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

Technical Data Fabric architecture

A Data Fabric platform is infused with intelligent metadata that acts as a parallel universe, tracing and understanding the flow of data across its various stages, tools, systems, and processes. You can think about it as the kids’ game “copy me,” where one copies everything another says or does. In the case of metadata, it works in a similar manner except that it also derives insights and knowledge as the metadata is collected. It learns from its navigation and proposes improved approaches to data management. Active metadata is at the center of the Data Fabric universe. It focuses on enabling data that is fit for purpose, secure, and delivered with speed while increasing efficiency. Active metadata captures, from creation to end of life, all data details such as facts, decisions, relationships, and policies, to then take action by influencing its strategic and efficient direction.

A technical architecture facilitates the implementation...