{
  "format": "dataset-manifest/1",
  "slug": "community-help-and-support-platform",
  "version": 4,
  "seed": "community-help-and-support-platform:1",
  "engine": 1,
  "engineVersion": "1.0.0",
  "spec": {
    "format": "dataset/1",
    "slug": "community-help-and-support-platform",
    "name": "Support Interaction Metrics",
    "tagline": "Support requests, user responses, engagement stats, ratings, and issue categories from a community support platform.",
    "description": "Users log support requests to seek assistance for various issues on a community-driven platform designed to connect those in need with those who can help. These interactions track the dynamics of support exchanges, showcasing how users engage with each other through both requests and responses. The platform serves as a hub where inquiries are categorized by issue types, allowing users to navigate common topics or delve into more complex questions that may require extensive back-and-forth communication. Support ratings add a layer of quality assessment to each interaction, enabling the community to gauge the effectiveness of assistance provided.\n\nThe dataset includes several related tables that allow for a comprehensive analysis of user interactions. The 'support_requests' table lists individual requests for help, detailing the nature of the inquiries and their associated issue categories. Each request links to the 'user_responses' table, where users can provide answers or insights, creating a direct line of communication between those asking for help and those offering it. The 'user_engagement' table captures metrics on how actively users participate in discussions, while 'support_ratings' records feedback on the quality of assistance rendered. The 'users' table holds information about the individuals engaged in these interactions, and the 'issue_categories' table classifies each request by topic, facilitating easier navigation through the data.\n\nThis dataset enables developers to explore a variety of analytical questions, such as identifying trends in support requests, evaluating user engagement levels, or measuring the effectiveness of responses based on support ratings. It is an excellent resource for practicing data analysis techniques, including joins, aggregations, and visualizations, providing insights into user behavior and interaction patterns. Please note that all data in this collection is synthetic, designed to simulate real-world scenarios while ensuring user privacy.",
    "domain": "customer-support",
    "shape": "event-log",
    "useCases": [
      "analytics-demo",
      "etl-pipelines"
    ],
    "keywords": [
      "support interactions",
      "community help",
      "customer support",
      "user engagement",
      "response ratings",
      "issue tracking"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "support_requests": {
        "description": "This table records individual support requests made by users, linking to the user who made the request and the type of issue they faced.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each support request."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user making the support request."
          },
          "issue_type": {
            "kind": "enum",
            "values": [
              "Technical",
              "Billing",
              "Account",
              "General Inquiry"
            ],
            "description": "Type of issue being reported.",
            "weights": [
              6,
              2,
              1,
              1
            ]
          },
          "created_at": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the support request was made.",
            "nullable": true,
            "dayProfile": "business"
          },
          "status": {
            "kind": "enum",
            "values": [
              "Open",
              "Resolved",
              "Closed"
            ],
            "description": "Current status of the support request.",
            "nullable": true,
            "when": {
              "column": "issue_type",
              "in": [
                "Technical",
                "Billing",
                "Account",
                "General Inquiry"
              ]
            },
            "weights": [
              3,
              5,
              7
            ]
          }
        }
      },
      "user_responses": {
        "description": "This table captures the responses provided by users to support requests, linking back to the specific request and user.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user response."
          },
          "request_id": {
            "kind": "fk",
            "ref": "support_requests.id",
            "description": "Identifier for the support request being responded to."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user providing the response."
          },
          "response_content": {
            "kind": "sentence",
            "min": 5,
            "max": 200,
            "description": "Content of the user's response to the support request.",
            "nullable": true
          },
          "created_at": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the response was submitted.",
            "dayProfile": "waking"
          },
          "response_length": {
            "kind": "int",
            "min": 0,
            "max": 500,
            "distribution": "normal",
            "description": "Length of the user's response in characters."
          },
          "sentiment_score": {
            "kind": "decimal",
            "min": -1,
            "max": 1,
            "scale": 2,
            "distribution": "normal",
            "description": "Sentiment score of the response, where -1 is negative and 1 is positive."
          }
        }
      },
      "user_engagement": {
        "description": "This table tracks user engagement metrics, linking users to their activity on the support platform.",
        "rows": 250,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each engagement record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the engaged user."
          },
          "requests_count": {
            "kind": "int",
            "min": 0,
            "max": 100,
            "description": "Total number of support requests made by the user.",
            "distribution": "long-tail"
          },
          "responses_count": {
            "kind": "int",
            "min": 0,
            "max": 100,
            "description": "Total number of responses provided by the user.",
            "distribution": "long-tail"
          },
          "last_active": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the user was last active.",
            "nullable": true
          }
        }
      },
      "support_ratings": {
        "description": "This table records ratings given by users for the support responses they received.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each rating."
          },
          "response_id": {
            "kind": "fk",
            "ref": "user_responses.id",
            "description": "Identifier for the response being rated."
          },
          "rating_value": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Rating value provided by the user.",
            "distribution": "high"
          },
          "created_at": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the rating was submitted.",
            "nullable": true,
            "dayProfile": "business"
          },
          "response_time": {
            "kind": "int",
            "min": 0,
            "max": 120,
            "distribution": "normal",
            "description": "Time taken in minutes to respond to the support request."
          }
        }
      },
      "users": {
        "description": "This table holds information about users on the platform, including their unique identifiers and basic details.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Full name of the user.",
            "nullable": true
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the user.",
            "nullable": true
          },
          "joined_at": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp when the user joined the platform.",
            "trend": "growing"
          }
        }
      },
      "issue_categories": {
        "description": "This table defines various categories of issues that users can report, linking them to the requests.",
        "rows": 20,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each issue category."
          },
          "category_name": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Name of the issue category.",
            "pool": [
              "login",
              "payment",
              "error",
              "account",
              "subscription",
              "billing",
              "technical",
              "feature",
              "access",
              "support",
              "refund",
              "upgrade",
              "downtime",
              "installation",
              "configuration",
              "performance",
              "security",
              "compatibility",
              "service",
              "notification",
              "report"
            ]
          },
          "description": {
            "kind": "sentence",
            "min": 10,
            "max": 100,
            "description": "Description of the issue category.",
            "nullable": true
          },
          "priority_level": {
            "kind": "enum",
            "values": [
              "Low",
              "Medium",
              "High"
            ],
            "weights": [
              50,
              30,
              20
            ],
            "description": "Priority level of the issue category."
          },
          "average_resolution_time": {
            "kind": "decimal",
            "min": 0,
            "max": 48,
            "scale": 2,
            "distribution": "normal",
            "description": "Average resolution time in hours for issues in this category."
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What types of issues are most commonly reported by users?",
      "How do response ratings vary by issue type?",
      "Which users are the most active in providing support?",
      "What is the average response time for support requests?",
      "How does user engagement correlate with support satisfaction?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Support Requests and User Responses",
        "sql": "SELECT sr.id, sr.issue_type, ur.response_content FROM support_requests sr JOIN user_responses ur ON sr.id = ur.request_id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Responses per Issue Type",
        "sql": "SELECT issue_type, COUNT(*) as response_count FROM support_requests sr JOIN user_responses ur ON sr.id = ur.request_id GROUP BY issue_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average Rating per Issue Type",
        "sql": "SELECT sr.issue_type, AVG(sr.rating_value) as average_rating FROM support_requests sr JOIN support_ratings ra ON sr.id = ra.response_id GROUP BY sr.issue_type;",
        "dialect": "postgres"
      },
      {
        "title": "User Activity Over Time",
        "sql": "SELECT user_id, COUNT(*) as engagement_count, DATE_TRUNC('month', last_active) as month FROM user_engagement GROUP BY user_id, month ORDER BY month;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Customer Support Analytics",
        "body": "Support analysts can use this dataset to evaluate the effectiveness of the community help platform by analyzing response times, satisfaction ratings, and common issues. This helps in identifying areas for improvement in user support."
      },
      {
        "title": "User Engagement Insights",
        "body": "Marketing teams can leverage engagement metrics to tailor communication strategies and enhance user participation in the support community. Understanding user behavior can inform promotional efforts and community-building initiatives."
      },
      {
        "title": "Quality Assurance for Support Responses",
        "body": "Quality assurance teams can utilize the ratings data to monitor the quality of support interactions. They can identify high-performing users and develop training programs for those who may need improvement."
      },
      {
        "title": "ETL Pipeline Testing",
        "body": "Data engineers can test their ETL pipelines using this dataset to ensure that data flows correctly between systems. The synthetic nature of the dataset allows for easy manipulation and validation of data processing workflows."
      }
    ]
  },
  "counts": {
    "issue_categories": 20,
    "users": 150,
    "support_requests": 200,
    "user_engagement": 250,
    "user_responses": 300,
    "support_ratings": 400
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