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


Remediation has always been one of the most challenging parts of a data quality initiative. It can be incredibly difficult to get sufficient resources to make meaningful changes to data quality scores in a reasonably short period of time. This chapter has outlined how to ensure that the resources allocated are working on what the organization believes are the key priorities and that the approach taken is the most effective possible.

This chapter has outlined how to show stakeholders the progress being made and how to tie progress to the benefits that were agreed upon in the business case chapter.

With successful remediation, you will be asked to continue your data quality initiative into previously unsupportive business areas and deliver even more benefits.

To sustain business benefits, it is critical to make permanent changes to the way the organization manages its data and to embed further data quality improvement into the fabric of its business processes. The next...