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)
1
Part 1: The Building Blocks
4
Part 2: Complementary Data Management Approaches and Strategies
8
Part 3: Designing and Realizing Data Fabric Architecture

Data Fabric reference architecture

We have introduced and reviewed the design of three layers in a Data Fabric architecture. This establishes a Data Fabric reference architecture that could be leveraged as an approach in a digital transformation journey. It can also serve as a reference to build a roadmap on what, when, and how you can progress toward the building or buying of solutions to build a Data Fabric architecture.

Data Fabric architecture highlights

Let’s briefly highlight key points in each of the three layers of a Data Fabric architecture.

Data Governance layer

This represents the checks and balances of a Data Fabric architecture. It contains the brain (Metadata Knowledge Graph) that powers the body (Data Integration and Self-Service layers) to support the development and delivery of data that is quality controlled, trusted, and enforced. The Data Governance layer heavily relies on a sophisticated, active metadata- and event-driven approach. It applies...