Master Data Governance Framework

In today’s competitive business landscape, the key to success lies within the heart of your organization’s data–the Master Data. This book brings together insights and techniques needed to navigate the complex world of Master Data governance and management, and revolutionize how Master Data and information are handled within an organization.
Master Data, the backbone of every successful enterprise, encapsulates the fundamental information essential for conducting business seamlessly. At the same time, Master Data governance helps businesses stay focused on what really matters–using Master Data to grow revenue, cut hidden costs, and stay safe and compliant with regulations.
This comprehensive guide dives into practical applications, showing you how to harness the potential of your Master Data resources to fuel strategic decision making, reliable business operations, and market-driven product innovation. As companies worldwide recognize the pivotal role of Master Data in shaping their future, the demand for comprehensive, actionable guidance is greater than ever. With a wealth of non-technical illustrations, real-world examples, and practical tools, this book demystifies the complexities of Master Data governance and management.
At its core, this book introduces a proven Master Data governance framework that empowers you to take charge systematically and methodically. Whether you’re taking your first steps or you’re well-versed in Master Data governance and management, you’ll find step-by-step guidance to ensure that you’re always moving forward.
What You Will Learn
- Easily distinguish your company’s data types within its data ecosystem using icons and illustrations
- Control Master Data using a unique Master Data governance framework with three interconnected gears: Master Data, systems, and organization
- Ensure that business data needs are met using a non-technical data modelling working tool that includes the core identifiers and attributes to describe customers, products, suppliers, and more
- Create the Master Data overview using illustrated data and system landscapes, and the data flow mapping method
- Create a Master Data organization using a described and illustrated structure, roles, and meeting forums
- Design Master Data processes, procedures, and policies using concrete Master Data quality examples
- Ensure high Master Data quality and data-driven decisions to realize data value
- Select and use Master Data platforms and use AI and machine learning wisely to achieve a single source of truth
- Improve the Master Data area in system implementation using a project framework, processes, and tools
Who This Books Is For
Data professionals without a theoretical data background and who work with data daily and need a deper understandng of what data is and how to handle master data and its quality in practice; trained data professionals needing inspiration as they seek to refine their methods and strategies for managing master data tasks and initiatives in practice; and readers who want more than a theory book and need a reference book with non-technical illustrations, practical work tools and methods, and concrete examples, plus instructions that can be used directly in daily work

Peter Folmer Hansen is a Senior Business Consultant, primarily serving as a Data Analyst and Information Architect. He has extensive hands-on experience with Master Data analyses, architecture, governance, and organization and has worked for many companies with diverse data entity types and system setups. Peter has created overall data architecture with structure and overview by mapping data and its system landscape to data and process flows. He also has handled the relationships between the data and information models and domains, and he has visualized and documented tailor-made data entity models. As the responsible Master Data manager and as consultant, Peter has built Master Data organizations and governance with control over data and system ownership, where roles with tasks and responsibilities are described. He has designed data handling and maintenance processes, procedures, and guidelines that must support quality assurance and data life cycle management.