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The practitioner's guide to data quality improvement [electronic resource]

The practitioner's guide to data quality improvement [electronic resource]

자료유형
E-Book(소장)
개인저자
Loshin, David, 1963-.
서명 / 저자사항
The practitioner's guide to data quality improvement [electronic resource] / David Loshin.
발행사항
Burlington, MA :   Morgan Kaufmann,   2011.  
형태사항
1 online resource (xxiii, 398 p.) : ill.
기타형태 저록
Print version:   Loshin, David, 1963-   Practitioner's guide to data quality improvement.   Burlington, MA : Morgan Kaufmann, 2011   9780123737175   (DLC) 2010025189   (OCoLC)645889424  
ISBN
9780123737175 (electronic bk.) 0123737176 (electronic bk.) 9780080920344 (electronic bk.) 0080920349 (electronic bk.)
요약
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. 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.
일반주기
Title from e-Book title page.  
내용주기
Business impacts of poor data quality -- The organizational data quality program -- Data quality maturity -- Enterprise initiative integration -- Developing a business case and a data quality road map -- Metrics and performance improvement -- Data governance -- Dimensions of data quality -- Data requirement analysis -- Metadata and data standards -- Data quality assessment -- Remediation and improvement planning -- Data quality service level agreements -- Data profiling -- Parsing and standardization -- Entity identity resolution -- Inspection, monitoring, auditing, and tracking -- Data enhancement -- Master data management and data quality -- Bringing it all together.
서지주기
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Database management --Quality control. Databases --Quality control.
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ScienceDirect   URL
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100 1 ▼a Loshin, David, ▼d 1963-.
245 1 4 ▼a The practitioner's guide to data quality improvement ▼h [electronic resource] / ▼c David Loshin.
260 ▼a Burlington, MA : ▼b Morgan Kaufmann, ▼c 2011.
300 ▼a 1 online resource (xxiii, 398 p.) : ▼b ill.
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Business impacts of poor data quality -- The organizational data quality program -- Data quality maturity -- Enterprise initiative integration -- Developing a business case and a data quality road map -- Metrics and performance improvement -- Data governance -- Dimensions of data quality -- Data requirement analysis -- Metadata and data standards -- Data quality assessment -- Remediation and improvement planning -- Data quality service level agreements -- Data profiling -- Parsing and standardization -- Entity identity resolution -- Inspection, monitoring, auditing, and tracking -- Data enhancement -- Master data management and data quality -- Bringing it all together.
520 ▼a 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. 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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Database management ▼x Quality control.
650 0 ▼a Databases ▼x Quality control.
776 0 8 ▼i Print version: ▼a Loshin, David, 1963- ▼t Practitioner's guide to data quality improvement. ▼d Burlington, MA : Morgan Kaufmann, 2011 ▼z 9780123737175 ▼w (DLC) 2010025189 ▼w (OCoLC)645889424
856 4 0 ▼3 ScienceDirect ▼u https://oca.korea.ac.kr/link.n2s?url=http://www.sciencedirect.com/science/book/9780123737175
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 005.7406 등록번호 E14002843 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

컨텐츠정보

목차

Business impacts of poor data quality
The organizational data quality program
Data quality maturity
Enterprise initiative integration
Developing a business case and a data quality road map
Metrics and performance improvement
Data governance
Dimensions of data quality
Data requirement analysis
Metadata and data standards
Data quality assessment
Remediation and improvement planning
Data quality service level agreements
Data profiling
Parsing and standardization
Entity identity resolution
Inspection, monitoring, auditing, and tracking
Data enhancement
Master data management and data quality
Bringing it all together.

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