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

Designing a Data Fabric Architecture

A Data Fabric design represents the evolution of lessons learned from other data architecture approaches that have taken a crack at resolving critical pain points in managing digital data. A Data Fabric architecture design is based on recognized data principles, best practices, and architecture elements. Three foundational layers compose Data Fabric architecture – Data Integration, Data Governance, and Self-Service. Data Integration handles the development and processing of data; Data Governance establishes controls that govern, protect, and secure data; and Self-Service facilitates data sharing. All three layers work together to provide the right balance of control to attain, govern, and share data effectively.

In this chapter, I’ll introduce a logical Data Fabric architecture and a point of view on the necessary architecture components. You will navigate through the various layers that compose Data Fabric architecture using simple...