Music Data

What Is Music Data?

Music data is the collection of information on songs, artists, producers, recording studios, rights holders, distributors, charts, and listeners. Legal cases related to music and revenue generated by ticket sales or merchandise also count as music data.

Where Does Music Data Come From?

There are a large number of music databases, some open-source and some private B2B companies working with media. However, recording companies and distributors like music streaming applications generate most music data.

These sources may analyze the music itself for tempo, recording type (live, remix, etc.), and genre. Record companies often provide official data on artist, writer, composer, and year of release. Data on the number and type of listeners comes from streaming services, radio stations, and official sellers.

Data on unofficial merchandise sales or pirated downloads is, of course, difficult to find yet contributes to a fair amount of music revenue data. In both cases, however, decent web scraping tools can generate good data as these transactions are now often made online.

What Types of Columns/Attributes Should I Expect When Working with This Data?

Common music data attributes, in addition to artist, genre, composer, and right-holder, include charting data: in other words, how popular was the song, and for how long?

This data also includes a lot of information about listeners, especially audience demographics, preferred listening service, and online behavior.

What Is Music Data Used For?

Advertisers, tv show producers, and other media professionals use this data to contact rights-holders to songs they’d like to use in their programs. They also use the data to buy ad space on streaming services before songs that their target demographic listens to.

Artists, managers, and researchers also use the data as research, to determine what (currently or in general) makes a song popular or how artists became popular.

Fans of certain music or musicians may also use the data to find more artists they may like.

How Should I Test the Quality of This Data?

Particularly since legal issues tend to pop up from time to time in the music industry, keep the data set as up-to-date and accurate as possible. Outdated information or misattributed credits can cause a number of headaches.

Interesting Case Studies and Blogs to Look Into

Chartmetric: 6MO Report
FuturePulse Use Cases and Business Scenarios

Tangible Examples of Impact

Others have also speculated about Spotify’s potential to create A.I.-generated music, especially after the firm hired François Pachet, head of Spotify’s Creator Technology Research Lab, though Spotify has dodged questions about whether that’s one of their ultimate goals.

Pachet is listed as an inventor on Spotify’s patent application. He is well-known in the world of A.I. for his decades of research on creating algorithms that can produce new music, as well as delving into why humans like specific music. Much of Pachet’s previous work has focused on using lead sheets as the standard format for machines to understand music.

OneZero: Is Spotify’s Newly Patented A.I. Plagiarism Detector a Data Collection Scheme?