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

Top 16 best practices

There are many well-known data management pain points in the IT industry. Some of these pain points are expensive data operations, data silos, bad business decisions from unreliable data, data breaches, and data access bottlenecks. These challenges are faced by enterprises due to the high volume of data and its extensive proliferation. Data is growing at an exponentially high rate each day and it’s difficult for organizations to manage data effectively and efficiently while ensuring data is protected and of high quality. Best practices alongside architecture principles and data management frameworks are embedded into a Data Fabric design in order to address many of these pain points. These attributes create a high-performing and mature data architecture capable of handling a diverse set of use cases, across industries, that is optimized to address typical pain points faced by organizations in data management.

The key best practices discussed throughout...