Does data have a purpose?

We continually move towards better data-led decisions; however, we can easily ask our dataset’s the wrong question. Without understanding “What is the purpose of data” on which we are basing decisions and judgements, it is easy to get an answer that is not in the data. How can we understand if our direction, Northstar or decision is a good one? Why am I interested in this? I am focusing on how we improve governance and oversight in a data-led world.

I wrote a lengthy article on Data is Data. It was a kickback at the analogies that data is oil, gold, labour, sunlight — data is not. Data is unique; it has unique characteristics. That article concluded that the word “Data” is also part of the problem, but we should think of data as if discovering a new element with unique characteristics.

Data is a word, and it is part of the problem. Data doesn’t have meaning or shape, and data will not have meaning unless we can give it context. As Theodora Lau eloquently put it; if her kiddo gets 10 points in a test today (data as a state), the number 10 has no meaning, unless we say, she scored 10 points out of 10 in the test today (data is information). And even then, we still need to explain the type of test (data is knowledge) and what to do next or how to improve (data is insights). Each of these is a “data” point, and we don’t differentiate the use of the word “data” in these contexts.

Data’s most fundamental representation is “state” where it represents the particular condition something is in at a specific time. I love Hugh’s work @gapingvoid (below) representation Information is knowing that there are different “states” (on/off). Knowledge is finding patterns and connections. Insight knows comparatives to state. Wisdom is the journey. We live in the hope that the data we have will have an impact.

For a while, the data community has rested on two key characteristics of data: non-rivalrous (which plays havoc with our current understanding of ownership) and non-fungible (which is true if you assume that data carries information.) Whilst these are both accurate observations; they are not that good as universal characteristics.

• Non-rivalrous. Economists call an item that can only be used by one person at a time as “rivalrous.” Money and capital are rivalrous. Data is non-rivalrous as a…