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Data as a Service: A Framework for Providing Reusable Enterprise Data Services

Book Description

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

    1. Guest Introduction
    2. Guest Introduction
    3. Preface (Includes the Reader's Guide)
      1. The Reader's Guide
      2. PART 1: Overview of Fundamental Concepts Includes Chapters 1 to 3
      3. PART 2: DaaS Architecture Framework and Components Includes Chapters 4 to 8
      4. PART 3: DaaS Solution Blueprints Includes Chapters 9 to 11
      5. PART 4: Ensuring Organizational Success Includes Chapters 12 to 14
      6. What Is Not Covered in this Book
    4. Acknowledgments
    5. Part One: Overview of Fundamental Concepts
      1. Chapter 1: Introduction to DaaS
        1. Topics covered in this chapter
        2. Data-Driven Enterprise
        3. Defining a Service
        4. Drivers for Providing Data as a Service
        5. Data as a Service Framework: A Paradigm Shift
      2. Chapter 2: DaaS Strategy and Reference Architecture
        1. Topics Covered in this Chapter
        2. Enterprise Data Strategy, Goals, and Principles
        3. Critical Success Factors
        4. Reference Architecture of the DaaS Framework
        5. How to leverage the DaaS Reference Architecture
        6. Summary
      3. Chapter 3: Data Asset Management
        1. Topics Covered in this Chapter
        2. Introduction to Major Categories of Enterprise Data
        3. Transaction Data (Includes Big Data)
        4. Significance of EIM in Supporting the DaaS Program
        5. Role of Enterprise Data Architect
        6. Summary
    6. Part Two: DaaS Architecture Framework and Components
      1. Chapter 4: Enterprise Data Services
        1. Topics Covered in this Chapter
        2. Emergence of Enterprise Data Services
        3. Need for an Enterprise Perspective
        4. Emergence of Enterprise Data Services
        5. Publication of Enterprise Data
        6. Interdependencies between DaaS, EIM, and SOA
        7. Case Study: Amazon's Adoption of Public Data Service Interfaces
        8. Summary
      2. Chapter 5: Enterprise and Canonical Modeling
        1. Topics Covered in this Chapter
        2. A Model-Driven Approach Toward Developing Reusable Data Services
        3. Defining a Standards-Driven Approach toward Developing New Data Services
        4. Role of the Enterprise Data Model
        5. Developing the Canonical Model
        6. Enterprise Data Model
        7. Canonical Model
        8. Implementing the Canonical Model
        9. Publishing Data Services with the Canonical Model as a Foundation
        10. Implementing the Canonical Model in Real-life Projects
        11. Data Services Roll Out and Future Releases
        12. Case Study: DaaS in Real Life, Electronic-Data Interchange in U.S. Healthcare Exchanges
        13. Summary
      3. Chapter 6: Business Glossary for DaaS
        1. Topics Covered in this Chapter
        2. Problem of Meaning and the Case for a Shared Business Glossary
        3. Using Metadata in Various Disciplines
        4. Role of an Organization's Business Glossary
        5. Enterprise Metadata Repository
        6. Implementing the Enterprise Metadata Repository
        7. Metadata Standards for Enterprise Data Services
        8. Metadata Governance
        9. Summary
      4. Chapter 7: SOA and Data Integration
        1. Topics Covered in this Chapter
        2. SOA as an Enabler of Data Integration
        3. Role of Enterprise Service Bus
        4. What is a Data Service?
        5. Foundational Components of a Data Service
        6. Service Interface
        7. Major Service Categories
        8. Overview of Data Virtualization
        9. Consolidated Data Infrastructure Platform
        10. Summary
      5. Chapter 8: Data Quality and Standards
        1. Topics Covered in this Chapter
        2. Where to Begin Data Standardization Efforts in Your Organization
        3. Role of Data Discovery/Profiling to Identify DaaS Quality Issues
        4. Data Quality and the Investment Paradox
        5. Quality of a Data Service
        6. Setting Up Standards in a DaaS environment
        7. Summary
    7. Part Three: DaaS Solution Blueprints
      1. Chapter 9: Reference Data Services
        1. Topics Covered in this Chapter
        2. Delivering Market and Reference Data Using Real-Time Data Services
        3. Comparing Usage of Reference Data Against Master Data
        4. Understanding Challenges of Reference Data Management
        5. Other Reference Data Management Challenges
        6. Role of Reference Data Standards and Vocabulary Management
        7. Collaborative Reference Data Management Implementation Using Business Process Management/Workflow
        8. Summary
      2. Chapter 10: Master Data Services
        1. Topics Covered in this Chapter
        2. Introduction to Master Data Services
        3. Pros and Cons of Master Data Services (Virtual Master Data Management)
        4. Leveraging the Golden Source to Resolve Deep-Rooted Source Differences
        5. Future Trends in Master Data Management Using DaaS
        6. Comparing Master Data Services Approach (Virtual) with Master Data Management Approach Involving Physical Consolidation
        7. Case Study: Master Data Services for a Premier Investment Bank
        8. Detailed Scope and Benefits
        9. Proposed Solution Architecture for Master Data Services
        10. Enterprise and Canonical Model for Master Data Management Implementation
        11. Summary
      3. Chapter 11: Big Data and Analytical Services
        1. Topics Covered in this Chapter
        2. Big Data
        3. Big Data Analytics
        4. Relationship Between DaaS and Big Data Analytics
        5. Future Impact of DaaS on Big Data Analytics
        6. Extending DaaS Reference Architecture for Big Data and Cloud Services
        7. Fostering an Enterprise Data Mindset
        8. Case Study: Big DaaS in the Automotive Industry
        9. Summary
    8. Part Four: Ensuring Organizational Success
      1. Chapter 12: DaaS Governance Framework
        1. Topics Covered in this Chapter
        2. Role of Data Governance
        3. Data Governance
        4. People Governance
        5. Process Governance
        6. Service Governance
        7. Technology Governance
        8. Summary
      2. Chapter 13: Securing the DaaS Environment
        1. Topics covered in this chapter
        2. Impact of Data Breach on DaaS Operations
        3. Major Security Considerations for DaaS
        4. Multilayered Security for the DaaS Environment
        5. Identity and Access Management
        6. Data Entitlements to Safeguard Privacy
        7. Impact of Increased Privacy Regulations on Data Providers
        8. Information Risk Management
        9. Important Data Security and Privacy Regulations that Impact DaaS
        10. Checklist to Protect Data Providers from Data Breaches
        11. Summary
      3. Chapter 14: Taking DaaS from Concept to Reality
        1. Topics Covered in this Chapter
        2. Service Performance Measurement Using the Balanced Scorecard
        3. Implementing the Performance Scorecard to Improve Data Services
        4. Embarking on the DaaS Journey with a Vision
        5. Using AGILE Principles for New Data Services Development
        6. Sustaining DaaS in an Organization: How to Keep the Program Going
        7. In Conclusion
    9. Appendix A: Data Standards Initiatives and Resources
    10. Appendix B: Data Privacy & Security Regulations
    11. Appendix C: Terms and Acronyms
    12. Appendix D: Bibliography
      1. Internet Resources and Further Reading
    13. Index
    14. EULA