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Record Nr. |
UNINA9910713830103321 |
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Autore |
Hopper Mary Anne |
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Titolo |
Practitioner's guide to operationalizing data governance / / Mary Anne Hopper |
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Pubbl/distr/stampa |
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Wiley-Blackwell |
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Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023] |
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©2023 |
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ISBN |
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1-119-85145-9 |
1-119-85146-7 |
1-119-85143-2 |
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Descrizione fisica |
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1 online resource (243 pages) |
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Collana |
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Wiley and SAS business series |
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Disciplina |
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Soggetti |
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Database management |
Management information systems - Management |
Data integrity |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover -- Title Page -- Copyright Page -- Contents -- Acknowledgments -- Chapter 1 Introduction -- Intended Audience -- Experience -- Common Challenge Themes -- Metadata -- Access to Data -- Trust in Data -- Data Integration -- Data Ownership -- Reporting/Analytics -- Data Architecture -- Reliance on Individual Knowledge -- Culture -- How Data Governance Can Help -- Metadata -- Access to Data -- Trust in Data -- Data Integration -- Data Ownership -- Reporting/Analytics -- Data Architecture -- Reliance on Individual Knowledge -- Culture -- Chapter 1 - Introduction Summary -- Chapter 2 - Rethinking Data Governance -- Chapter 3 - Data Governance and Data Management -- Chapter 4 - Priorities -- Chapter 5 - Common Starting Points -- Chapter 6 - Data Governance Planning -- Chapter 7 - Organizational Framework -- Chapter 8 - Roles and Responsibilities -- Chapter 9 - Operating Procedures -- Chapter 10 - Communication -- Chapter 11 - Measurement -- Chapter 12 - Roadmap -- Chapter 13 - Policies -- Chapter 14 - Data Governance Maturity -- Chapter 2 Rethinking Data Governance -- |
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Results You Can Expect With Common Approaches to Data Governance -- Here Comes Panera -- Voluntelling -- Misaligning Titles and Roles -- Project Delivery -- Tool Deployment -- What Does Work -- Adopting Consistent Definitions -- Disciplined Approach to Program Planning, Design, and Execution -- Rethinking Data Governance Summary -- Chapter 3 Data Governance and Data Management -- Results You Can Expect Focusing Purely on Data Governance or Data Management -- SAS Data Management Framework -- Data Governance -- Data Management -- Data Stewardship -- Business Drivers -- Solutions -- Methods -- Aligning Data Governance and Data Management Outcomes -- Data Architecture -- Data Administration -- Data Quality -- Data Security -- Metadata -- Reference and Master Data. |
Reporting and Analytics -- Data Life Cycle -- Misaligning Data Governance and Data Management -- Data Governance and Data Management Summary -- Chapter 4 Priorities -- Results You Can Expect Using the Most Common Approaches to Prioritization -- The List -- Level -- Volume -- Lunch -- Communication -- Emergency -- A Disciplined Approach to Priorities -- Business Value -- Achievability -- Utilizing the Model -- University - Formal Weighted Model -- Retailer - A Different Approach -- Priorities Summary -- Chapter 5 Common Starting Points -- Results You Can Expect With Too Many Entry Points -- Building a Data Portfolio -- Metadata -- Metadata Categories -- Business Metadata -- Technical Metadata -- Operational Metadata -- Data Quality -- Business Definition -- Data Element -- Data Record -- Data Movement -- Data Profiling -- Common Starting Points Summary -- Chapter 6 Data Governance Planning -- Results You Can Expect Without Planning -- Defining Objectives -- Our Objectives -- Defining Guiding Principles -- Data Governance Planning Summary -- Chapter 7 Organizational Framework -- Results You Can Expect When There Is No Defined Organizational Structure -- Organizational Framework Roles -- Support -- Oversight -- Operations -- Facilitation -- Defining a Framework -- Data Governance Steering Committee -- Program Management -- Data Owner -- Working Group -- Data Stewardship -- Data Management -- Aligning the Model to Existing Structures -- Leadership Team -- Data Manager Team -- Domain Definitions - Student -- Domain Definitions - Business Operations -- Domain Definitions - External -- Data Manager -- Data Steward -- Ad-Hoc Working Group -- Data Governance Management -- Technical Data Operations -- Aligning the Framework to the Culture -- Data Governance Steering Committee -- Data Governance Sub-Committee -- Data Governance Office -- Data Steward. |
Simplifying the Model -- Defining the Right Data Stewardship Model -- Data Domain Model -- Application Model -- Project Model -- Organizational Framework Summary -- Chapter 8 Roles and Responsibilities -- Results You Can Expect When Roles and Responsibilities Are Not Clearly Defined -- Aligning Actions and Decisions to Program Objectives -- Strategy & -- Alignment -- Establish Data Governance Program -- Data Governance Operations -- Data Architecture -- Metadata -- Data Quality -- Reference & -- Master Data -- Using a RACI Model -- Strategy & -- Alignment -- Establish Data Governance Program -- Data Governance Program Operations -- Data Architecture -- Metadata -- Data Quality -- Reference & -- Master Data -- Defining Roles and Responsibilities -- Data Governance Steering Committee -- Program Management -- Data Governance Council -- Data Owner Team -- Working Group -- Data Stewardship -- Data Management -- Naming Names -- Roles and Responsibilities Summary -- Chapter 9 Operating Procedures -- |
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Results You Can Expect Without Operating Procedures -- Operating Procedures -- Data Governance Steering Committee -- Data Governance Council -- Data Owner -- Data Steward Team -- Working Group -- Program Management Team -- Data Management Team -- A Simplified View of Operating Procedures -- Workflows -- Policy Development -- Data Issue Intake -- Compliance Monitoring -- Prioritization -- Operating Procedures Summary -- Chapter 10 Communication -- Results You Can Expect Without Communication -- Communication Plan Components -- Message -- Objective -- Author(s) -- Audience -- Frequency -- Medium -- Sample Communication Plan -- Communication Summary -- Chapter 11 Measurement -- Results You Can Expect Without Measurement -- What Measurements to Define -- Program Scorecard - A Starting Point -- Data Governance Participation. |
Data Governance Program Milestones -- Policy Compliance -- Program Scorecard Sample -- Measurement Summary -- Chapter 12 Roadmap -- Results You Can Expect Without a Roadmap -- First Step in Defining a Roadmap: Implementing Your Framework -- Defining a Roadmap -- Workstreams -- Launch Data Governance -- Data Warehouse Program Management -- Data Architecture -- Metadata -- Data Quality -- Data Management -- Formality First or Save it For Later? -- Critical Success Factors -- Roadmap Summary -- Chapter 13 Policies -- Results You Can Expect Without Policies -- Breaking Down a Policy -- Policy -- Procedure -- Standard -- Best Practice -- Data Management -- Contents of a Policy -- Policy Example - Metadata -- Name -- Policy Purpose -- Policy Objectives -- Policy Statement -- Attendant Procedures and Standards -- Metadata Collection Standard Template -- Scope/Affected Area(s) -- Roles and Responsibilities -- Compliance -- Effective Date -- Maintenance and Review -- Policy Example - Data Quality -- Policy Purpose -- Policy Objectives -- Policy Statement -- Procedures -- Standards -- Scope/Affected Area(s) -- Roles and Responsibilities -- Policy Summary -- Chapter 14 Data Governance Maturity -- Results You Can Expect With Maturity -- Data Governance Maturity Cycle -- Stage 1 - Define Program -- Stage 2 - Identify Challenges -- Stage 3 - Develop Policy -- Stage 4 - Policy Execution -- Stage 5 - Monitor and Communicate -- Maturing Your Program -- Summary -- About the Author -- Glossary of Terms -- Index -- EULA. |
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Sommario/riassunto |
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Discover what does--and doesn't--work when designing and building a data governance program. In A Practitioner's Guide to Operationalizing Data Governance, veteran SAS and data management expert Mary Anne Hopper walks readers through the planning, design, operationalization, and maintenance of an effective data governance program. She explores the most common challenges organizations face during and after program development and offers sound, hands-on advice to meet tackle those problems head-on. Ideal for companies trying to resolve a wide variety of issues around data governance, this book: Offers a straightforward starting point for companies just beginning to think about data governance ;Provides solutions when company employees and leaders don't--for whatever reason--trust the data the company has ;Suggests proven strategies for getting a data governance program that's gone off the rails back on track ;Complete with visual examples based in real-world case studies, A Practitioner's Guide to Operationalizing Data Governance will earn a place in the libraries of information technology executives and managers, data professionals, and project managers seeking a one-stop resource to help them deliver practical data governance solutions. |
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