In January of 1610, Galileo Galilei turned a new 30x telescope of his own manufacture to the heavens, specifically to view the “wandering star” Jupiter. What he saw must have been astonishing, even if he was already looking for evidence to support the heliocentric model of the solar system. Three small “stars” that had previously never been seen were in a line through Jupiter, and, as he continued his nightly observations, these tiny stars moved. One night, he saw one star disappear and on another night, reappear. These tiny stars appeared to be orbiting Jupiter.

Today, we might have a hard time appreciating just how shocking this must have been to people at the time. Everybody knew that the stars didn’t move and that the planets wandered around the sky, and everybody knew that the Earth was still and that the Sun and all the planets orbited it - you just had to look outside every day to know that. It would have been easy for Galileo to create, as many others had done, an ever more complicated model of the solar system that accounted for these little stars orbiting the big planet. But Galileo felt this confirmed his earlier suspicion that the Earth orbited the Sun. Even more remarkably, he brought together mathematics and observation to create the core of what we consider the scientific method today.

This isn’t a book about Galileo or astronomy, but about business and data. However, the history of Galileo can inform us as we pass through what is likely to be an even more disruptive societal change than that of popularizing heliocentrism. The advent of “Big Data” offers possibilities and dangers unlike anything we have seen before in the world of science or business.

Why did Galileo make his revolutionary discovery?

It wasn’t the hardware. Lenses had been around for quite some time. The oldest lens dates back to the 7th century BCE and the concept of magnification had been mentioned a century earlier. Spectacles had been in use about three hundred years before Galileo’s discoveries. He wasn’t even the first person to invent the telescope, although during his lifetime, his were among the finest.

For our purposes, it seems to have been due to three things: knowing where to look, having a good-enough tool to look there, and doing it first. Pointing a telescope anywhere at the sky at that time resulted in many discoveries, but pointing a telescope of sufficient power at Jupiter led to the discovery that, in at least a poetical sense, moved the world.

Why was it Galileo who made his discovery, and not someone else?

Frankly, it seems like there were many other people who could have done the same thing within a few years, and some of those would even have come to the correct conclusion about heliocentrism. The problems with the Ptolemaic system of the Earth at the center of the universe was well-known amongst natural philosophers and had been for quite some time. Galileo was a genius polymath, but the consequence of moons orbiting Jupiter did not take a genius to figure out: If there were moons that orbited other planets, perhaps our planet also orbited the sun. Although it may be banal, it is probably because he was the first and had a framework to make conclusions on what he saw rather than on what he expected to see. Tycho Brahe had made a model that was mathematically consistent with the rich observations he had made over the years, called the Tychonic system. In this system, the Sun orbited the Earth daily, and all the other planets orbited the Sun. This interpretation was more appealing to him both on the philosophical and commonsensical levels and was completely consistent mathematically with the heliocentric system. It was really not until early in the 18th century that more precise measurements showed the stars’ apparent motion through the year and back again (parallax) that required the Tychonic system to be fully abandoned.

There is another thing that could have allowed for a sooner choice between the geocentric and heliocentric models. This was Sir Isaac Newton’s formulation of his law of universal gravitation in 1687. The one thing that the Tychonic system was completely lacking was a naturalistic explanation as to why the Sun moved around the Earth. What is relevant for our discussion here is that Galileo arrived at the right conclusion even while lacking high-precision observations and a fundamental explanatory theory. This perfectly describes the current state of big data in business and is why we believe we can learn from Galileo today.

What does that have to do with business and big data?

When a person or an organization uses the right tools the right way in order to accomplish something for which they were designed, they have a chance at success. If they do it first, they tend to set the pattern for those who follow. Today, we have a very powerful tool called big data that is being used in many different ways. But we contend that if you don’t know the purpose behind collecting huge amounts of data, “knowing where to look” if you will, it is unlikely that you are collecting the right data or using it in a way that will result in the most benefit for the organization. We will show you how to do both by describing a system that will point you in the right direction, and that will be designed to be good enough to see that which you are looking for. As far as being first, well that depends on if you or your competitors are reading this…

Chances are that if you are reading this book, you have certain expectations of what data can do for you. If you are working in for-profit sector, you would not object to making money. If you are in the non-for-profit or government sector, you are hoping to make a difference – the most good for the resources expended. This book will help you use data to do both.

But let’s first start by dispelling a common myth. What you have been told can probably be summarized as:

Data + Data Science = $

This is partially true. Actually, in at least one situation that is completely true - if “$” stands for cost, you can rest assured that most certainly those systems (and the people knowing how to operate them) will come with significant cost.

However, if you want “$” to stand for profit, the equation looks somewhat different:

Data + Data Science + Business Insight = Profit

This book is about how to achieve profit by linking the business and data sides of an organization.

In order to marry these, up to now, apparently separate disciplines, we are going to do two things.

First, we will present a process that will allow you to determine the “human scale” aspects of the business – what does the organization’s leadership want the business to do and be – and turn these into an integrated set of metrics across the organization that will enable it to do so. Without this, your big data systems will likely be answering the wrong questions.

However, even with good insight into what the business is supposed to do, if you don’t have data, you can’t make decisions that allow you to do it. What makes this book timely is that there is now the opportunity to collect data that is fundamentally different from what we have been used to for generations and so requires fundamentally different systems for using such data to inform business decisions. We will also explore the concept of being “right enough” and how being first is becoming an important requirement for success.

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