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
Table of Contents:
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
About the Author :
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.
