{
  "format": "dataset-manifest/1",
  "slug": "ai-powered-customizable-personal-finance-solutions",
  "version": 3,
  "seed": "ai-powered-customizable-personal-finance-solutions:1",
  "spec": {
    "format": "dataset/1",
    "slug": "ai-powered-customizable-personal-finance-solutions",
    "name": "Personal Finance Insights",
    "tagline": "User profiles, financial institutions, transactions, budgets, and loans in personal finance management.",
    "description": "Individuals manage their money, seeking to achieve financial stability and growth through careful tracking of income, expenses, and savings. Users create profiles that detail their financial situations, providing insights into their unique spending habits. They interact with various financial institutions, where they hold accounts, take out loans, and make investments. Users record transactions that detail their spending across multiple categories, including common expenses such as groceries and utilities, as well as less frequent but significant financial activities like loan payments and investment purchases. \n\nThe users table holds individual profiles, each representing a unique person using the platform. Each user can link to multiple transactions in the transactions table, which records every financial activity associated with them, detailing amounts, categories, and dates. Financial institutions from the financial_institutions table are referenced in these transactions, indicating where users have accounts or loans. The budgets table provides insights into users' planned expenditures compared to actual spending through transactions, while the loans table tracks any debts and payment schedules associated with the users. \n\nThis dataset is particularly useful for answering questions related to personal finance management, such as how spending patterns change over time, the effectiveness of budgeting strategies, and the relationship between users' financial habits and their loan repayments. Analysts can explore correlations between spending categories and income levels, assess the impact of budgeting on financial health, or identify trends in loan usage among different user demographics. As this data is synthetic, it allows developers and analysts to practice their skills without the constraints of real-world data privacy and compliance issues.",
    "domain": "fintech",
    "shape": "ledger",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "personal finance",
      "transactions",
      "budgeting",
      "loans",
      "financial institutions",
      "user profiles"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table contains user profiles, linking to their financial activities. Each row represents a unique user with their financial situation.",
        "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": "Email address of the user."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Account creation date.",
            "dayProfile": "business"
          }
        }
      },
      "financial_institutions": {
        "description": "This table lists various financial institutions where users can manage their accounts. Each institution has unique offerings.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each financial institution."
          },
          "name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the financial institution.",
            "pool": [
              "bank",
              "credit",
              "union",
              "trust",
              "capital",
              "financial",
              "services",
              "investments",
              "group",
              "associates",
              "advisors",
              "partners",
              "holdings",
              "wealth",
              "management",
              "solutions",
              "insurance",
              "mortgage",
              "lending",
              "cooperative",
              "brokerage",
              "pension",
              "retirement",
              "fund",
              "asset",
              "advisory",
              "strategies",
              "global",
              "international",
              "regional",
              "local",
              "community",
              "investment",
              "development",
              "research",
              "analytics",
              "payments",
              "technology",
              "digital",
              "platform",
              "app",
              "mobile",
              "online",
              "service",
              "network",
              "exchange",
              "marketplace",
              "creditor",
              "debtor",
              "fintech",
              "innovation",
              "growth",
              "equity",
              "debt",
              "portfolio",
              "risk",
              "compliance",
              "regulatory"
            ]
          },
          "type": {
            "kind": "enum",
            "values": [
              "bank",
              "credit_union",
              "investment_firm"
            ],
            "description": "Type of financial institution.",
            "weights": [
              7,
              2,
              1
            ]
          },
          "website": {
            "kind": "url",
            "description": "Website URL of the financial institution.",
            "nullable": true,
            "when": {
              "column": "type",
              "in": [
                "bank",
                "credit_union",
                "investment_firm"
              ]
            }
          }
        }
      },
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        "description": "This table records all financial transactions made by users, including income and expenses. Each transaction is linked to a user.",
        "rows": 800,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each transaction."
          },
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            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "amount": {
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            "min": 0,
            "max": 10000,
            "scale": 2,
            "description": "Transaction amount in USD.",
            "nullable": true,
            "when": {
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                "groceries",
                "utilities",
                "rent",
                "entertainment",
                "investment"
              ]
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          },
          "category": {
            "kind": "enum",
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              "groceries",
              "utilities",
              "rent",
              "entertainment",
              "investment"
            ],
            "description": "Category of the transaction.",
            "weights": [
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              4,
              3,
              2,
              1
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            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "Date of the transaction.",
            "dayProfile": "waking",
            "trend": "growing"
          }
        }
      },
      "budgets": {
        "description": "This table outlines budget plans for users, indicating their financial goals. Each budget entry links to a user.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each budget."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "total_budget": {
            "kind": "decimal",
            "min": 100,
            "max": 5000,
            "scale": 2,
            "description": "Total budget amount in USD.",
            "nullable": true,
            "when": {
              "column": "category",
              "in": [
                "groceries",
                "utilities",
                "entertainment"
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            "distribution": "high"
          },
          "category": {
            "kind": "enum",
            "values": [
              "groceries",
              "utilities",
              "entertainment"
            ],
            "description": "Budget category.",
            "weights": [
              6,
              3,
              1
            ]
          },
          "created_at": {
            "kind": "datetime",
            "from": "2021-01-01",
            "to": "2023-01-01",
            "description": "Date when the budget was created.",
            "dayProfile": "business"
          }
        }
      },
      "loans": {
        "description": "This table contains information regarding loans taken by users, including details about the lender and loan amount.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each loan."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier linking to the user."
          },
          "financial_institution_id": {
            "kind": "fk",
            "ref": "financial_institutions.id",
            "description": "Identifier linking to the financial institution."
          },
          "amount": {
            "kind": "decimal",
            "min": 1000,
            "max": 50000,
            "scale": 2,
            "description": "Loan amount in USD.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "active",
                "paid_off",
                "defaulted"
              ]
            },
            "distribution": "heavy-tail"
          },
          "status": {
            "kind": "enum",
            "values": [
              "active",
              "paid_off",
              "defaulted"
            ],
            "description": "Current status of the loan.",
            "weights": [
              6,
              3,
              1
            ]
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Date when the loan was issued.",
            "dayProfile": "business"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "monetary",
      "nullable",
      "timestamped"
    ],
    "analysisQuestions": [
      "What are the most common categories for user expenses?",
      "How much do users typically allocate for savings each month?",
      "What percentage of users have loans, and how does it affect their budgeting?",
      "Which financial institutions are most frequently used by users?",
      "What trends can be observed in the income and expenses over the year?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users and Transactions",
        "sql": "SELECT u.full_name, t.amount, t.category FROM users u JOIN transactions t ON u.id = t.user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Average Budget by Category",
        "sql": "SELECT b.category, AVG(b.total_budget) as average_budget FROM budgets b GROUP BY b.category;",
        "dialect": "postgres"
      },
      {
        "title": "Total Loan Amount by Financial Institution",
        "sql": "SELECT fi.name, SUM(l.amount) as total_loans FROM loans l JOIN financial_institutions fi ON l.financial_institution_id = fi.id GROUP BY fi.name;",
        "dialect": "postgres"
      },
      {
        "title": "Monthly Spending Trends",
        "sql": "SELECT DATE_TRUNC('month', t.transaction_date) as month, SUM(t.amount) as total_spent FROM transactions t GROUP BY month ORDER BY month;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Personal Finance Educator",
        "body": "An educator teaching personal finance can use this dataset to demonstrate how different financial elements interact. By analyzing user transactions and budgets, they can create real-world scenarios that help students understand budgeting, savings, and managing loans."
      },
      {
        "title": "Financial Analyst",
        "body": "A financial analyst can leverage this dataset to assess spending patterns among users. By identifying trends in transaction categories, they can provide insights on common financial behaviors and suggest areas where users can optimize their spending."
      },
      {
        "title": "App Developer",
        "body": "An app developer can use this dataset to build a personal finance management application. By simulating user interactions with budgets, transactions, and loans, the developer can test features and ensure the app provides valuable insights to users."
      }
    ]
  },
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    "users": 200,
    "budgets": 150,
    "loans": 100,
    "transactions": 800
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