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In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, ...
In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM.
Part I: Planning Your Customer MDM Initiative.
Chapter 1: Defining Your MDM Scope and Approach.
MDM Approaches and Architectures.
Defining the Business Case.
Selecting the Right MDM Approach.
Data Management Maturity Level.
Addressing the ROI Question.
Chapter 2: Establishing Effective Ownership.
The Question of Data Ownership.
MDM with Segmented Business Practices.
A Top-Down and Bottom-Up Approach.
Creating Collaborative Partnerships.
Can Your Current IT and Business Model Effectively Support MDM?
The Acceptance Factor.
Business Access to Data.
Coordination of MDM Roles and Responsibilities.
Chapter 3: Priming the MDM Engine.
Positioning MDM Tools.
Data Integration and Synchronization.
Data Consolidation and Segmentation.
Part II: The Implementation Fundamentals.
Chapter 4: Data Governance.
Initiating a Customer Data Governance Model.
Planning and Design.
Establishing the Charter.
Policies, Standards, and Controls.
Maintain and Improve.
Chapter 5: Data Stewardship.
From Concept to Practice.
MDM Process Core Team.
Operational Process Areas.
Chapter 6: Data Quality Management.
Implementing a Data Quality Model.
A Process for Data Quality.
Data Quality Forum (DQF).
IT Support/Data Stewards.
Establishing a Data Quality Baseline.
Data Quality Dimensions.
Entities and Attributes.
Putting It All Together.
Data Alignment and Fitness Assessment.
Data Correction Initiatives.
Chapter 7: Data Access Management.
Creating the Business Discipline.
Beyond the System Administrator.
Creating the Right Gatekeeper Model.
Access Management Requirements.
Add User Group Names.
Map Privileges to Requirement Categories.
Profiling the Data.
Implementing and Managing the Process.
Testing and Launching the Process.
Resolve Issues Immediately.
Auditing and Monitoring.
Segregation of Duty Management.
Part III: Achieving a Steady State.
Chapter 8: Data Maintenance and Metrics.
Specify, Profile, and Analyze.
Data Quality Metrics.
Chapter 9: Maturing Your MDM Model.
How to Recognize and Gauge Maturity?
Data Governance Maturity.
Data Stewardship Maturity.
Data Quality Maturity.
Data Access Management Maturity.
Part IV: Advanced Practices.
Chapter 10: Creating the Customer 360° View.
Hierarchy Management (HM).
Operational versus Analytical Hierarchies.
Single versus Multiple Hierarchies.
Number of Levels in the Customer Hierarchy.
Virtual versus Physical Customer Records.
Legal versus Non-legal Hierarchies.
The Elusive, yet Achievable, 360° Customer View.
Chapter 11: Surviving Organizational Change.
How Adaptable Is Your Customer Master Data?
Data Quality Factors.
The Change Management Challenge.
Data Governance Can Greatly Assist a Transitioning State.
Leveraging the Data Stewards and Analyst.
Adopting Best Practices.
Chapter 12: Beyond Customer MDM.
The Leading and Lagging Ends.
Technology Influence on MDM.
Overcoming the IT and Business Constraints.
Achieving an Effective Enterprise-wide MDM Model.
Where Does MDM Lead?
About the Authors.