Implementing Data Mesh Jean-Georges Perrin, Eric Broda

Spis treści książki

• Foreword
• Preface
  • Who Is This Book For?
  • Overview of the Parts and Chapters
  • What This Book Isnt
  • Conventions Used in This Book
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgments
• I. The Basics
• 1. Understanding Data Mesh: The Essentials
  • Making Data Agile
  • Local Autonomy + Speed = Agility
  • Solving Todays Data Challenges
    • Bridging Data Silos
    • Shifting Toward Higher Quality Data
    • Transforming Data Governance
  • Data Volume, Variety, and Variability
  • Turning Principles into Practice
  • Summary
• 2. Applying Data Mesh Principles
  • Data Mesh Principles
    • Data as a Product
    • Decentralized Domain Ownership
    • Self-Serve Data Platform
    • Federated Computational Governance
  • Defining a Good Data Product
    • Defining a Principled Data Product
    • Defining a FAIR Data Product
    • Defining an Enterprise-Grade Data Product
    • Defining a Valuable Data Product
    • Defining a Balanced Data Product
    • Defining a Modern Data ProductMore than Just Regular Data
    • Defining a Practical Data Product Lifecycle
    • Defining a Practical Data Mesh Roadmap
    • A Good Data Product Has an Empowered Data Product Owner
  • Identifying a Data Product
  • Summary
• 3. Our Case Study: Climate Quantum Inc.
  • Making Climate Data Easier to Find, Consume, Share, and Trust
  • Introducing Climate Quantum Inc.
  • Climate Quantum Data Landscape
  • Applying Climate Quantum Inc. to Your Enterprise
  • Summary
• II. Designing, Building, and Deploying Data Mesh
• 4. Defining the Data Mesh Architecture
  • Data Product Architecture
    • Data Product Artifacts
    • Development Architecture Components
      • Data product definition
      • Artifact definition
      • Policy definition
    • Runtime Architecture Components
      • Data product gateway
      • Ingestion interfaces
      • Consumption interfaces
    • Operations Architecture Components
      • Discoverability interfaces
      • Observability interfaces
      • Governance interfaces
      • Control interfaces
  • Data Mesh Architecture
    • Data Mesh Marketplace and Registry
    • Data Mesh Backbone Services
  • Climate Quantum Use Case Considerations
  • Summary
• 5. Driving Data Products with Data Contracts
  • Bringing Value Through Trust
  • Navigating the Data Contract
    • Going Through the Theory
    • Stacking Up Good Information
    • Its All About Proper Versioning
    • Keeping It Simple and Semantic
    • Walking Through an Example: Complementing Tribal Knowledge
      • Documenting in a slightly better way
      • Creating a human lineage
  • What is Data QoS and Why Is It Critical?
    • Representation
      • Periods
      • Groups
    • Why Does It Matter?
    • Why Data Quality Is Not Enough
      • Accuracy (Ac)
      • Completeness (Cp)
      • Conformity (Cf)
      • Consistency (Cs)
      • Coverage (Cv)
      • Timeliness (Tm)
      • Uniqueness (Uq)
    • Service Levels Complement Quality
      • Availability (Av)
      • Throughput (Th)
      • Error rate (Er)
      • General availability (Ga)
      • End of support (Es)
      • End of life
      • Retention (Re)
      • Frequency of update (Fy)
      • Latency (Ly)
      • Time to detect (an issue) (Td)
      • Time to notify (Tn)
      • Time to repair (Tr)
  • Applying Data QoS to the Data Contract
    • Checking Conformity of Measurements
    • Completeness
    • Accuracy
    • Engaging Service Levels
  • Summary
• 6. Building Your First Data Product
  • Anatomy of a Data Product
  • The Data Contract to the Rescue
  • Connecting Your Data Sources
  • Ensuring Higher Data Quality with Observability
  • Getting Faster Data Discovery
  • Enabling Operability and Control
  • Building and Packaging
  • Summary
• 7. Aligning with the Experience Planes
  • The Three Planes
    • The Infrastructure Plane Remains Key
    • The Data Product Experience Plane Is Independent
    • The Mesh Experience Plane Is About Synergy
  • Building a Capability Model for Each Plane
    • Capabilities of the Infrastructure Experience Plane
    • Capabilities of the Data Product Experience Plane
    • Capabilities of the Mesh Experience Plane
  • Gathering Key Metrics Through Feedback Loops
  • Summary
• 8. Meshing Your Data Products
  • Registering Your Data Product
  • Connecting to Your Products in the Mesh
    • Meshing Data Products Together
    • Describing Your Data Lineage
    • Notification Through the Mesh
  • Summary
• III. GenAI, Teams, Operating Model, and Roadmap for Data Mesh
• 9. Running and Operating Your Data Mesh
  • Making Data Products Discoverable, Observable, and Secure
    • Data Product Discovery Interface
    • Data Product Observability Interface
    • Data Product Control Interface
    • Data Product Security
  • Climate Quantum Use Case Considerations
  • Toward Dynamic Data Products
  • The Power of Dynamic Data Products
  • Summary
• 10. Creating a Data Mesh Marketplace
  • Challenges with Traditional Data Catalogs
  • The Data Mesh Marketplace
  • A Window into Data Mesh
  • The Consumer User Journey
  • The Producer User Journey
  • Self-Publishing of Data Products
  • The Power of Discoverability
  • Bootstrapping Your Marketplace
  • Climate Quantums Data Mesh Marketplace
  • Summary
• 11. Establishing Data Mesh Governance
  • Data Governance
  • Data Product Certification
  • Federated Data Product Certification
  • Implementing Data Product Certification
  • Data Contracts and Certification
  • Climate Quantums Certification Approach
  • Summary
• 12. Understanding Data Product Supply Chains
  • The Modern Manufacturing Supply Chain
  • The Modern Software Factory
  • The Data Product Factory
  • The Data Product Supply Chain
  • Climate Quantums Data Product Supply Chain
  • Summary
• 13. Integrating Data Mesh and Generative AI
  • Generative AI Background
    • Large Language Models
    • Embeddings
    • Vector Databases
    • Prompts
    • Challenges
  • Data Mesh and Generative AI
    • Improve Data Quality with Generative AI
    • Elevate Models as Primary Artifacts
    • Consume Models Inside Data Products
    • Generate Data Product Code
    • Complement Data Product Capabilities
  • Climate Quantum and Generative AI
    • Simplifying Climate Data Search
    • Analyzing and Summarizing Climate Data
    • Creating Disclosure Reports
    • Generating Code to Simplify Climate Data Processing
  • Summary
• 14. Establishing Data Mesh Teams
  • Team Topologies in Data Mesh
    • The Data Product Team
      • Key roles and responsibilities
      • Data product owner
      • Release management
      • Metadata engineering
      • Data and security engineering
      • Consumption engineering
      • Ingestion engineering
    • Platform Teams
    • Enabling Teams
  • Climate Quantum Teams
  • Summary
• 15. Defining a Data Mesh Operating Model
  • Characteristics of an Operating Model
  • The Operating Model Continuum
    • Centralized Organizations
    • Matrixed Organizations
    • Federated Organizations
    • Distributed Organizations
  • Data Mesh Operating Model
  • Data Mesh Maturity Model
  • Climate Quantums Data Mesh Operating Model
  • Summary
• 16. Establishing a Practical Data Mesh Roadmap
  • Roadmap Structure
    • Strategy and Roadmap Stream
    • Technology Stream
      • Foundational phase deliverables
      • Industrialization phase deliverables
    • Factory Stream
    • Operating Model Stream
    • Socialization Stream
    • Rollout Stream
  • Climate Quantums Data Mesh Roadmap
  • Summary
• Index

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