{
  "format": "dataset-manifest/1",
  "slug": "enterprise-knowledge-base-system",
  "version": 2,
  "seed": "enterprise-knowledge-base-system:1",
  "spec": {
    "format": "dataset/1",
    "slug": "enterprise-knowledge-base-system",
    "name": "Knowledge Management Insights",
    "tagline": "User interactions, articles, subscriptions, and reviews in customer support environments.",
    "description": "Users engage actively with a variety of knowledge articles, seeking quick solutions to their queries. Each user belongs to a specific department, which helps streamline the support process by categorizing inquiries and resources accordingly. As users interact with the articles, they leave reviews and comments that provide insights into the effectiveness of the content, fostering a continuous feedback loop that enhances the knowledge base. Subscriptions indicate which articles users are following, highlighting topics of high interest or urgency within their departments.\n\nThe relationships among the tables form a rich landscape of interactions. A single row in the users table represents an individual seeking assistance, while the departments table details the organizational structure each user belongs to. Articles are entries in the knowledge base that users reference, and subscriptions track which articles users have chosen to follow. Reviews and comments are both linked to articles, with each review providing qualitative feedback on the content, and comments offering a space for more casual or conversational insights. This interconnectedness allows for a nuanced understanding of how knowledge is consumed and valued within customer support contexts.\n\nThis dataset offers a wealth of opportunities for exploring questions such as: Which articles receive the most engagement? How does the feedback from reviews and comments influence article revisions? Are there patterns in subscriptions that correlate with departmental needs? By practicing with this data, developers can simulate user interactions, analyze trends in knowledge consumption, and identify areas for improving content delivery. Please note that all data is synthetic, designed to imitate real-world user behavior without representing actual users or organizations.",
    "domain": "customer-support",
    "shape": "slowly-changing",
    "useCases": [
      "etl-pipelines",
      "teaching"
    ],
    "keywords": [
      "knowledge management",
      "customer support",
      "user interaction",
      "article versions",
      "departmental subscriptions",
      "content management"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "users": {
        "description": "This table contains information about users who interact with the knowledge base, linked to their respective departments.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "Full name of the user."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "Email address of the user."
          },
          "department_id": {
            "kind": "fk",
            "ref": "departments.id",
            "description": "Foreign key linking to the user's department."
          }
        }
      },
      "departments": {
        "description": "This table outlines the various departments within the organization, which users belong to.",
        "rows": 10,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each department."
          },
          "name": {
            "kind": "words",
            "max": 3,
            "description": "Name of the department.",
            "pool": [
              "support",
              "sales",
              "technical",
              "customer",
              "billing",
              "operations",
              "marketing",
              "human",
              "resources",
              "quality",
              "service",
              "development",
              "training",
              "analytics",
              "design",
              "strategy",
              "research",
              "compliance",
              "management",
              "solutions",
              "engagement"
            ],
            "min": 1
          }
        }
      },
      "articles": {
        "description": "This table tracks the articles available in the knowledge base, including their versions and statuses.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each article."
          },
          "title": {
            "kind": "words",
            "max": 5,
            "description": "Title of the article.",
            "pool": [
              "guide",
              "tips",
              "troubleshooting",
              "overview",
              "best",
              "practices",
              "faq",
              "introduction",
              "update",
              "report",
              "analysis",
              "case",
              "study",
              "review",
              "strategy",
              "insight",
              "framework",
              "approach",
              "methodology",
              "solution",
              "resource"
            ],
            "min": 1
          },
          "version": {
            "kind": "int",
            "min": 1,
            "max": 10,
            "description": "Version of the article."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Date when the article was created.",
            "dayProfile": "business"
          },
          "updated_at": {
            "kind": "datetime",
            "after": "created_at",
            "withinDays": 30,
            "description": "Date when the article was last updated."
          },
          "status": {
            "kind": "enum",
            "values": [
              "published",
              "draft",
              "archived"
            ],
            "description": "Current status of the article."
          }
        }
      },
      "subscriptions": {
        "description": "This table captures which departments are subscribed to which articles, indicating interest and access.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each subscription."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Foreign key linking to the user who subscribed."
          },
          "article_id": {
            "kind": "fk",
            "ref": "articles.id",
            "description": "Foreign key linking to the subscribed article."
          },
          "subscribed_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Date when the subscription was made.",
            "dayProfile": "waking"
          }
        }
      },
      "reviews": {
        "description": "This table captures user reviews on articles, providing feedback on their usefulness.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each review."
          },
          "article_id": {
            "kind": "fk",
            "ref": "articles.id",
            "description": "Foreign key linking to the article being reviewed."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Foreign key linking to the user who wrote the review."
          },
          "rating": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Rating given by the user, on a scale from 1 to 5.",
            "distribution": "high"
          },
          "comment": {
            "kind": "sentence",
            "max": 200,
            "nullable": true,
            "description": "Comment provided by the user in the review."
          },
          "reviewed_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Date when the review was submitted.",
            "dayProfile": "waking"
          }
        }
      },
      "comments": {
        "description": "This table captures comments made by users on articles, fostering discussions around knowledge.",
        "rows": 50,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each comment."
          },
          "article_id": {
            "kind": "fk",
            "ref": "articles.id",
            "description": "Foreign key linking to the article being commented on."
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Foreign key linking to the user who made the comment."
          },
          "content": {
            "kind": "sentence",
            "max": 250,
            "description": "Content of the comment made by the user."
          },
          "commented_at": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "Date when the comment was made.",
            "dayProfile": "waking"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "nullable",
      "timestamped",
      "categorical",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "Which articles receive the most user reviews and why might that be?",
      "How does the user engagement with articles vary by department?",
      "What trends can be observed in article version updates over time?",
      "Which articles have the highest average ratings from users?",
      "How frequently do users comment on articles compared to writing reviews?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Users with Article Reviews",
        "sql": "SELECT users.full_name, articles.title, reviews.rating FROM reviews JOIN users ON reviews.user_id = users.id JOIN articles ON reviews.article_id = articles.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Article Subscriptions by Department",
        "sql": "SELECT departments.name, COUNT(subscriptions.id) AS subscription_count FROM subscriptions JOIN users ON subscriptions.user_id = users.id JOIN departments ON users.department_id = departments.id GROUP BY departments.name;",
        "dialect": "postgres"
      },
      {
        "title": "Average Rating of Each Article",
        "sql": "SELECT articles.title, AVG(reviews.rating) AS average_rating FROM articles LEFT JOIN reviews ON articles.id = reviews.article_id GROUP BY articles.title;",
        "dialect": "postgres"
      },
      {
        "title": "Latest Comments on Articles",
        "sql": "SELECT articles.title, comments.content, comments.commented_at FROM comments JOIN articles ON comments.article_id = articles.id ORDER BY comments.commented_at DESC LIMIT 10;",
        "dialect": "postgres"
      },
      {
        "title": "Article Engagement Trends Over Time",
        "sql": "SELECT articles.title, COUNT(reviews.id) AS review_count, COUNT(comments.id) AS comment_count FROM articles LEFT JOIN reviews ON articles.id = reviews.article_id LEFT JOIN comments ON articles.id = comments.article_id GROUP BY articles.title ORDER BY review_count DESC;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Customer Support Analysis",
        "body": "Customer support managers can leverage this dataset to analyze which articles are most frequently reviewed and commented on. By identifying high-engagement articles, they can prioritize updates and improvements based on user feedback, ultimately enhancing the knowledge base's effectiveness."
      },
      {
        "title": "Training and Development",
        "body": "Instructors can use this dataset in a classroom setting to teach students about data analysis in customer support contexts. By working with real-like datasets, students can learn how to extract insights from user interactions, fostering skills in SQL and data interpretation."
      },
      {
        "title": "Content Management Strategies",
        "body": "Content managers can utilize this dataset to track the evolution of articles over time, examining how updates and versions correlate with user engagement. By understanding the dynamics of knowledge consumption, they can develop strategies to optimize content for better accessibility and relevance."
      },
      {
        "title": "Departmental Engagement Insights",
        "body": "Department heads can analyze the subscription patterns of their teams to determine which articles resonate most with their members. This can drive targeted training sessions and encourage departments to engage more deeply with the knowledge base, promoting a culture of knowledge sharing."
      }
    ]
  },
  "counts": {
    "articles": 150,
    "departments": 10,
    "users": 200,
    "comments": 50,
    "reviews": 100,
    "subscriptions": 300
  },
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