{
  "format": "dataset-manifest/1",
  "slug": "blockchain-based-secure-digital-transactions",
  "version": 1,
  "seed": "blockchain-based-secure-digital-transactions:1",
  "spec": {
    "format": "dataset/1",
    "slug": "blockchain-based-secure-digital-transactions",
    "name": "Secure Transaction Ledger",
    "tagline": "A synthetic dataset for practicing secure digital transaction scenarios.",
    "description": "Users execute secure digital transactions, fostering trust between themselves and service providers. This fintech business allows them to create multisignature wallets that require multiple approvals for optimal security. Every transaction adheres to compliance standards like Know Your Customer (KYC) regulations, ensuring a trustworthy environment. The heart of the operation lies in reliable transaction records, highlighting patterns of swift confirmations alongside occasional multisignature proposals that emerge during intricate deal-making scenarios. \n\nThe dataset features a single table: transactions. Each row in this table represents a distinct transaction, capturing critical details such as transaction IDs, timestamps, amounts, and the involved parties. By analyzing the transaction records, developers can explore relationships between user behavior and transaction patterns, as well as the frequency of multisignature proposals versus standard transactions. \n\nThis dataset answers pertinent questions in the fintech sphere: How often do users leverage multisignature wallets? What are the average transaction amounts? What patterns exist in transaction timing and frequency? Developers can practice their skills in database management, querying, and data visualization by interrogating these records to uncover insights into user activities and transaction behaviors. Keep in mind, the data presented here is synthetic, designed to simulate a real-world environment while maintaining user privacy.",
    "domain": "fintech",
    "shape": "ledger",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "transactions",
      "multisignature",
      "wallets",
      "fintech",
      "ledger",
      "synthetic data",
      "compliance",
      "KYC"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "transactions": {
        "description": "Each row represents a secure digital transaction, including details about the transaction amount, timestamp, user identifier, and transaction type. This table serves as a ledger for tracking user interactions with the multisignature wallets.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the transaction."
          },
          "user_id": {
            "kind": "uuid",
            "description": "Unique identifier for the user involved in the transaction.",
            "nullable": true
          },
          "amount": {
            "kind": "decimal",
            "min": 0,
            "max": 10000,
            "scale": 2,
            "description": "Transaction amount in the specified currency.",
            "nullable": true,
            "when": {
              "column": "confirmation_status",
              "in": [
                "failed"
              ]
            }
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date and time when the transaction occurred.",
            "dayProfile": "business"
          },
          "transaction_type": {
            "kind": "enum",
            "values": [
              "regular",
              "multisignature"
            ],
            "description": "Type of transaction, indicating whether it is a standard transaction or a multisignature proposal."
          },
          "confirmation_status": {
            "kind": "enum",
            "values": [
              "pending",
              "confirmed",
              "failed"
            ],
            "description": "Current status of the transaction confirmation.",
            "nullable": true,
            "when": {
              "column": "transaction_type",
              "in": [
                "multisignature"
              ]
            }
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "monetary",
      "timestamped",
      "categorical"
    ],
    "analysisQuestions": [
      "What is the distribution of transaction amounts over time?",
      "How frequently do multisignature transactions occur compared to regular transactions?",
      "What are the common confirmation statuses for transactions?"
    ],
    "suggestedQueries": [
      {
        "title": "List all transactions by user",
        "sql": "SELECT * FROM transactions WHERE user_id = 'some-uuid';",
        "dialect": "postgres"
      },
      {
        "title": "Count transactions by type",
        "sql": "SELECT transaction_type, COUNT(*) FROM transactions GROUP BY transaction_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average transaction amount by confirmation status",
        "sql": "SELECT confirmation_status, AVG(amount) FROM transactions GROUP BY confirmation_status;",
        "dialect": "postgres"
      },
      {
        "title": "Get transactions within a specific date range",
        "sql": "SELECT * FROM transactions WHERE timestamp BETWEEN '2023-06-01' AND '2023-06-30';",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Teaching SQL Basics",
        "body": "In a classroom setting, educators can utilize this dataset to teach students the fundamentals of SQL, including SELECT statements, JOIN operations, and aggregation functions. The varied transaction types and statuses provide rich opportunities for hands-on learning."
      },
      {
        "title": "Financial Analysis Practice",
        "body": "Financial analysts can practice their skills on this dataset to understand transaction trends within digital finance, exploring the impacts of transaction types on user behavior and the effectiveness of multisignature wallets."
      },
      {
        "title": "Testing Reporting Tools",
        "body": "Developers can use this synthetic dataset to test their reporting tools by creating dashboards that visualize transaction trends, user engagement, and confirmation rates, honing their skills in data presentation and analysis."
      }
    ]
  },
  "counts": {
    "transactions": 500
  },
  "stats": {
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      "columns": {
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          "nulls": 0,
          "distinct": 500,
          "min": 1,
          "max": 500
        },
        "user_id": {
          "nulls": 43,
          "distinct": 457
        },
        "amount": {
          "nulls": 410,
          "distinct": 90,
          "min": 153.46,
          "max": 9954.88
        },
        "timestamp": {
          "nulls": 0,
          "distinct": 500,
          "min": "2023-01-02 12:58:57",
          "max": "2023-12-31 18:57:14"
        },
        "transaction_type": {
          "nulls": 0,
          "distinct": 2,
          "min": "multisignature",
          "max": "regular"
        },
        "confirmation_status": {
          "nulls": 239,
          "distinct": 3,
          "min": "confirmed",
          "max": "pending"
        }
      }
    }
  },
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