Page 179 - Data Architecture

Chapter 4.7: Taxonomies
Chapter 4.7

Taxonomies

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

Taxonomies are classifications of information. Taxonomies play a large and important
role in the disambiguation of narrative information. Fig. 4.7.1 shows that taxonomies are
to unstructured data what the data model is to structured data.

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