Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)

Data quality problems cost businesses billions of dollars each year in unnecessary printing, postage, and staffing costs, in the steady erosion of an organization's credibility among customers and suppliers, and the inability to make sound decisions.

Danette McGilvray presents a systematic, proven approach to improving data quality by combining a conceptual framework for understanding information quality with techniques and instructions for improving it. The Ten Step approach applies to all types of data and to all types of organizations.

* Includes numerous templates, detailed examples, and practical advice for executing every step of The Ten Steps approach.
* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.
* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from The Ten Step methodology, and other tools and information that is available online.