Content Performance & Music Catalog Analytics Dataset

Group Category: Dataset

Product Category: Database Design & Development

Sub Category: PostgreSQL

Evaluate content performance, measure listener preferences, and optimize music catalogs with structured, SQL-ready analytics datasets.

Business Overview:

This dataset focuses on catalog and content performance, offering relational data across songs, albums, artists, and genres. It enables detailed analysis of music consumption trends and supports catalog optimization efforts.

Product Highlights:

Well-structured CSV datasets (songs, albums, artists, genres, listening history)
Allows analysis of content hierarchy and performance
Ideal for editorial teams, licensing strategy, and A&R functions
Supports SQL practice on normalized catalog data

Learning Outcomes:

Analyze genre and album-level engagement
Evaluate completion rates and song performance
Practice many-to-many mapping through song-genre tables
Understand relational data modeling in media analytics

1/6

genres

| CSV

Defines the available music genres along with optional descriptions. This file supports genre-based filtering, classification, and music preference modeling.

Key Features:

70 genre entries with descriptions
Enables categorization of songs and content clusters
Useful for genre trend analysis or tagging pipelines

albums

| CSV

Contains structured metadata about music albums including titles, release dates, and artist associations. This file supports catalog organization, artist discography analysis, and release tracking.

Key Features:

3,197 album records with titles and release data
Direct linkage to artists via foreign key
Enables chronological or artist-based album exploration

artists

| CSV

Includes descriptive records of music artists, such as names, bios, and profiles. Useful for analyzing content contributors, artist catalog depth, and metadata completeness.

Key Features:

1,097 artist records with rich metadata
Supports artist profiling and contribution aggregation
Ideal for catalog attribution and artist-based queries

song_genres

| CSV

Maps songs to their respective genres, allowing for multi-genre tagging and classification. Enables thematic analysis and genre-based recommendation features.

Key Features:

9,383 records linking songs to genres
Supports multi-genre mapping per song
Enables genre analytics, filtering, and mood analysis

songs

| CSV

Includes detailed song-level metadata like title, duration, album, and artist references. This file supports playback analytics, catalog navigation, and track popularity insights.

Key Features:

9,383 song entries with duration and creator metadata
Links to both albums and artists tables
Ideal for catalog indexing, filtering, and performance comparison

user_listening_history

| CSV

Captures timestamped listening events for users across songs. Enables behavioral modeling, listening trend analysis, and peak usage discovery.

Key Features:

Tracks listening sessions with user and song references
Timestamped to support daily, weekly, or seasonal analysis
Core dataset for behavioral and engagement analytics

Content Performance & Music Catalog Analytics Dataset

$1.54 $1.00 35% OFF