{
  "format": "dataset-manifest/1",
  "slug": "concert-keep-up-app",
  "version": 3,
  "seed": "concert-keep-up-app:1",
  "spec": {
    "format": "dataset/1",
    "slug": "concert-keep-up-app",
    "name": "Concert Connections",
    "tagline": "Artists, concerts, fans, ticket sales, and reviews from live music events and their interactions.",
    "description": "Artists perform electrifying shows that engage thousands of enthusiastic fans, creating unforgettable live music experiences. These events hinge on the dynamic interplay between artists, their concerts, and the devoted followers who flock to see them. This business thrives on capturing the relationships among artists, their genres, concert events, ticket sales, and the feedback shared by fans through reviews. By examining these connections, one can observe how different factors drive audience engagement and ticket demand, revealing patterns that inform future concert planning and marketing strategies.\n\nEach table contributes vital information to the operation. The 'artists' table provides profiles of musicians, including their genres and backgrounds. 'concerts' lists specific events, detailing venues, dates, and associated artists, while 'fans' captures information about concertgoers, including their preferences and attendance history. The 'ticket_sales' table tracks the financial transactions related to ticket purchases, offering insights into trends in sales volume and pricing strategies. Finally, 'reviews' contains feedback from fans, which helps gauge audience satisfaction and can influence the reputation of artists and the venues they perform at.\n\nBy exploring this dataset, developers can practice answering critical questions such as which artists are trending, the impact of concert reviews on ticket sales, and how fan demographics correlate with concert attendance. This data can also help identify which venues are proving most successful in attracting large audiences and how concert timing affects ticket purchase behavior. Understanding these relationships can provide invaluable insights into the live music industry.\n\nAll data in this dataset is synthetic, providing a safe and realistic environment for developers to hone their skills without the constraints of real-world data.",
    "domain": "media",
    "shape": "graph-edges",
    "useCases": [
      "sql-practice",
      "teaching"
    ],
    "keywords": [
      "concerts",
      "artists",
      "fans",
      "venues",
      "ticket sales",
      "reviews",
      "genres",
      "engagement",
      "events"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "artists": {
        "description": "This table contains information about various music artists, including their genres and popularity metrics. Each row represents a unique artist linked to their genre.",
        "rows": 100,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each artist."
          },
          "name": {
            "kind": "fullName",
            "description": "The full name of the artist."
          },
          "genre": {
            "kind": "enum",
            "values": [
              "Rock",
              "Pop",
              "Hip-Hop",
              "Jazz",
              "Classical"
            ],
            "description": "The musical genre of the artist.",
            "weights": [
              5,
              4,
              3,
              2,
              1
            ]
          },
          "popularity": {
            "kind": "int",
            "min": 1,
            "max": 100,
            "description": "Popularity score from 1 to 100.",
            "nullable": true,
            "when": {
              "column": "genre",
              "in": [
                "Rock",
                "Pop"
              ]
            },
            "distribution": "high"
          }
        }
      },
      "concerts": {
        "description": "This table holds data about concerts, including details of the artists performing and the venues hosting the events. Each row represents a unique concert.",
        "rows": 150,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each concert."
          },
          "artist_id": {
            "kind": "fk",
            "ref": "artists.id",
            "description": "The artist performing at the concert."
          },
          "venue": {
            "kind": "sentence",
            "description": "Name of the venue hosting the concert.",
            "nullable": true
          },
          "date": {
            "kind": "date",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Date of the concert."
          },
          "ticket_price": {
            "kind": "decimal",
            "min": 10,
            "max": 200,
            "scale": 2,
            "description": "Price of concert tickets.",
            "nullable": true,
            "distribution": "long-tail"
          }
        }
      },
      "fans": {
        "description": "This table includes information about fans attending concerts, linking them to their favorite artists. Each row represents a unique fan.",
        "rows": 200,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each fan."
          },
          "name": {
            "kind": "fullName",
            "description": "The full name of the fan."
          },
          "favorite_artist_id": {
            "kind": "fk",
            "ref": "artists.id",
            "description": "The favorite artist of the fan."
          },
          "email": {
            "kind": "email",
            "from": "name",
            "description": "Email address of the fan.",
            "nullable": true
          }
        }
      },
      "ticket_sales": {
        "description": "This table tracks ticket sales for concerts, linking fans to the concerts they attend. Each row represents a ticket sale.",
        "rows": 300,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each ticket sale."
          },
          "concert_id": {
            "kind": "fk",
            "ref": "concerts.id",
            "description": "The concert for which the ticket was sold."
          },
          "fan_id": {
            "kind": "fk",
            "ref": "fans.id",
            "description": "The fan who purchased the ticket."
          },
          "purchase_date": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "dayProfile": "business",
            "description": "Date and time of ticket purchase."
          }
        }
      },
      "reviews": {
        "description": "This table contains user-generated reviews for concerts, linking fans to their feedback. Each row represents a unique review.",
        "rows": 250,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each review."
          },
          "concert_id": {
            "kind": "fk",
            "ref": "concerts.id",
            "description": "The concert being reviewed."
          },
          "fan_id": {
            "kind": "fk",
            "ref": "fans.id",
            "description": "The fan who wrote the review."
          },
          "rating": {
            "kind": "int",
            "min": 1,
            "max": 5,
            "description": "Rating given by the fan from 1 to 5.",
            "distribution": "high"
          },
          "comment": {
            "kind": "sentence",
            "description": "Text of the fan's review.",
            "nullable": true
          }
        }
      }
    },
    "structure": "multi-table",
    "traits": [
      "categorical",
      "nullable",
      "timestamped",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What genres are most popular among fans?",
      "How do ticket sales vary by artist and venue?",
      "What is the average rating given by fans for concerts?",
      "Which artists have the most reviews from fans?",
      "How does the popularity of an artist correlate with ticket sales?"
    ],
    "suggestedQueries": [
      {
        "title": "Join Concerts and Artists",
        "sql": "SELECT concerts.venue, artists.name FROM concerts JOIN artists ON concerts.artist_id = artists.id;",
        "dialect": "postgres"
      },
      {
        "title": "Count Ticket Sales by Concert",
        "sql": "SELECT concert_id, COUNT(*) as total_sales FROM ticket_sales GROUP BY concert_id;",
        "dialect": "postgres"
      },
      {
        "title": "Average Rating by Artist",
        "sql": "SELECT artists.name, AVG(reviews.rating) as average_rating FROM reviews JOIN concerts ON reviews.concert_id = concerts.id JOIN artists ON concerts.artist_id = artists.id GROUP BY artists.name;",
        "dialect": "postgres"
      },
      {
        "title": "Ticket Sales Trend Over Time",
        "sql": "SELECT DATE_TRUNC('month', purchase_date) as month, COUNT(*) as sales FROM ticket_sales GROUP BY month ORDER BY month;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Music Event Organizers",
        "body": "Event organizers can use this dataset to analyze trends in ticket sales and identify which artists and genres draw the largest crowds. By understanding audience preferences, they can tailor their events to maximize attendance and engagement."
      },
      {
        "title": "Music Industry Analysts",
        "body": "Analysts in the music industry can leverage this dataset to assess artist popularity and the impact of reviews on concert attendance. By analyzing the relationships between artist ratings and ticket sales, they can provide insights to record labels and promoters."
      },
      {
        "title": "Music Fans and Reviewers",
        "body": "Fans can explore their favorite artists and see how their reviews compare to others. This dataset allows them to analyze which concerts received the highest ratings and engage with fellow fans through shared experiences and feedback."
      },
      {
        "title": "Educators and Students",
        "body": "Educators can use this dataset in teaching data analysis and SQL skills. Students can practice writing queries to extract insights about artist popularity, concert attendance, and fan engagement, making the learning process interactive and relevant to a current industry."
      }
    ]
  },
  "counts": {
    "artists": 100,
    "concerts": 150,
    "fans": 200,
    "reviews": 250,
    "ticket_sales": 300
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