Book Image

Principles of Data Fabric

By : Sonia Mezzetta
Book Image

Principles of Data Fabric

By: Sonia Mezzetta

Overview of this book

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.
Table of Contents (16 chapters)
Part 1: The Building Blocks
Part 2: Complementary Data Management Approaches and Strategies
Part 3: Designing and Realizing Data Fabric Architecture

Introducing Data Fabric

Data Fabric is a distributed data architecture that connects scattered data across tools and systems with the objective of providing governed access to fit-for-purpose data at speed. Data Fabric focuses on Data Governance, Data Integration, and Self-Service data sharing. It leverages a sophisticated active metadata layer that captures knowledge derived from data and its operations, data relationships, and business context. Data Fabric continuously analyzes data management activities to recommend value-driven improvements. Data Fabric works with both centralized and decentralized data systems and supports diverse operational models. This book focuses on Data Fabric and describes its data management approach, differentiating design, and emphasis on automated Data Governance.

In this chapter, we’ll focus on understanding the definition of Data Fabric and why it’s important, as well as introducing its building blocks. By the end of this chapter, you’ll have an understanding of what a Data Fabric design is and why it’s essential.

In this chapter, we’ll cover the following topics:

  • What is Data Fabric?
  • Why is Data Fabric important?
  • Data Fabric building blocks
  • Operational Data Governance models


The views expressed in the book belong to the author and do not necessarily represent the opinions or views of their employer, IBM.