It’s the translation that makes your data sing – what song are you singing?

Some of you probably know by now that I'm also a musician, and this includes composing for my instrumental jazz/chamber music quintet. What does this have to do with translation of your data?

When I talk about data in on the DFA mailing list, I'm usually talking about the raw ingredients that may (or may not) be translated into useful information or meaningful output via good design.

Data translation examples:

  1. The 1010101s of image files aren't useful to humans in their raw format. No information is conveyed to the viewer until the binary is translated by the computer into a picture that can be seen by eyes and processed by the brain into meaningful output.  (Sure, some exceptions with ML may challenge this notion, but hear me out).
  2. Got audio data? Same deal. The playback device has to translate the data into audio sound. Ears then translate the audio into meaningful output (perhaps music!)
  3. When I compose a new work for my quintet, it's in also in code at first and requires translation to become music or meaningful output. It's messier than this in real life, but goes something like this:
    1. Vague ideas in the composer's mind materialize into notated musical composition over days/weeks/months. This is a translation of abstract concepts into concrete ideas the composer can revisit, mature, and rework until the final composition materializes. While meaningless to the audience/listener at this stage, codifying my ideas into a musical score is a translation of abstract ideas into meaningful output for me, the composer.
    2. My composition's individual part assignments for each instrument are extracted from the full score and only then do they become ​meaningful output for the individual musicians. While I could put a full score in front of every player, this would introduce tremendous noise and difficulty for the players and would not benefit the listener. (How much noise surrounds the information your end users seek?)
    3. Performers translate individual parts of the score into audible music, or ​meaningful output. The scores are effectively meaningless to the audience/listeners.

So, my questions for you are:

Have your analytics translated the data into meaningful output for your end users?

Where could you be doing better translations?

Are you giving your musicians the full score, or just the parts they need to enable their contribution to the ensemble? (Remember: design is as much about what to take away as it is what to add).

Good luck!

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