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Master Data Management in Practice: Achieving True Customer MDM

ISBN: 978-0-470-91055-9
272 pages
July 2011
Master Data Management in Practice: Achieving True Customer MDM (0470910550) cover image
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.
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Foreword.

Preface.

Acknowledgments.

Introduction.

Part I: Planning Your Customer MDM Initiative.

Chapter 1: Defining Your MDM Scope and Approach.

MDM Approaches and Architectures.

Analytical MDM.

Operational MDM.

Enterprise MDM.

Defining the Business Case.

Cost Reduction.

Risk Management.

Revenue Growth.

Selecting the Right MDM Approach.

Data Management Maturity Level.

Addressing the ROI Question.

Summary.

Note.

Chapter 2: Establishing Effective Ownership.

The Question of Data Ownership.

Executive Involvement.

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.

Summary.

Notes.

Chapter 3: Priming the MDM Engine.

Introduction.

Positioning MDM Tools.

Data Integration and Synchronization.

Data Profiling.

Data Migration.

Data Consolidation and Segmentation.

Reference Data.

Metadata.

Summary.

Notes.

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.

Implementation.

Process Readiness.

Implement.

Maintain and Improve.

Summary.

Notes.

Chapter 5: Data Stewardship.

From Concept to Practice.

People.

MDM Process Core Team.

Operational Process Areas.

Processes.

Data Caretaking.

Summary.

Chapter 6: Data Quality Management.

Implementing a Data Quality Model.

A Process for Data Quality.

Drivers.

Data Quality Forum (DQF).

Controls/Data Governance.

Data Analysts.

Design Team.

IT Support/Data Stewards.

Metrics.

Establishing a Data Quality Baseline.

Context.

Data Quality Dimensions.

Entities and Attributes.

Putting It All Together.

Data Alignment and Fitness Assessment.

Data Correction Initiatives.

Summary.

Note.

Chapter 7: Data Access Management.

Creating the Business Discipline.

Beyond the System Administrator.

Creating the Right Gatekeeper Model.

Preparing.

Employee Data.

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.

Summary.

Notes.

Part III: Achieving a Steady State.

Chapter 8: Data Maintenance and Metrics.

Data Maintenance.

Specify, Profile, and Analyze.

Improve.

Data Quality Metrics.

Monitors.

Scorecards.

Summary.

Note.

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.

Summary.

Notes.

Part IV: Advanced Practices.

Chapter 10: Creating the Customer 360° View.

Introduction.

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.

Summary.

Chapter 11: Surviving Organizational Change.

How Adaptable Is Your Customer Master Data?

Data Quality Factors.

Data Completeness.

Data Consistency.

Data Integrity.

The Change Management Challenge.

Data Governance Can Greatly Assist a Transitioning State.

Leveraging the Data Stewards and Analyst.

Adopting Best Practices.

Summary.

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?

Summary.

Note.

Recommended Reading.

About the Authors.

Index.

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DALTON CERVO is Senior Solutions Consultant at DataFlux Corporation, assisting customers with master data management, data governance, and data quality implementations.¿Prior to joining DataFlux, Dalton was a senior program manager at both Sun Microsystems and Oracle, leading the data quality efforts as a member of the data governance team responsible for defining policies and procedures governing the oversight of master customer data. He is an expert panelist and a featured blogger for Data Quality PRO and a contributing author in The Next Wave of Technologies: Opportunities in Chaos (Wiley).

MARK ALLEN is a Senior Consultant and Enterprise Data Governance Lead at WellPoint, Inc. Prior to joining WellPoint, Mark was a senior program manager in customer operations groups at both Sun Microsystems and Oracle. Mark has led Sun's Customer Data Governance Board and has been a member of customer advisory boards for DataFlux, Oracle, and Dun & Bradstreet, where he was a presenter and panel member for various data governance and master data management events and forums.

Please visit their website at www.mdm-in-practice.com.

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