{
  "format": "dataset-manifest/1",
  "slug": "gaming-community-insights",
  "version": 3,
  "seed": "gaming-community-insights:1",
  "spec": {
    "format": "dataset/1",
    "slug": "gaming-community-insights",
    "name": "Gaming Community Insights",
    "tagline": "User profiles, game titles, transactions, support tickets, and friendships from a vibrant gaming community.",
    "description": "Gamers interact daily, diving into a vast library of titles and community-driven content. They explore diverse genres, track their achievements, and manage game downloads while building connections with friends and moderators. This vibrant ecosystem thrives on user engagement and frequent transactions, as players purchase games, in-game items, and downloadable content. Support teams address a variety of user issues through tickets and replies, ensuring a smooth gaming experience for everyone involved.\n\nIn this data model, the users table offers insights into individual gamer profiles, including their preferences and activity levels. The games table catalogs the diverse range of titles available, detailing genre, popularity, and unique attributes. Transactions are recorded in the transactions table, providing a snapshot of the financial aspects of gamers’ purchases. Support tickets within the support_tickets table reflect user inquiries and issues, paired with responses from support staff, revealing trends in user concerns and satisfaction. Lastly, the friendships table captures the relationships formed between users, showcasing social interactions that enhance the gaming experience.\n\nEach row in the users table connects to multiple entries in the transactions table, as individual gamers often make numerous purchases. The support_tickets table correlates with both users and games, highlighting specific issues related to particular titles. Friendships offer a social dimension, linking users through their interactions, which can be analyzed alongside game preferences and purchase behaviors. \n\nThis synthetic dataset presents an exciting opportunity to explore questions such as: What are the most popular games among different user demographics? How do friendships impact game purchases? What common issues arise in support tickets, and how quickly are they resolved? By analyzing this data, developers can practice honing their skills in data manipulation, aggregation, and visualization, turning insights into actionable strategies.",
    "domain": "media",
    "shape": "hierarchical",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "gaming",
      "community",
      "transactions",
      "support",
      "users",
      "games",
      "friendships"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table contains information about users in the gaming community, including their registration details and preferences.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "username": {
            "kind": "fullName",
            "description": "The username chosen by the user."
          },
          "join_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "The date the user registered on the platform.",
            "nullable": true,
            "trend": "growing"
          },
          "email": {
            "kind": "email",
            "from": "username",
            "description": "The user's email address, linked to their username.",
            "nullable": true
          },
          "country": {
            "kind": "country",
            "description": "Country of residence of the user.",
            "nullable": true
          }
        }
      },
      "games": {
        "description": "This table catalogs games available in the community, including their genres and release dates.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each game."
          },
          "title": {
            "kind": "productName",
            "description": "Title of the game."
          },
          "genre": {
            "kind": "enum",
            "values": [
              "Action",
              "Adventure",
              "RPG",
              "Simulation",
              "Strategy"
            ],
            "description": "Genre classification of the game.",
            "weights": [
              5,
              3,
              2,
              1,
              1
            ]
          },
          "release_date": {
            "kind": "date",
            "from": "2015-01-01",
            "to": "2023-01-01",
            "description": "The release date of the game.",
            "nullable": true,
            "trend": "seasonal"
          }
        }
      },
      "transactions": {
        "description": "This table records transactions made by users for purchasing games and other in-game items.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 1,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each transaction."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user making the transaction."
          },
          "game_id": {
            "kind": "fk",
            "ref": "games.id",
            "description": "Identifier for the game being purchased."
          },
          "transaction_date": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date and time of the transaction.",
            "dayProfile": "waking"
          },
          "amount": {
            "kind": "decimal",
            "min": 0.99,
            "max": 59.99,
            "scale": 2,
            "description": "Total amount for the transaction.",
            "nullable": true,
            "distribution": "long-tail"
          }
        }
      },
      "support_tickets": {
        "description": "This table tracks support tickets submitted by users to address issues or inquiries.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 0,
          "max": 3,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each support ticket."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user who submitted the ticket."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date and time when the ticket was created.",
            "nullable": true,
            "dayProfile": "business"
          },
          "issue_type": {
            "kind": "enum",
            "values": [
              "Technical",
              "Billing",
              "General Inquiry"
            ],
            "description": "Type of issue reported in the ticket.",
            "nullable": true,
            "when": {
              "column": "status",
              "in": [
                "Open",
                "Pending"
              ]
            },
            "weights": [
              6,
              2,
              2
            ]
          },
          "status": {
            "kind": "enum",
            "values": [
              "Open",
              "Closed",
              "Pending"
            ],
            "description": "Current status of the support ticket.",
            "nullable": true,
            "when": {
              "column": "issue_type",
              "in": [
                "Technical",
                "Billing"
              ]
            },
            "weights": [
              8,
              3,
              1
            ]
          }
        }
      },
      "friendships": {
        "description": "This table captures friendships between users, highlighting social interactions within the community.",
        "rows": {
          "per": "users",
          "via": "user_id",
          "min": 0,
          "max": 5,
          "skew": "long-tail"
        },
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each friendship."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user who initiated the friendship."
          },
          "friend_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Identifier for the user who is the friend."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "The date and time when the friendship was established.",
            "dayProfile": "waking"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "nullable",
      "timestamped",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most popular game genres among users?",
      "How do transaction amounts vary by user country?",
      "What common issues do users report in support tickets?",
      "How does the number of friendships correlate with user activity?",
      "What trends can be observed in transaction dates over the year?"
    ],
    "suggestedQueries": [
      {
        "title": "Retrieve all transactions for a user",
        "sql": "SELECT * FROM transactions WHERE user_id = 1;",
        "dialect": "postgres"
      },
      {
        "title": "Count the number of support tickets by status",
        "sql": "SELECT status, COUNT(*) FROM support_tickets GROUP BY status;",
        "dialect": "postgres"
      },
      {
        "title": "Find the average transaction amount per game",
        "sql": "SELECT game_id, AVG(amount) FROM transactions GROUP BY game_id;",
        "dialect": "postgres"
      },
      {
        "title": "List users and their friends",
        "sql": "SELECT u.username, f.friend_id FROM users u JOIN friendships f ON u.id = f.user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Get the total number of transactions per user for a given month",
        "sql": "SELECT user_id, COUNT(*) FROM transactions WHERE transaction_date BETWEEN '2022-01-01' AND '2022-01-31' GROUP BY user_id;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "SQL Practice for Data Analysts",
        "body": "Data analysts can utilize this dataset to practice SQL skills by querying user activity, transaction patterns, and support interactions. By engaging with various queries, they can develop proficiency in handling relational databases and gain insights into users' behaviors within the gaming community."
      },
      {
        "title": "Teaching Database Management",
        "body": "Educators can use this dataset as a teaching tool in database management courses. It provides a practical example of how to structure hierarchical data and demonstrate relationships between tables, enabling students to learn about foreign keys, joins, and data integrity in a real-world context."
      },
      {
        "title": "Understanding Gaming Community Dynamics",
        "body": "Researchers interested in gaming communities can leverage this dataset to analyze user engagement, friendship dynamics, and support ticket trends. By examining correlations between user interactions and transaction behaviors, they can better understand the social fabric of gaming communities."
      },
      {
        "title": "Game Development Insights",
        "body": "Game developers can use this dataset to gain insights into user preferences and behaviors regarding game purchases and support needs. Understanding these patterns can guide developers in creating more engaging content and improving user experiences based on actual community data."
      }
    ]
  },
  "counts": {
    "games": 150,
    "users": 200,
    "friendships": 310,
    "support_tickets": 185,
    "transactions": 427
  },
  "stats": {
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          "distinct": 200,
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        },
        "username": {
          "nulls": 0,
          "distinct": 197,
          "min": "Alice Adams",
          "max": "Zoe Patel"
        },
        "join_date": {
          "nulls": 23,
          "distinct": 167,
          "min": "2020-01-02",
          "max": "2023-01-01"
        },
        "email": {
          "nulls": 26,
          "distinct": 173
        },
        "country": {
          "nulls": 19,
          "distinct": 42,
          "min": "Argentina",
          "max": "United States"
        }
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    },
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        "title": {
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          "min": "2020-01-04 05:47:41",
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}