Beyond Big Data : Using Social MDM to Drive Deep Customer Insight (Ibm Press)

Beyond Big Data : Using Social MDM to Drive Deep Customer Insight (Ibm Press)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 234 p.
  • 言語 ENG
  • 商品コード 9780133509809
  • DDC分類 005

Full Description


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

Contents

Preface xviiiChapter 1 Introduction to Social MDM 1Definition of Social MDM 1Customer Insight and Opportunities with Social Data 2Product Insight and Opportunities with Product Reviews 3Traditional Master Data Management 4Master Data Defined 5Master Data Management-Today 8Business Value of Traditional MDM 10Customer Service 11Marketing and Targeted Product Offers 11Compliance 11Hidden IT Costs 11Case Study: Financial Institution 11Social MDM 13Data Distillation 14Profile Linking 16Available Throughout the Enterprise 16Governance 16Business Value of Social MDM 16Conclusion 17References 17Additional Reading 17Chapter 2 Use Cases and Requirements for Social MDM 19Business Value of Social MDM-Use Cases and Customer Value 19Improved Customer Experience Use Cases 20Improved Target Marketing Use Cases 26Underlying Capabilities Required for Social MDM 30Cultural Awareness Capabilities for Social MDM 30Locale, Location, and Location Awareness in Social MDM 32Advanced Relationships in Social MDM 34Person-to-Person Relationships 35Person-to-Product Relationships: Sentiment 37Person@Organization: The Social MDM-Driven Evolution of the B2B Business Model 40Conclusion 43References 43Chapter 3 Capability Framework for Social MDM 47Introduction 47Data Domains 49Differences Between Metadata, Reference Data, and Master Data 53Embedding of the Social MDM RA in Enterprise Architecture 57Capability Framework 58Insight 60Information Virtualization 61Information Preparation 64Information Engines 65Deployment 73Information Governance 74Server Administration 76Conclusion 78References 78Chapter 4 Social MDM Reference Architecture 81Introduction 81Architecture Overview 81MDM as Central Nervous System for Enterprise Data 82MDM: Architecture Overview 83Component Model 87Component Relationship Diagram from an Enterprise SOA Perspective 88Component Relationship Diagram for Social MDM from an Information Architecture Perspective 89Component Interaction Diagram 91Subject-Oriented Integration 94Conclusion 95References 95Chapter 5 Product Capabilities for Social MDM 97Social Master Data Management (MDM) 99Master Data Governance and Data Stewardship 100Probabilistic Matching Engine (PME) 102Social MDM Matching 104InfoSphere BigInsights Architecture 106Connectivity, Integration, and Security 108Infrastructure 112Analytics and Discovery 115InfoSphere MDM and BigInsights Integration 119IBM Watson Explorer Integration with BigInsights and Streams 120Trusted Information Integration 121InfoSphere Information Server 122InfoSphere DataStage Balanced Optimization for Hadoop 124Real-Time Data Processing 125Pervasive Analytics Capabilities 127References 129Chapter 6 Social MDM and Customer Care 133Gauging Social Media Data 133Customer Centricity 135Moving Toward Social Customer Centricity 135Social Customer Care Reference Model 136Customer Lifetime View 140Next Best Action (NBA) 142NBA Technology Components 143NBA Solution Architecture 143Sentiment Analytics 147Scope of Sentiment Analytics 147Solution Capabilities 148MDM and Sentiment Analytics Scenario 148Social Influencer Determination 150Solution Capabilities 151Key Concepts and Methodology 152Social Network Analytics 154Types of Social Networks 154Insight Derived from Social Networks 157Trustworthiness of Social Media for Customer Care 158References 161Chapter 7 Social MDM and Marketing 165Social Media Marketing and the Role of MDM 166Social Media-Enabled Marketing Campaigns 169Contextual Marketing: Location and Time 172Social Media Marketing 173Mobile Marketing 176Viral Marketing 178Interest Groups 184Summary 187References 188Chapter 8 Mobile MDM 191Evolution of Interaction with Consumers 191Master Data and the Mobile Revolution 193Combining Location and Sensor Data with Master Data 193Empowering Knowledge Workers on the Go: Data Stewardship 195IT Impact of Mobile MDM 195Architecture Overview for Mobile MDM in the Banking Industry 196IBM MobileFirst 197Mobile Banking Applications 198IT Impact of a Mobile Channel 200Security 204Conclusion 204References 205Chapter 9 Future Trends in MDM 207Entity Resolution and Matching 208Semantic MDM 209Ethics of Information 214Explore and Analyze 219Decide and Act 220An Ethical Framework 221Conclusion 223References 223Index 225

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