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Data governance = from the fundament...
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Caballero, Ismael.
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Data governance = from the fundamentals to real cases /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Data governance/ edited by Ismael Caballero, Mario Piattini.
其他題名:
from the fundamentals to real cases /
其他作者:
Caballero, Ismael.
出版者:
Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:
xxiii, 241 p. :ill. (some col.), digital ;24 cm.
內容註:
Part I: Data Governance Fundamentals -- 1. Introduction to Data Governance: A bespoke program is required for success -- 2. Data Strategy and Policies: The Role of Data Governance in Data Ecosystems -- 3. Human Resources Management and Data Governance Roles: Executive Sponsor, Data Governors, and Data Stewards -- 4. Data Value and Monetizing Data -- 5. Data Governance Methodologies: The CC CDQ Reference Model for Data & Analytics Governance -- 6. Data Governance Tools -- 7. Maturity Models for Data Governance -- Part II: Data Governance Applied -- 8. Data Governance in the Banking Sector -- 9. Data has the power to transform society -- 10. Data Governance in the insurance industry -- 11. Data Governance in the Health Sector -- 12. Data Governance in the Telco Sector.
Contained By:
Springer Nature eBook
標題:
Knowledge management. -
電子資源:
https://doi.org/10.1007/978-3-031-43773-1
ISBN:
9783031437731
Data governance = from the fundamentals to real cases /
Data governance
from the fundamentals to real cases /[electronic resource] :edited by Ismael Caballero, Mario Piattini. - Cham :Springer Nature Switzerland :2023. - xxiii, 241 p. :ill. (some col.), digital ;24 cm.
Part I: Data Governance Fundamentals -- 1. Introduction to Data Governance: A bespoke program is required for success -- 2. Data Strategy and Policies: The Role of Data Governance in Data Ecosystems -- 3. Human Resources Management and Data Governance Roles: Executive Sponsor, Data Governors, and Data Stewards -- 4. Data Value and Monetizing Data -- 5. Data Governance Methodologies: The CC CDQ Reference Model for Data & Analytics Governance -- 6. Data Governance Tools -- 7. Maturity Models for Data Governance -- Part II: Data Governance Applied -- 8. Data Governance in the Banking Sector -- 9. Data has the power to transform society -- 10. Data Governance in the insurance industry -- 11. Data Governance in the Health Sector -- 12. Data Governance in the Telco Sector.
This book presents a set of models, methods, and techniques that allow the successful implementation of data governance (DG) in an organization and reports real experiences of data governance in different public and private sectors. To this end, this book is composed of two parts. Part I on "Data Governance Fundamentals" begins with an introduction to the concept of data governance that stresses that DG is not primarily focused on databases, clouds, or other technologies, but that the DG framework must be understood by business users, systems personnel, and the systems themselves alike. Next, chapter 2 addresses crucial topics for DG, such as the evolution of data management in organizations, data strategy and policies, and defensive and offensive approaches to data strategy. Chapter 3 then details the central role that human resources play in DG, analysing the key responsibilities of the different DG-related roles and boards, while chapter 4 discusses the most common barriers to DG in practice. Chapter 5 summarizes the paradigm shifts in DG from control to value creation. Subsequently chapter 6 explores the needs, characteristics and key functionalities of DG tools, before this part ends with a chapter on maturity models for data governance. Part II on "Data Governance Applied" consists of five chapters which review the situation of DG in different sectors and industries. Details about DG in the banking sector, public administration, insurance companies, healthcare and telecommunications each are presented in one chapter. The book is aimed at academics, researchers and practitioners (especially CIOs, Data Governors, or Data Stewards) involved in DG. It can also serve as a reference for courses on data governance in information systems.
ISBN: 9783031437731
Standard No.: 10.1007/978-3-031-43773-1doiSubjects--Topical Terms:
563681
Knowledge management.
LC Class. No.: HD30.2
Dewey Class. No.: 658.4038
Data governance = from the fundamentals to real cases /
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Part I: Data Governance Fundamentals -- 1. Introduction to Data Governance: A bespoke program is required for success -- 2. Data Strategy and Policies: The Role of Data Governance in Data Ecosystems -- 3. Human Resources Management and Data Governance Roles: Executive Sponsor, Data Governors, and Data Stewards -- 4. Data Value and Monetizing Data -- 5. Data Governance Methodologies: The CC CDQ Reference Model for Data & Analytics Governance -- 6. Data Governance Tools -- 7. Maturity Models for Data Governance -- Part II: Data Governance Applied -- 8. Data Governance in the Banking Sector -- 9. Data has the power to transform society -- 10. Data Governance in the insurance industry -- 11. Data Governance in the Health Sector -- 12. Data Governance in the Telco Sector.
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This book presents a set of models, methods, and techniques that allow the successful implementation of data governance (DG) in an organization and reports real experiences of data governance in different public and private sectors. To this end, this book is composed of two parts. Part I on "Data Governance Fundamentals" begins with an introduction to the concept of data governance that stresses that DG is not primarily focused on databases, clouds, or other technologies, but that the DG framework must be understood by business users, systems personnel, and the systems themselves alike. Next, chapter 2 addresses crucial topics for DG, such as the evolution of data management in organizations, data strategy and policies, and defensive and offensive approaches to data strategy. Chapter 3 then details the central role that human resources play in DG, analysing the key responsibilities of the different DG-related roles and boards, while chapter 4 discusses the most common barriers to DG in practice. Chapter 5 summarizes the paradigm shifts in DG from control to value creation. Subsequently chapter 6 explores the needs, characteristics and key functionalities of DG tools, before this part ends with a chapter on maturity models for data governance. Part II on "Data Governance Applied" consists of five chapters which review the situation of DG in different sectors and industries. Details about DG in the banking sector, public administration, insurance companies, healthcare and telecommunications each are presented in one chapter. The book is aimed at academics, researchers and practitioners (especially CIOs, Data Governors, or Data Stewards) involved in DG. It can also serve as a reference for courses on data governance in information systems.
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