Pushpak Sarkar

Data as a Service

A Framework for Providing Reusable Enterprise Data Services

• Gebundenes Buch

Produktbeschreibung

Data as a Service shows how organizations can leverage "data as a service" by providing real-life case studies on the various and innovative architectures and related patterns
Comprehensive approach to introducing data as a service in any organization
A reusable and flexible SOA based architecture framework
Roadmap to introduce 'big data as a service' for potential clients
Presents a thorough description of each component in the DaaS reference architecture so readers can implement solutions

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 368
• Erscheinungstermin: 24. August 2015
• Englisch
• Abmessung: 240mm x 161mm x 24mm
• Gewicht: 644g
• ISBN-13: 9781119046585
• ISBN-10: 1119046580
• Artikelnr.: 41607243

Autorenporträt

Pushpak Sarkar is an Executive IT Architect at New York Life Insurance, USA . The author received a bachelor's degree from Indian Institute of Technology, his master's from the University of Pennsylvania, and an MBA from FMS, University of Delhi, India. He has been running Data Management & Analysis Service Centers of Excellence (COE) at several globally renowned organizations. His professional interest lies in data management, business intelligence, and big data analytics.

Inhaltsangabe

Guest Introduction - Sanjoy Paul xiii Guest Introduction - Christopher
Surdak xv Preface (Includes the Reader's Guide) xvii Acknowledgments xxvii
Part One Overview of Fundamental Concepts 1. Introduction to DaaS 3 Topics
Covered in this Chapter 3 Data-Driven Enterprise 4 Defining a Service 6
Drivers for Providing Data as a Service 7 Data as a Service Framework: A
Paradigm Shift 12 2. DaaS Strategy and Reference Architecture 25 Topics
Covered in this Chapter 25 Enterprise Data Strategy, Goals, and Principles
26 Critical Success Factors 28 Reference Architecture of the DaaS Framework
30 How to leverage the DaaS Reference Architecture 41 Summary 41 3. Data
Asset Management 43 Topics Covered in this Chapter 43 Introduction to Major
Categories of Enterprise Data 46 Transaction Data (Includes Big Data) 54
Significance of EIM in Supporting the DaaS Program 56 Role of Enterprise
Data Architect 57 Summary 59 Part Two DaaS Architecture Framework and
Components 4. Enterprise Data Services 63 Topics Covered in this Chapter 63
Emergence of Enterprise Data Services 64 Need for an Enterprise Perspective
65 Emergence of Enterprise Data Services 66 Publication of Enterprise Data
69 Interdependencies between DaaS, EIM, and SOA 73 Case Study: Amazon's
Adoption of Public Data Service Interfaces 76 Summary 79 5. Enterprise and
Canonical Modeling 80 Topics Covered in this Chapter 80 A Model-Driven
Approach Toward Developing Reusable Data Services 81 Defining a
Standards-Driven Approach toward Developing New Data Services 82 Role of
the Enterprise Data Model 83 Developing the Canonical Model 84 Enterprise
Data Model 85 Canonical Model 85 Implementing the Canonical Model 89
Publishing Data Services with the Canonical Model as a Foundation 93
Implementing the Canonical Model in Real-life Projects 95 Data Services
Roll Out and Future Releases 97 Case Study: DaaS in Real Life,
Electronic-Data Interchange in U.S. Healthcare Exchanges 98 Summary 102 6.
Business Glossary for DaaS 103 Topics Covered in this Chapter 103 Problem
of Meaning and the Case for a Shared Business Glossary 104 Using Metadata
in Various Disciplines 106 Role of an Organization's Business Glossary 108
Enterprise Metadata Repository 113 Implementing the Enterprise Metadata
Repository 115 Metadata Standards for Enterprise Data Services 116 Metadata
Governance 121 Summary 121 7. SOA and Data Integration 123 Topics Covered
in this Chapter 123 SOA as an Enabler of Data Integration 124 Role of
Enterprise Service Bus 127 What is a Data Service? 128 Foundational
Components of a Data Service 131 Service Interface 133 Major Service
Categories 133 Overview of Data Virtualization 136 Consolidated Data
Infrastructure Platform 143 Summary 145 8. Data Quality and Standards 146
Topics Covered in this Chapter 146 Where to Begin Data Standardization
Efforts in Your Organization 150 Role of Data Discovery/Profiling to
Identify DaaS Quality Issues 152 Data Quality and the Investment Paradox
156 Quality of a Data Service 157 Setting Up Standards in a DaaS
Environment 158 Summary 163 Part Three DaaS Solution Blueprints 9.
Reference Data Services 167 Topics Covered in this Chapter 167 Delivering
Market and Reference Data Using Real-Time Data Services 169 Comparing Usage
of Reference Data Against Master Data 171 Understanding Challenges of
Reference Data Management 173 Other Reference Data Management Challenges
174 Role of Reference Data Standards and Vocabulary Management 177
Collaborative Reference Data Management Implementation Using Business
Process Management/Workflow 180 Summary 185 10. Master Data Services 187
Topics Covered in this Chapter 187 Introduction to Master Data Services 188
Pros and Cons of Master Data Services (Virtual Master Data Management) 192
Leveraging the Golden Source to Resolve Deep-Rooted Source Differences 193
Future Trends in Master Data Management Using DaaS 194 Comparing Master
Data Services Approach (Virtual) with Master Data Management Approach
Involving Physical Consolidation 196 Case Study: Master Data Services for a
Premier Investment Bank 197 Detailed Scope and Benefits 198 Proposed
Solution Architecture for Master Data Services 199 Enterprise and Canonical
Model for Master Data Management Implementation 202 Summary 208 11. Big
Data and Analytical Services 210 Topics Covered in this Chapter 210 Big
Data 212 Big Data Analytics 213 Relationship Between DaaS and Big Data
Analytics 217 Future Impact of DaaS on Big Data Analytics 220 Extending
DaaS Reference Architecture for Big Data and Cloud Services 221 Fostering
an Enterprise Data Mindset 228 Case Study: Big DaaS in the Automotive
Industry 231 Summary 233 Part Four Ensuring Organizational Success 12. DaaS
Governance Framework 237 Topics Covered in this Chapter 237 Role of Data
Governance 238 Data Governance 240 People Governance 245 Process Governance
248 Service Governance 253 Technology Governance 258 Summary 261 13.
Securing the DaaS Environment 262 Topics Covered in this Chapter 262 Impact
of Data Breach on DaaS Operations 263 Major Security Considerations for
DaaS 264 Multilayered Security for the DaaS Environment 266 Identity and
Access Management 270 Data Entitlements to Safeguard Privacy 271 Impact of
Increased Privacy Regulations on Data Providers 272 Information Risk
Management 273 Important Data Security and Privacy Regulations that Impact
DaaS 275 Checklist to Protect Data Providers from Data Breaches 277 Summary
278 14. Taking DaaS from Concept to Reality 280 Topics Covered in this
Chapter 280 Service Performance Measurement Using the Balanced Scorecard
284 Implementing the Performance Scorecard to Improve Data Services 286
Embarking on the DaaS Journey with a Vision 287 Using AGILE Principles for
New Data Services Development 290 Sustaining DaaS in an Organization: How
to Keep the Program Going 292 In Conclusion 295 Appendix A Data Standards
Initiatives and Resources 297 Appendix B Data Privacy & Security
Regulations 305 Appendix C Terms and Acronyms 309 Appendix D Bibliography
312 Index 315