A Practitioner's Guide to Data Governance
A Case-Based Approach
Published on 8. July 2020
Book
Paperback/Softback
248 pages
978-1-78973-570-3 (ISBN)
Description
Data governance looks deceptively simple on paper. In reality, it is complex. And it is increasingly recognized as a key foundational element necessary to advance analytics and improve operations for organizations of all types across industry.
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. Using case studies, the authors provide insight into how to address the myriad of data governance challenges facing organizations today, with useful and sensible actions and practices. The chapters focus on filling in the blanks of other data governance information, as well as providing both basic and forward-thinking suggestions for some of today's greatest challenges. It is peppered throughout with practical tips for data strategy, data literacy, and data quality.
If you are new to data governance, or a seasoned practitioner looking to understand how to better address new issues, this book can help guide you through core elements such as communication, culture, and change management.
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. Using case studies, the authors provide insight into how to address the myriad of data governance challenges facing organizations today, with useful and sensible actions and practices. The chapters focus on filling in the blanks of other data governance information, as well as providing both basic and forward-thinking suggestions for some of today's greatest challenges. It is peppered throughout with practical tips for data strategy, data literacy, and data quality.
If you are new to data governance, or a seasoned practitioner looking to understand how to better address new issues, this book can help guide you through core elements such as communication, culture, and change management.
More details
Language
English
Place of publication
Bingley
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 198 mm
Width: 129 mm
Thickness: 14 mm
Weight
268 gr
ISBN-13
978-1-78973-570-3 (9781789735703)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
07/2020
1st Edition
Emerald Publishing Limited
€41.99
Available for download
Persons
Uma G. Gupta, Ph.D., is the Director of Business Analytics at the University of South Carolina at Upstate. Author of more than seventy papers, four textbooks in information technology, and editor of a book on testing expert systems, Uma is frequently a keynote speaker on the impact of technology on personal and organizational productivity. She is the Founder of a non-profit that helps school children and families in poverty.
Sandra "San" Cannon, Ph.D., is the first Chief Data Officer at the University of Rochester. She is responsible for the University's enterprise-wide data strategy, data policy and process development, and data support services. In addition, she teaches data science courses and conducts research on data organization and dissemination, data quality metrics and outcomes, research support processes, and applications of data science techniques. Prior to joining the University, San worked in data management and analytics in the Federal Reserve System for more than 20 years.
Sandra "San" Cannon, Ph.D., is the first Chief Data Officer at the University of Rochester. She is responsible for the University's enterprise-wide data strategy, data policy and process development, and data support services. In addition, she teaches data science courses and conducts research on data organization and dissemination, data quality metrics and outcomes, research support processes, and applications of data science techniques. Prior to joining the University, San worked in data management and analytics in the Federal Reserve System for more than 20 years.
Content
Chapter 1. Foundations of Data Governance Chapter 2. Impact of Organizational Culture and the Need for Change Management
Chapter 3. Communication: Key to Success
Chapter 4. Data Strategy
Chapter 5. Data Governance Frameworks
Chapter 6. Data Governance Components: Data Quality, Literacy, and Ethics
Chapter 7. Data Governance Maturity Models
Chapter 8. Summary Case Studies
Chapter 9. Detailed Case Study
Chapter 10. Execution Road Map
Chapter 3. Communication: Key to Success
Chapter 4. Data Strategy
Chapter 5. Data Governance Frameworks
Chapter 6. Data Governance Components: Data Quality, Literacy, and Ethics
Chapter 7. Data Governance Maturity Models
Chapter 8. Summary Case Studies
Chapter 9. Detailed Case Study
Chapter 10. Execution Road Map