Language Evolves, But Data Is Constant...Or Is It?

I was running this morning and went past Fairview Lane. And I thought to myself, "hmm, why would anyone name a street by essentially saying 'the view here isn't great, but it also isn't terrible!"

Of course, that's not the intent of that name. The intent is from the older definition of the word fair, which used to mean "beautiful". Words and their meanings evolve.

But data is solid. It's the most indisputable, immutable of things...right?

No. You know that's not true. First of all, there are bias and assumptions baked into every single data set. I had a great conversation about bias in data with my two Data Fundamentals Unpacked partners in crime, Robin Hunt and Gini von Courter , along with our special guest Stacey A. Gordon, MBA last month. Data is not "factual" but always based on perspective.

And data evolves, just like language. It evolves in many different ways.

For instance, back in the 16th century, when astronomy was making leaps and bounds as a formalized science, astronomers were using their eyeballs and pretty simple telescopes to literally see what they could see in the sky. Their data collection was limited in scope and accuracy. Even as recently as the early 20th century, a lot of astronomy was done using telescopes that generated photographic plates, which a human would then look at, count objects, and annotate by hand. Data was still limited in scope and accuracy. Today, telescopes produce visual (and audio and other types of) data, which is process by algorithms, as well as humans. But you know what? The data is still limited in scope and accuracy. The scope and accuracy has evolved, but it will never be complete

Our understanding of our data also evolves. During the cholera outbreaks in London in the 19th century, scientists had data about the level of disease and the associated smells in the areas most prone to disease. The smell "data" may have been more anecdotal than quantitative, but it was considered "data". And logically, scientists concluded that the miasma–the noxious air–carried the disease. But as the data evolved, and another point of view was taken, scientists realized it was the tainted water at a single water pump that was really to blame. Wait a few more years, and microscopes would identify what it was in the water that was the ultimate culprit.

There are endless examples of the constant evolution of our data and our understanding based on data. The most important thing, therefore, is to keep evolving ourselves. We need to constantly remember that we only know what we know based on the data at hand. And that data might change. Scratch that...the data WILL change.

Nothing is 100%. Nothing is permanent. We can only judge now based on the context of now...tomorrow is another day.

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