Chapter 3. Capturing information in Generative Analysis

3.1 Introduction

Generative Analysis is predicated on these facts:

• Most of the information you get in analysis (especially the early stages) is informal and unstructured.

• Most of the information sources you need to perform effective analysis are subject to the forces of distortion, deletion, and generalization that we have already mentioned.

• Generative AIs need precise inputs to get meaningful outputs.

• Generative AI outputs are prone to distortion, deletion, and generalization.

In this chapter, you will learn four techniques used in Generative Analysis to capture informal unstructured information and in later chapters you will learn how to process and transform that into the precise, ...

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