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E-raamat: Master Data Management in Practice: Achieving True Customer MDM

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(DataFlux Corporation), Foreword by , (WellPoint, Inc)
  • Formaat: EPUB+DRM
  • Sari: Wiley Corporate F&A
  • Ilmumisaeg: 25-May-2011
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118085684
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Master Data Management in Practice: Achieving True Customer MDMSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Wiley Corporate F&A
  • Ilmumisaeg: 25-May-2011
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118085684
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Expert guidance for Master Data Management (MDM) implementation

Master Data Management in Practice provides a logical order toward planning, implementation, ongoing management, and advanced practices of Customer MDM with tables, graphs, and charts. Authors Dalton Cervo and Mark Allen show organizations how to implement Master Data Management (MDM) within their business model to create a more quality controlled approach for sucessfully managing and maintaining their customer master data. This book focuses 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.

  • Designed for data management professionals and data management consulting firms
  • Addresses the aspects of defining the underlying scope, approach, architecture, and objectives necessary for the planning and execution of a Customer MDM initiative
  • Provides the practical insight, guidance, questions, and examples related to the implementation of the four foundational Customer MDM disciplines: Data Governance, Data Stewardship, Data Quality Management, and Data Access Management

Packed with helpful tables, graphs, and charts, Master Data Management in Practice discusses current concepts and future implications associated to Customer MDM, revealing a logical order toward the planning, implementation, and ongoing management of solid Customer MDM practices.

Foreword xiii
Preface xvii
Acknowledgments xxi
Introduction 1(6)
PART I PLANNING YOUR CUSTOMER MDM INITIATIVE
7(58)
Chapter 1 Defining Your MDM Scope and Approach
9(20)
MDM Approaches and Architectures
9(11)
Analytical MDM
11(3)
Operational MDM
14(4)
Enterprise MDM
18(2)
Defining the Business Case
20(3)
Cost Reduction
21(1)
Risk Management
22(1)
Revenue Growth
23(1)
Selecting the Right MDM Approach
23(1)
Data Management Maturity Level
24(3)
Addressing the ROI Question
27(1)
Summary
27(1)
Note
28(1)
Chapter 2 Establishing Effective Ownership
29(10)
The Question of Data Ownership
29(2)
Executive Involvement
31(2)
MDM with Segmented Business Practices
31(1)
A Top-Down and Bottom-Up Approach
32(1)
Creating Collaborative Partnerships
33(5)
Can Your Current IT and Business Model Effectively Support MDM?
33(1)
The Acceptance Factor
34(1)
Business Access to Data
35(1)
Coordination of MDM Roles and Responsibilities
36(2)
Summary
38(1)
Notes
38(1)
Chapter 3 Priming the MDM Engine
39(26)
Introduction
39(1)
Positioning MDM Tools
40(2)
Data Integration and Synchronization
42(15)
Data Profiling
43(3)
Data Migration
46(9)
Data Consolidation and Segmentation
55(2)
Reference Data
57(3)
Metadata
60(3)
Summary
63(1)
Notes
63(2)
PART II THE IMPLEMENTATION FUNDAMENTALS
65(98)
Chapter 4 Data Governance
67(28)
Initiating a Customer Data Governance Model
67(2)
Planning and Design
69(16)
Establishing the Charter
70(8)
Policies, Standards, and Controls
78(7)
Implementation
85(8)
Process Readiness
85(3)
Implement
88(3)
Maintain and Improve
91(2)
Summary
93(1)
Notes
94(1)
Chapter 5 Data Stewardship
95(16)
From Concept to Practice
95(1)
People
96(11)
MDM Process Core Team
97(5)
Operational Process Areas
102(5)
Processes
107(1)
Data Caretaking
108(1)
Summary
109(2)
Chapter 6 Data Quality Management
111(30)
Implementing a Data Quality Model
111(3)
A Process for Data Quality
114(13)
Drivers
115(2)
Data Quality (DQ) Forum
117(2)
Controls/Data Governance
119(1)
Data Analysts
120(3)
Design Team
123(2)
IT Support/Data Stewards
125(1)
Metrics
126(1)
Establishing a Data Quality Baseline
127(9)
Context
127(2)
Data Quality Dimensions
129(1)
Entities and Attributes
129(3)
Putting It All Together
132(4)
Data Alignment and Fitness Assessment
136(1)
Data Correction Initiatives
137(3)
Summary
140(1)
Note
140(1)
Chapter 7 Data Access Management
141(22)
Creating the Business Discipline
141(4)
Beyond the System Administrator
142(2)
Creating the Right Gatekeeper Model
144(1)
Preparing
145(5)
Employee Data
146(1)
Access Management Requirements
146(2)
Add User Group Names
148(1)
Map Privileges to Requirement Categories
149(1)
Profiling the Data
150(2)
Implementing and Managing the Process
152(9)
Testing and Launching the Process
157(1)
Resolve Issues Immediately
157(1)
Auditing and Monitoring
158(1)
Segregation of Duty (SoD) Management
159(2)
Summary
161(1)
Notes
161(2)
PART III ACHIEVING A STEADY STATE
163(38)
Chapter 8 Data Maintenance and Metrics
165(26)
Data Maintenance
165(19)
Specify, Profile, and Analyze
167(1)
Improve
167(17)
Data Quality Metrics
184(5)
Monitors
185(2)
Scorecards
187(2)
Summary
189(1)
Note
190(1)
Chapter 9 Maturing Your MDM Model
191(10)
How to Recognize and Gauge Maturity?
191(7)
Data Governance Maturity
193(1)
Data Stewardship Maturity
194(1)
Data Quality Maturity
195(2)
Data Access Management Maturity
197(1)
Summary
198(1)
Notes
199(2)
PART IV ADVANCED PRACTICES
201(36)
Chapter 10 Creating the Customer 360° View
203(12)
Introduction
203(3)
Hierarchy Management (HM)
206(7)
Operational versus Analytical Hierarchies
207(1)
Single versus Multiple Hierarchies
208(1)
Number of Levels in the Customer Hierarchy
209(2)
Virtual versus Physical Customer Records
211(1)
Legal versus Non-Legal Hierarchies
212(1)
The Elusive, yet Achievable, 360° Customer View
213(1)
Summary
213(2)
Chapter 11 Surviving Organizational Change
215(10)
How Adaptable Is Your Customer Master Data?
215(1)
Data Quality Factors
216(3)
Data Completeness
217(1)
Data Consistency
217(1)
Data Integrity
218(1)
The Change Management Challenge
219(3)
Data Governance Can Greatly Assist a Transitioning State
220(1)
Leveraging the Data Stewards and Analysts
220(2)
Adopting Best Practices
222(1)
Summary
222(3)
Chapter 12 Beyond Customer MDM
225(12)
The Leading and Lagging Ends
225(1)
Technology's Influence on MDM
226(2)
Overcoming the IT and Business Constraints
228(2)
Achieving an Effective Enterprise-Wide MDM Model
230(3)
Where Does MDM Lead?
233(2)
Summary
235(1)
Note
236(1)
Recommended Reading 237(2)
About the Authors 239(2)
Index 241
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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