Once upon a time, music industry insiders and observers believed that technology and the Internet were slowly destroying the music business. Between illegal music downloads and high prices for CDs, music consumers had turned away from the age old successful model of paying for music in favor of a cheaper and more convenient way. Music companies tried to change with the times but were late to do so. Apple made some headway with its now- famous iTunes and streaming music services offered still more promise as a means to the end of distributing music to any electronic device at any place and time. Yet something was still missing that the music industry desperately needed to truly make online music both efficient and profitable, as these downloading services like YouTube and Spotify were free or mostly free.

Big Data to the Music Industry’s Rescue

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Enter Big Data and technology, which have come riding to the rescue of the once-beleaguered music business and model. In their wake have come numerous changes to the business, not the least of which is the fact that the stogy-smoking record company executives have given way to coffee swilling techy kids. Technology and the world of music are now joined at the hip once again, thanks in no small part to this transfer of power from the old guard to the newer generation, and also to the capabilities brought to the table by Big Data and its constant ally analytics.

How Big Data Changed and Saved the Music World

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Big Data has been utilized to totally transform the ailing music business so much that a person who looks back on the industry only twenty years ago would no longer recognize it. This is not just about online music downloads and streaming music. This is a total metamorphosis in the way that listeners and record labels both connect and interact.

A great example of this is the way that Big Data has enabled the music industry to finally understand who exactly purchases their CD’s (or in the past, cassette tapes or LP records). Downloading, long considered the enemy of music and artists as it took revenues away from them, has now become a savior of sorts. Thanks to downloading of music tracks, the record companies now can say with certainty for the first time ever who is listening to what and what their listening habits and preferences are, as Amazon has long done with books and reading habits and interest.

How Big Data Makes Music Listening and Buying a Two Way Street

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The streaming model of music opens up the proverbial information gates to those interested in listening to the big data. Thanks to the power provided by programs like OLAP on Hadoop, data including who, how, when, and where everyone is listening to music is now available. Big Data makes it possible to understand both the customers and their interests, and also the music and how it relates to other music. Using this technology, algorithms are able to predict what musical tracks listeners would like to hear or buy next, and even to predict what particular music will be popular in the future.

It works like this. Music is digitizable, which means that it can be tangibly analyzed and measured with sufficient computing power and Big Data. A project called the Musical Genome Project that began in 1999 structured the data of music manually and with computer automated algorithms. With 450 different data points gathered on all 30 million songs in the database, they have been able to compare tracks against each other and make algorithmic decisions about what other specific musical tracks the listener will want to hear next, and also in the future. Pandora developed this groundbreaking Big Data-powered musical project and prospered for years as a result with their market-leading Pandora streaming music offering. (https://www.pandora.com/about/mgp)

Pandora’s long-term rival Spotify has furthered this technology another step. By purchasing The Echo Nest and its technology, they are able to perform this musical data analysis with an almost entirely automated protocol. Besides the useful process of working with powerful algorithms to deconstruct, analyze, and categorize music, it also crawls through the Internet to gather information on bands and artists and their recordings to consider in the analytics.

Using Big Data to Predict the Future Direction of Music

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Predicting the future is the name of the game in music. This is not just about what the listener wants to hear and download next, but more importantly what he or she will like in the future. The next hit band, artist, and song may be discovered by this all-important ability of Big Data.

Already at the University of Antwerp in Belgium, researchers have demonstrated that an algorithm they created can forecast with relative accuracy the number position of where various dance records will finish on the chart Billboard Dance Singles. Using its potent analysis of every record that charted from the years 1985 to 2014, Big Data took this thirty years of musical interest to come up with a forecast for the records that would chart in the top 10 for 2015 with minimally 65% accuracy. For seven of the charting 10, the algorithm demonstrated 70% certainty for which of them would achieve this coveted status.

In Conclusion

This speaks volumes for the future decisions of which artists and bands will receive the nod for having records made, released, and marketed by the major players in the music industry. Thanks to the Internet, unheard of artists are now able to build a fan base, then perform, and even sell their music online. Soon these algorithms will be predicting which artists should be backed and become the next big stars. Look out world; Big Data is about to become the next huge hit artists’ big boss.