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

The Data Fabric’s governance applied

The data life cycle is typically represented by the journey data takes from when it comes into existence to the point at which it is destroyed. As this applies to the Data Governance layer in a Data Fabric architecture, certain specific steps and considerations are taken. Each of the actions taken respects the Data Fabric principles as part of the overall architecture. Figure 7.6 represents the logical data life cycle phases in which Data Governance must be applied. Data won’t always flow across every phase. However, the Data Governance layer must account for every phase with the necessary capabilities to ensure it is properly protected and secured.

Figure 7.6 – Data life cycle phases

Figure 7.6 – Data life cycle phases

Note

The life cycle of data can be represented in different ways with various points of view depending on the scope and objectives. There isn’t one standard, as all have their own level of focus. Some might...