{
  "format": "dataset-manifest/1",
  "slug": "virtual-reality-home-interior-design-simulator",
  "version": 2,
  "seed": "virtual-reality-home-interior-design-simulator:1",
  "spec": {
    "format": "dataset/1",
    "slug": "virtual-reality-home-interior-design-simulator",
    "name": "Virtual Reality Design Insights",
    "tagline": "User engagement metrics, design projects, support requests, product categories and invoices for a VR design simulator.",
    "description": "Users immerse themselves in a virtual reality home interior design simulator, crafting and visualizing their ideal living spaces. By interacting with an array of design elements, they create design projects that encompass various room types, lighting configurations, and material choices. Collaboration with other users enhances the experience, allowing for shared insights and diverse design inspirations. As users navigate through the design process, they also manage their subscriptions, which provide access to premium features and tools within the simulator.\n\nThe dataset contains several interconnected tables that mirror this operational landscape. The 'users' table captures individual user profiles and their engagement metrics, while 'design_projects' records the specifics of each project created by users, linking back to the individuals responsible. 'support_requests' tracks inquiries and issues faced by users, providing insight into common challenges and areas for improvement in the user experience. The 'product_categories' table delineates the various design elements available within the simulator, showcasing the diversity of choices offered. Lastly, 'invoices' document the financial transactions associated with subscriptions and services, revealing trends in user spending and engagement over time.\n\nBy exploring this dataset, developers can answer questions related to user behavior, such as which design themes are most popular or how frequently users engage with different product categories. The data also allows for analysis of support request trends, providing a clearer picture of user satisfaction and areas that may need attention. Invoices can reveal patterns in user subscription habits, particularly in relation to promotional campaigns. This synthetic dataset offers a rich environment for practicing data analysis and visualization techniques.",
    "domain": "telecom",
    "shape": "time-series",
    "useCases": [
      "analytics-demo",
      "bi-dashboards"
    ],
    "keywords": [
      "virtual reality",
      "interior design",
      "user engagement",
      "subscriptions",
      "design projects",
      "support requests",
      "product categories"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table contains information about users of the VR design simulator, including their subscription status and engagement metrics over time.",
        "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": "User's email address."
          },
          "subscription_status": {
            "kind": "enum",
            "values": [
              "active",
              "inactive",
              "trial"
            ],
            "description": "Current subscription status of the user.",
            "weights": [
              8,
              2,
              1
            ]
          },
          "engagement_score": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "description": "Score indicating user engagement level.",
            "nullable": true,
            "when": {
              "column": "subscription_status",
              "in": [
                "trial"
              ]
            },
            "distribution": "high"
          },
          "created_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "description": "Date when the user registered.",
            "dayProfile": "business"
          }
        }
      },
      "design_projects": {
        "description": "This table tracks individual design projects created by users, including project details and associated engagement metrics.",
        "rows": 600,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each design project."
          },
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            "kind": "fk",
            "ref": "users.id",
            "description": "Reference to the user who created the project."
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              "engagement",
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              "environment",
              "visualization",
              "feedback",
              "development",
              "concept",
              "testing",
              "analytics",
              "strategy"
            ],
            "min": 1
          },
          "created_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "description": "Date when the project was created.",
            "dayProfile": "business"
          },
          "updated_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "description": "Date when the project was last updated.",
            "nullable": true,
            "dayProfile": "business"
          },
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            "kind": "int",
            "min": 0,
            "max": 10000,
            "description": "Number of views the project has received.",
            "distribution": "long-tail"
          }
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        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each support request."
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            "description": "Date when the support request was submitted.",
            "nullable": true,
            "dayProfile": "waking"
          },
          "issue_type": {
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              "billing",
              "general inquiry"
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            "weights": [
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              3,
              2
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          },
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            "values": [
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            "nullable": true,
            "when": {
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            },
            "weights": [
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              1
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          }
        }
      },
      "product_categories": {
        "description": "This table catalogs different product categories used in design projects, helping to identify trends in user preferences.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each product category."
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            "pool": [
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              "accessories",
              "applications",
              "platforms",
              "devices",
              "tools",
              "systems",
              "interfaces",
              "solutions",
              "services",
              "content",
              "media",
              "networks",
              "analytics",
              "frameworks",
              "environments",
              "experiences",
              "technologies",
              "components"
            ],
            "min": 1
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          "popularity_score": {
            "kind": "int",
            "min": 1,
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            "description": "Score indicating the popularity of the category.",
            "nullable": true,
            "distribution": "high"
          }
        }
      },
      "invoices": {
        "description": "This table records invoice details for user subscriptions, reflecting financial interactions over time.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each invoice."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Reference to the user linked to the invoice."
          },
          "amount": {
            "kind": "decimal",
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            "scale": 2,
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            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "pending",
                "cancelled"
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            "distribution": "long-tail"
          },
          "invoice_date": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-12-31",
            "description": "Date when the invoice was issued.",
            "trend": "growing"
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            "description": "Payment status of the invoice.",
            "weights": [
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    },
    "structure": "multi-table",
    "traits": [
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      "categorical",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most common issues reported in support requests?",
      "How do user engagement scores correlate with subscription status?",
      "Which product categories are trending in design projects?",
      "What time of year sees the most invoice activity?",
      "How does the number of views impact project updates?"
    ],
    "suggestedQueries": [
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        "title": "Join Users and Design Projects",
        "sql": "SELECT users.full_name, design_projects.project_name FROM users JOIN design_projects ON users.id = design_projects.user_id;",
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        "title": "Count Support Requests by Issue Type",
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        "dialect": "postgres"
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      {
        "title": "Average Engagement Score by Subscription Status",
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        "dialect": "postgres"
      },
      {
        "title": "Monthly Invoice Totals",
        "sql": "SELECT DATE_TRUNC('month', invoice_date) AS month, SUM(amount) FROM invoices GROUP BY month ORDER BY month;",
        "dialect": "postgres"
      },
      {
        "title": "Product Category Popularity Trend",
        "sql": "SELECT category_name, AVG(popularity_score) FROM product_categories GROUP BY category_name ORDER BY AVG(popularity_score) DESC;",
        "dialect": "postgres"
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    "usageScenarios": [
      {
        "title": "User Engagement Analysis",
        "body": "Data analysts can utilize this dataset to analyze user engagement trends over time, identifying how engagement scores fluctuate with different subscription statuses. By pinpointing patterns, they can recommend strategies to enhance user retention and satisfaction."
      },
      {
        "title": "Support Request Optimization",
        "body": "Customer support teams can leverage the support requests table to analyze common issues faced by users. By categorizing and prioritizing these issues, they can streamline support operations and improve user experience through targeted solutions."
      },
      {
        "title": "Financial Reporting",
        "body": "Finance teams can employ invoice data to track revenue trends, identifying peak billing periods and analyzing payment statuses. This insight helps in forecasting future revenues and preparing for promotional events that could influence user subscriptions."
      },
      {
        "title": "Product Development Insights",
        "body": "Product managers can analyze product categories to determine which items are gaining popularity in design projects. This data can guide inventory decisions and inform marketing strategies to promote trending products effectively."
      }
    ]
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