{
  "format": "dataset-manifest/1",
  "slug": "claims-warehouse",
  "version": 3,
  "seed": "claims-warehouse:1",
  "spec": {
    "format": "dataset/1",
    "slug": "claims-warehouse",
    "name": "Claims Warehouse",
    "tagline": "Claims, policies, product lines, and regions for analyzing insurance loss ratios and frequencies.",
    "description": "Claims are processed and analyzed in an insurance firm, where dedicated teams assess incidents and determine payouts based on various policies. Each claim is linked to a specific insurance policy, which outlines the coverage details and terms agreed upon between the insurer and the policyholder. The claims operation dives into the specifics of each incident, helping the company assess the financial implications of claims against the premiums collected. Data from the claims table provides insights into the frequency and financial outcomes of these claims, allowing the business to evaluate their overall performance and determine loss ratios for informed decision-making.\n\nThe dataset includes several interconnected tables that enhance the analysis. The claims table serves as the central fact table, with every row representing a unique claim submission. This fact table is linked to the policies table, where each claim is associated with a specific policy that defines the coverage terms. Additionally, each claim is categorized under a product line from the product_lines table, detailing the type of insurance coverage provided. The regions table further segments data, linking claims to geographical areas, which can reveal trends and patterns in claims across different locations. Lastly, the dates table allows users to analyze claims over time, understanding how trends may shift based on seasonality or other temporal factors.\n\nThis data empowers analysts to answer critical business questions such as: Which product lines generate the most claims? How does the loss ratio vary by region? What are the claim frequencies in different periods? Practicing with this dataset equips developers with the skills to perform complex joins and aggregations, fostering a deeper understanding of relational databases in the insurance domain. Additionally, it's important to note that the data provided is synthetic, designed for learning and practice purposes.",
    "domain": "insurance",
    "shape": "star-schema",
    "useCases": [
      "bi-dashboards",
      "etl-pipelines"
    ],
    "keywords": [
      "claims",
      "insurance",
      "data warehouse",
      "analytics",
      "ETL",
      "business intelligence",
      "star-schema"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "claims": {
        "description": "This table records individual claims, linking to dimensions such as policy, product line, region, and date.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each claim."
          },
          "policy_id": {
            "kind": "fk",
            "ref": "policies.id",
            "description": "References the related policy for the claim."
          },
          "product_line_id": {
            "kind": "fk",
            "ref": "product_lines.id",
            "description": "References the product line associated with the claim."
          },
          "region_id": {
            "kind": "fk",
            "ref": "regions.id",
            "description": "References the region where the claim occurred."
          },
          "date_id": {
            "kind": "fk",
            "ref": "dates.id",
            "description": "References the date when the claim was filed."
          },
          "claim_amount": {
            "kind": "decimal",
            "min": 100,
            "max": 50000,
            "scale": 2,
            "description": "Amount claimed in the insurance.",
            "distribution": "long-tail"
          },
          "status": {
            "kind": "enum",
            "values": [
              "open",
              "closed",
              "pending"
            ],
            "description": "Current status of the claim.",
            "weights": [
              8,
              12,
              3
            ]
          }
        }
      },
      "policies": {
        "description": "This table contains policy details linked to claims, including policyholder information and coverage types.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each policy."
          },
          "policyholder_name": {
            "kind": "fullName",
            "description": "Name of the policyholder."
          },
          "coverage_type": {
            "kind": "enum",
            "values": [
              "basic",
              "standard",
              "premium"
            ],
            "description": "Type of coverage provided by the policy.",
            "weights": [
              5,
              7,
              3
            ]
          },
          "start_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the policy became effective.",
            "trend": "growing"
          },
          "end_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the policy expires.",
            "trend": "growing"
          }
        }
      },
      "product_lines": {
        "description": "This table defines different product lines available in the insurance offerings.",
        "rows": 3,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each product line."
          },
          "name": {
            "kind": "title",
            "description": "Name of the product line (e.g., auto, health, home).",
            "pool": [
              "auto",
              "health",
              "home",
              "life",
              "travel",
              "disability",
              "property",
              "liability",
              "flood",
              "earthquake",
              "marine",
              "pet",
              "business",
              "workers-compensation",
              "critical-illness",
              "long-term-care",
              "accident",
              "vision",
              "dental",
              "umbrella",
              "title"
            ],
            "min": 1,
            "max": 3
          }
        }
      },
      "regions": {
        "description": "This table captures geographical regions where claims are filed.",
        "rows": 10,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each region."
          },
          "region_name": {
            "kind": "words",
            "description": "Name of the region (e.g., North, South).",
            "pool": [
              "North",
              "South",
              "East",
              "West",
              "Central",
              "Northeast",
              "Southeast",
              "Northwest",
              "Southwest",
              "Midwest",
              "Pacific",
              "Atlantic",
              "Mountain",
              "Plains",
              "GreatLakes",
              "Appalachian",
              "Desert",
              "Coastal",
              "Urban",
              "Rural",
              "Suburban"
            ],
            "min": 1,
            "max": 2
          }
        }
      },
      "dates": {
        "description": "This table provides a date dimension for analyzing claims over time.",
        "rows": 365,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each date."
          },
          "date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "The date value.",
            "trend": "seasonal"
          },
          "month": {
            "kind": "int",
            "min": 1,
            "max": 12,
            "description": "Numeric representation of the month."
          },
          "year": {
            "kind": "int",
            "min": 2020,
            "max": 2023,
            "description": "Year of the date."
          },
          "day_of_week": {
            "kind": "enum",
            "values": [
              "Monday",
              "Tuesday",
              "Wednesday",
              "Thursday",
              "Friday",
              "Saturday",
              "Sunday"
            ],
            "description": "Day of the week.",
            "weights": [
              5,
              5,
              5,
              5,
              5,
              3,
              2
            ]
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable"
    ],
    "analysisQuestions": [
      "What is the average claim amount by product line?",
      "How do claims vary across different regions?",
      "What is the loss ratio for each product line over the years?"
    ],
    "suggestedQueries": [
      {
        "title": "Join claims with policies",
        "sql": "SELECT claims.id, policies.policyholder_name FROM claims JOIN policies ON claims.policy_id = policies.id;",
        "dialect": "postgres"
      },
      {
        "title": "Aggregate claims by product line",
        "sql": "SELECT product_lines.name, COUNT(claims.id) AS total_claims FROM claims JOIN product_lines ON claims.product_line_id = product_lines.id GROUP BY product_lines.name;",
        "dialect": "postgres"
      },
      {
        "title": "Monthly claims report",
        "sql": "SELECT dates.month, COUNT(claims.id) AS claim_count FROM claims JOIN dates ON claims.date_id = dates.id GROUP BY dates.month ORDER BY dates.month;",
        "dialect": "postgres"
      },
      {
        "title": "Average claim amount by year",
        "sql": "SELECT dates.year, AVG(claims.claim_amount) AS average_claim FROM claims JOIN dates ON claims.date_id = dates.id GROUP BY dates.year;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Underwriting Analysis",
        "body": "Insurance underwriters can use this dataset to analyze claims data and assess risk factors associated with different policies and regions. By understanding loss ratios and claim frequencies, they can make informed decisions on policy pricing and coverage."
      },
      {
        "title": "Claims Management",
        "body": "Claims adjusters can utilize this dataset to track and manage claims more effectively. By examining the status of claims across various product lines, they can identify trends, manage workloads, and ensure timely resolutions to claims."
      },
      {
        "title": "Performance Reporting",
        "body": "Business analysts can leverage this dataset to create performance dashboards that visualize claims data over time. By exploring metrics such as claims by month or product line, stakeholders can gain insights into operational efficiency and identify areas for improvement."
      }
    ]
  },
  "counts": {
    "dates": 365,
    "policies": 200,
    "product_lines": 3,
    "regions": 10,
    "claims": 500
  },
  "stats": {
    "claims": {
      "rows": 500,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 500,
          "min": 1,
          "max": 500
        },
        "policy_id": {
          "nulls": 0,
          "distinct": 181,
          "min": 1,
          "max": 200
        },
        "product_line_id": {
          "nulls": 0,
          "distinct": 3,
          "min": 1,
          "max": 3
        },
        "region_id": {
          "nulls": 0,
          "distinct": 10,
          "min": 1,
          "max": 10
        },
        "date_id": {
          "nulls": 0,
          "distinct": 274,
          "min": 1,
          "max": 364
        },
        "claim_amount": {
          "nulls": 0,
          "distinct": 500,
          "min": 100.03,
          "max": 49809.9
        },
        "status": {
          "nulls": 0,
          "distinct": 3,
          "min": "closed",
          "max": "pending"
        }
      }
    },
    "policies": {
      "rows": 200,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 200,
          "min": 1,
          "max": 200
        },
        "policyholder_name": {
          "nulls": 0,
          "distinct": 200,
          "min": "Alice Becker",
          "max": "Zoe Smith"
        },
        "coverage_type": {
          "nulls": 0,
          "distinct": 3,
          "min": "basic",
          "max": "standard"
        },
        "start_date": {
          "nulls": 0,
          "distinct": 184,
          "min": "2020-01-05",
          "max": "2023-12-30"
        },
        "end_date": {
          "nulls": 0,
          "distinct": 190,
          "min": "2020-01-19",
          "max": "2023-12-31"
        }
      }
    },
    "product_lines": {
      "rows": 3,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 3,
          "min": 1,
          "max": 3
        },
        "name": {
          "nulls": 0,
          "distinct": 3
        }
      }
    },
    "regions": {
      "rows": 10,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 10,
          "min": 1,
          "max": 10
        },
        "region_name": {
          "nulls": 0,
          "distinct": 9
        }
      }
    },
    "dates": {
      "rows": 365,
      "columns": {
        "id": {
          "nulls": 0,
          "distinct": 365,
          "min": 1,
          "max": 365
        },
        "date": {
          "nulls": 0,
          "distinct": 320,
          "min": "2020-01-07",
          "max": "2023-12-26"
        },
        "month": {
          "nulls": 0,
          "distinct": 12,
          "min": 1,
          "max": 12
        },
        "year": {
          "nulls": 0,
          "distinct": 4,
          "min": 2020,
          "max": 2023
        },
        "day_of_week": {
          "nulls": 0,
          "distinct": 7,
          "min": "Friday",
          "max": "Wednesday"
        }
      }
    }
  },
  "artifacts": [
    {
      "file": "csv/dates.csv",
      "format": "csv",
      "table": "dates",
      "key": "datasets/claims-warehouse/v3/csv/dates.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/csv/dates.csv",
      "bytes": 11376,
      "sha256": "4c2be34f9b448286ef8c260fbadad176e4c96e06f44288d01ec5106ad7fa5270",
      "rows": 365,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/policies.csv",
      "format": "csv",
      "table": "policies",
      "key": "datasets/claims-warehouse/v3/csv/policies.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/csv/policies.csv",
      "bytes": 9319,
      "sha256": "a2e019c5553cb4f034c4cb2e5736f6985e1210340441191c466aaed466f5e902",
      "rows": 200,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/product_lines.csv",
      "format": "csv",
      "table": "product_lines",
      "key": "datasets/claims-warehouse/v3/csv/product_lines.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/csv/product_lines.csv",
      "bytes": 76,
      "sha256": "653b917f8f427ab8b12f4b61466d859f3b487696bb218249f100e875de982438",
      "rows": 3,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/regions.csv",
      "format": "csv",
      "table": "regions",
      "key": "datasets/claims-warehouse/v3/csv/regions.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/csv/regions.csv",
      "bytes": 177,
      "sha256": "a93523945595b5b358244da3689ad92325a7d6802d145d8902417699b1a209bf",
      "rows": 10,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "csv/claims.csv",
      "format": "csv",
      "table": "claims",
      "key": "datasets/claims-warehouse/v3/csv/claims.csv",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/csv/claims.csv",
      "bytes": 15588,
      "sha256": "acc917b8f956cca14a879bad10dbf25ccbb613a01194101026e8217e30b8641b",
      "rows": 500,
      "contentType": "text/csv; charset=utf-8"
    },
    {
      "file": "claims-warehouse.json",
      "format": "json",
      "table": null,
      "key": "datasets/claims-warehouse/v3/claims-warehouse.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/claims-warehouse.json",
      "bytes": 171837,
      "sha256": "25d1020df09e99e761dc7a900e899245b7d4c51af88e14e51cc429d4d61179f2",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    },
    {
      "file": "sql/postgres.sql",
      "format": "sql-postgres",
      "table": null,
      "key": "datasets/claims-warehouse/v3/sql/postgres.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/sql/postgres.sql",
      "bytes": 55122,
      "sha256": "8184c094272ebb97312ba7427e79f3a170e597702e58f4cb32fbc1326a8a7a96",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mysql.sql",
      "format": "sql-mysql",
      "table": null,
      "key": "datasets/claims-warehouse/v3/sql/mysql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/sql/mysql.sql",
      "bytes": 54569,
      "sha256": "28d6c66191f3aadf537a0032e5907123ccd3e17b44d2db0eeb8d201d9e54efd7",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/mssql.sql",
      "format": "sql-mssql",
      "table": null,
      "key": "datasets/claims-warehouse/v3/sql/mssql.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/sql/mssql.sql",
      "bytes": 56921,
      "sha256": "b8f0df31e2cde5d18bd5863ee6b9c5074a1c98f2d6391d28a4443b7226306148",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "sql/sqlite.sql",
      "format": "sql-sqlite",
      "table": null,
      "key": "datasets/claims-warehouse/v3/sql/sqlite.sql",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/sql/sqlite.sql",
      "bytes": 54410,
      "sha256": "c540dd032b5afa3ac53b5ff8b9fd3e684a5068fcda54860dba84eaeeb155930f",
      "rows": null,
      "contentType": "application/sql; charset=utf-8"
    },
    {
      "file": "prisma/seed.ts",
      "format": "prisma-seed",
      "table": null,
      "key": "datasets/claims-warehouse/v3/prisma/seed.ts",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/prisma/seed.ts",
      "bytes": 127318,
      "sha256": "62d5306718385ba8d1eed398ba3b31a591826cf8a3ba9ae79f356129005f55db",
      "rows": null,
      "contentType": "application/typescript; charset=utf-8"
    },
    {
      "file": "django/fixtures.json",
      "format": "django-fixture",
      "table": null,
      "key": "datasets/claims-warehouse/v3/django/fixtures.json",
      "url": "https://database-sample-website.s3.eu-north-1.amazonaws.com/datasets/claims-warehouse/v3/django/fixtures.json",
      "bytes": 211940,
      "sha256": "2819ff193985ec4e1ee2b8ceba27b992fdaac1611ca8c33941f35d56e6188953",
      "rows": null,
      "contentType": "application/json; charset=utf-8"
    }
  ],
  "publishedAt": 1788733870711,
  "updatedAt": 1788782785407
}