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What Is Data? Part 4 : A is for ‘Another Way Of Looking At DATA’

Data. Is. Energy.

There, I said it.

Given that we are only just beginning to understand energy to describe life, it is not surprising that most people haven’t yet got their heads around the idea of energy to describe data, much less come up with methods of application and solutions that are useful. But yes. Data is energy.

If you want to find the secrets of the universe, think in terms of energy, frequency, and vibration.

–Nikola Tesla

Trust me, if energy, frequency, and vibration are good enough to find the secrets of the universe, then they stand a pretty good chance of helping us understand data. And let’s not forget that most (if not all) data is changing (vibrating), continually, continuously and constantly.

EDITOR’S NOTE: ENJOY PART 3 AND PRIOR IN THIS EXTRAORDINARY SERIES BELOW⤵︎

What Is Data? Part 3 : T is for ‘Terminating Analogies’

As I mentioned in part three, LaVonne’s musical analogy is as close to my own thinking as I have seen.  It is because music starts at ‘vibration’ and vibration is energy. Current science would suggest that energy itself is fundamental to existence and music is one specific example of energy.

Developing the Music Analogy.

Each note has its own peculiar vibration and yet is connected to the next note with a centering around that data point of a middle ‘C’ …vibrating at 261.Hz.

But music is not all vibration … there is so much more to the music than comes from that note ….

  • the order it appears compared to the note before and after to create (the melody)
  • the other notes it appears with at a moment in time (the chord)
  • how fast it is played (the measure)
  • with what rhythm (the tempo)

… not to mention the sharpening and flattering of notes, beat, pulse, harmony, tone, dynamic range, instruments used, sound settings and so on. Music is a complex language and probably a whole lot more that a musician could tell you about [1].

But in turn, what that means is that the data of the note and its associated frequency is as close to meaningless when it comes to music as knowing my birthday is next week [2].

But surround that piece of data with context, information, connections, knowledge, insights and the understanding just keeps growing and the rewards are great.”

Trouble is when it comes to data about us, the rewards are only great for ‘the other side’. The people selling. ‘Us’, the people buying – not so much. At least for now.

Data In Action Today.

Have you ever received an email making you an ‘offer you can’t refuse’? Of course, you have. All the time, right? Those emails, those alerts, those tracking ads that you are constantly presented with are examples of data tracking and data warehousing in action.

Somehow they have an email id that gets to you. They probably know your name, they might know roughly where you are’.

Dear <John>

Find out now why 55% of the people who live in <Polk County> …..

is a common email, with <variables> being pulled from some database. We are so used to those emails that it doesn’t even cross our mind as to how they do it.

But why is the sweater that they are trying to sell you blue?

Answer

(Do you remember answering those three questions to ‘help us better protect your security – and one of the questions was ‘what is your favorite color?’) Yeah, it’s not just about security, it’s profiling.

And yes … July 4th is coming up, so of course, an email about the long weekend would make sense … but it specifically suggested that it was my birthday coming up next week, how is that done?

John Philpin
John Philpinhttps://peoplefirst.business/
JOHN'S career spans 30 years, 2 continents, and organizations as diverse as Oracle, Citibank and GE. A Mathematics graduate, John moved to California in 1990. He helps technology companies create, develop and deliver their story for fund raising, market development and influencer programs. He also works with businesses to ensure they understand, and are ready, for the ever accelerating changes that technology is bringing to their industry. John is a co-founder of Expert Alumni and gleXnet and long before futurists and industry watchers were writing about the impending challenges that industries were going to be facing, they predicted a perfect storm of issues like skills gap, declining work forces, the gig economy, people trained to do work no longer needed, demographic shifts, economic and social change, market upheaval and rapidly changing ways of doing work. From the beginning they have promoted the idea that massive change was coming to how organizations should think about their workforce, with a singular focus on simplifying the interface between people and their work. Understanding the challenges ahead of the curve, the solution was built to arrive at a better understanding of the greatest restraint to business operations - competence, not capital. gleXnet provides unparalleled insights into an organizations people and operations by flipping the problem from the perspective of people, not the business.

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