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

Designing Data Governance

The job of the Data Governance layer in a Data Fabric architecture is to govern, protect, secure, and enable the discovery and understanding of data. A Data Governance layer in a Data Fabric builds a connected data ecosystem with metadata, embedding Data Quality, Data Lineage, Data Security, Protection and Privacy, and Master Data Management (MDM) into every phase of the life cycle of data. It is driven by an active metadata-infused framework that enables enforcement and automation.

In this chapter, we’ll review the design of the Data Governance layer in a Data Fabric architecture. We’ll discuss its metadata-driven and Event-Driven Architecture (EDA) patterns. Finally, we’ll step through how the Data Governance layer is applied to the data life cycle.

In this chapter, we’ll cover the following topics:

  • Data Governance architecture
  • Metadata as a service
  • The Data Governance layer
  • Data Fabric’s governance...