{
  "format": "dataset-manifest/1",
  "slug": "media-project-management",
  "version": 2,
  "seed": "media-project-management:1",
  "spec": {
    "format": "dataset/1",
    "slug": "media-project-management",
    "name": "Media Project Management",
    "tagline": "Project details, audio streams, video filters, codec data, and user interactions from media content creators.",
    "description": "Content creators collaborate and manage intricate workflows, meticulously enhancing their media projects with the right combination of audio adjustments and video filters. Each project captures essential details such as the title, description, and status, allowing creators to track their progress and maintain organization. Users play a pivotal role, as they interact with various audio streams and video filters, making artistic choices that define the final output. This dataset provides insight into how these elements converge, showcasing the dynamic nature of media production.\n\nThe tables within this dataset interrelate to depict the full scope of project management in a media context. The 'projects' table serves as the central hub, with each row representing a distinct media project. It connects to the 'audio_streams' table, where each audio stream tied to a project can be examined. Similarly, the 'video_filters' table captures the specific filters applied to enhance visual appeal, while the 'codecs' table provides information on the encoding standards used for project outputs. The 'users' table records the individuals involved, linking their actions to specific projects and highlighting their contributions to the creative process.\n\nThis dataset answers various questions related to media project management. Developers can explore trends in audio and video preferences, analyze user involvement across projects, and identify unique combinations of filters and codecs that lead to standout results. It is particularly useful for practicing SQL joins and exploring relationships between tables, as well as gaining insight into user behavior and project outcomes. Note that the data within this dataset is synthetic, designed to simulate real-world scenarios while providing a flexible platform for learning.",
    "domain": "media",
    "shape": "transactional",
    "useCases": [
      "sql-practice",
      "orm-seeding"
    ],
    "keywords": [
      "media",
      "projects",
      "filters",
      "audio",
      "video",
      "codecs",
      "user interactions",
      "content creation"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "projects": {
        "description": "This table holds the details of each media project. Each row represents a distinct project and links to its associated filters and audio streams.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the project."
          },
          "name": {
            "kind": "title",
            "description": "The title of the media project."
          },
          "created_at": {
            "kind": "datetime",
            "from": "2022-01-01",
            "to": "2023-01-01",
            "description": "The date and time when the project was created.",
            "dayProfile": "business"
          },
          "description": {
            "kind": "paragraph",
            "max": 500,
            "description": "A brief description of the project.",
            "nullable": true
          },
          "user_id": {
            "kind": "fk",
            "ref": "users.id",
            "description": "Reference to the user who created the project."
          }
        }
      },
      "audio_streams": {
        "description": "This table contains information about audio streams associated with projects. Each row links to a specific project and details the audio configuration.",
        "rows": 400,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the audio stream."
          },
          "project_id": {
            "kind": "fk",
            "ref": "projects.id",
            "description": "Reference to the related media project."
          },
          "codec": {
            "kind": "enum",
            "values": [
              "AAC",
              "MP3",
              "WAV",
              "FLAC"
            ],
            "description": "Audio codec used for the stream.",
            "weights": [
              6,
              3,
              1,
              1
            ]
          },
          "bitrate": {
            "kind": "int",
            "min": 64,
            "max": 320,
            "description": "Bitrate of the audio stream in kbps.",
            "nullable": true,
            "when": {
              "column": "codec",
              "in": [
                "AAC",
                "MP3",
                "WAV",
                "FLAC"
              ]
            },
            "distribution": "normal"
          },
          "channels": {
            "kind": "int",
            "min": 1,
            "max": 8,
            "description": "Number of audio channels.",
            "nullable": true,
            "when": {
              "column": "codec",
              "in": [
                "AAC",
                "MP3",
                "WAV",
                "FLAC"
              ]
            }
          }
        }
      },
      "video_filters": {
        "description": "This table lists the video filters applied to projects. Each row represents a filter linked to a specific project.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the video filter."
          },
          "project_id": {
            "kind": "fk",
            "ref": "projects.id",
            "description": "Reference to the related media project."
          },
          "filter_type": {
            "kind": "enum",
            "values": [
              "Brightness",
              "Contrast",
              "Saturation",
              "Blur",
              "Sharpen"
            ],
            "description": "Type of video filter applied.",
            "weights": [
              5,
              4,
              3,
              2,
              1
            ]
          },
          "strength": {
            "kind": "decimal",
            "min": 0,
            "max": 1,
            "scale": 2,
            "description": "Strength of the filter effect.",
            "nullable": true,
            "when": {
              "column": "filter_type",
              "in": [
                "Brightness",
                "Contrast",
                "Saturation",
                "Blur",
                "Sharpen"
              ]
            }
          }
        }
      },
      "codecs": {
        "description": "This table holds codec information used in projects. Each row provides details about a specific codec.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the codec."
          },
          "name": {
            "kind": "enum",
            "values": [
              "H.264",
              "H.265",
              "VP9",
              "AV1"
            ],
            "description": "Name of the codec.",
            "weights": [
              7,
              5,
              3,
              1
            ]
          },
          "resolution": {
            "kind": "enum",
            "values": [
              "480p",
              "720p",
              "1080p",
              "4K"
            ],
            "description": "Resolution supported by the codec.",
            "nullable": true,
            "when": {
              "column": "name",
              "in": [
                "H.264",
                "H.265",
                "VP9",
                "AV1"
              ]
            },
            "weights": [
              4,
              6,
              5,
              2
            ]
          },
          "max_bitrate": {
            "kind": "int",
            "min": 1000,
            "max": 20000,
            "description": "Maximum bitrate supported by the codec in kbps.",
            "nullable": true,
            "when": {
              "column": "name",
              "in": [
                "H.264",
                "H.265",
                "VP9",
                "AV1"
              ]
            },
            "distribution": "heavy-tail"
          }
        }
      },
      "users": {
        "description": "This table contains information about users who create media projects. Each row represents a distinct user.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for the user."
          },
          "full_name": {
            "kind": "fullName",
            "description": "The full name of the user."
          },
          "email": {
            "kind": "email",
            "from": "full_name",
            "description": "The email address of the user."
          },
          "registration_date": {
            "kind": "datetime",
            "from": "2020-01-01",
            "to": "2023-01-01",
            "description": "The date the user registered.",
            "dayProfile": "waking",
            "trend": "growing"
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "timestamped",
      "nullable"
    ],
    "analysisQuestions": [
      "What are the most commonly used audio codecs across projects?",
      "How do filter strengths vary among different projects?",
      "Which users create the most projects?",
      "What is the average bitrate of audio streams in completed projects?",
      "How does the choice of video resolution impact the selected codecs?"
    ],
    "suggestedQueries": [
      {
        "title": "List all projects with their user names",
        "sql": "SELECT projects.name, users.full_name FROM projects JOIN users ON projects.user_id = users.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count projects per user",
        "sql": "SELECT users.full_name, COUNT(projects.id) AS project_count FROM users LEFT JOIN projects ON users.id = projects.user_id GROUP BY users.full_name;",
        "dialect": "postgres"
      },
      {
        "title": "Average audio bitrate by codec",
        "sql": "SELECT audio_streams.codec, AVG(audio_streams.bitrate) AS average_bitrate FROM audio_streams GROUP BY audio_streams.codec;",
        "dialect": "postgres"
      },
      {
        "title": "Filter usage frequency in projects",
        "sql": "SELECT video_filters.filter_type, COUNT(video_filters.id) AS usage_count FROM video_filters GROUP BY video_filters.filter_type;",
        "dialect": "postgres"
      },
      {
        "title": "Find projects with specific filter strength",
        "sql": "SELECT projects.name FROM projects JOIN video_filters ON projects.id = video_filters.project_id WHERE video_filters.strength > 0.5;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Content Creator Analysis",
        "body": "A content creator can use this dataset to analyze their media projects, exploring which filters are most effective and how different audio streams impact the final product. By querying the data, they can refine their workflows and make informed decisions about future projects."
      },
      {
        "title": "Codec Performance Evaluation",
        "body": "A media engineer can perform a detailed analysis of codec performance across various projects. By examining the relationship between codec choice and project resolution, they can identify the best configurations for different content types, optimizing rendering times and output quality."
      },
      {
        "title": "User Engagement Insights",
        "body": "A product manager can leverage this dataset to gain insights into user engagement with the media project platform. By analyzing project counts per user and filter usage frequency, they can make data-driven decisions to improve user experience and engagement metrics."
      },
      {
        "title": "Educational Purpose",
        "body": "Educators can utilize this dataset in workshops or classes to teach SQL and data analysis techniques. Students can practice writing queries to extract meaningful insights from media project data, fostering skills in both database management and media production."
      }
    ]
  },
  "counts": {
    "codecs": 150,
    "users": 100,
    "projects": 200,
    "audio_streams": 400,
    "video_filters": 300
  },
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