The Practitioner's Guide to Data Quality Improvement

Häftad, Engelska, 2010

Av David Loshin, USA) Loshin, David (President, Knowledge Integrity Incorporated, Silver Spring, MD

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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.

Produktinformation

Utgivningsdatum2010-11-22
Mått191 x 235 x 22 mm
Vikt730 g
FormatHäftad
SpråkEngelska
SerieThe Morgan Kaufmann Series on Business Intelligence
Antal sidor432
FörlagElsevier Science
ISBN9780123737175

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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.

PrefaceChapter 1: Business Impacts of Poor Data QualityChapter 2: The Organizational Data Quality ProgramChapter 3: Data Quality MaturityChapter 4: Enterprise Initiative IntegrationChapter 5: Developing a Business Case and a Data Quality RoadmapChapter 6: Metrics and Performance ImprovementChapter 7: Data GovernanceChapter 8: Dimensions of Data QualityChapter 9: Data Requirement AnalysisChapter 10: Metadata and Data StandardChapter 11: Data Quality AssessmentChapter 12: Remediation and Improvement PlanningChapter 13: Data Quality Service Level AgreementsChapter 14: Data ProfilingChapter 15: Parsing and StandardizationChapter 16: Entity Identity ResolutionChapter 17: Inspection, Monitoring, Auditing, and TrackingChapter 18: Data EnhancementChapter 19: Master Data Management and Data QualityChapter 20: Bringing It All Together

"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