Shows how organizations can leverage "data as a service" by providing real-life case studies on the various and innovative architectures and related patterns. This book presents a comprehensive approach to introducing data as a service in any organization. It features a re-usable and flexible SOA based architecture framework.
This book provides the nuts-and-bolts information to transform the way your organization designs, manages, and distributes enterprise data to consumers.
Data has always been considered as an essential part of the IT infrastructure across most organizations in supporting their business operations. However, a complete paradigm shift has occurred in recent years as data is increasingly recognized as an asset that could be commercially sold as a service, in and of itself.
Based on the author’s first-hand experience and expertise, this book offers a proven framework for sharing core enterprise data using reusable data services. The book will cover how organizations can generate business revenues by providing data as a service to their clients for fee-based subscriptions. The book goes on to explain, in detail, how to acquire and distribute data across heterogeneous platforms effectively using enterprise SOA principles, industry data standards and leveraging new technologies such as data virtualization, cloud, and Big Data stream computing.
Topics covered in this book are wide-ranging starting with the presentation of the need for providing data as a service and the technical challenges involved in making that transformation.
Pushpak Sarkar is a Corporate Vice President- Enterprise Technology at New York Life Insurance, USA. The author received a bachelor’s degree from Indian Institute of Technology(IIT) Kharagpur and his master’s in Technology Management from the University of Pennsylvania, and an MBA from FMS, University of Delhi, India. He has been running Data Management & BI/Analytics Service Centers of Excellence (COE) at several globally renowned organizations. His professional interest lies in data management, business intelligence, and big data analytics.