1. The purpose of analytics is to derive competitive advantage for the organization / firm / entity.
2. Data alone does not yield competitive advantage.
3. A sequence of progressive hypothesis testing is the most efficient and effective method to derive competitive advantage from data.
4. Predicting the future requires an understanding of cause and effect.
5. Correlation is not always Causality.
6. Accuracy over Precision.
7. It is possible for there to be two optimal, equally true, answers to a problem. (And Sometimes More!) (X^2 = 4, x=-2, 2).
And what's the point of the seven axioms?
I'm stating, as clearly as possible, what I believe to be at the root of how analytics should be practiced and it should be anchored to reality. Explicit in language are values. And I'm accepting that not everybody shares my values. And that's just fine.
The second point is that I'm opting out of an Information Architecture style debate that may go on for years. There's too much data and too much opportunity out there to be expending energy on a debate that doesn't matter to anybody else outside of that debate.
The first axiom is the anchor. It anchors analytics into the real world, and since it contains the word 'purpose', I'm expecting some protest.
The second axiom is pretty clear. Data needs to be interpreted before it yields any sort of competitive advantage.
The third axiom leaves the door open for genetic algorithms. I prefer the Scientific Method as the key tool between now and then.
The fourth axiom makes the explicit link between the predictive value of analytics when it is used for prediction, and the requirement of understanding cause and effect.
The fifth axiom is on purpose.
The sixth axiom rehashes a debate that was settled long ago, but continues to be broken by some.
The seventh axiom is, I intend, to enable an analyst to 'see where somebody else is coming from'.
Well, if the Universe is, after all, what I say it is, just say.