A Big Data Analytics Framework for Enterprise Service Ecosystems in an e-Governance Scenario
| Autor: | Supriya N. Pal, Swapnil Shrivastava |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Service (systems architecture)
business.industry Computer science Big data Process mining 02 engineering and technology Data science Conformance checking World Wide Web Business process discovery Enterprise system Analytics 020204 information systems 0202 electrical engineering electronic engineering information engineering Semantic analytics 020201 artificial intelligence & image processing business |
| Zdroj: | ICEGOV |
| DOI: | 10.1145/3047273.3047274 |
| Popis: | In the recent times we have been seeing a fundamental shift from Enterprise Applications towards large scale Enterprise Service Ecosystems. Enterprise Service Ecosystems are developed by modularizing and bundling of individual business rules and functions in the form of services. These services are loosely coupled, distributed and heterogeneous components which orchestrate amongst themselves in a seamless manner. Ecosystem components record the events that are related to the activities performed by them. These components could span across Data Centre, Cloud Infrastructure and Internet of Things. Aadhaar Authentication Ecosystem and e-Governance Service Exchange are examples of Enterprise Service Ecosystems which recently emerged in national e-Governance scenario. A Big Data Analytics Framework for comprehensive mining and analyzing event data of Enterprise Service Ecosystems is proposed in this paper. The offered framework facilitates interesting real time analytics (e.g. Process Conformance Checking, Bottleneck Detection) as well as performing offline analytics (e.g. Process Discovery). The application of the proposed framework for real time analytics is explained using Aadhaar (Unique Identity) Authentication Ecosystem case study. |
| Databáze: | OpenAIRE |
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