A Practitioner's Guide to Data Governance : A Case-Based Approach.

Cover -- A PRACTITIONER'S GUIDE TO DATA GOVERNANCE -- A PRACTITIONER'S GUIDE TO DATA GOVERNANCE: A Case-based Approach -- Copyright -- CONTENTS -- 1. Foundations of Data Governance -- Introduction -- Why Invest in Data Governance? -- What Is Data Governance? -- Why Is Data Governance Difficult? -- Data Control Is Not Easy -- Data Problems Are Usually Business Problems -- Requires Hard and Soft Skills -- Current Report Card Is Not Good -- Data Governance Is Complex -- Data Governance Requires Change -- The Three Core Elements of Data Governance -- Communications -- Culture -- Change Management -- Who Is Responsible for Data Governance? -- Goals of This Book -- Questions to Consider -- 2. Impact of Organizational Culture and the Need for Change Management -- Introduction -- Organizational Culture -- Cultural Models -- Multidimensional Aspects of Culture -- Dimension One -- Dimension Two -- Mission, Adaptability, Involvement, and Values Cultural Model -- Clan, Adhocracy, Market, and Hierarchy Cultural Model -- Power, Role, Task, and Person Cultural Model -- Change Management -- Effect of Culture -- Managing the Process -- Data-driven Culture -- Conclusion -- Questions to Consider -- 3. Communication: Key to Success -- Introduction -- Foundational Work Is Necessary -- Definitions Matter -- Context Matters -- Standards Matter -- Agreement Matters -- Documentation Matters -- Politics Matter -- Emotions Matter -- When the Language Is Incomplete -- Words to Describe Data -- Words about People -- Using the Common Language -- Push versus Pull -- Oral versus Written -- Inform versus Persuade -- Repeat versus Reiterate -- Summary -- Questions to Consider -- 4. Data Strategy -- Introduction -- What Is Data Strategy? -- IT-driven Data Strategy vs Business-driven Data Strategy -- Align Data Strategy with Business Strategy -- Examples -- O-Foods -- Strategy.

Goals -- Offensive versus Defensive Strategyxiv -- Asking the Right Questions -- Quality, Quantity, and Source of Data -- Cost -- Ownership, Usage, and Accessibility -- Risks -- Data Quality and Integrity -- Communications -- Strategic -- Roles and Responsibilities -- Symptoms of a Weak or No Data Strategy -- Conclusion -- Questions to Consider -- 5. Data Governance Frameworks -- Data Governance Structure -- Chief Data Officer -- Organizational Placement -- Research versus Institutional Data -- What Does This Mean for Data Governance? -- Cloud Computing Framework -- Big Data Management Frameworks -- Conclusion -- Questions to Consider -- 6. Data Governance Components: Data Quality, Literacy, and Ethics -- Introduction -- Data Quality -- Quality Assessment Frameworks -- Completeness -- Data Literacy -- How to Use It? -- Data Ethics -- Ethics and Data Collection -- Ethics and Data Sharing -- Ethics and Analytics -- Conclusion -- Questions to Consider -- 7. Data Governance Maturity Models -- Introduction -- The Three I's of Data Assessment -- Data Integration -- Data Integrity -- Data Insights -- What Is the Purpose Behind Assessment? -- Descriptive -- Prescriptive -- Predictive -- Comparative -- A Word of Caution -- Five Levels of Maturity -- Data Maturity Models -- The Mother of All Maturity Models: The Capability Maturity Model -- The Data Management Maturity Model -- EDM Council's Data Capability Assessment Model -- IBM Maturity Model -- Conclusion -- Questions to Consider -- 8. Summary Case Studies -- Case Study #1 -- Introduction -- Data Governance Need Identified -- Process -- Current Data Governance Landscape -- Lessons Learned -- General Advice -- Case Study #2 -- Introduction -- Data Governance Need Identified -- Process -- Current Data Governance Landscape -- Lessons Learned -- General Advice -- 9. Detailed Case Study -- Introduction.

Organizational Background -- Culture -- Need for Data Governance Recognized -- Data Governance Organization - Timeline -- 2012: First-generation Data Warehouse (EDW 1.0) -- 2013-2014: Second-generation Data Warehouse (EDW 2.0) -- 2015-2016: EHR Preparation -- 2017-2018: EHR Implementation (EDW 3.0) -- 2019: Current State (Post EHR Implementation) -- Getting Started -- Results -- Lessons Learned: What Helped with Success -- Lessons Learned: What Got in the Way -- Lessons Learned: What to Do Differently -- Ongoing Challenges -- 10. Execution Roadmap -- Key Points -- Lessons Learned from the Case Studies -- Conclusion -- NOTES -- RESOURCES AND REFERENCES -- INDEX.

Data governance looks simple on paper, but in reality it is a complex issue facing organizations. In this practical guide, data experts Uma Gupta and San Cannon look to demystify data governance through pragmatic advice based on real-world experience and cutting-edge academic research.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.