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


As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.


Infrastructure as Code (IaC) 116


active metadata 13, 14, 97, 98

event management 98

intelligent agent 98

metadata collection and integration 98

Metadata Knowledge Graph 97

ML and AI technologies 98

moving, from passive metadata 14

semantic language 98

Agile 47

principles 47

AIOps 53

analytical data 83

API architecture

versus microservices 90

Application programming interfaces (APIs) 110

application/system architecture 74, 77

Architecture Decision Records (ADRs) 147

diverse data management styles and operational models 147, 148

artificial intelligence (AI) 5

Atomicity, Consistency, Isolation, and Durability (ACID) 76


business architecture 74, 76

business event 96

business metadata 154


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