First case in point: In a recent blog post I let you know that the music business is a big data business?
Second case in point: I’m here to once again sing (pun intended) the praises of big data because of its ability to help music rights holders lay claim to royalties they’re legally owed for the use of their music.
How, you ask?
Well, TuneSat, a New York-based company whose leaders have deep-seated ties to the music and entertainment industries, has figured out a way to put big data in the hands of the folks who own the rights to the music to ensure that they get the money that’s coming to them.
In fact, since its launch in 2009, TuneSat has helped rights holders collect millions of dollars that would otherwise have been lost or undiscovered without the critical detection data.
TuneSat uses big data and advanced analytics to let artists and other rights holders know exactly when and where their audio content is being performed on hundreds of TV channels in the US and Europe as well as millions of websites around the globe, in the “dirtiest of audio environments,” such as voice-overs, sound effects, or crowd noise, according to the company. TuneSat then makes the reports that detail when and how music is being used available to rights holders.
Working much like a fingerprint scanner, TuneSat’s proprietary audio fingerprinting technology analyzes the unique characteristics of each music file and compares it to other content such as broadcast TV and multimedia files from the Internet in order to detect a match.
And TuneSat can do it in as little as three seconds.
For a nominal subscription fee (starting at $10/month for 10 tracks of music), any artist and music publishing organization can actively track music across a wide range of media outlets. Subscribers can access TuneSat’s servers and its proprietary analytics tools using a web-based app.
“The result is yet another way big data and advanced analytics disrupt existing business models by quickly and inexpensively revealing information either actively hidden via intentional secrecy, or passively buried in the depths of bureaucracy and tangled processes,” says Brian Proffitt in the ReadWriteWeb piece.
The value of the part of the business that’s driven by big data could even surpass revenue from the core business of composing and producing music, according to The Wall Street Journal.
Here’s how TuneSat works:
- Subscribers submit high-quality recordings of their music.
- TuneSat then fingerprints these recordings and takes a digital snapshot (deciphers and records) of the unique DNA of the file.
- These fingerprinted recordings are then compared to complete live broadcasts from the top national network and cable broadcasters around the globe, all of which TuneSat monitors in real time, 24/7.
- When a match is found between TuneSat’s fingerprint database and a TV broadcast, TuneSat records in-context audio of that broadcast for proof of performance and verification purposes.
- Clients can sign into TuneSat’s secure subscriber portal anytime through a web browser on a Mac or PC to view detections of their fingerprinted music, or export music usage reports.
Proffitt says because there’s so much variation in musical performances, you’d expect TuneSat to need a back-end infrastructure that uses Hadoop or some other big-data tool for unstructured data.
But you’d be wrong.
What’s ultimately stored and used to track and find songs is a very structured digital signature that can be stored and analyzed with a PostgreSQL database and analyzed using a custom data processing tool, according to the article in ReadWriteWeb.
The bottom line is that TuneSat decentralizes and automates what was once a burdensome data-gathering process.
The result: It no longer takes months for performing rights organizations like ASCAP and BMI to figure out who should get paid. Now it can be done within an hour – thanks to big data.
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- To hear how organizations that have adopted in-memory computing can analyze larger amounts of data in less time – and much faster – than their competitors, watch our on-demand webcast, “In-Memory Computing: Lifting the Burden of Big Data,” presented by Nathaniel Rowe, Research Analyst, Aberdeen Group and Michael O’Connell, PhD, Sr. Director, Analytics, TIBCO Spotfire.
- Download a copy of the Aberdeen In-Memory Big Data whitepaper here.