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

Anticipating leadership challenges

The time has come to present your business case to a board – a set of senior leaders who have a limited budget and what they feel is a “never-ending” set of projects trying to take up that budget.

It is a hard position for them to be in. They have to disappoint some of the presenters and deny their requests, and they know that people have worked extremely hard in most cases to produce a strong business case.

To make quality decisions and accept the projects and initiatives that will have the greatest impact on the organization, leaders have to ask challenging questions. They have to ensure assumptions are truly valid and do not “fall apart” under the slightest exploration.

This means that any presenter must expect challenges. Our intention in this section is to prepare you as well as possible for these challenges and give you the best chance of approval. We will cover the most common challenges to a data...