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Beyond Big Data: Using Social MDM to Drive Deep Customer Insight

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Beyond Big Data: Using Social MDM to Drive Deep Customer Insight


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  • Breakthrough techniques that go beyond segmentation to deliver truly personalized experiences for every customer
  • Shows how to leverage the unprecedented wealth of customer information now available on Facebook, LinkedIn, Twitter, and other social media platforms
  • Includes cutting-edge techniques for more effective social interactions with mobile customers
  • By a team of IBM’s leading experts in Master Data Management, Big Data, and CRM/marketing analytics


  • Copyright 2015
  • Dimensions: 7" x 9-1/8"
  • Pages: 264
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-350980-X
  • ISBN-13: 978-0-13-350980-9

Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data

Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources.

In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels.

Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects.

Coverage Includes

  • How Social MDM extends fundamental MDM concepts and techniques
  • Architecting Social MDM: components, functions, layers, and interactions
  • Identifying high value relationships: person to product and person to organization
  • Mapping Social MDM architecture to specific products and technologies
  • Using Social MDM to create more compelling customer experiences
  • Accelerating your transition to highly-targeted, contextual marketing
  • Incorporating mobile data to improve employee productivity
  • Avoiding privacy and ethical pitfalls throughout your ecosystem
  • Previewing Semantic MDM and other emerging trends

Sample Content

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Beyond Big Data: Understanding Social MDM Reference Architecture

Sample Pages

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Table of Contents

Preface    xviii

Chapter 1  Introduction to Social MDM    1

Definition of Social MDM    1

Customer Insight and Opportunities with Social Data    2

Product Insight and Opportunities with Product Reviews    3

Traditional Master Data Management    4

Master Data Defined    5

Master Data Management—Today    8

Business Value of Traditional MDM    10

Customer Service    11

Marketing and Targeted Product Offers    11

Compliance    11

Hidden IT Costs    11

Case Study: Financial Institution    11

Social MDM    13

Data Distillation    14

Profile Linking    16

Available Throughout the Enterprise    16

Governance    16

Business Value of Social MDM    16

Conclusion    17

References    17

Additional Reading    17

Chapter 2  Use Cases and Requirements for Social MDM    19

Business Value of Social MDM—Use Cases and Customer Value    19

Improved Customer Experience Use Cases    20

Improved Target Marketing Use Cases    26

Underlying Capabilities Required for Social MDM    30

Cultural Awareness Capabilities for Social MDM    30

Locale, Location, and Location Awareness in Social MDM    32

Advanced Relationships in Social MDM    34

Person-to-Person Relationships    35

Person-to-Product Relationships: Sentiment    37

Person@Organization: The Social MDM–Driven Evolution of the B2B Business Model    40

Conclusion    43

References    43

Chapter 3  Capability Framework for Social MDM    47

Introduction    47

Data Domains    49

Differences Between Metadata, Reference Data, and Master Data    53

Embedding of the Social MDM RA in Enterprise Architecture    57

Capability Framework    58

Insight    60

Information Virtualization    61

Information Preparation    64

Information Engines    65

Deployment    73

Information Governance    74

Server Administration    76

Conclusion    78

References    78

Chapter 4  Social MDM Reference Architecture    81

Introduction    81

Architecture Overview    81

MDM as Central Nervous System for Enterprise Data    82

MDM: Architecture Overview    83

Component Model    87

Component Relationship Diagram from an Enterprise SOA Perspective    88

Component Relationship Diagram for Social MDM from an Information Architecture Perspective    89

Component Interaction Diagram    91

Subject-Oriented Integration    94

Conclusion    95

References    95

Chapter 5  Product Capabilities for Social MDM    97

Social Master Data Management (MDM)    99

Master Data Governance and Data Stewardship    100

Probabilistic Matching Engine (PME)    102

Social MDM Matching    104

InfoSphere BigInsights Architecture    106

Connectivity, Integration, and Security    108

Infrastructure    112

Analytics and Discovery    115

InfoSphere MDM and BigInsights Integration    119

IBM Watson Explorer Integration with BigInsights and Streams    120

Trusted Information Integration    121

InfoSphere Information Server    122

InfoSphere DataStage Balanced Optimization for Hadoop    124

Real-Time Data Processing    125

Pervasive Analytics Capabilities    127

References    129

Chapter 6  Social MDM and Customer Care    133

Gauging Social Media Data    133

Customer Centricity    135

Moving Toward Social Customer Centricity    135

Social Customer Care Reference Model    136

Customer Lifetime View    140

Next Best Action (NBA)    142

NBA Technology Components    143

NBA Solution Architecture    143

Sentiment Analytics    147

Scope of Sentiment Analytics    147

Solution Capabilities    148

MDM and Sentiment Analytics Scenario    148

Social Influencer Determination    150

Solution Capabilities    151

Key Concepts and Methodology    152

Social Network Analytics    154

Types of Social Networks    154

Insight Derived from Social Networks    157

Trustworthiness of Social Media for Customer Care    158

References    161

Chapter 7  Social MDM and Marketing    165

Social Media Marketing and the Role of MDM    166

Social Media–Enabled Marketing Campaigns    169

Contextual Marketing: Location and Time    172

Social Media Marketing    173

Mobile Marketing    176

Viral Marketing    178

Interest Groups    184

Summary    187

References    188

Chapter 8  Mobile MDM    191

Evolution of Interaction with Consumers    191

Master Data and the Mobile Revolution    193

Combining Location and Sensor Data with Master Data    193

Empowering Knowledge Workers on the Go: Data Stewardship    195

IT Impact of Mobile MDM    195

Architecture Overview for Mobile MDM in the Banking Industry    196

IBM MobileFirst    197

Mobile Banking Applications    198

IT Impact of a Mobile Channel    200

Security    204

Conclusion    204

References    205

Chapter 9  Future Trends in MDM    207

Entity Resolution and Matching    208

Semantic MDM    209

Ethics of Information    214

Explore and Analyze    219

Decide and Act    220

An Ethical Framework    221

Conclusion    223

References    223

Index    225


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