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Beyond Big Data

Using Social Mdm To Drive Deep Customer Insight

Beyond Big Data - Wolfson, Dan; Schumacher, Scott; Milman, Ivan; Hechler, Eberhard; Oberhofer, Martin - ISBN: 9780133509809
Prijs: € 33,95
Levertijd: 5 tot 15 werkdagen
Bindwijze: Boek, Paperback
Genre: Databases
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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




Titel: Beyond Big Data
auteur: Wolfson, Dan; Schumacher, Scott; Milman, Ivan; Hechler, Eberhard; Oberhofer, Martin
Mediatype: Boek
Bindwijze: Paperback
Taal: Engels
Druk: 1
Aantal pagina's: 272
Uitgever: Pearson Education (us)
Plaats van publicatie: 01
NUR: Databases
Afmetingen: 231 x 179 x 15
Gewicht: 448 gr
ISBN/ISBN13: 9780133509809
Intern nummer: 24486291

Biografie (woord)

Martin Oberhofer works as Executive Architect in the area of Enterprise Information Architecture with large clients world-wide. He helps customers to define their Enterprise Information Strategy and Architecture solving information-intense business problems. His areas of expertise include master data management based on an SOA, data warehousing, Big Data solutions, information integration, and database technologies. Martin delivers Enterprise Information Architecture and Solution workshops to large customers and major system integrators and provides expert advice in a lab advocate role for Information Management to large IBM clients. He started his career at IBM in the IBM Silicon Valley Labs in the United States at the beginning of 2002 as a software engineer and is currently based in the IBM Research and Development Lab in Germany. Martin co-authored the books Enterprise Master Data Management: An SOA Approach to Managing Core Information (IBM Press, 2008) and The Art of Enterprise Information Architecture: A Systems-Based Approach for Unlocking Business Insight (IBM Press, 2010) as well as numerous research articles and developerWorks articles. As inventor, he contributed to more than 70 patent applications for IBM and received the IBM Master Inventor title. Martin is certified by The Open Group as a Distinguished Architect and holds a master’s degree in mathematics from the University of Constance/ Germany.


Eberhard Hechler is an Executive Architect who works out of the IBM Boeblingen R&D Lab in Germany. He is currently on a three-year assignment to IBM Singapore, working as the Lead Architect in the Communications Sector of IBM’s Software Group. Prior to moving to Asia, he was a member of IBM’s Information Management “Integration and Solutions Engineering” development organization. After a two-and-a-half year international assignment to the IBM Kingston Development Lab in New York, he has worked in software development, performance optimization and benchmarking, IT/solution architecture and design, and technical consultancy. In 1992, he began to work with DB2 for MVS, focusing on testing and performance measurements. Since 1999, he has concentrated on Information Management and DB2 on distributed platforms. His main expertise includes the areas of relational database management systems, data warehouse and BI solutions, IT architectures and industry solutions, information integration, and Master Data Management (MDM). He has worked worldwide with communication service providers and IBM clients from other industries. Eberhard Hechler is a member of the IBM Academy of Technology, the IBM InfoSphere Architecture Board, and the IBM Asset Architecture Board. He coauthored the books Enterprise Master Data Management (IBM Press, 2008) and The Art of Enterprise Information Architecture: A Systems-Based Approach for Unlocking Business Insight (IBM Press, 2010). He holds a master’s degree (Diplom-Mathematiker) in Pure Mathematics and a bachelor’s degree (Diplom-Ingenieur (FH)) in Electrical Engineering (Telecommunications).


Ivan Milman is a Senior Technical Staff Member at IBM working as a security and governance architect for IBM’s Master Data Management (MDM) and InfoSphere product groups. Ivan co-authored the leading book on MDM: Enterprise Master Data Management: SOA Approach to Managing Core Information (IBM Press, 2008). Over the course of his career, Ivan has worked on a variety of distributed systems and security technology, including OS/2® Networking, DCE, IBM Global Sign-On, and Tivoli® Access Manager. Ivan has also represented IBM to standards bodies, including The Open Group and IETF. Prior to his current position, Ivan was the lead architect for the IBM Tivoli Access Manager family of security products. Ivan is a member of the IBM Academy of Technology and the IBM Data Governance Council. Ivan is a Certified Information Systems Security Professional and a Master Inventor at IBM, and has been granted 14 U.S. patents. Ivan’s current focus is the integration of InfoSphere technology, including reference data management, data quality and security tools, and information governance processes.


Scott Schumacher, Ph.D., is an IBM Distinguished Engineer, the InfoSphere MDM Chief Scientist, and a technology expert specializing in statistical matching algorithms for healthcare, enterprise, and public sector solutions. For more than 20 years, Dr. Schumacher has been heavily involved in research, development, testing, and implementation of complex data analysis solutions, including work commissioned by the Department of Defense. As chief scientist, Scott is responsible for the InfoSphere MDM product architecture. He is also responsible for the research and development of the InfoSphere Initiate matching algorithms, and holds multiple patents in the entity resolution area. Scott has a Bachelor of Science degree in Mathematics from the University of California, Davis, and received his Master of Arts and Doctorate degrees in Mathematics from the University of California, Los Angeles (UCLA). He is currently a member of the Institute for Mathematical Statistics, the American Statistical Association, and IEEE.


Dan Wolfson is an IBM Distinguished Engineer and the chief architect/CTO for the Info- Sphere segment of the IBM Information Management Division of the IBM Software Group. He is responsible for architecture and technical leadership across the rapidly growing areas of Information Integration and Quality for Big Data including Information Quality Tools, Information Integration, Master Data Management, and Metadata Management. Dan is also CTO for Cloud and Mobile within Information Management, working closely with peers throughout IBM. Dan has more than 30 years of experience in research and commercial distributed computing, covering a broad range of topics including transaction and object-oriented systems, software fault tolerance, messaging, information integration, business integration, metadata management, and database systems. He has written numerous papers, blogs, and is the coauthor of Enterprise Master Data Management: An SOA Approach to Managing Core Business Information (IBM Press, 2008). Dan is a member of the IBM Academy of Technology Leadership Team and an IBM Master Inventor. In 2010, Dan was also recognized by the Association of Computing Machinery (ACM) as an ACM Distinguished Engineer.


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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