Skip to main content

Save up to 30% on Elsevier print and eBooks with free shipping. No promo code needed.

Save up to 30% on print and eBooks.

Executing Data Quality Projects

Ten Steps to Quality Data and Trusted Information (TM)

  • 1st Edition - July 11, 2008
  • Author: Danette McGilvray
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 1 2 - 3 7 4 3 6 9 - 5
  • eBook ISBN:
    9 7 8 - 0 - 0 8 - 0 5 5 8 3 9 - 4

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) presents a systematic, proven approach to improving and creating data and informati… Read more

Executing Data Quality Projects

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) presents a systematic, proven approach to improving and creating data and information quality within the enterprise.

Recent 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.

This book describes a Ten Step approach that combines a conceptual framework for understanding information quality with the tools, techniques, and instructions for improving and creating information quality. It includes numerous templates, detailed examples, and practical advice for executing every step of the approach. It allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.

The author's trademarked approach, in which she has trained Fortune 500 clients and hundreds of workshop attendees, applies to all types of data and all types of organizations.