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 Mesh multi-plane requirements

A Data Mesh architecture defines three logical architecture layers, referred to as a multi-plane architecture. Each layer has an expected set of capabilities, personas supported, and required interactions. Let’s discuss the objectives of this logical architecture.

Multi-plane architecture

A Data Mesh multi-plane logical architecture consists of three planes: mesh experience, Data Product experience, and infrastructure utility. The mesh experience plane oversees and manages, as a whole, the connected Data Products as part of the Data Mesh(es). The Data Product experience plane is granularly focused at the Data Product level and manages the Data Product life cycle. The infrastructure utility plane is the technical infrastructure that supports both Mesh and Data Product experience planes. Figure 9.5 illustrates a Data Mesh’s multi-plane data platform.

Figure 9.5 – Data Mesh multi-plane data platform

Figure 9.5 – Data Mesh multi-plane data platform...