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

Developing quantitative benefit estimates

As explained in Chapter 1, one of the most difficult challenges when getting a data quality initiative “off the ground” is quantifying the benefits. I have already said that it is not possible to identify a comprehensive set of benefits.

At the business case stage of an initiative, there are usually few (or no) data quality rules in place to measure a full population of data. This means the size of the problem is not known and therefore the benefits of fixing the problem are also not known.

On top of this, “fixing” the data quality issue does not in itself provide business benefits. The benefit is “one step removed” because the corrected data only provides benefit at the point that it is used in a successful business process or in a meeting where a better decision is made based on more complete reporting.

For anyone thinking that calculating the benefits of data quality improvement cannot be...