{
  "format": "dataset-manifest/1",
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  "version": 1,
  "seed": "visual-studio-code:1",
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    "slug": "visual-studio-code",
    "name": "Code Collaboration in Banking",
    "tagline": "User interactions, project files, and installed extensions in banking code collaboration.",
    "description": "Developers collaborate on various projects, sharing code snippets and utilizing different extensions in the fast-paced environment of banking software development. As teams work together to create secure and efficient applications that manage sensitive financial data, they engage in real-time interactions that significantly enhance productivity and innovation. This dataset captures these user interactions, detailing how code is developed, shared, and managed across different workspaces.\n\nThe primary table, collaboration_data, contains rows representing individual coding sessions, which include timestamps, user IDs, project IDs, and details about the extensions employed during collaboration. Each row provides a snapshot of activity, such as who was present during a session, what files were worked on, and what tools were utilized. This structure allows you to explore the relationships between users, their projects, and the effectiveness of various coding practices in different scenarios.\n\nYou can answer questions like: Which extensions are most popular among developers? How often do teams collaborate on the same projects? What patterns emerge in user engagement based on the type of project being worked on? By analyzing this data, you can practice skills in data manipulation, querying relationships, and deriving insights from user behaviors in collaborative coding environments. \n\nKeep in mind that this data is synthetic, designed to mimic real-world interactions while providing a controlled environment for analysis and practice.",
    "domain": "banking",
    "shape": "multi-tenant",
    "useCases": [
      "orm-seeding",
      "api-mocking"
    ],
    "keywords": [
      "banking",
      "collaboration",
      "software development",
      "code snippets",
      "extensions",
      "projects"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "collaboration_data": {
        "description": "Each row represents a unique user interaction within a project, detailing their engagement with various files, extensions, and project settings. It links to multi-tenant environments where multiple users may collaborate on the same project.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "The unique identifier for each collaboration record."
          },
          "user_id": {
            "kind": "uuid",
            "description": "The unique identifier for the user involved in the collaboration."
          },
          "project_name": {
            "kind": "words",
            "min": 2,
            "max": 10,
            "description": "The name of the project the user is collaborating on."
          },
          "file_name": {
            "kind": "words",
            "min": 2,
            "max": 10,
            "description": "The name of the file the user is interacting with."
          },
          "action": {
            "kind": "enum",
            "values": [
              "edit",
              "commit",
              "share",
              "view"
            ],
            "description": "The action performed by the user on the project file."
          },
          "extension": {
            "kind": "words",
            "min": 2,
            "max": 5,
            "nullable": true,
            "description": "The name of the installed extension used during the interaction."
          },
          "timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "The date and time when the user interaction occurred.",
            "dayProfile": "waking"
          },
          "workspace": {
            "kind": "words",
            "min": 2,
            "max": 8,
            "description": "The name of the workspace where the interaction took place."
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "categorical",
      "nullable",
      "timestamped"
    ],
    "analysisQuestions": [
      "What actions are most commonly performed by users within projects?",
      "How does the usage of different extensions affect user collaboration?",
      "What projects have the highest level of user engagement?",
      "At what times do users typically collaborate on projects?",
      "Are there specific workspaces that are more popular among developers?"
    ],
    "suggestedQueries": [
      {
        "title": "List all user interactions for a specific project",
        "sql": "SELECT * FROM collaboration_data WHERE project_name = 'Project A';",
        "dialect": "postgres"
      },
      {
        "title": "Count actions performed by each user",
        "sql": "SELECT user_id, COUNT(action) FROM collaboration_data GROUP BY user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Find the most common actions in a specific workspace",
        "sql": "SELECT action, COUNT(*) FROM collaboration_data WHERE workspace = 'Workspace 1' GROUP BY action;",
        "dialect": "postgres"
      },
      {
        "title": "Get user interactions within a specific date range",
        "sql": "SELECT * FROM collaboration_data WHERE timestamp BETWEEN '2023-01-01' AND '2023-01-31';",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Developers Analyzing Collaboration Patterns",
        "body": "Developers in the banking sector can utilize this dataset to analyze collaboration patterns across different projects. By understanding how often users interact with specific files and extensions, they can identify tools that enhance productivity and streamline workflows."
      },
      {
        "title": "API Mocking for Banking Applications",
        "body": "API developers can use this dataset to create mock data for testing banking applications. By simulating user interactions and project files, they can ensure their applications handle various scenarios effectively before deployment."
      },
      {
        "title": "Training New Team Members",
        "body": "Team leads in banking institutions can leverage this dataset to train new developers on collaborative practices. By showcasing real user interactions and project management, new hires can better understand the tools and processes used in their teams."
      }
    ]
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