{
  "format": "dataset-manifest/1",
  "slug": "ai-powered-personal-finance-planner",
  "version": 1,
  "seed": "ai-powered-personal-finance-planner:1",
  "spec": {
    "format": "dataset/1",
    "slug": "ai-powered-personal-finance-planner",
    "name": "Personal Finance Ledger",
    "tagline": "User financial records including income, expenses, investments, savings goals, and insurance policies.",
    "description": "Users actively manage their financial journeys through a personal finance service that helps optimize income and expenditures. By tracking income predictions, monitoring investment accounts, and managing savings goals, individuals gain valuable insights into their financial health. This operation collects data on various financial transactions and interactions, offering a comprehensive view of each user's financial landscape. The interactions are not limited to income and expenses; users also regularly engage with their insurance policies, ensuring they manage risks effectively while pursuing financial stability.\n\nThe dataset consists of several interconnected tables: 'users' captures individual profiles, while 'income' and 'expenses' provide detailed records of financial inflows and outflows, respectively. The 'investments' table contains data on users' assets aimed at growing their wealth, while 'savings_goals' outlines specific targets users set for future savings. Lastly, 'insurance_policies' records the different insurance coverage each user holds, reflecting their risk management strategies. Each row in these tables represents a unique aspect of a user's financial situation, allowing for a variety of queries about their economic behavior.\n\nThis data is excellent for exploring questions such as how income and expenses correlate, what investment strategies are most common among users, and how effectively individuals are reaching their savings goals. Additionally, users' interactions with their insurance policies can highlight trends in risk management and protection choices. The dataset is synthetic, ensuring that it simulates realistic financial behaviors while maintaining user privacy. It offers a rich environment for developers to practice data analysis, financial modeling, and visualization techniques.",
    "domain": "insurance",
    "shape": "ledger",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "personal finance",
      "income tracking",
      "expense management",
      "investment accounts",
      "savings goals",
      "insurance policies"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table holds user profiles, each representing a unique individual utilizing the finance planner. It links to other tables through user identifiers.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the user."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "The email address of the user."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "The date when the user account was created.",
            "dayProfile": "business"
          }
        }
      },
      "income": {
        "description": "This table captures various income streams for users, linking back to the users table through user identifiers.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each income record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "amount": {
            "kind": "decimal",
            "min": 1000,
            "max": 20000,
            "scale": 2,
            "distribution": "heavy-tail",
            "description": "The amount of income in currency."
          },
          "source": {
            "kind": "words",
            "min": 3,
            "max": 50,
            "description": "Description of the income source.",
            "nullable": true
          },
          "received_at": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "The date when the income was received.",
            "trend": "growing"
          }
        }
      },
      "expenses": {
        "description": "This table records various expenses incurred by users, linked to the users table through user identifiers.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 10,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each expense record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "amount": {
            "kind": "decimal",
            "min": 1,
            "max": 5000,
            "scale": 2,
            "distribution": "normal",
            "description": "The amount of the expense in currency."
          },
          "category": {
            "kind": "enum",
            "values": [
              "food",
              "transport",
              "entertainment",
              "utilities",
              "health",
              "education"
            ],
            "description": "The category of the expense.",
            "nullable": true
          },
          "incurred_at": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "The date when the expense was incurred.",
            "nullable": true,
            "when": {
              "column": "category",
              "in": [
                "food",
                "transport",
                "entertainment",
                "utilities",
                "health",
                "education"
              ]
            },
            "trend": "growing"
          }
        }
      },
      "investments": {
        "description": "This table tracks user investments, linking back to users through user identifiers. It captures significant financial decisions.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 0,
          "max": 3,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each investment record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "amount": {
            "kind": "decimal",
            "min": 1000,
            "max": 100000,
            "scale": 2,
            "distribution": "heavy-tail",
            "description": "The amount invested in currency."
          },
          "investment_type": {
            "kind": "enum",
            "values": [
              "stocks",
              "bonds",
              "real estate",
              "mutual funds"
            ],
            "description": "Type of investment.",
            "nullable": true
          },
          "invested_at": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "The date when the investment was made.",
            "nullable": true,
            "when": {
              "column": "investment_type",
              "in": [
                "stocks",
                "bonds",
                "real estate",
                "mutual funds"
              ]
            },
            "trend": "growing"
          }
        }
      },
      "savings_goals": {
        "description": "This table represents various savings goals set by users, linking back to users through user identifiers.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each savings goal record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "goal_name": {
            "kind": "words",
            "min": 3,
            "max": 50,
            "description": "The name of the savings goal.",
            "nullable": true
          },
          "target_amount": {
            "kind": "decimal",
            "min": 100,
            "max": 50000,
            "scale": 2,
            "description": "The target amount for the savings goal in currency."
          },
          "deadline": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2025-12-31",
            "description": "The target date for achieving the savings goal.",
            "trend": "seasonal"
          }
        }
      },
      "insurance_policies": {
        "description": "This table contains information about various insurance policies held by users, linking to the users table.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 0,
          "max": 2,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each insurance policy record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "policy_type": {
            "kind": "enum",
            "values": [
              "health",
              "life",
              "auto",
              "home"
            ],
            "description": "Type of insurance policy."
          },
          "premium": {
            "kind": "decimal",
            "min": 50,
            "max": 2000,
            "scale": 2,
            "description": "The premium amount for the policy in currency."
          },
          "coverage_amount": {
            "kind": "decimal",
            "min": 10000,
            "max": 500000,
            "scale": 2,
            "description": "The coverage amount of the insurance policy in currency."
          },
          "start_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "The date when the policy started.",
            "nullable": true,
            "when": {
              "column": "policy_type",
              "in": [
                "health",
                "life",
                "auto",
                "home"
              ]
            },
            "trend": "seasonal"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "monetary",
      "categorical",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most common sources of income among users?",
      "How do users categorize their expenses, and which category has the highest spending?",
      "What percentage of users have specific types of insurance policies?",
      "How do savings goals vary among different users?",
      "What trends can be observed in user investments over time?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users and Income",
        "sql": "SELECT users.full_name, income.amount FROM users JOIN income ON users.id = income.user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Aggregate Total Expenses by Category",
        "sql": "SELECT category, SUM(amount) AS total_expenses FROM expenses GROUP BY category;",
        "dialect": "postgres"
      },
      {
        "title": "Count Investments by Type",
        "sql": "SELECT investment_type, COUNT(*) AS investment_count FROM investments GROUP BY investment_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average Savings Goal Amount",
        "sql": "SELECT AVG(target_amount) AS average_savings FROM savings_goals;",
        "dialect": "postgres"
      },
      {
        "title": "Insurance Policy Coverage Analysis",
        "sql": "SELECT policy_type, AVG(coverage_amount) AS average_coverage FROM insurance_policies GROUP BY policy_type;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Financial Educators",
        "body": "Financial educators can utilize this dataset to teach students about personal finance management, including budgeting, saving, investing, and understanding insurance. By analyzing the data, learners can gain insights into real-world financial scenarios and improve their financial literacy."
      },
      {
        "title": "Developers Building Financial Applications",
        "body": "Developers creating personal finance applications can use this dataset to test features like income tracking, expense categorization, and savings goal management. The realistic data allows for effective testing of functionalities and performance of financial tools."
      },
      {
        "title": "Data Analysts in Finance",
        "body": "Data analysts working in finance can leverage this dataset to perform deeper analyses on user spending habits, investment trends, and savings behaviors. Insights derived from the dataset can inform financial advising and strategies for improving user financial health."
      },
      {
        "title": "Researchers in Personal Finance",
        "body": "Researchers studying personal finance behaviors can use this dataset to conduct studies on income disparities, spending patterns, and the impact of savings goals on financial stability. The data provides a valuable resource for academic research in the field of finance."
      }
    ]
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    "income": 464,
    "insurance_policies": 133,
    "investments": 190,
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