{ "format": "dataset-manifest/1", "slug": "travel-insurance-database", "version": 3, "seed": "travel-insurance-database:1", "engine": 1, "engineVersion": "1.0.0", "spec": { "format": "dataset/1", "slug": "travel-insurance-database", "name": "Travel Insurance Insights", "tagline": "Travelers, policies, claims, and emergency services data from various travel insurance incidents and destinations.", "description": "Travelers purchase insurance plans to safeguard their journeys against unexpected events. This business focuses on providing essential coverage for situations like trip cancellations, medical emergencies, and other unforeseen incidents, ensuring that individuals can travel with peace of mind. The data includes a variety of records from different travelers, detailing their flight information, the types of policies they choose, and any claims they might file after their trips. The operations involve assessing the needs of customers based on popular destinations and common risk factors, allowing companies to tailor their offerings effectively.\n\nIn this dataset, the travelers table contains individual records with information such as personal details and trip specifics. Each traveler is linked to a policy in the policies table, which outlines the type of coverage chosen, its duration, and related costs. Claims are logged in the claims table, where each claim reflects incidents that may occur during a trip, such as medical emergencies or lost luggage. The emergency_services table provides insights into the medical assistance and support available to travelers, while the destinations table lists popular locations where travelers are heading. Lastly, claims_history connects claims to specific travelers and policies, ensuring a comprehensive view of insurance incidents.\n\nThis relational structure allows for a variety of analyses and could answer questions such as which destinations have the highest claim rates, what types of policies are most popular among travelers, and how claims correlate with the services provided. Practicing on this data can help develop skills in data manipulation, visualization, and business intelligence, to better understand customer behaviors and insurance trends. Note that all entries are synthetic, designed to simulate realistic scenarios without representing actual individuals or events.", "domain": "insurance", "shape": "transactional", "useCases": [ "sql-practice", "orm-seeding" ], "keywords": [ "travel insurance", "claims", "policies", "travel details", "emergency services", "data insights" ], "locale": "en", "license": "CC0-1.0", "version": 1, "tables": { "travelers": { "description": "This table contains records of travelers who purchase insurance policies, linking to their respective policies and claims.", "rows": 300, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each traveler." }, "full_name": { "kind": "fullName", "description": "Traveler's full name.", "nullable": true }, "email": { "kind": "email", "from": "full_name", "description": "Traveler's email address.", "nullable": true }, "country": { "kind": "country", "description": "Country of residence for the traveler.", "nullable": true }, "date_of_birth": { "kind": "date", "from": "1950-01-01", "to": "2005-01-01", "description": "Traveler's date of birth.", "nullable": true } } }, "policies": { "description": "This table outlines the different travel insurance policies available, linking policies to travelers and claims.", "rows": 150, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each insurance policy." }, "policy_type": { "kind": "enum", "values": [ "Standard", "Premium", "Basic" ], "description": "Type of insurance policy.", "weights": [ 6, 3, 1 ] }, "coverage_amount": { "kind": "decimal", "min": 1000, "max": 100000, "scale": 2, "description": "Maximum coverage amount for the policy.", "nullable": true, "when": { "column": "policy_type", "in": [ "Standard", "Premium" ] }, "distribution": "long-tail" }, "traveler_id": { "kind": "fk", "ref": "travelers.id", "description": "Links to the traveler who purchased this policy." }, "premium_amount": { "kind": "decimal", "min": 100, "max": 2000, "distribution": "long-tail", "description": "Monthly premium amount for the insurance policy." }, "duration_months": { "kind": "int", "min": 1, "max": 24, "distribution": "normal", "description": "Duration of the policy in months." } } }, "claims": { "description": "This table records claims made by travelers, linking claims to both the traveler and their respective policies.", "rows": 120, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each claim." }, "claim_amount": { "kind": "decimal", "min": 100, "max": 50000, "scale": 2, "description": "Amount claimed by the traveler.", "distribution": "long-tail" }, "claim_date": { "kind": "date", "from": "2020-01-01", "to": "2023-12-31", "description": "Date the claim was filed.", "nullable": true, "when": { "column": "status", "in": [ "Approved", "Rejected" ] }, "trend": "growing" }, "policy_id": { "kind": "fk", "ref": "policies.id", "description": "Links to the policy associated with this claim." }, "status": { "kind": "enum", "values": [ "Pending", "Approved", "Rejected" ], "description": "Current status of the claim.", "weights": [ 5, 4, 1 ] } } }, "emergency_services": { "description": "This table lists emergency services available to travelers, linking to the policies they are associated with.", "rows": 80, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each emergency service." }, "service_name": { "kind": "words", "max": 3, "description": "Name of the emergency service.", "nullable": true, "pool": [ "ambulance", "hospital", "clinic", "rescue", "evacuation", "firstaid", "urgentcare", "treatment", "support", "advice", "consultation", "transport", "surgery", "rehabilitation", "medication", "therapy", "diagnosis", "monitoring", "assessment", "intervention" ], "min": 1 }, "contact_number": { "kind": "phone", "description": "Contact number for the emergency service.", "nullable": true }, "policy_id": { "kind": "fk", "ref": "policies.id", "description": "Links to the policy associated with this emergency service." }, "availability_hours": { "kind": "int", "min": 0, "max": 24, "distribution": "normal", "description": "Number of hours the service is available per day." } } }, "destinations": { "description": "This table records popular travel destinations for insured travelers, linking to claims and policies.", "rows": 100, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each destination." }, "destination_name": { "kind": "words", "max": 3, "description": "Name of the travel destination.", "nullable": true, "pool": [ "paris", "tokyo", "newyork", "london", "sydney", "rome", "berlin", "dubai", "bangkok", "barcelona", "madrid", "singapore", "losangeles", "amsterdam", "toronto", "beijing", "moscow", "cairo", "seoul", "lisbon" ], "min": 1 }, "country": { "kind": "country", "description": "Country where the destination is located.", "nullable": true }, "policy_id": { "kind": "fk", "ref": "policies.id", "description": "Links to the policy associated with this destination." }, "popularity_rating": { "kind": "int", "min": 1, "max": 10, "distribution": "high", "description": "Rating of the destination's popularity among travelers." }, "average_cost": { "kind": "decimal", "min": 100, "max": 5000, "distribution": "long-tail", "description": "Average cost of travel to the destination." } } }, "claims_history": { "description": "This table logs the history of all claims made by travelers, providing insights into trends and patterns.", "rows": 200, "columns": { "id": { "kind": "pk", "description": "Unique identifier for each claim record." }, "traveler_id": { "kind": "fk", "ref": "travelers.id", "description": "Links to the traveler who made the claim." }, "claim_id": { "kind": "fk", "ref": "claims.id", "description": "Links to the specific claim." }, "claim_date": { "kind": "date", "from": "2020-01-01", "to": "2023-12-31", "description": "Date of the claim.", "trend": "seasonal" }, "resolution_time_days": { "kind": "int", "min": 1, "max": 90, "distribution": "normal", "description": "Number of days taken to resolve the claim." }, "resolution_status": { "kind": "enum", "values": [ "Resolved", "Unresolved", "Under Review" ], "weights": [ 50, 30, 20 ], "description": "Current status of the claim resolution." }, "claim_type": { "kind": "enum", "values": [ "Medical", "Trip Cancellation", "Lost Luggage" ], "weights": [ 40, 40, 20 ], "description": "Type of claim being made." } } } }, "structure": "multi-table", "traits": [ "categorical", "timestamped", "nullable", "high-cardinality" ], "analysisQuestions": [ "What are the most common types of claims made by travelers?", "How does claim frequency vary by travel destination?", "What is the average claim amount for different policy types?", "Are there any trends in claims based on the traveler's age?", "Which emergency services are most frequently utilized?" ], "suggestedQueries": [ { "title": "Join Travelers and Policies", "sql": "SELECT travelers.full_name, policies.policy_type FROM travelers JOIN policies ON travelers.id = policies.traveler_id;", "dialect": "postgres" }, { "title": "Total Claims by Policy Type", "sql": "SELECT policies.policy_type, SUM(claims.claim_amount) AS total_claims FROM claims JOIN policies ON claims.policy_id = policies.id GROUP BY policies.policy_type;", "dialect": "postgres" }, { "title": "Claim Status Distribution", "sql": "SELECT claims.status, COUNT(*) AS status_count FROM claims GROUP BY claims.status;", "dialect": "postgres" }, { "title": "Claim Amounts Over Time", "sql": "SELECT DATE_TRUNC('month', claims.claim_date) AS month, AVG(claims.claim_amount) AS avg_claim FROM claims GROUP BY month ORDER BY month;", "dialect": "postgres" }, { "title": "Emergency Services Utilization", "sql": "SELECT emergency_services.service_name, COUNT(claims.id) AS claim_count FROM emergency_services LEFT JOIN policies ON emergency_services.policy_id = policies.id LEFT JOIN claims ON policies.id = claims.policy_id GROUP BY emergency_services.service_name;", "dialect": "postgres" } ], "usageScenarios": [ { "title": "Insurance Analyst", "body": "An insurance analyst can utilize this dataset to identify trends in travel insurance claims, helping the company understand which types of claims are most frequent and adjusting their policies accordingly. By analyzing the data, they can make informed decisions on risk management and pricing strategies." }, { "title": "Data Scientist", "body": "A data scientist interested in predictive modeling can use this dataset to build models that forecast future claims based on traveler demographics and policy types. This analysis can help the company anticipate potential losses and refine their insurance offerings to better serve customers." }, { "title": "Customer Support Specialist", "body": "A customer support specialist can leverage this dataset to provide better assistance to travelers by identifying common issues related to claims and emergency services. Understanding the claims process and service utilization can enhance customer interactions and improve overall satisfaction." }, { "title": "Marketing Manager", "body": "A marketing manager can analyze this dataset to target promotions effectively by identifying popular destinations and policy types among travelers. By understanding customer preferences, they can design tailored marketing campaigns that resonate with potential customers, driving sales and enhancing brand loyalty." } ] }, "counts": { "travelers": 300, "policies": 150, "claims": 120, "claims_history": 200, "destinations": 100, "emergency_services": 80 }, "stats": { "travelers": { "rows": 300, "columns": { "id": { "nulls": 0, "distinct": 300, "min": 1, "max": 300 }, "full_name": { "nulls": 38, "distinct": 257, "min": "Alice Gupta", "max": "Zoe Schneider" }, "email": { "nulls": 60, "distinct": 239 }, "country": { "nulls": 34, "distinct": 42, "min": "Argentina", "max": "United States" }, "date_of_birth": { "nulls": 36, "distinct": 262, "min": "1950-01-01", "max": "2004-06-08" } } }, "policies": { "rows": 150, "columns": { "id": { "nulls": 0, "distinct": 150, "min": 1, "max": 150 }, "policy_type": { "nulls": 0, "distinct": 3, "min": "Basic", "max": "Standard" }, "coverage_amount": { "nulls": 19, "distinct": 131, "min": 1012.35, "max": 96510.41 }, "traveler_id": { "nulls": 0, "distinct": 120, "min": 1, "max": 300 }, "premium_amount": { "nulls": 0, "distinct": 150, "min": 100.67, "max": 1989.58 }, "duration_months": { "nulls": 0, "distinct": 17, "min": 3, "max": 20 } } }, "claims": { "rows": 120, "columns": { "id": { "nulls": 0, "distinct": 120, "min": 1, "max": 120 }, "claim_amount": { "nulls": 0, "distinct": 120, "min": 100.68, "max": 49807.91 }, "claim_date": { "nulls": 70, "distinct": 49, "min": "2020-05-31", "max": "2023-12-19" }, "policy_id": { "nulls": 0, "distinct": 83, "min": 1, "max": 146 }, "status": { "nulls": 0, "distinct": 3, "min": "Approved", "max": "Rejected" } } }, "emergency_services": { "rows": 80, "columns": { "id": { "nulls": 0, "distinct": 80, "min": 1, "max": 80 }, "service_name": { "nulls": 6, "distinct": 60 }, "contact_number": { "nulls": 11, "distinct": 69 }, "policy_id": { "nulls": 0, "distinct": 62, "min": 1, "max": 146 }, "availability_hours": { "nulls": 0, "distinct": 15, "min": 6, "max": 21 } } }, "destinations": { "rows": 100, "columns": { "id": { "nulls": 0, "distinct": 100, "min": 1, "max": 100 }, "destination_name": { "nulls": 12, "distinct": 74 }, "country": { "nulls": 17, "distinct": 35, "min": "Argentina", "max": "United States" }, "policy_id": { "nulls": 0, "distinct": 68, "min": 2, "max": 147 }, "popularity_rating": { "nulls": 0, "distinct": 10, "min": 1, "max": 10 }, "average_cost": { "nulls": 0, "distinct": 100, "min": 104.07, "max": 4963.67 } } }, "claims_history": { "rows": 200, "columns": { "id": { "nulls": 0, "distinct": 200, "min": 1, "max": 200 }, "traveler_id": { "nulls": 0, "distinct": 138, "min": 2, "max": 298 }, "claim_id": { "nulls": 0, "distinct": 93, "min": 1, "max": 120 }, "claim_date": { "nulls": 0, "distinct": 186, "min": "2020-01-09", "max": "2023-12-28" }, "resolution_time_days": { "nulls": 0, "distinct": 53, "min": 9, "max": 77 }, "resolution_status": { "nulls": 0, "distinct": 3, "min": "Resolved", "max": "Unresolved" }, "claim_type": { "nulls": 0, "distinct": 3, "min": "Lost Luggage", "max": "Trip Cancellation" } } } }, "artifacts": [ { "file": "csv/travelers.csv", "format": "csv", "table": "travelers", "key": "datasets/travel-insurance-database/v3/csv/travelers.csv", "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/travel-insurance-database/v3/csv/travelers.csv", "bytes": 15788, "sha256": "547e04348b35294d82e562e5daae4d73cfcce6aa6fdd3547d8aff8933b0ec237", "rows": 300, "contentType": "text/csv; 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