Data as a Service

Name: Data as a Service | A Framework for Providing Reusable Enterprise Data Services
Brand: Wiley
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A Framework for Providing Reusable Enterprise Data Services

Pushpak Sarkar(Autor*in)

Wiley (Verlag)

Erschienen am 5. August 2015

368 Seiten

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Inhalt

Intro
Data as a Service
Contents
Guest Introduction
Guest Introduction
Preface (Includes the Readers Guide)
The Readers Guide
PART 1: Overview of Fundamental Concepts Includes Chapters to 3
PART 2: DaaS Architecture Framework and Components Includes Chapters to 8
PART 3: DaaS Solution Blueprints Includes Chapters to 11
PART 4: Ensuring Organizational Success Includes Chapters to 14
What Is Not Covered in this Book
Acknowledgments
Part One Overview of Fundamental Concepts
1 Introduction to DaaS
Topics covered in this chapter
Data-Driven Enterprise
Concept of a Data Service Bus
Defining a Service
Service Taxonomy and Decomposition
Drivers for Providing Data as a Service
Engaging Customers with Data-Driven Choices
Monetization
Public Sector and Government
Technology Shift
Pioneering Organizations
Data as a Service Framework: A Paradigm Shift
Creating New Products
Successfully Delivering Value
IT Planners and Enterprise Architects
Exploding Data
DaaS Benefit Summary
DaaS Pricing Models
Data Services Enablement: Role of the Service Delivery Model
Guiding Principles of DaaS
DaaS Drawbacks and Limitations
Summary
2 DaaS Strategy and Reference Architecture
Topics Covered in this Chapter
Evolution of Data Services within the Enterprise
Enterprise Data Strategy, Goals, and Principles
Critical Success Factors
Reference Architecture of the DaaS Framework
How to leverage the DaaS Reference Architecture
Summary
3 Data Asset Management
Topics Covered in this Chapter
Managing Data Assets
Introduction to Major Categories of Enterprise Data
Master Data
Reference Data
Analytical Data
Transaction Data (Includes Big Data)
Comparing Various Types of Enterprise Data
Significance of EIM in Supporting the DaaS Program
Role of Enterprise Data Architect
Summary
Part Two DaaS Architecture Framework and Components
4 Enterprise Data Services
Topics Covered in this Chapter
Emergence of Enterprise Data Services
Need for an Enterprise Perspective
Emergence of Enterprise Data Services
Architecture and Strategy
Governance Process
Reusable Data Services
Service Delivery
Publication of Enterprise Data
Interdependencies between DaaS, EIM, and SOA
Role of Enterprise Data Services in Supporting Big Data and Predictive Analytics
Case Study: Amazons Adoption of Public Data Service Interfaces
Summary
5 Enterprise and Canonical Modeling
Topics Covered in this Chapter
A Model-Driven Approach Toward Developing Reusable Data Services
Defining a Standards-Driven Approach toward Developing New Data Services
Role of the Enterprise Data Model
Developing the Canonical Model
Conceptual Model (or Functional Model)
Enterprise Data Model
Canonical Model
Enterprise Canonical Model Covers
Implementing the Canonical Model
Joint Application Development (JAD)
Team Roles During the Canonical Model Development Process
Publishing Data Services with the Canonical Model as a Foundation
Capture Requirements
Mapping to the Source-of-truth Systems
Testing and User Validation
Deploy Data Services
Implementing the Canonical Model in Real-life Projects
Service Catalog
Data Services Roll Out and Future Releases
Case Study: DaaS in Real Life, Electronic-Data Interchange in U.S. Healthcare Exchanges
Role of the Canonical Model for U.S. Healthcare Exchanges
Summary
6 Business Glossary for DaaS
Topics Covered in this Chapter
Problem of Meaning and the Case for a Shared Business Glossary
Using Metadata in Various Disciplines
Role of an Organizations Business Glossary
Why a Business Glossary is Crucial for Enterprise Data Services
Standardizing Business Term Definitions and Business Rules
Enterprise Metadata Repository
Data Definition of Data Entities and Data Attributes
Clarity of Relationships and Hierarchies
Service Integration-Related Metadata
Implementing the Enterprise Metadata Repository
Metadata Standards for Enterprise Data Services
Semantic Definition of Data
Structural Definition
Standardize Data Definitions
Determine List of Valid Value Domains for Some Data Elements
Metadata Governance
Summary
7 SOA and Data Integration
Topics Covered in this Chapter
SOA as an Enabler of Data Integration
Service
Service Repository
Service Provider
Service Consumer
Role of Enterprise Service Bus
What is a Data Service?
Foundational Components of a Data Service
Service Interface
Major Service Categories
Basic Services
Intermediary Services
Process-Enabled or Business Services
Overview of Data Virtualization
Consuming Applications
Data Sources
New Technology to Further Improve Data Integration
Consolidated Data Infrastructure Platform
Summary
8 Data Quality and Standards
Topics Covered in this Chapter
Achieving Data Sharing and Interoperability Adopting Data Standards
Where to Begin Data Standardization Efforts in Your Organization
Data Lineage and Analysis
Role of Data Discovery/Profiling to Identify DaaS Quality Issues
Data Mappings
Periodic Data Audits
Data Quality and the Investment Paradox
Quality of a Data Service
Setting Up Standards in a DaaS environment
Use of a Metrics-Driven Approach to Improve the Quality of a Data Service
Example of Common Data Service Quality Improvement Metrics
Summary
Part Three DaaS Solution Blueprints
9 Reference Data Services
Topics Covered in this Chapter
Defining Reference Data
Delivering Market and Reference Data Using Real-Time Data Services
Comparing Usage of Reference Data Against Master Data
Understanding Challenges of Reference Data Management
Other Reference Data Management Challenges
Role of Reference Data Standards and Vocabulary Management
Collaborative Reference Data Management Implementation Using Business Process Management/Workflow
Case Study: Using Standardized Clinical Reference Data in U.S. Healthcare Sector
Summary
10 Master Data Services
Topics Covered in this Chapter
Introduction to Master Data Services
Pros and Cons of Master Data Services (Virtual Master Data Management)
Leveraging the Golden Source to Resolve Deep-Rooted Source Differences
Future Trends in Master Data Management Using DaaS
Demerits of Master Data Services and Addressing Gaps
Comparing Master Data Services Approach (Virtual) with Master Data Management Approach Involving Physical Consolidation
Case Study: Master Data Services for a Premier Investment Bank
Detailed Scope and Benefits
Proposed Solution Architecture for Master Data Services
Enterprise and Canonical Model for Master Data Management Implementation
Technical Architecture
Data Governance
Summary
11 Big Data and Analytical Services
Topics Covered in this Chapter
Promise of Analyzing Big Data
Big Data
Big Data Analytics
Relationship Between DaaS and Big Data Analytics
Future Impact of DaaS on Big Data Analytics
Extending DaaS Reference Architecture for Big Data and Cloud Services
Real-Time Analytical Services for Big Data with Stream Computing
Fostering an Enterprise Data Mindset
Addressing Big Data Privacy Concerns
Case Study: Big DaaS in the Automotive Industry
How the Service Works
Summary
Part Four Ensuring Organizational Success
12 DaaS Governance Framework
Topics Covered in this Chapter
Role of Data Governance
Data Governance
EIM As an Enabler for Data Governance
Data Asset Inventory (DAI)
Data Policies and Standards
People Governance
Chief Data Officer (CDO)
Business and Data Stewards
Process Governance
Establish a Data Governance Roadmap
Change Management Process for Enterprise Data Services
Establish Enterprise and Local Data-governance Processes
Data-Governance Executive Steering Committee Roles and Responsibilities
Service Governance
EDS Governance Working Committee
Service Governance Charter
Technology Governance
Technology Vendor Strategy and Oversight
Summary
13 Securing the DaaS Environment
Topics covered in this chapter
Impact of Data Breach on DaaS Operations
Major Security Considerations for DaaS
Multilayered Security for the DaaS Environment
Logical Security Controls
Physical Security Controls
Techniques to Protect Data-in-Motion
Identity and Access Management
Data Entitlements to Safeguard Privacy
Impact of Increased Privacy Regulations on Data Providers
Information Risk Management
Operational Risk
Reputation Risk
Compliance Risk
Third Party Information Risk
Intellectual Property Risk
Important Data Security and Privacy Regulations that Impact DaaS
Governance of Data Security and Privacy
Checklist to Protect Data Providers from Data Breaches
Summary
14 Taking DaaS from Concept to Reality
Topics Covered in this Chapter
Getting Ready to Adopt DaaS into an Organization
Identify Core Business Capabilities
Define Shared Data
Identify Key Strategies for Data Sharing and Integration
Service Performance Measurement Using the Balanced Scorecard
Implementing the Performance Scorecard to Improve Data Services
Embarking on the DaaS Journey with a Vision
Maturity Level 1: Initial
Maturity Level 2: Repeatable
Maturity Level 3: Defined
Maturity Level 4: Managed
Maturity Level 5: Optimized
Using AGILE Principles for New Data Services Development
Sustaining DaaS in an Organization: How to Keep the Program Going
Managing Risks to a DaaS Program
DaaS and Its Value Proposition
In Conclusion
Appendix A Data Standards Initiatives and Resources
Appendix B Data Privacy & Security Regulations
Appendix C Terms and Acronyms
Appendix D Bibliography
Index
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