The Practitioner's Guide to Data Quality Improvement (The Morgan Kaufmann Series on Business Intelligence)

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9780123737175: The Practitioner's Guide to Data Quality Improvement (The Morgan Kaufmann Series on Business Intelligence)

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.

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From the Back Cover:

Business problems are directly related to missed data quality expectations. Flawed information production processes introduce risks preventing the successful achievement of critical business objectives. However, these flaws are mitigated through data quality management and control: controlling the quality of the information production process from beginning to end to ensure that any imperfections are identified early, prioritized, and remediated before material impacts can be incurred. The Practitioner's Guide to Data Quality Improvement 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. This book shares templates and processes for business impact analysis, defining data quality metrics, inspection and monitoring, remediation, and using data quality tools. Never shying away from the difficult topics or subjects, this is the seminal book that offers advice on how to actually get the job done.

About the Author:

David Loshin is President of Knowledge Integrity, Inc., a company specializing in data management consulting. The author of numerous books on performance computing and data management, including “Master Data Management" (2008) and “Business Intelligence - The Savvy Manager’s Guide" (2003), and creator of courses and tutorials on all facets of data management best practices, David is often looked to for thought leadership in the information management industry.

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David Loshin
Editorial: ELSEVIER SCIENCE TECHNOLOGY, United States (2011)
ISBN 10: 0123737176 ISBN 13: 9780123737175
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Descripción ELSEVIER SCIENCE TECHNOLOGY, United States, 2011. Paperback. Estado de conservación: New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. 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. Nº de ref. de la librería EOD9780123737175

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David Loshin
Editorial: ELSEVIER SCIENCE TECHNOLOGY, United States (2011)
ISBN 10: 0123737176 ISBN 13: 9780123737175
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Descripción ELSEVIER SCIENCE TECHNOLOGY, United States, 2011. Paperback. Estado de conservación: New. Language: English . Brand New Book. 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. Nº de ref. de la librería AAZ9780123737175

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David Loshin
Editorial: Elsevier Science 2010-11-22, Amsterdam |London (2010)
ISBN 10: 0123737176 ISBN 13: 9780123737175
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Descripción Elsevier Science 2010-11-22, Amsterdam |London, 2010. paperback. Estado de conservación: New. Nº de ref. de la librería 9780123737175

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David Loshin
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Descripción ELSEVIER SCIENCE TECHNOLOGY, United States, 2011. Paperback. Estado de conservación: New. Language: English . Brand New Book. 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. Nº de ref. de la librería AAZ9780123737175

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Descripción 2010. PAP. Estado de conservación: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Nº de ref. de la librería TE-9780123737175

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Descripción Elsevier Science & Technology. Paperback. Estado de conservación: new. BRAND NEW, The Practitioner's Guide to Data Quality Improvement, David Loshin, Business problems are directly related to missed data quality expectations. Flawed information production processes introduce risks preventing the successful achievement of critical business objectives. However, these flaws are mitigated through data quality management and control: controlling the quality of the information production process from beginning to end to ensure that any imperfections are identified early, prioritized, and remediated before material impacts can be incurred. "The Practitioner's Guide to Data Quality Improvement" 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. This book shares templates and processes for business impact analysis, defining data quality metrics, inspection and monitoring, remediation, and using data quality tools. Never shying away from the difficult topics or subjects, this is the seminal book that offers advice on how to actually get the job done. It offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shows 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. Nº de ref. de la librería B9780123737175

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Descripción Estado de conservación: New. This item is Print on Demand - Depending on your location, this item may ship from the US or UK. Nº de ref. de la librería POD_9780123737175

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ISBN 10: 0123737176 ISBN 13: 9780123737175
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Descripción Elsevier Science & Technology, 2010. Estado de conservación: New. 2010. 1st Edition. Paperback. Business problems are directly related to missed data quality expectations. This book 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. Series: The Morgan Kaufmann Series on Business Intelligence. Num Pages: 432 pages, 42 illustrations. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 233 x 191 x 22. Weight in Grams: 816. . . . . . . Nº de ref. de la librería V9780123737175

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LOSHIN, DAVID
Editorial: Morgan Kaufmann (2010)
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Descripción Morgan Kaufmann, 2010. Paperback. Estado de conservación: NEW. 9780123737175 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Nº de ref. de la librería HTANDREE0891816

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