{
  "format": "dataset-manifest/1",
  "slug": "local-farmer-s-market-and-organic-food-finder",
  "version": 2,
  "seed": "local-farmer-s-market-and-organic-food-finder:1",
  "spec": {
    "format": "dataset/1",
    "slug": "local-farmer-s-market-and-organic-food-finder",
    "name": "Farmers Market Activity Log",
    "tagline": "Sales transactions, vendor participation, product offerings, and customer interactions from a local farmers market.",
    "description": "Vendors sell fresh organic produce and specialty food items directly to consumers and restaurants at the local farmer's market. Each market event draws a diverse crowd, where customers engage with various vendors offering unique products ranging from seasonal fruits to artisanal baked goods. This bustling environment is captured in the dataset, which revolves around the intricacies of sales transactions, vendor participation, customer preferences, product availability, and event schedules. Most entries represent lively market days filled with multiple vendors, while the occasional record highlights quieter weekdays or special events that feature distinctive offerings.\n\nThe dataset consists of several interconnected tables: events, vendors, products, transactions, and customers. Each event row details a specific market occurrence, including the date, location, and participating vendors. The vendors table outlines individual vendors, their product offerings, and stall locations. The products table lists various items for sale, from fruits to baked goods, with descriptions and pricing. Transactions capture the sales made during each event, linking customers to the vendors and products they purchased. Lastly, the customers table holds information about buyers, their preferences, and demographics, providing context for shopping behavior.\n\nBy exploring this data, developers can answer a variety of questions. What types of products are most popular among customers? How does vendor participation fluctuate across different events? What demographics are most likely to shop at the market? How do sales trends vary with seasons or special events? Practicing with this dataset offers a valuable opportunity to analyze real-world market dynamics and consumer behavior, all while working with synthetic data crafted to mimic genuine farmer's market operations.",
    "domain": "restaurants",
    "shape": "event-log",
    "useCases": [
      "analytics-demo",
      "etl-pipelines"
    ],
    "keywords": [
      "farmers market",
      "vendors",
      "transactions",
      "organic produce",
      "customers",
      "events",
      "sales"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "events": {
        "description": "This table records each market event, detailing when it occurs and which vendors participated. It serves as a reference for all activities on market days.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each event."
          },
          "date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The date of the market event.",
            "trend": "seasonal"
          },
          "location": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "The location of the farmers market.",
            "nullable": true,
            "pool": [
              "park",
              "square",
              "street",
              "community",
              "lot",
              "farm",
              "plaza",
              "pavilion",
              "field",
              "garden",
              "market",
              "venue",
              "center",
              "location",
              "area",
              "district",
              "site",
              "corner",
              "block",
              "zone"
            ]
          },
          "vendor_count": {
            "kind": "int",
            "min": 1,
            "max": 50,
            "description": "Number of vendors present at the event.",
            "nullable": true
          },
          "customer_count": {
            "kind": "int",
            "min": 10,
            "max": 500,
            "description": "Estimated number of customers attending the event.",
            "nullable": true,
            "distribution": "normal"
          }
        }
      },
      "vendors": {
        "description": "This table lists all vendors participating in the farmers market, detailing their specialties and the products they offer.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each vendor."
          },
          "name": {
            "kind": "fullName",
            "description": "The name of the vendor or business."
          },
          "specialty": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "The primary product or service offered by the vendor.",
            "nullable": true,
            "pool": [
              "vegetables",
              "fruits",
              "baked",
              "dairy",
              "meat",
              "seafood",
              "herbs",
              "jams",
              "sauces",
              "honey",
              "flowers",
              "crafts",
              "snacks",
              "beverages",
              "condiments",
              "sweets",
              "cheese",
              "bread",
              "pasta",
              "jewelry",
              "art"
            ]
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.id",
            "description": "The event this vendor is associated with."
          }
        }
      },
      "products": {
        "description": "This table details the products available for purchase at the farmers market, linking each product to its vendor.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each product."
          },
          "name": {
            "kind": "productName",
            "description": "Name of the product being sold."
          },
          "price": {
            "kind": "decimal",
            "min": 1,
            "max": 100,
            "scale": 2,
            "description": "Selling price of the product.",
            "nullable": true,
            "distribution": "long-tail"
          },
          "vendor_id": {
            "kind": "fk",
            "ref": "vendors.id",
            "description": "The vendor selling this product."
          }
        }
      },
      "transactions": {
        "description": "This table captures individual sales transactions, linking customers to the products they purchase and the corresponding vendors.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each transaction."
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.id",
            "description": "The event during which the transaction took place."
          },
          "customer_id": {
            "kind": "fk",
            "ref": "customers.id",
            "description": "The customer making the purchase."
          },
          "product_id": {
            "kind": "fk",
            "ref": "products.id",
            "description": "The product being purchased."
          },
          "amount": {
            "kind": "decimal",
            "min": 1,
            "max": 1000,
            "scale": 2,
            "description": "Total sale amount for the transaction.",
            "distribution": "heavy-tail"
          },
          "transaction_time": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2024-12-31",
            "description": "The exact time the transaction occurred.",
            "dayProfile": "waking"
          }
        }
      },
      "customers": {
        "description": "This table provides demographic information about customers who attend the farmers market, linking them to their transactions.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each customer."
          },
          "age": {
            "kind": "int",
            "min": 18,
            "max": 90,
            "description": "Age of the customer.",
            "nullable": true,
            "distribution": "normal"
          },
          "city": {
            "kind": "city",
            "description": "City where the customer resides.",
            "nullable": true
          },
          "preferred_products": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Types of products the customer prefers.",
            "nullable": true,
            "pool": [
              "organic",
              "local",
              "fresh",
              "seasonal",
              "glutenfree",
              "vegan",
              "artisan",
              "cooked",
              "raw",
              "gourmet",
              "handmade",
              "preserved",
              "smoked",
              "pickled",
              "canned",
              "frozen",
              "sustainable",
              "natural",
              "exotic",
              "traditional"
            ]
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most popular products sold at the market?",
      "Which vendors attract the most customers?",
      "Are there specific days when sales peak more than others?",
      "What demographic trends can be observed among regular customers?",
      "How do vendor offerings impact customer purchases?"
    ],
    "suggestedQueries": [
      {
        "title": "List all vendors at a specific event",
        "sql": "SELECT v.name FROM vendors v JOIN events e ON v.event_id = e.id WHERE e.date = '2023-06-01';",
        "dialect": "postgres"
      },
      {
        "title": "Count products sold by each vendor",
        "sql": "SELECT v.name, COUNT(p.id) FROM vendors v JOIN products p ON v.id = p.vendor_id GROUP BY v.name;",
        "dialect": "postgres"
      },
      {
        "title": "Total sales amount by customer",
        "sql": "SELECT c.id, SUM(t.amount) FROM customers c JOIN transactions t ON c.id = t.customer_id GROUP BY c.id;",
        "dialect": "postgres"
      },
      {
        "title": "Average transaction amount per event",
        "sql": "SELECT e.date, AVG(t.amount) FROM transactions t JOIN events e ON t.event_id = e.id GROUP BY e.date;",
        "dialect": "postgres"
      },
      {
        "title": "Daily customer count trend",
        "sql": "SELECT e.date, SUM(e.customer_count) FROM events e GROUP BY e.date ORDER BY e.date;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Market Organizer Analysis",
        "body": "A market organizer can utilize this dataset to analyze sales trends and customer attendance patterns over time. By examining peak sales days and the performance of various vendors, they can make informed decisions about vendor selection and event marketing strategies, ultimately enhancing the market experience for both vendors and customers."
      },
      {
        "title": "Vendor Performance Evaluation",
        "body": "Vendors can leverage the insights from this dataset to evaluate their performance at the market. By analyzing their sales data and customer demographics, they can tailor their product offerings to better meet customer demands, improve customer engagement, and increase their overall sales during market events."
      },
      {
        "title": "Customer Preference Insights",
        "body": "Researchers or marketers interested in consumer behavior can analyze the customer data to identify preferences and buying habits. Understanding which products are popular among different demographics can help businesses design targeted marketing strategies, ultimately leading to increased customer satisfaction."
      },
      {
        "title": "Event Planning and Optimization",
        "body": "Local government or community planners can use this dataset to optimize future market events. By analyzing customer turnout and vendor participation, they can make data-driven decisions regarding the timing and marketing of events, ensuring that they attract the maximum number of participants and vendors."
      }
    ]
  },
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    "customers": 400,
    "events": 200,
    "vendors": 100,
    "products": 300,
    "transactions": 500
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