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

Data Governance best practices

Data Governance in today’s era enables access to high-quality and trusted data via automation and mature technologies despite the need to enforce security and regulatory requirements. There is consensus across the IT industry on the criticality of Data Governance to be successful in data management.

Let’s review best practice 13.

Best practice 13

Define and enforce data policies that address Data Privacy, Data Protection, and Data Security to avoid data breaches.

There should be a high degree of consideration of how an organization addresses Data Privacy, Data Protection, and Data Security. In the event of a data breach, there needs to be a planned course of action to avoid further risk. Data policies need to handle Data Privacy, Data Retention, and Data Security. Data should be classified as sensitive, government, financial, or other to drive data protection. Automated enforcement policies should be leveraged to take appropriate...