Abstract

The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program.

It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.

This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers.

• Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology.
• Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics.
• Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.

"There is NOTHING like this out there that I am aware of, and certainly nothing from anyone with same stature as David Loshin."--David Plotkin, Wells Fargo Bank

"The book provides a comprehensive look at data quality from both a business and IT perspective. It does not just cover technology issues, but discusses people, process, and technology. And that is important, because this is the mix that is needed in order to initiate any type of quality improvement regimen."--Data Technology Today Blog