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

Use cases

The business use cases that could be realized using a Data Fabric solution are numerous. They include Customer 360, migration to the cloud, regulatory compliance, data democratization, and more. The theme throughout this book has been the criticality and emphasis on mature Data Governance, where active metadata is the glue that binds distributed data during its life cycle. Data Fabric is a technical approach that is positioned to address a diverse set of use cases.

At the time of writing this book, there has been a big shift toward distributed data management and achieving this via a Data Mesh, an organizational approach with specific data management principles. The accountability and responsibility of data management are moved to each business domain as opposed to a central IT organization leveraged across business domains. It has a federated Data Governance model that is accountable for global data policies and decision-making in order to adhere to government regulations...