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

Who this book is for

This book is for an organization looking to venture on a digital transformation journey, or an existing data-driven organization looking to mature further in their data journey. It is intended for a diverse set of roles, both business and technical, with a vested interest in strategic, automated, and modern data management, including the following:

  • Executive leaders such as chief data officers, chief technology officers, chief information officers, and data leaders prioritizing strategic investments to execute an enterprise data strategy
  • Enterprise architects, data architects, Data Governance roles such as data security, data privacy roles, and technical leaders tasked with designing and implementing a mature and governed Self-Service data platform
  • Business analysts and data scientists looking to understand their role as data producers or data consumers in a Self-Service ecosystem leveraging Data Fabric architecture
  • Developers such as data engineers, software engineers, and business intelligence developers looking to comprehend Data Fabric architecture to learn how it achieves the rapid development of governed, trusted data