Preface
Data constitutes facts, statistics, and information based on real-world entities and events. The word fabric represents a body of material with texture and structure, such as silk cloth. These two keywords, Data Fabric, create a representation of disparate data that has been connected by a data architecture driven by governance, active metadata, automated data integration, and self-service. In today’s big data era, there are many complexities faced by enterprises looking to become data driven. Many of these issues, such as data silos, agility, lack of collaboration between business and IT, high maintenance costs, data breach, and data integrity, revolve around the large volume and velocity of proliferated data. Data Fabric is a mature, composable data architecture that faces these complexities head-on to enable the management of data at a high scale with established business value.
I wrote this book to introduce a slightly different perspective on the definition of Data Fabric architecture. The view I offer is flexible and use case agnostic and supports diverse data management styles, operational models, and technologies. I describe Data Fabric architecture as taking a people, process, and technology approach that can be applied in a complementary manner with other trending data management frameworks, such as Data Mesh and DataOps. The main theme of this book is to provide a guide to the design of Data Fabric architecture, explain the foundational role of Data Governance, and provide an understanding of how Data Fabric architecture achieves automated Data Integration and Self-Service. The technique I use is by describing “a day in the life of data” as it steps through the phases of its life cycle: create, ingest, integrate, consume, archive, and destroy. I talk about how each layer in Data Fabric architecture executes in a high-performing and thorough manner to address today’s big data complexities. I provide a set of guidelines, architecture principles, best practices, and key concepts to enable the design and implementation of a successful Data Fabric architecture.
The perspective I offer is based on decades of experience in the areas of Enterprise Architecture, Data Architecture, Data Governance, and Product Management. I remember when I started my career in Data Governance, I faced many challenges convincing others of the business value that successful data management with Data Governance achieves. I saw what many others failed to see at that time, and that was when I knew data was my passion! Since then, I’ve broadened and increased my knowledge and experience. I have learned from brilliant thought leaders at IBM and a diverse set of clients. All these experiences have shaped the frame of reference in this book.
As technologists, we are very passionate about our points of view, ideas, and perspectives. This is my point of view on what a Data Fabric architecture design represents, which aims to achieve significant business value while addressing the complexities enterprises face today.
Note
The views expressed in the book belong to the author and do not necessarily represent the opinions or views of their employer, IBM.
