{
  "format": "dataset-manifest/1",
  "slug": "eco-friendly-product-transactions",
  "version": 2,
  "seed": "eco-friendly-product-transactions:1",
  "spec": {
    "format": "dataset/1",
    "slug": "eco-friendly-product-transactions",
    "name": "Eco-Friendly Product Transactions",
    "tagline": "Transactions, user behaviors, and product details from an eco-friendly fashion marketplace.",
    "description": "Eco-conscious consumers browse and purchase sustainable fashion products through a vibrant marketplace that prioritizes ethical consumption. Users explore various products, making decisions guided by their values and preferences for environmentally friendly materials. Each transaction sheds light on customer behaviors, with data reflecting interactions that span from product selection to final purchase, shipping logistics, and potential returns due to fit or satisfaction issues. This marketplace not only facilitates sales but also fosters a community that values transparency and sustainable practices.\n\nThe dataset consists of several interconnected tables: 'users' captures information about shoppers, including demographics and preferences that shape their buying decisions. 'products' provides detailed descriptions of the items available, including sizes, materials, and sustainability ratings. 'orders' records the transactions made by users, while 'order_items' breaks down individual products within each order, linking back to the products table. The 'returns' table tracks instances where products are sent back, allowing for analysis of trends in customer satisfaction and product performance. Lastly, 'shipping' details the logistical aspects of delivering products, crucial for understanding the efficiency of operations.\n\nWith this data, developers can answer a variety of questions, such as: What are the most popular products among eco-conscious consumers? How do return rates vary by product type or size? What shipping methods are preferred for timely deliveries? Analyzing these aspects aids in understanding user preferences, optimizing inventory, and improving customer experiences. This synthetic dataset offers a rich ground for practicing data manipulation, analysis, and visualization, allowing developers to simulate real-world e-commerce scenarios within a sustainable context.",
    "domain": "ecommerce",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "sustainable fashion",
      "eco-friendly",
      "transactions",
      "user behavior",
      "product details",
      "returns",
      "shipping logistics"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "Each row represents a user in the marketplace, linking to their orders and preferences.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the user.",
            "nullable": true
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "The user's email address.",
            "nullable": true
          },
          "signup_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-10-01",
            "description": "Date when the user signed up.",
            "trend": "growing"
          },
          "preferences": {
            "kind": "json",
            "template": {
              "size": {
                "kind": "enum",
                "values": [
                  "S",
                  "M",
                  "L",
                  "XL"
                ]
              },
              "material": {
                "kind": "words",
                "max": 10
              }
            },
            "description": "User preferences for size and material.",
            "nullable": true
          }
        }
      },
      "products": {
        "description": "This table contains information about the products available in the marketplace, linking to orders and returns.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each product."
          },
          "name": {
            "kind": "productName",
            "description": "The name of the product."
          },
          "category": {
            "kind": "enum",
            "values": [
              "Clothing",
              "Accessories",
              "Footwear"
            ],
            "description": "The category of the product."
          },
          "material": {
            "kind": "words",
            "max": 3,
            "description": "Material(s) used in the product.",
            "nullable": true,
            "when": {
              "column": "category",
              "in": [
                "Clothing",
                "Accessories",
                "Footwear"
              ]
            },
            "pool": [
              "bamboo",
              "recycled",
              "organic",
              "biodegradable",
              "sustainable",
              "natural",
              "cotton",
              "jute",
              "hemp",
              "glass",
              "ceramic",
              "metal",
              "wood",
              "paper",
              "silicone",
              "linen",
              "plant",
              "corn",
              "soy",
              "rubber",
              "stone",
              "fabric",
              "fiber",
              "canvas",
              "composite",
              "polyester",
              "nylon",
              "vinyl",
              "latex",
              "aluminum",
              "steel",
              "cork",
              "bioplastic"
            ],
            "min": 1
          },
          "price": {
            "kind": "decimal",
            "min": 10,
            "max": 300,
            "scale": 2,
            "description": "Price of the product.",
            "distribution": "long-tail"
          },
          "stock_quantity": {
            "kind": "int",
            "min": 0,
            "max": 100,
            "description": "Available stock of the product."
          }
        }
      },
      "orders": {
        "description": "Each row represents an order made by a user, linking to the respective user and containing multiple order items.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each order."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "The user who made the order."
          },
          "order_date": {
            "kind": "datetime",
            "from": "2021-01-01",
            "to": "2023-10-01",
            "dayProfile": "business",
            "description": "Date and time when the order was placed."
          },
          "total_amount": {
            "kind": "decimal",
            "min": 10,
            "max": 3000,
            "scale": 2,
            "description": "Total amount of the order.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "Shipped",
                "Delivered"
              ]
            },
            "distribution": "heavy-tail"
          },
          "status": {
            "kind": "enum",
            "values": [
              "Pending",
              "Shipped",
              "Delivered",
              "Returned"
            ],
            "description": "Current status of the order."
          }
        }
      },
      "order_items": {
        "description": "This table contains items within each order, linking to the respective order and product.",
        "rows": {
          "per": "orders",
          "via": "order_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each order item."
          },
          "order_id": {
            "kind": "fk",
            "ref": "orders.id",
            "description": "The order this item belongs to."
          },
          "product_id": {
            "kind": "fk",
            "ref": "products.id",
            "description": "The product being ordered."
          },
          "quantity": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Quantity of the product ordered.",
            "distribution": "long-tail"
          }
        }
      },
      "returns": {
        "description": "This table records returns made by users, linking to the respective order and product.",
        "rows": {
          "per": "order_items",
          "via": "order_item_id",
          "min": 0,
          "max": 3,
          "skew": "heavy-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each return."
          },
          "order_item_id": {
            "kind": "fk",
            "ref": "order_items.id",
            "description": "The order item being returned."
          },
          "return_date": {
            "kind": "datetime",
            "from": "2021-01-01",
            "to": "2023-10-01",
            "description": "Date when the return was initiated.",
            "dayProfile": "waking"
          },
          "reason": {
            "kind": "sentence",
            "description": "Reason for the return.",
            "nullable": true
          }
        }
      },
      "shipping": {
        "description": "This table contains shipping information for each order, linking to the respective order.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each shipping record."
          },
          "order_id": {
            "kind": "fk",
            "ref": "orders.id",
            "description": "The order this shipping record belongs to."
          },
          "shipping_date": {
            "kind": "datetime",
            "from": "2021-01-01",
            "to": "2023-10-01",
            "description": "Date when the order was shipped.",
            "dayProfile": "business"
          },
          "delivery_date": {
            "kind": "datetime",
            "after": "shipping_date",
            "withinDays": 10,
            "description": "Expected delivery date.",
            "nullable": true,
            "when": {
              "column": "shipping_method",
              "in": [
                "Standard",
                "Express",
                "Overnight"
              ]
            }
          },
          "shipping_method": {
            "kind": "enum",
            "values": [
              "Standard",
              "Express",
              "Overnight"
            ],
            "description": "Method used for shipping."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "timestamped",
      "categorical",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most common reasons for product returns?",
      "Which product categories generate the highest revenue?",
      "How do user preferences for size and material impact purchasing decisions?",
      "What is the average delivery time across different shipping methods?",
      "Are there specific times of the year when orders peak?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users with Orders",
        "sql": "SELECT users.full_name, orders.order_date FROM users JOIN orders ON users.id = orders.user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Orders by Status",
        "sql": "SELECT status, COUNT(*) FROM orders GROUP BY status;",
        "dialect": "postgres"
      },
      {
        "title": "Average Order Total by User",
        "sql": "SELECT user_id, AVG(total_amount) FROM orders GROUP BY user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Retrieve Returns with Reasons",
        "sql": "SELECT returns.return_date, returns.reason FROM returns JOIN order_items ON returns.order_item_id = order_items.id;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "E-commerce Analysts",
        "body": "E-commerce analysts can use this dataset to explore purchasing patterns and return trends in the sustainable fashion market. By analyzing the data, they can gain insights into customer preferences and identify areas for improvement in product offerings and marketing strategies."
      },
      {
        "title": "Data Scientists",
        "body": "Data scientists can leverage this dataset to build predictive models for customer behavior, such as forecasting returns based on product features or user preferences. This can help the marketplace optimize inventory and enhance customer satisfaction."
      },
      {
        "title": "Developers",
        "body": "Developers can use the dataset for ORM seeding in applications that focus on sustainable fashion. By integrating this data into their applications, they can create realistic user scenarios and improve the overall user experience."
      },
      {
        "title": "Marketing Teams",
        "body": "Marketing teams can analyze user preferences and product performance to tailor their campaigns effectively. This dataset allows them to understand which products resonate with eco-conscious consumers and how to best reach their target audience."
      }
    ]
  },
  "counts": {
    "products": 150,
    "users": 200,
    "orders": 300,
    "order_items": 666,
    "returns": 468,
    "shipping": 300
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