{
  "format": "dataset-manifest/1",
  "slug": "real-estate-crowdfunding-platform",
  "version": 2,
  "seed": "real-estate-crowdfunding-platform:1",
  "spec": {
    "format": "dataset/1",
    "slug": "real-estate-crowdfunding-platform",
    "name": "Real Estate Investment Dynamics",
    "tagline": "Investor records, property details, investment tiers, and dividend flows from a real estate crowdfunding platform.",
    "description": "Investors engage in real estate projects by pooling funds through a crowdfunding platform, allowing them to diversify their portfolios with various properties. Each investment tier represents a different level of financial commitment, with higher tiers typically offering greater potential returns but also involving higher risks. Properties are listed on the platform, each with distinct characteristics that attract different investor profiles. Some properties may be in high-demand locations, enticing more conservative investors, while others in emerging markets may appeal to those looking for higher risk and reward. The flow of dividends from successful ventures provides investors with returns on their investments, fostering continued participation in the platform.\n\nIn this dataset, the 'investors' table captures individual or institutional investors, detailing their profiles and investment behaviors. The 'properties' table lists the different real estate assets available for investment, including their locations and market potential. 'Investment_tiers' defines the various levels of investment opportunities, outlining what returns each tier may offer. The 'dividends' table tracks the returns generated from each property investment, while the 'user_demographics' table provides insights into the investors' backgrounds, allowing for analysis of their investment preferences and performance.\n\nOne row in the 'investors' table represents a unique investor, while a row in the 'properties' table corresponds to a specific property available for investment. The 'investment_tiers' table connects to both investors and properties, indicating which tier each investor uses for their investments. The flow of dividend data links back to the properties and investment tiers, revealing how returns are distributed. Questions that can be explored using this data include: What investment tiers yield the highest dividends? What demographic factors influence investment choices? How do property characteristics align with investor preferences? The dataset is synthetic, designed for practice and exploration in real estate investment analytics.",
    "domain": "real-estate",
    "shape": "ledger",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "real estate",
      "crowdfunding",
      "investment",
      "investors",
      "properties",
      "dividends",
      "financial data",
      "analytics",
      "portfolio",
      "user demographics"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "investors": {
        "description": "Each row represents an investor participating in the crowdfunding platform, linking to their investment activities and demographic data.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each investor."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Full name of the investor."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the investor."
          },
          "accreditation_status": {
            "kind": "enum",
            "values": [
              "accredited",
              "non-accredited"
            ],
            "description": "Investor's accreditation status.",
            "weights": [
              7,
              3
            ]
          },
          "join_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the investor joined the platform.",
            "trend": "growing"
          }
        }
      },
      "properties": {
        "description": "Each row represents a property available for investment, detailing its location, value, and associated investment tiers.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each property."
          },
          "address": {
            "kind": "sentence",
            "min": 5,
            "max": 50,
            "description": "Complete address of the property."
          },
          "location": {
            "kind": "city",
            "description": "City where the property is located."
          },
          "market_value": {
            "kind": "decimal",
            "min": 50000,
            "max": 5000000,
            "scale": 2,
            "description": "Market value of the property in USD.",
            "distribution": "long-tail"
          },
          "investment_tiers": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Number of investment tiers available for this property."
          }
        }
      },
      "investment_tiers": {
        "description": "Each row represents an investment tier associated with a property, detailing minimum investment amounts and expected returns.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each investment tier."
          },
          "property_id": {
            "kind": "fk",
            "ref": "properties.id",
            "description": "Reference to the property this investment tier is associated with."
          },
          "tier_level": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Level of the investment tier."
          },
          "min_investment": {
            "kind": "decimal",
            "min": 1000,
            "max": 500000,
            "scale": 2,
            "description": "Minimum investment amount for this tier.",
            "distribution": "long-tail"
          },
          "expected_return": {
            "kind": "decimal",
            "min": 0,
            "max": 0.3,
            "scale": 2,
            "description": "Expected return percentage for this investment tier."
          }
        }
      },
      "dividends": {
        "description": "Each row represents dividends paid to investors based on their investments in properties, linked to both investors and investment tiers.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each dividend payment."
          },
          "investor_id": {
            "kind": "fk",
            "ref": "investors.id",
            "description": "Reference to the investor receiving the dividend."
          },
          "investment_tier_id": {
            "kind": "fk",
            "ref": "investment_tiers.id",
            "description": "Reference to the investment tier generating the dividend."
          },
          "amount": {
            "kind": "decimal",
            "min": 10,
            "max": 50000,
            "scale": 2,
            "description": "Dividend amount paid to the investor.",
            "distribution": "long-tail"
          },
          "payment_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the dividend was paid.",
            "trend": "seasonal"
          }
        }
      },
      "user_demographics": {
        "description": "Each row captures demographic information about investors, linking to their profiles and investment habits.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each demographic record."
          },
          "investor_id": {
            "kind": "fk",
            "ref": "investors.id",
            "description": "Reference to the investor whose demographics are recorded."
          },
          "age": {
            "kind": "int",
            "min": 18,
            "max": 80,
            "description": "Age of the investor."
          },
          "income_level": {
            "kind": "enum",
            "values": [
              "low",
              "medium",
              "high"
            ],
            "description": "Income level of the investor.",
            "weights": [
              5,
              4,
              1
            ]
          },
          "investment_experience": {
            "kind": "enum",
            "values": [
              "beginner",
              "intermediate",
              "expert"
            ],
            "description": "Experience level of the investor in real estate.",
            "weights": [
              6,
              2,
              1
            ]
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "monetary",
      "nullable"
    ],
    "analysisQuestions": [
      "What is the average dividend payment received by different tiers of investments?",
      "How does the accreditation status affect the average investment amount?",
      "Which properties attract the most investments and why?",
      "What demographic factors correlate with higher investment returns?",
      "How do dividend payments vary across different properties?"
    ],
    "suggestedQueries": [
      {
        "title": "Get all investors and their details",
        "sql": "SELECT * FROM investors",
        "dialect": "postgres"
      },
      {
        "title": "Find properties with their investment tiers",
        "sql": "SELECT properties.address, investment_tiers.tier_level, investment_tiers.min_investment FROM properties JOIN investment_tiers ON properties.id = investment_tiers.property_id",
        "dialect": "postgres"
      },
      {
        "title": "Calculate total dividends paid to each investor",
        "sql": "SELECT investor_id, SUM(amount) AS total_dividends FROM dividends GROUP BY investor_id",
        "dialect": "postgres"
      },
      {
        "title": "Average return by investment tier",
        "sql": "SELECT investment_tier_id, AVG(expected_return) AS avg_return FROM investment_tiers GROUP BY investment_tier_id",
        "dialect": "postgres"
      },
      {
        "title": "Demographic analysis of investment behavior",
        "sql": "SELECT age, income_level, COUNT(investor_id) AS num_investors FROM user_demographics GROUP BY age, income_level",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Real Estate Educators",
        "body": "Instructors can use this dataset to teach students about the dynamics of real estate investment. They can create exercises that require analyzing investor behavior, property valuation, and understanding dividends. This practical approach helps students grasp concepts more effectively and prepares them for real-world applications."
      },
      {
        "title": "Data Analysts",
        "body": "Data analysts can leverage this dataset to perform exploratory data analysis on investment trends and demographics. By running queries, they can identify patterns in investment behavior, assess the impact of investor accreditation on returns, and make data-driven recommendations for marketing strategies."
      },
      {
        "title": "Developers Building Investment Platforms",
        "body": "Developers creating real estate investment platforms can utilize this dataset to test their applications. They can simulate investor interactions, test the accuracy of dividend calculations, and analyze how different investment tiers perform under various market conditions, ensuring their platform meets user expectations."
      },
      {
        "title": "Investment Advisors",
        "body": "Investment advisors can use this dataset to analyze the performance of different investment tiers and properties. By examining the data, they can provide tailored advice to clients based on their financial goals, helping them make informed decisions about their real estate investments."
      }
    ]
  },
  "counts": {
    "investors": 500,
    "properties": 150,
    "investment_tiers": 300,
    "dividends": 400,
    "user_demographics": 300
  },
  "stats": {
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          "min": "Alice Smith",
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