Executing Data Quality Projects Second Edition presents a structured yet flexible approach for creating improving sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year with poor data linked to waste and inefficiency damaged credibility among customers and suppliers and an organizational inability to make sound decisions. Help is here This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques tools and instructions for practically putting the approach to work with the end result of highquality trusted data and information so critical to todays datadependent organizations. The Ten Steps approach applies to all types of data and all types of organizations forprofit in any industry nonprofit government education healthcare science research and medicine. This book includes numerous templates detailed examples and practical advice for executing every step. At the same time readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easytouse format highlighting key concepts and definitions important checkpoints communication activities best practices and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include 1 focused data quality improvement projects such as improving data used in supply chain management 2 data quality activities in other projects such as building new applications and migrating data from legacy systems integrating data because of mergers and acquisitions or untangling data due to organizational breakups and 3 ad ho