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

Preventing issue re-occurrence

In Chapter 8, we provided a table of the key governance activities that are required during the remediation phase. The last of these was the prevention of re-occurrence. This starts in the remediation phase but becomes a key activity as your initiative transitions from a project-style activity to a business-as-usual activity.

If remediation is completed as a one-off activity without understanding why the data quality issue arose in the first place, the issues will simply re-occur in the future. The remediation effort will eventually need to be repeated. It is possible to avoid this with a proper understanding of the cause, a change in systems or processes to resolve that cause, and then ongoing monitoring to ensure the quality remains sufficiently high.

One organization that I worked with used a Big Four consulting firm to complete and correct their supplier data. The work was completed on an entirely manual basis (from detecting the issues to remediation...