rental operations.",
    "description": "Car rental agencies efficiently manage short-term vehicle access for diverse customers, catering to needs from vacation travel to business engagements. These operations hinge on the effective coordination of vehicle fleets, customer transactions, and vehicle upkeep, ensuring a seamless rental experience. The business thrives on understanding its customers' preferences, tracking vehicle conditions, and keeping up with insurance requirements to mitigate risks and maintain service quality.\n\nThe dataset comprises several interconnected tables: customers, vehicles, rentals, payments, maintenance, and insurance_plans. Each row in the customers table details a unique individual, encapsulating demographics and preferences, while the vehicles table lists the fleet available for rent, each entry including specifications like make and model. Rentals serve as pivotal records, linking customers to vehicles rented, complete with transaction dates and durations. This allows insights into customer behavior and seasonal trends. Payments document the financial aspects, indicating methods and amounts settled by customers, which can reveal preferred payment types and any outstanding balances. The maintenance table tracks necessary upkeep performed on vehicles, detailing types of repairs or services provided, while insurance_plans outlines the various coverage options available for customers, highlighting the importance of risk management in vehicle rentals.\n\nThis data can answer vital questions about customer trends, maintenance needs, and payment behaviors, making it ideal for practicing data analysis skills. Developers can explore patterns in rental frequency, identify popular vehicle types during peak seasons, and evaluate the efficiency of maintenance schedules. The dataset is synthetic, designed to simulate real-world scenarios, thus providing a safe environment for experimentation and learning without the complexities of real data.",
    "domain": "real-estate",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "vehicle rental",
      "car rental",
      "fleet management",
      "customer transactions",
      "insurance plans",
      "maintenance records"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "customers": {
        "description": "This table holds data about customers who rent vehicles, including their preferences and demographics.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each customer."
          },
          "first_name": {
            "kind": "firstName",
            "description": "The customer's first name."
          },
          "last_name": {
            "kind": "lastName",
            "description": "The customer's last name."
          },
          "email": {
            "kind": "email",
            "from": [
              "first_name",
              "last_name"
            ],
            "description": "The customer's email address."
          },
          "phone": {
            "kind": "phone",
            "description": "The customer's contact phone number."
          },
          "preferred_vehicle_type": {
            "kind": "enum",
            "values": [
              "economy",
              "mid-size",
              "SUV",
              "luxury"
            ],
            "description": "The type of vehicle preferred by the customer."
          }
        }
      },
      "vehicles": {
        "description": "This table contains details about the vehicles available for rental, including their types and maintenance status.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each vehicle."
          },
          "make": {
            "kind": "words",
            "description": "The make of the vehicle."
          },
          "model": {
            "kind": "words",
            "description": "The model of the vehicle."
          },
          "year": {
            "kind": "int",
            "min": 2000,
            "max": 2023,
            "description": "The year the vehicle was manufactured."
          },
          "vehicle_type": {
            "kind": "enum",
            "values": [
              "economy",
              "mid-size",
              "SUV",
              "luxury"
            ],
            "description": "The category of the vehicle."
          },
          "availability_status": {
            "kind": "enum",
            "values": [
              "available",
              "rented",
              "maintenance"
            ],
            "description": "Current availability status of the vehicle."
          }
        }
      },
      "rentals": {
        "description": "This table records each rental transaction, linking customers to the vehicles they rented and the rental duration.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each rental transaction."
          },
          "customer_id": {
            "kind": "fk",
            "ref": "customers.id",
            "description": "The customer who rented the vehicle."
          },
          "vehicle_id": {
            "kind": "fk",
            "ref": "vehicles.id",
            "description": "The vehicle that was rented."
          },
          "rental_start": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Start date and time of the rental.",
            "dayProfile": "waking"
          },
          "rental_end": {
            "kind": "datetime",
            "after": "rental_start",
            "withinDays": 30,
            "description": "End date and time of the rental."
          },
          "total_cost": {
            "kind": "decimal",
            "min": 20,
            "max": 500,
            "scale": 2,
            "description": "Total cost of the rental transaction."
          }
        }
      },
      "payments": {
        "description": "This table logs payment details associated with each rental transaction, including payment methods used.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each payment record."
          },
          "rental_id": {
            "kind": "fk",
            "ref": "rentals.id",
            "description": "The rental transaction this payment is associated with."
          },
          "payment_method": {
            "kind": "enum",
            "values": [
              "credit card",
              "debit card",
              "cash",
              "paypal"
            ],
            "description": "Method used for payment."
          },
          "payment_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date and time when the payment was made.",
            "trend": "growing"
          },
          "amount": {
            "kind": "decimal",
            "min": 20,
            "max": 500,
            "scale": 2,
            "description": "Amount paid for the rental."
          }
        }
      },
      "maintenance": {
        "description": "This table captures the maintenance records for each vehicle, detailing the type of service performed.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each maintenance record."
          },
          "vehicle_id": {
            "kind": "fk",
            "ref": "vehicles.id",
            "description": "The vehicle that underwent maintenance."
          },
          "maintenance_type": {
            "kind": "enum",
            "values": [
              "oil change",
              "tire rotation",
              "brake service",
              "full service"
            ],
            "description": "Type of maintenance performed."
          },
          "maintenance_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date when maintenance was performed.",
            "dayProfile": "business"
          },
          "cost": {
            "kind": "decimal",
            "min": 50,
            "max": 500,
            "scale": 2,
            "description": "Cost of the maintenance service."
          }
        }
      },
      "insurance_plans": {
        "description": "This table outlines the various insurance plans available for customers renting vehicles.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each insurance plan."
          },
          "plan_name": {
            "kind": "words",
            "description": "Name of the insurance plan."
          },
          "coverage_details": {
            "kind": "sentence",
            "description": "Details of what the insurance covers."
          },
          "premium": {
            "kind": "decimal",
            "min": 10,
            "max": 100,
            "scale": 2,
            "description": "Monthly premium for the insurance plan."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "monetary"
    ],
    "analysisQuestions": [
      "What is the average rental duration for economy vehicles?",
      "Which payment methods are most popular among customers?",
      "How often do vehicles require maintenance, and what types of services are most common?",
      "What is the total revenue generated from rentals during peak holiday periods?",
      "How do insurance plan selections vary based on customer demographics?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Rentals and Customers",
        "sql": "SELECT r.id, c.first_name, c.last_name FROM rentals r JOIN customers c ON r.customer_id = c.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Rentals by Vehicle Type",
        "sql": "SELECT v.vehicle_type, COUNT(r.id) AS rental_count FROM rentals r JOIN vehicles v ON r.vehicle_id = v.id GROUP BY v.vehicle_type;",
        "dialect": "postgres"
      },
      {
        "title": "Total Revenue by Payment Method",
        "sql": "SELECT p.payment_method, SUM(p.amount) AS total_revenue FROM payments p JOIN rentals r ON p.rental_id = r.id GROUP BY p.payment_method;",
        "dialect": "postgres"
      },
      {
        "title": "Average Maintenance Cost per Vehicle",
        "sql": "SELECT v.make, v.model, AVG(m.cost) AS avg_maintenance_cost FROM maintenance m JOIN vehicles v ON m.vehicle_id = v.id GROUP BY v.make, v.model;",
        "dialect": "postgres"
      },
      {
        "title": "Insurance Plan Selection by Vehicle Type",
        "sql": "SELECT v.vehicle_type, COUNT(i.id) AS plan_count FROM insurance_plans i JOIN rentals r ON i.id = r.insurance_plan_id JOIN vehicles v ON r.vehicle_id = v.id GROUP BY v.vehicle_type;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Data Analysis for Rental Agencies",
        "body": "Car rental agencies can utilize this dataset to analyze customer rental patterns and preferences. By examining rental durations and vehicle types, agencies can optimize their fleet management and marketing strategies to cater to peak seasons and customer demands."
      },
      {
        "title": "Insurance Plan Development",
        "body": "Insurance companies can leverage this dataset to evaluate the effectiveness of various insurance plans offered to rental customers. Analyzing the correlation between vehicle types and insurance selections can guide the development of tailored coverage options."
      },
      {
        "title": "Maintenance Scheduling",
        "body": "Fleet managers can use the maintenance records to schedule timely vehicle servicing and ensure optimal fleet performance. By tracking the types of maintenance performed, they can identify recurring issues and improve the overall vehicle reliability."
      },
      {
        "title": "Customer Relationship Management",
        "body": "CRM specialists can analyze customer data to develop targeted marketing campaigns. Understanding customer preferences, such as preferred vehicle types and payment methods, allows for personalized offers that enhance customer satisfaction and loyalty."
      }
    ]
  },
  "counts": {
    "customers": 200,
    "insurance_plans": 50,
    "vehicles": 150,
    "maintenance": 100,
    "rentals": 300,
    "payments": 300
  },
  "stats": {
    "customers": {
      "rows": 200,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 200,
          "min": 1,
          "max": 200
        },
        "first_name": {
          "nulls": 0,
          "distinct": 69,
          "min": "Ana",
          "max": "Zoe"
        },
        "last_name": {
          "nulls": 0,
          "distinct": 78,
          "min": "Adams",
          "max": "Zhang"
        },
        "email": {
          "nulls": 0,
          "distinct": 199
        },
        "phone": {
          "nulls": 0,
          "distinct": 195
        },
        "preferred_vehicle_type": {
          "nulls": 0,
          "distinct": 4,
          "min": "SUV",
          "max": "mid-size"
        }
      }
    },
    "vehicles": {
      "rows": 150,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 150,
          "min": 1,
          "max": 150
        },
        "make": {
          "nulls": 0,
          "distinct": 150
        },
        "model": {
          "nulls": 0,
          "distinct": 150
        },
        "year": {
          "nulls": 0,
          "distinct": 24,
          "min": 2000,
          "max": 2023
        },
        "vehicle_type": {
          "nulls": 0,
          "distinct": 4,
          "min": "SUV",
          "max": "mid-size"
        },
        "availability_status": {
          "nulls": 0,
          "distinct": 3,
          "min": "available",
          "max": "rented"
        }
      }
    },
    "rentals": {
      "rows": 300,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 300,
          "min": 1,
          "max": 300
        },
        "customer_id": {
          "nulls": 0,
          "distinct": 165,
          "min": 1,
          "max": 200
        },
        "vehicle_id": {
          "nulls": 0,
          "distinct": 126,
          "min": 1,
          "max": 150
        },
        "rental_start": {
          "nulls": 0,
          "distinct": 300,
          "min": "2023-01-02 19:56:39",
          "max": "2023-12-30 18:35:49"
        },
        "rental_end": {
          "nulls": 0,
          "distinct": 300,
          "min": "2023-01-09 16:09:16",
          "max": "2024-01-20 02:03:06"
        },
        "total_cost": {
          "nulls": 0,
          "distinct": 299,
          "min": 21.36,
          "max": 499.93
        }
      }
    },
    "payments": {
      "rows": 300,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 300,
          "min": 1,
          "max": 300
        },
        "rental_id": {
          "nulls": 0,
          "distinct": 194,
          "min": 3,
          "max": 299
        },
        "payment_method": {
          "nulls": 0,
          "distinct": 4,
          "min": "cash",
          "max": "paypal"
        },
        "payment_date": {
          "nulls": 0,
          "distinct": 300,
          "min": "2023-01-08 19:40:37",
          "max": "2023-12-31 23:12:47"
        },
        "amount": {
          "nulls": 0,
          "distinct": 300,
          "min": 20.1,
          "max": 499.9
        }
      }
    },
    "maintenance": {
      "rows": 100,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 100,
          "min": 1,
          "max": 100
        },
        "vehicle_id": {
          "nulls": 0,
          "distinct": 77,
          "min": 2,
          "max": 150
        },
        "maintenance_type": {
          "nulls": 0,
          "distinct": 4,
          "min": "brake service",
          "max": "tire rotation"
        },
        "maintenance_date": {
          "nulls": 0,
          "distinct": 100,
          "min": "2023-01-03 15:08:17",
          "max": "2023-12-18 17:05:19"
        },
        "cost": {
          "nulls": 0,
          "distinct": 99,
          "min": 50.59,
          "max": 495.19
        }
      }
    },
    "insurance_plans": {
      "rows": 50,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 50,
          "min": 1,
          "max": 50
        },
        "plan_name": {
          "nulls": 0,
          "distinct": 50
        },
        "coverage_details": {
          "nulls": 0,
          "distinct": 50
        },
        "premium": {
          "nulls": 0,
          "distinct": 50,
          "min": 10.17,
          "max": 97.98
        }
      }
    }
  },
  "artifacts": [
    {
      "file": "csv/customers.csv",
      "format": "csv",
      "table": "customers",
      "key": "datasets/vehicle-rental-operations/v1/csv/customers.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/customers.csv",
      "bytes": 12877,
      "sha256": "41981581253e76600491162250a71eb8d0b4d5b9b03179d448bf5668a8531df5",
      "rows": 200,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/insurance_plans.csv",
      "format": "csv",
      "table": "insurance_plans",
      "key": "datasets/vehicle-rental-operations/v1/csv/insurance_plans.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/insurance_plans.csv",
      "bytes": 4463,
      "sha256": "a1bf7c31860b9b36a34bdd47c071455493414acbc782562119990308ab92e69b",
      "rows": 50,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/vehicles.csv",
      "format": "csv",
      "table": "vehicles",
      "key": "datasets/vehicle-rental-operations/v1/csv/vehicles.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/vehicles.csv",
      "bytes": 12220,
      "sha256": "fed349795bd31b05db323cbf27f0cf5ac31eca58a72e0936d9ea83a09f1847f0",
      "rows": 150,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/maintenance.csv",
      "format": "csv",
      "table": "maintenance",
      "key": "datasets/vehicle-rental-operations/v1/csv/maintenance.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/maintenance.csv",
      "bytes": 4755,
      "sha256": "d60640abed3ebdae904ef50f99c6f456b7b782afc18593ddafb97b7fa90102c1",
      "rows": 100,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/rentals.csv",
      "format": "csv",
      "table": "rentals",
      "key": "datasets/vehicle-rental-operations/v1/csv/rentals.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/rentals.csv",
      "bytes": 17517,
      "sha256": "230da34042af39d4336a447f9538bcb051d481482f0c3c5596a7bdda4b2f2115",
      "rows": 300,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/payments.csv",
      "format": "csv",
      "table": "payments",
      "key": "datasets/vehicle-rental-operations/v1/csv/payments.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/csv/payments.csv",
      "bytes": 13153,
      "sha256": "9ede88d90c336aff8290c3c75f6687bda9fa0e0e8b65baa4c7195e877b87b1ba",
      "rows": 300,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "vehicle-rental-operations.json",
      "format": "json",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/vehicle-rental-operations.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/vehicle-rental-operations.json",
      "bytes": 203498,
      "sha256": "17fb1be0ff2e42e30303118a9a9d5c51fc70074e4344294bbbb53c9707494049",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    },
    {
      "file": "sql/postgres.sql",
      "format": "sql-postgres",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/sql/postgres.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/sql/postgres.sql",
      "bytes": 86192,
      "sha256": "093ea6d81c776824a2915d69707436eb228c60abc73f399c92dd7bac61b850c3",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mysql.sql",
      "format": "sql-mysql",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/sql/mysql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/sql/mysql.sql",
      "bytes": 85509,
      "sha256": "7f93c9bab67ee7a97e86b4e438f7a01611dcbaed0a78ffea9caf317d1af274a6",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mssql.sql",
      "format": "sql-mssql",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/sql/mssql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/sql/mssql.sql",
      "bytes": 89020,
      "sha256": "514a69f6d5054ec698964c78c53b74f7bf0b20333c93335d135630ccf1c66250",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/sqlite.sql",
      "format": "sql-sqlite",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/sql/sqlite.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/sql/sqlite.sql",
      "bytes": 85264,
      "sha256": "f434a5bf0d4e2a2e6c1be5e2d465ab3f8ad9fd4e84ba147e3756d8f48cd37270",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "prisma/seed.ts",
      "format": "prisma-seed",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/prisma/seed.ts",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/prisma/seed.ts",
      "bytes": 172677,
      "sha256": "995f5269ff6c6a955b00b529cfc9ee88312e71b8031cbb2937481c25cf3fcc6c",
      "rows": null,
      "contentType": "application/typescript; charset=utf-8"
    },
    {
      "file": "django/fixtures.json",
      "format": "django-fixture",
      "table": null,
      "key": "datasets/vehicle-rental-operations/v1/django/fixtures.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/vehicle-rental-operations/v1/django/fixtures.json",
      "bytes": 251957,
      "sha256": "c73df597846e883e85b98bba28e6e0f504bc39cfc5482e346159942e61d05bfe",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    }
  ],
  "publishedAt": 1788765851710,
  "updatedAt": 1788765851710
}