Chapter 4.1

A Brief History of Big Data

Abstract

There are different definitions of big data. The definition used here is that big data
encompasses a lot of data, is based on inexpensive storage, manages data by the “Roman
census” method, and stores data in an unstructured format. There are two major types of
big data—repetitive big data and nonrepetitive big data. Only a small fraction of
repetitive big data has business value, whereas almost all of nonrepetitive big data has
business value. In order to achieve business value, the context of data in big data must be
determined. Contextualization of repetitive big data is easily achieved. But
contextualization of nonrepetitive data is done by means of textual disambiguation.

Keywords

Big data; Roman census method; Unstructured data; Repetitive data; Nonrepetitive data;
Contextualization; Textual disambiguation

There are many ways to describe history. When it comes to describing parts of the history
of computer science, one way to describe it is in terms of technology. Another way to
describe it is in terms of organizations.

The way that we will describe a brief history of big data is from a marketing standpoint.

An Analogy—Taking the High Ground

Using an analogy to describe the history of big data and how things came to be is useful.
The analogy that will be used is the military tactic of taking the high ground.

Fig. 4.1.1 shows that military tacticians have long known that taking the high ground was
important in any military conflict.

Chapter 4.1: A Brief History of Big Data