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)
Part 1 – Getting Started
Part 2 – Understanding and Monitoring the Data That Matters
Part 3 – Improving Data Quality for the Long Term

Embedding Data Quality in Organizations

At the end of Chapter 8, we established how to go about calculating and publicizing the benefits of the work that’s done in the organization to remediate data. This chapter is about how to make those benefits sustainable in the long term. If the organization remediates the data as a “one-off exercise,” there will be benefits, but in the medium to long term, the data will return to a low state of quality.

Essentially, sustaining the benefits comes from two areas – firstly, making changes to the way that data is collected in the first place and secondly, continuing the activities outlined in Chapters 3 to 8, but on a smaller scale, in a business-as-usual context.

I will refer regularly to the term “business as usual” throughout this chapter. The term means the day-to-day operational work to keep an organization running smoothly, excluding all project and one-off activities. For example, one of the...