Principles of Data Fabric

Principles of Data Fabric

by Sonia Mezzetta
Released April 2023
Publisher(s): Packt Publishing
ISBN: 9781804615225

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Book description

Apply Data Fabric solutions to automate Data Integration, Data Sharing, and Data Protection across disparate data sources using different data management styles. Purchase of the print or Kindle book includes a free PDF eBook

Key Features

  • Learn to design Data Fabric architecture effectively with your choice of tool
  • Build and use a Data Fabric solution using DataOps and Data Mesh frameworks
  • Find out how to build Data Integration, Data Governance, and Self-Service analytics architecture

Book Description

Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered.

The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You’ll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you’ll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles.

By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.

What you will learn

  • Understand the core components of Data Fabric solutions
  • Combine Data Fabric with Data Mesh and DataOps frameworks
  • Implement distributed data management and regulatory compliance using Data Fabric
  • Manage and enforce Data Governance with active metadata using Data Fabric
  • Explore industry best practices for effectively implementing a Data Fabric solution

Who this book is for

If you are a data engineer, data architect, or business analyst who wants to learn all about implementing Data Fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate Data Fabric architecture into the broader ecosystem.

Table of contents

  1. Principles of Data Fabric
  2. Contributors
  3. About the author
  4. About the reviewers
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Conventions used
    5. Get in touch
    6. Share Your Thoughts
    7. Download a free PDF copy of this book
  6. Part 1: The Building Blocks
  7. Chapter 1: Introducing Data Fabric
    1. What is Data Fabric?
      1. What Data Fabric is
      2. What Data Fabric is not
    2. Why is Data Fabric important?
      1. Drawbacks of centralized data management
      2. Decentralized data management
      3. Building Data Fabric architecture
    3. Data Fabric building blocks
      1. Data Fabric principles
      2. The four Vs
      3. Data Governance
      4. Knowledge layer
      5. Data Integration
      6. Self-Service
    4. Operational Data Governance models
    5. Summary
  8. Chapter 2: Show Me the Business Value
    1. Digital transformation
    2. Data monetization
      1. Revenue
      2. Cost savings
    3. Data Fabric’s value proposition
      1. Trusting your decisions with governed data
      2. Creating a unified view of your data with intelligent Data Integration
      3. Gaining a competitive advantage with Self-Service
    4. Data Fabric for large, medium, and small enterprises
      1. Large enterprise organizations
      2. Small and medium-sized businesses
    5. Summary
  9. Part 2: Complementary Data Management Approaches and Strategies
  10. Chapter 3: Choosing between Data Fabric and Data Mesh
    1. Introducing Data Mesh
      1. Domain ownership
      2. Data as a product
      3. Self-Serve data platform
      4. Federated computational governance
    2. Comparing Data Fabric and Data Mesh
      1. Objectives
    3. Data Fabric and Data Mesh’s friendship
      1. How Data Fabric supports a federated-based organization
      2. How Data Fabric manages data as a product
      3. Self-Service data platform via a Data Fabric and Data Mesh architecture
      4. Federated computational governance with Data Fabric
    4. Summary
  11. Chapter 4: Introducing DataOps
    1. What is DataOps?
      1. DataOps’ principles
      2. The evolution of DataOps
      3. DataOps’ dimensions
      4. MLOps and AIOps depend on DataOps
    2. DataOps’ value
      1. From traditional Data Quality to data observability
    3. Data Fabric with DataOps
      1. Develop
      2. Orchestrate
      3. Test
      4. Deploy
      5. Monitor
    4. Summary
  12. Chapter 5: Building a Data Strategy
    1. Why create a data strategy?
      1. A data maturity framework
      2. A data maturity assessment
    2. Creating a data strategy
      1. Topics in a data strategy document
      2. Creating a data strategy document
    3. Data strategy implementation
    4. Summary
  13. Part 3: Designing and Realizing Data Fabric Architecture
  14. Chapter 6: Designing a Data Fabric Architecture
    1. Introduction to enterprise architecture
      1. Types of enterprise architecture
    2. Data Fabric principles
      1. Data Fabric architecture principles
    3. Data Fabric architecture layers
      1. Data Governance
      2. Data Integration
      3. Self-Service
    4. Summary
  15. Chapter 7: Designing Data Governance
    1. Data Governance architecture
      1. Metadata-driven architecture
      2. EDA
    2. Metadata as a service
      1. Metadata collection
      2. Metadata integration
      3. Metadata-based events
    3. The Data Governance layer
      1. Active metadata
      2. Life cycle governance
      3. Operational models
    4. The Data Fabric’s governance applied
      1. The Create phase
      2. The Ingest phase
      3. The Integrate phase
      4. The Consume phase
      5. The Archive and Destroy phase
    5. Summary
  16. Chapter 8: Designing Data Integration and Self-Service
    1. DataOps-based architecture
    2. Data Integration layer
      1. Data management
      2. Development workflow
    3. Self-Service layer
      1. Data democratization
      2. Data consumption
    4. Data journey in a Data Fabric architecture
      1. Phase 1 – Create phase in the Data Integration layer
      2. Phases 2 and 3 – Ingest and Integrate phases in the Data Integration layer
      3. Phase 4 – Consume phase in the Self-Service layer
      4. Phase 5 – Archive and Destroy phase
    5. Data Fabric reference architecture
      1. Data Fabric architecture highlights
    6. Summary
  17. Chapter 9: Realizing a Data Fabric Technical Architecture
    1. Technical Data Fabric architecture
      1. Data Fabric tools
      2. Vendor and open source tools
    2. Use cases
      1. Distributed data management and sharing via Data Mesh
      2. Regulatory compliance
    3. Data Mesh multi-plane requirements
      1. Multi-plane architecture
      2. Data Mesh assumptions
    4. Data Fabric with Data Mesh reference architecture
      1. Reference architecture explained
      2. Federated operational model
    5. Summary
  18. Chapter 10: Industry Best Practices
    1. Top 16 best practices
    2. Data strategy best practices
      1. Best practice 1
      2. Best practice 2
      3. Best practice 3
      4. Best practice 4
    3. Data architecture best practices
      1. Best practice 5
      2. Best practice 6
      3. Best practice 7
      4. Best practice 8
      5. Best practice 9
    4. Data Integration and Self-Service best practices
      1. Best practice 10
      2. Best practice 11
      3. Best practice 12
    5. Data Governance best practices
      1. Best practice 13
      2. Best practice 14
      3. Best practice 15
    6. Summary
  19. Index
    1. Why subscribe?
  20. Other Books You May Enjoy
    1. Packt is searching for authors like you
    2. Share Your Thoughts
    3. Download a free PDF copy of this book

Product information

  • Title: Principles of Data Fabric
  • Author(s): Sonia Mezzetta
  • Release date: April 2023
  • Publisher(s): Packt Publishing
  • ISBN: 9781804615225