{
  "format": "dataset-manifest/1",
  "slug": "user-engagement-analytics",
  "version": 1,
  "seed": "user-engagement-analytics:1",
  "spec": {
    "format": "dataset/1",
    "slug": "user-engagement-analytics",
    "name": "User Engagement Analytics",
    "tagline": "User engagement data including progress, achievements, and study deck interactions in fintech educational tools.",
    "description": "Users interact with educational tools designed to enhance their financial literacy through engaging study decks, where they can learn various aspects of managing finances effectively. As users navigate through these decks, their progress is meticulously tracked, allowing for tailored experiences that help them achieve specific learning goals. Each user's journey is encapsulated in a dynamic system that records their actions, milestones, and achievements as they delve deeper into financial topics. The emphasis on user engagement not only promotes learning but also cultivates a community where users can share insights and collaborate on understanding complex subjects.\n\nThis dataset includes several interconnected tables that illustrate the structure of user engagement within the platform. The 'users' table captures essential information about each individual, such as their demographics and activity levels. The 'study_decks' table contains details about the various educational resources available, including their popularity and topics covered. 'user_progress' links users to the specific decks they are working through, detailing their completion rates and ongoing activities. 'achievements' tracks any milestones users have unlocked, providing insight into their learning journeys and rewards earned. Additionally, the 'note_tags' table categorizes users' notes, enhancing the ability to filter and search through personal insights and annotations.\n\nBy analyzing this data, developers can answer questions related to user engagement patterns, the effectiveness of different study decks, and factors contributing to users' achievements. Practicing on this dataset allows one to explore insights such as which topics resonate most with users, how engagement evolves over time, and the potential impact of personalized learning pathways. This synthetic dataset offers a rich resource for developers to hone their skills in data analysis, visualization, and user behavior interpretation.",
    "domain": "fintech",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "user engagement",
      "financial literacy",
      "education",
      "analytics",
      "study decks",
      "achievements",
      "collaboration"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table contains user profiles, with each row representing a unique user. Each user can engage with multiple study decks and track their progress.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the user.",
            "nullable": true
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "User's email address.",
            "nullable": true
          },
          "registration_date": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "The date the user registered.",
            "trend": "growing"
          }
        }
      },
      "study_decks": {
        "description": "This table lists study decks available for users. Each deck contains various learning modules and can be associated with multiple tags.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each study deck."
          },
          "title": {
            "kind": "words",
            "min": 3,
            "max": 10,
            "description": "Title of the study deck.",
            "nullable": true
          },
          "created_at": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Creation date of the study deck.",
            "trend": "growing"
          }
        }
      },
      "user_progress": {
        "description": "Tracks the progress of users through learning modules in each study deck. Each row links a user to their progress in a specific deck.",
        "rows": 600,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each progress record."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "The user associated with this progress record."
          },
          "deck_id": {
            "kind": "fk",
            "ref": "study_decks.id",
            "description": "The study deck associated with this progress record."
          },
          "completed_modules": {
            "kind": "int",
            "min": 0,
            "max": 10,
            "description": "Number of completed modules in the deck.",
            "nullable": true
          },
          "last_accessed": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Last date and time the user accessed the deck.",
            "nullable": true,
            "dayProfile": "waking"
          }
        }
      },
      "achievements": {
        "description": "This table records achievements unlocked by users as they progress through study decks. Each achievement corresponds to specific milestones.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each achievement."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "The user who unlocked this achievement."
          },
          "description": {
            "kind": "sentence",
            "description": "Description of the achievement unlocked.",
            "nullable": true
          },
          "date_unlocked": {
            "kind": "date",
            "from": "2020-01-01",
            "to": "2023-12-31",
            "description": "Date when the achievement was unlocked.",
            "nullable": true,
            "trend": "seasonal"
          }
        }
      },
      "note_tags": {
        "description": "This table associates tags with user notes within study decks. It allows users to categorize their notes for better organization.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each note tag."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "The user who created the tag."
          },
          "deck_id": {
            "kind": "fk",
            "ref": "study_decks.id",
            "description": "The study deck in which the note tag is used."
          },
          "tag": {
            "kind": "words",
            "min": 1,
            "max": 3,
            "description": "Tag associated with the user's notes.",
            "nullable": true
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most popular study decks among users?",
      "How does user progress correlate with the number of achievements unlocked?",
      "Which tags are most frequently used by users in their notes?",
      "What patterns can be identified in user engagement over time?"
    ],
    "suggestedQueries": [
      {
        "title": "List all users and their email addresses",
        "sql": "SELECT full_name, email FROM users;",
        "dialect": "postgres"
      },
      {
        "title": "Count completed modules by each user",
        "sql": "SELECT user_id, SUM(completed_modules) FROM user_progress GROUP BY user_id;",
        "dialect": "postgres"
      },
      {
        "title": "Find users who unlocked achievements in 2023",
        "sql": "SELECT DISTINCT user_id FROM achievements WHERE date_unlocked BETWEEN '2023-01-01' AND '2023-12-31';",
        "dialect": "postgres"
      },
      {
        "title": "Get the average number of completed modules per deck",
        "sql": "SELECT deck_id, AVG(completed_modules) FROM user_progress GROUP BY deck_id;",
        "dialect": "postgres"
      },
      {
        "title": "Identify the most used tags in notes",
        "sql": "SELECT tag, COUNT(*) FROM note_tags GROUP BY tag ORDER BY COUNT(*) DESC;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Educational Tool Developers",
        "body": "Developers creating educational fintech applications can use this dataset to simulate user engagement scenarios. By analyzing user progress and achievements, they can optimize the design of their applications to enhance learning experiences."
      },
      {
        "title": "Market Analysts",
        "body": "Market analysts can leverage this dataset to understand user behavior and preferences in fintech educational tools. Insights gained can guide product development and marketing strategies aimed at improving user engagement."
      },
      {
        "title": "Data Science Students",
        "body": "Students learning data analysis and SQL can practice on this dataset to develop their skills. By formulating queries and exploring user engagement metrics, they can gain practical experience that prepares them for real-world applications."
      },
      {
        "title": "Educational Researchers",
        "body": "Researchers studying the effectiveness of fintech educational tools can use this dataset to analyze user engagement patterns. They can identify trends and correlations that inform the development of more effective financial literacy programs."
      }
    ]
  },
  "counts": {
    "study_decks": 150,
    "users": 200,
    "achievements": 300,
    "note_tags": 400,
    "user_progress": 600
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