Generally accepted principles and terminology of data quality

Data quality as a recognized discipline has been around for a long time. Many organizations and individuals have developed methodologies that have developed our collective thinking and improved outcomes. This section aims to lay out the recognized principles and explain the terminology that every seasoned data quality professional should understand.

Naturally, this section builds on the work of many data governance experts, and there are many references to other existing content, particularly DAMA International (https://www.dama.org/cpages/home). Having said this, the section also includes my own interpretation and views on these accepted concepts as well as practical examples to bring them to life. The first part of this section outlines the basic concepts of data quality.

The basic terms of data quality defined

In Chapter 1, I outlined in detail what is meant by “bad data” and the impacts of bad...