{
  "format": "dataset-manifest/1",
  "slug": "virtual-event-networking-platform",
  "version": 2,
  "seed": "virtual-event-networking-platform:1",
  "spec": {
    "format": "dataset/1",
    "slug": "virtual-event-networking-platform",
    "name": "Virtual Engagement Metrics",
    "tagline": "Engagement metrics from virtual events, including user profiles, polls, connections, and event participation data.",
    "description": "Users engage in dynamic virtual events, creating profiles that showcase their interests and backgrounds. They participate in polls, ask questions, and connect with one another while navigating through various tracks and exploring sponsor booths. The platform is designed to foster meaningful interactions, allowing participants to tailor their experiences based on their preferences and event activities.\n\nThe relationships between tables paint a vivid picture of user interaction. Each row in the 'users' table represents an individual participant with their unique characteristics and activities. The 'events' table captures the various virtual occasions users can attend, detailing key information such as event types and schedules. 'Engagement_metrics' tracks user activity, including attendance, poll participation, and connection requests, which can be linked back to both the 'users' and 'events' tables. The 'polls' table holds information on the questions posed during events and the responses from users, while 'connections' logs the interactions made between users looking to network. Lastly, 'sponsors' details the companies participating in the events, showcasing their booths and involvement.\n\nThis data answers questions about user engagement levels, trends in event attendance, and the effectiveness of different poll options. It provides insights into which events attract the most interaction and how users are connecting with one another. Practicing with this dataset allows developers to explore patterns in user behavior, analyze the effectiveness of polls, and understand the dynamics of virtual networking.\n\nPlease note that the data presented is synthetic, simulating real-world interactions within a virtual engagement platform, which makes it ideal for testing and honing data analysis skills.",
    "domain": "telecom",
    "shape": "event-log",
    "useCases": [
      "analytics-demo",
      "etl-pipelines"
    ],
    "keywords": [
      "virtual events",
      "user engagement",
      "networking",
      "polls",
      "connection requests",
      "sponsor booths"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "Each row represents a user profile on the platform, linking to their engagement metrics and interactions during events.",
        "rows": 200,
        "columns": {
          "user_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."
          },
          "joined_at": {
            "kind": "date",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "Date the user joined the platform.",
            "trend": "growing"
          },
          "profile_picture": {
            "kind": "url",
            "description": "Link to the user's profile picture."
          }
        }
      },
      "events": {
        "description": "This table captures the events hosted on the platform, detailing their characteristics and user participation.",
        "rows": 50,
        "columns": {
          "event_id": {
            "kind": "pk",
            "description": "Unique identifier for each event."
          },
          "event_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "The name of the event.",
            "pool": [
              "webinar",
              "conference",
              "workshop",
              "summit",
              "panel",
              "session",
              "meetup",
              "forum",
              "presentation",
              "discussion",
              "expo",
              "launch",
              "demonstration",
              "roundtable",
              "symposium",
              "networking",
              "training",
              "class",
              "retreat",
              "showcase",
              "event"
            ]
          },
          "event_date": {
            "kind": "date",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date the event is held.",
            "trend": "seasonal"
          },
          "track_count": {
            "kind": "int",
            "min": 1,
            "max": 10,
            "description": "Number of tracks available during the event."
          },
          "sponsor_count": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Number of sponsors participating in the event."
          }
        }
      },
      "engagement_metrics": {
        "description": "Tracks the engagement of users during events, linking users to the events they participated in.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 6,
          "skew": "long-tail"
        },
        "columns": {
          "engagement_id": {
            "kind": "pk",
            "description": "Unique identifier for each engagement metric."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.user_id",
            "description": "Reference to the user participating in the event."
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.event_id",
            "description": "Reference to the event the user engaged with."
          },
          "poll_engaged": {
            "kind": "bool",
            "trueRate": 0.5,
            "description": "Indicates if the user engaged with a poll during the event."
          },
          "connections_made": {
            "kind": "int",
            "min": 0,
            "max": 10,
            "description": "Number of new connections made by the user during the event."
          },
          "joined_at": {
            "kind": "date",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "Date of user engagement with the event.",
            "trend": "growing"
          }
        }
      },
      "polls": {
        "description": "Details the polls available during events, capturing user interactions with each poll option.",
        "rows": 100,
        "columns": {
          "poll_id": {
            "kind": "pk",
            "description": "Unique identifier for each poll."
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.event_id",
            "description": "Reference to the event the poll is associated with."
          },
          "poll_question": {
            "kind": "sentence",
            "description": "The question posed in the poll."
          },
          "option_count": {
            "kind": "int",
            "min": 2,
            "max": 5,
            "description": "Number of options available for the poll."
          }
        }
      },
      "connections": {
        "description": "Records connection requests made by users during events, linking them to their profiles.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 0,
          "max": 3,
          "skew": "long-tail"
        },
        "columns": {
          "connection_id": {
            "kind": "pk",
            "description": "Unique identifier for each connection request."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.user_id",
            "description": "Reference to the user making the connection request."
          },
          "connected_user_id": {
            "kind": "fk",
            "ref": "users.user_id",
            "nullable": true,
            "description": "Reference to the user being connected to."
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.event_id",
            "description": "Reference to the event during which the connection is made."
          },
          "request_date": {
            "kind": "date",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "Date the connection request was made.",
            "trend": "growing"
          }
        }
      },
      "sponsors": {
        "description": "Captures information about sponsors participating in events, linking to their respective events.",
        "rows": {
          "per": "events",
          "via": "event_id",
          "min": 1,
          "max": 3,
          "skew": "long-tail"
        },
        "columns": {
          "sponsor_id": {
            "kind": "pk",
            "description": "Unique identifier for each sponsor."
          },
          "event_id": {
            "kind": "fk",
            "ref": "events.event_id",
            "description": "Reference to the event the sponsor is associated with."
          },
          "sponsor_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the sponsoring company.",
            "pool": [
              "telecom",
              "communications",
              "networking",
              "solutions",
              "services",
              "technology",
              "systems",
              "infrastructure",
              "digital",
              "innovation",
              "enterprise",
              "cloud",
              "analytics",
              "data",
              "software",
              "platform",
              "mobile",
              "connectivity",
              "security",
              "support",
              "consulting"
            ]
          },
          "booth_url": {
            "kind": "url",
            "description": "Link to the sponsor's booth for the event."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most popular events based on user participation?",
      "Which poll options received the highest engagement?",
      "How do user connection patterns vary across different events?",
      "What is the average number of connections made per user during events?",
      "Are there certain times of the year when user engagement peaks?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users and Engagement Metrics",
        "sql": "SELECT u.full_name, e.event_name FROM users u JOIN engagement_metrics em ON u.user_id = em.user_id JOIN events e ON em.event_id = e.event_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count of Connections Made per Event",
        "sql": "SELECT e.event_name, COUNT(c.connection_id) AS total_connections FROM events e LEFT JOIN connections c ON e.event_id = c.event_id GROUP BY e.event_name;",
        "dialect": "postgres"
      },
      {
        "title": "Average Connections Made per User",
        "sql": "SELECT u.full_name, AVG(c.connections_made) AS average_connections FROM users u JOIN engagement_metrics em ON u.user_id = em.user_id GROUP BY u.full_name;",
        "dialect": "postgres"
      },
      {
        "title": "Poll Engagement Analysis",
        "sql": "SELECT p.poll_question, COUNT(em.engagement_id) AS engagement_count FROM polls p LEFT JOIN engagement_metrics em ON p.event_id = em.event_id WHERE em.poll_engaged = true GROUP BY p.poll_question;",
        "dialect": "postgres"
      },
      {
        "title": "Event Participation Trends Over Time",
        "sql": "SELECT event_date, COUNT(DISTINCT user_id) AS participants FROM engagement_metrics em JOIN events e ON em.event_id = e.event_id GROUP BY event_date ORDER BY event_date;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Analytics Dashboard Development",
        "body": "Data analysts can utilize this dataset to develop analytics dashboards that visualize user engagement metrics across various events. By connecting and filtering data, they can present insights on user participation trends and popular polls, helping event organizers tailor their offerings."
      },
      {
        "title": "ETL Pipeline Testing",
        "body": "Data engineers can leverage this synthetic dataset to test their ETL pipelines, ensuring that data is correctly extracted, transformed, and loaded into data warehouses. They can simulate user interactions and event participation to verify that data integrity is maintained throughout the pipeline."
      },
      {
        "title": "Machine Learning Model Training",
        "body": "Data scientists can use this dataset to train machine learning models that predict user engagement based on historical data. By analyzing user behavior patterns, they can develop algorithms that recommend events or connections, enhancing the overall user experience on the platform."
      },
      {
        "title": "User Segmentation Analysis",
        "body": "Marketers can employ this dataset for user segmentation analysis, identifying different user profiles based on their engagement levels and preferences. This information can be used to create targeted campaigns that improve user retention and satisfaction on the platform."
      }
    ]
  },
  "counts": {
    "events": 50,
    "polls": 100,
    "sponsors": 79,
    "users": 200,
    "connections": 194,
    "engagement_metrics": 489
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