Do You Make Music With Data?


I'm sure there are plenty of data professionals in the All Analytics community who have spent some time working as musicians. I'm sure that some of those musicians even got paid for their work.

Credit: Pixabay
Credit: Pixabay

There always has been a bit of a bond between data and music. Even back in the pre-PC days of the 1960s computer scientists played with ways to make mainframes produce musical sounds. Then, performers used early computers -- synthesizers -- to enhance their music. Today, we hear about efforts to have computers create music, even though it usually is bad music.

But there is another bond between music and data. Consider the bumpy road that a startup band goes through to get its music on the air. Now, consider how business approaches big data. Yup, they have something in common, as Matthew Magne outlines in his TED Talk.

Magne, data management product marketer at SAS (sponsor of this site), spoke at a TED event in Wilmington, NC, and he went back to his roots as a musician to share some advice about big data strategies in Transforming Data Professionals into Data Rock Stars.

Standing isolated in the spotlight like all TED speakers, Magne couldn't resist strumming his guitar every now and then. His analogy has data points serving as notes. Musicians transform notes into songs, while data pros transform data into business insight.

But music doesn't improve without musicians gaining experience, learning by failing fast. Plus, better microphones, amplifiers, and other gear certainly help the music sound better. So it is with data. The organization needs comparable tools to help the data strategy evolve and improve.

Hint: We're talking about data and innovation strategies that rely on sandboxes and being able to fail fast, about automating manual tasks, and empowering non-technical data pros. Listen now, and consider what data has in common with music.

James M. Connolly, Editor of All Analytics

Jim Connolly is a versatile and experienced technology journalist who has reported on IT trends for more than two decades. As editor of All Analytics he writes about the move to big data analytics and data-driven decision making. Over the years he has covered enterprise computing, the PC revolution, client/server, the evolution of the Internet, the rise of web-based business, and IT management. He has covered breaking industry news and has led teams focused on product reviews and technology trends. Throughout his tech journalism career, he has concentrated on serving the information needs of IT decision-makers in large organizations and has worked with those managers to help them learn from their peers and share their experiences in implementing leading-edge technologies through publications including Computerworld. Jim also has helped to launch a technology-focused startup, as one of the founding editors at TechTarget, and has served as editor of an established news organization focused on technology startups and the Boston-area venture capital sector at MassHighTech. A former crime reporter for the Boston Herald, he majored in journalism at Northeastern University.

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Re: music
  • 9/28/2016 9:02:13 AM
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I just came across this: http://www.atlasobscura.com/articles/you-can-now-listen-to-the-first-computergenerated-music-ever?utm_source=twitter&utm_medium=atlas-page

Computer-generated music actually dates bakc to 1951, the work of  Alan Turing. You can hear a recording of it at https://soundcloud.com/guardianaustralia/first-ever-recording-of-computer-music 

Re: Parallesl and intersections
  • 9/9/2016 10:50:06 AM
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The analogy might break down when data scientists expect to get all their songs (or at least one Hit) to get played on the radio. In the music trade there's always the matter of luck, and big money for promotions. And a very competitive music field where's there so many out of work musicians. I wonder if that might apply to data scientists if and when the market becomes very competitive.

Re: Sonification
  • 9/1/2016 1:27:10 PM
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@sgreene123. That's an amazing story about sonifying the stars. Thanks for sharing.

Re: Sonification
  • 9/1/2016 8:57:10 AM
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@sgreene123, that is an amazing story.  Add me to the list of people who will be watching her TED talk.  Unconventional methods usually produce unconventional results and it sounds like she has had some great results. 

Re: Parallesl and intersections
  • 8/31/2016 10:46:03 PM
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Sane IT that's why the research indicates that playing an instrument influences math skills! I absolutely see the correlation.

Re: Sonification
  • 8/31/2016 4:39:45 PM
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Great Pierre! I think you will thoroughly enjoy!

Best regards,

Steve

Re: Sonification
  • 8/31/2016 4:38:13 PM
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Will do - would love to learn more. I am always fascinated by the stories on TED, and hers sounds extra-so! 

Re: Parallesl and intersections
  • 8/31/2016 4:36:22 PM
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Very good point about math and music. I had not heard of Circle of Fifths, but will look it up and learn more.

Sonification
  • 8/31/2016 3:42:37 PM
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I am proud to be a personal friend of Dr. Wanda Diaz. If you wish to know more about her, please check her out on TED.

I met her when she was doing research at the Harvard Smithsonian Institute here in the Boston Area.

As an astrophysicist, during an unfortunate illness, she was left totally blind, and seemingly shut out of her life's work.

Then, using music synthesizers, she was able to take data points from graphs, and "sonify" them. Using this technique, she has been able to push the science of astrophysics forward. As a result, she was able to save her career by translating data sets into sound.

As someone who has one foot in engineering and one foot in the arts (I'm a composer by trade) I can well appreciate the many thoughtful posts here.

Re: Parallesl and intersections
  • 8/31/2016 9:21:27 AM
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I think this has big implications for the composers of the future.

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