Book Image

Practical Data Quality

By : Robert Hawker
Book Image

Practical Data Quality

By: Robert Hawker

Overview of this book

Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating. Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you’ll work with real-world examples and utilize re-usable templates to accelerate your initiatives. By the end of this book, you’ll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.
Table of Contents (16 chapters)
1
Part 1 – Getting Started
6
Part 2 – Understanding and Monitoring the Data That Matters
10
Part 3 – Improving Data Quality for the Long Term

The Principles of Data Quality

In Chapter 1, I described the problems that organizations experience as a result of poor data quality. From this point on, the book will focus on facing those problems and resolving them in a sustainable manner.

This chapter will outline an end-to-end approach that I recommend, and each subsequent chapter will explore all the important aspects of each stage of the approach.

First, the chapter will provide an appropriate background and context. This context will include an explanation of data governance and the role of data quality within it, an outline of the generally accepted principles and terminology associated with data quality work, and finally, details of the main stakeholders that you will need support from and how they can help.

Therefore, in this chapter, we will cover the following topics:

  • Data quality in the wider context of data governance
  • The generally accepted principles and terminology of data quality
  • Stakeholders...