2015Unpublished venueRequires access

Enterprise Data Services

Pushpak Sarkar

Open publisher page 1 citations

Abstract

This chapter emphasizes the need for publishing common, reusable data services to distribute enterprise data to data consumers across an organization. It focuses on the need for standardization of enterprise data to enable data reuse and sharing across an organization (as well as with external subscribers). Each source application publishes enterprise data across the organization leveraging enterprise data services (EDS). The chapter enterprise disciplines such as enterprise information management (EIM), service-oriented architecture (SOA), and enterprise architecture (EA), all of which are relevant to Data as a service (Daas). It explains how data sharing and interoperability capabilities of the DaaS framework can improve prospects of big data and predictive analytics initiatives. The chapter concludes with the real-life example of Amazon, an organization that clearly understood the significance of using enterprise-wide services (both data and functionality) as their company grew larger for supporting application programming interfaces (APIs).

About this research paper

What this paper is about

This chapter emphasizes the need for publishing common, reusable data services to distribute enterprise data to data consumers across an organization. It focuses on the need for standardization of enterprise data to enable data reuse and sharing across an organization (as well as with external subscribers). Each source application publishes enterprise data across the organization leveraging enterprise data services (EDS). The chapter enterprise disciplines such as enterprise information management (EIM), service-oriented architecture (SOA), and enterprise architecture (EA), all of which are relevant to Data as a service (Daas). It explains how data sharing and interoperability capabilities of the DaaS framework can improve prospects of big data and predictive analytics initiatives. The chapter concludes with the real-life example of Amazon, an organization that clearly understood the significance of using enterprise-wide services (both data and functionality) as their company grew larger for supporting application programming interfaces (APIs).

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Available abstract

This chapter emphasizes the need for publishing common, reusable data services to distribute enterprise data to data consumers across an organization. It focuses on the need for standardization of enterprise data to enable data reuse and sharing across an organization (as well as with external subscribers). Each source application publishes enterprise data across the organization leveraging enterprise data services (EDS). The chapter enterprise disciplines such as enterprise information management (EIM), service-oriented architecture (SOA), and enterprise architecture (EA), all of which are relevant to Data as a service (Daas). It explains how data sharing and interoperability capabilities of the DaaS framework can improve prospects of big data and predictive analytics initiatives. The chapter concludes with the real-life example of Amazon, an organization that clearly understood the significance of using enterprise-wide services (both data and functionality) as their company grew larger for supporting application programming interfaces (APIs).

Key concepts: Computer science, Business, Data science

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