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


A Data Fabric design represents a data architecture that is part of enterprise architecture. It’s critical for a data architecture to align and support the business capabilities designed as part of the business architecture for an organization. To design Data Fabric, it must follow nine recognized industry principles, which are data are assets that can evolve into data products, data is shared, data is accessible, data product ownership, common vocabulary and data definitions, data security, interoperability, always be architecting, and design for automation. These principles provide the necessary guardrails in its design to ensure it provides business value while following successful practices.

In this chapter, we provided an introduction to a logical Data Fabric architecture consisting of three layers: Data Integration focused on inbound and outbound data management; Data Governance, ensuring the right level of data integrity, security, and trust are in place with...