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

Understanding business strategy, objectives, and challenges

The biggest mistake that can be made in a data quality initiative is focusing on the wrong data. If you fix data that does not impact a critical business process or drive important decisions, your initiative simply will not make the difference that you want it to. It could lead to the end of your work before it has had the chance to mature. Senior stakeholders have a lot of proposals competing for budget, and it is common for initiatives that do not make the right impact to lose their funding.

Focusing on the wrong data often happens when the person instigating the data quality initiative or sponsoring it has a particular background. One organization I worked with had a new data quality manager with a purchasing background. They came from a large organization with a manufacturing element, where the efficient purchasing of raw materials was make or break in terms of margin. Suppliers were managed really effectively, and...