Opis: Beyond Big Data - Dan Wolfson, Eberhard Hechler, Martin Oberhofer

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 trendsPreface 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

Szczegóły: Beyond Big Data - Dan Wolfson, Eberhard Hechler, Martin Oberhofer

Tytuł: Beyond Big Data
Autor: Dan Wolfson, Eberhard Hechler, Martin Oberhofer
Producent: IBM Press
ISBN: 9780133509809
Rok produkcji: 2014
Ilość stron: 272
Oprawa: Miękka
Waga: 0.44 kg

Recenzje: Beyond Big Data - Dan Wolfson, Eberhard Hechler, Martin Oberhofer