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

Book description

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

  • Table of contents

    1. About This eBook
    2. Title Page
    3. Copyright Page
    4. Dedication page
    5. Contents
    6. Foreword I
    7. Foreword II
    8. Preface
      1. What Is This Book About?
      2. Who Should Read This Book
      3. What You Will Learn
      4. How to Read This Book
      5. Conventions
    9. Acknowledgments
    10. About the Authors
    11. 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
      2. Traditional Master Data Management
        1. Master Data Defined
        2. Master Data Management—Today
      3. Business Value of Traditional MDM
        1. Customer Service
        2. Marketing and Targeted Product Offers
        3. Compliance
        4. Hidden IT Costs
        5. Case Study: Financial Institution
      4. Social MDM
        1. Data Distillation
        2. Profile Linking
        3. Available Throughout the Enterprise
        4. Governance
      5. Business Value of Social MDM
      6. Conclusion
      7. References
      8. Additional Reading
    12. Chapter 2. Use Cases and Requirements for Social MDM
      1. Business Value of Social MDM—Use Cases and Customer Value
        1. Improved Customer Experience Use Cases
        2. Improved Target Marketing Use Cases
      2. Underlying Capabilities Required for Social MDM
        1. Cultural Awareness Capabilities for Social MDM
        2. Locale, Location, and Location Awareness in Social MDM
      3. Advanced Relationships in Social MDM
        1. Person-to-Person Relationships
        2. Person-to-Product Relationships: Sentiment
        3. Person@Organization: The Social MDM–Driven Evolution of the B2B Business Model
      4. Conclusion
      5. References
    13. Chapter 3. Capability Framework for Social MDM
      1. Introduction
      2. Data Domains
        1. Differences Between Metadata, Reference Data, and Master Data
      3. Embedding of the Social MDM RA in Enterprise Architecture
      4. Capability Framework
        1. Insight
        2. Information Virtualization
        3. Information Preparation
        4. Information Engines
        5. Deployment
        6. Information Governance
        7. Server Administration
      5. Conclusion
      6. References
    14. Chapter 4. Social MDM Reference Architecture
      1. Introduction
      2. Architecture Overview
        1. MDM as Central Nervous System for Enterprise Data
        2. MDM: Architecture Overview
      3. Component Model
        1. Component Relationship Diagram from an Enterprise SOA Perspective
        2. Component Relationship Diagram for Social MDM from an Information Architecture Perspective
      4. Component Interaction Diagram
      5. Subject-Oriented Integration
      6. Conclusion
      7. References
    15. Chapter 5. Product Capabilities for Social MDM
      1. Social Master Data Management (MDM)
        1. Master Data Governance and Data Stewardship
        2. Probabilistic Matching Engine (PME)
        3. Social MDM Matching
      2. InfoSphere BigInsights Architecture
        1. Connectivity, Integration, and Security
        2. Infrastructure
        3. Analytics and Discovery
        4. InfoSphere MDM and BigInsights Integration
        5. IBM Watson Explorer Integration with BigInsights and Streams
      3. Trusted Information Integration
        1. InfoSphere Information Server
        2. InfoSphere DataStage Balanced Optimization for Hadoop
        3. Real-Time Data Processing
      4. Pervasive Analytics Capabilities
      5. References
    16. Chapter 6. Social MDM and Customer Care
      1. Gauging Social Media Data
      2. Customer Centricity
        1. Moving Toward Social Customer Centricity
        2. Social Customer Care Reference Model
        3. Customer Lifetime View
      3. Next Best Action (NBA)
        1. NBA Technology Components
        2. NBA Solution Architecture
      4. Sentiment Analytics
        1. Scope of Sentiment Analytics
        2. Solution Capabilities
        3. MDM and Sentiment Analytics Scenario
      5. Social Influencer Determination
        1. Solution Capabilities
        2. Key Concepts and Methodology
      6. Social Network Analytics
        1. Types of Social Networks
        2. Insight Derived from Social Networks
      7. Trustworthiness of Social Media for Customer Care
      8. References
    17. Chapter 7. Social MDM and Marketing
      1. Social Media Marketing and the Role of MDM
      2. Social Media–Enabled Marketing Campaigns
        1. Contextual Marketing: Location and Time
        2. Social Media Marketing
        3. Mobile Marketing
        4. Viral Marketing
      3. Interest Groups
      4. Summary
      5. References
    18. Chapter 8. Mobile MDM
      1. Evolution of Interaction with Consumers
        1. Master Data and the Mobile Revolution
        2. Combining Location and Sensor Data with Master Data
        3. Empowering Knowledge Workers on the Go: Data Stewardship
      2. IT Impact of Mobile MDM
        1. Architecture Overview for Mobile MDM in the Banking Industry
        2. IBM MobileFirst
        3. Mobile Banking Applications
        4. IT Impact of a Mobile Channel
      3. Security
      4. Conclusion
      5. References
    19. Chapter 9. Future Trends in MDM
      1. Entity Resolution and Matching
      2. Semantic MDM
      3. Ethics of Information
        1. Explore and Analyze
        2. Decide and Act
        3. An Ethical Framework
      4. Conclusion
      5. References
    20. Index
    21. Code Snippets

    Product information

    • Title: Beyond Big Data: Using Social MDM to Drive Deep Customer Insight
    • Author(s):
    • Release date: October 2014
    • Publisher(s): IBM Press
    • ISBN: 9780133509823