Gils Data Management: a gentle introduction – 2nd edition

Balancing theory and practice
2. Auflage 2025
ISBN: 978-94-018-1314-3
Verlag: Van Haren Publishing
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 388 Seiten

#html-body [data-pb-style=EGG8YBP]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}The overall objective of this second edition is to reaffirm that data management is an exciting and valuable capability - one that deserves dedicated time and effort. Building on the foundation of the first edition, this updated version introduces new chapters, fresh insights, and additional interviews with practitioners to reflect the evolving landscape of the field.
More specifically, the book now aims to:

Provide an enriched introduction to data management, combining core concepts with updated theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, and new real-world examples drawn from recent assignments.
Offer guidance on building effective data management capabilities, illustrated through a broader set of use cases and enriched by new practitioner stories that highlight current challenges and solutions.

The book continues to serve busy professionals actively involved in managing data, as well as Bachelor’s and Master’s students interested in the field. It remains industry-agnostic, with relevance across sectors such as government, finance, telecommunications, and more.
Intended roles include: members of data governance offices or councils, data owners, data stewards, enterprise and data architects, process managers, business analysts, and IT analysts.
The structure remains clear and accessible, divided into three main parts: theory, practice, and closing remarks. Chapters are concise and focused, with a clear separation between main text and examples. Readers familiar with a topic can easily skip ahead, while newcomers will find a smooth and engaging learning path.

Autoren/Hrsg.

Gils, Bas van

Inhaltsverzeichnis

Introduction
Data as an asset
Data management: why bother?
Positioning data management

Part I Theory

Introduction
Terminology
Data management: a definition
Types of data
Data governance
Metadata
Modeling
Architecture
Integration
Reference data
Master data
Quality
Document and content management
Risk and security
Business intelligence & analytics
Data science & AI
Technology
Data (handling) ethics & compliance

Part II Practice

Introduction
Building the business case for data management
Kick-starting data quality management
Finding data owners and data stewards
The role of training
Setting up a data management policy
Business concepts and the conceptual data model
Setting up a metadata repository
Leveraging enterprise architecture
Integration architecture
A pragmatic approach to data security
Roles in data management
Building a data management roadmap

Part III Closing remarks

Synthesis of the recommendations
Conclusion Bibliography