The Practitioner's Guide to Data Quality Improvement

Nonfiction, Computers, Database Management, Data Processing, General Computing
Cover of the book The Practitioner's Guide to Data Quality Improvement by David Loshin, Elsevier Science
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Author: David Loshin ISBN: 9780080920344
Publisher: Elsevier Science Publication: November 22, 2010
Imprint: Morgan Kaufmann Language: English
Author: David Loshin
ISBN: 9780080920344
Publisher: Elsevier Science
Publication: November 22, 2010
Imprint: Morgan Kaufmann
Language: English

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.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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