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Data, information and analytics as services
While organizations are trying to become more agile to better respond to market changes in the midst of rapidly globalizing competition by adopting service orientation—commoditization of business processes, architectures, software, infrastructures and platforms—they are also facing new challenges. I...
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Published in: | Decision Support Systems 2013-04, Vol.55 (1), p.359-363 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | While organizations are trying to become more agile to better respond to market changes in the midst of rapidly globalizing competition by adopting service orientation—commoditization of business processes, architectures, software, infrastructures and platforms—they are also facing new challenges. In this article, we provide a conceptual framework for service oriented managerial decision making process, and briefly explain the potential impact of service oriented architecture (SOA) and cloud computing on data, information and analytics. Today, SOA, cloud computing, Web 2.0 and Web 3.0 are converging, and transforming the information technology ecosystem for the better while imposing new complexities. With this convergence, a large amount of structured and unstructured data is being created and shared over disparate networks and virtual communities. To cope and/or to take advantage of these changes, we are in need of finding new and more efficient ways to collect, store, transform, share, utilize and dispose data, information and analytics.
► SOA helping to commoditize business processes, architectures and infrastructures. ► Managerial decision making processes can greatly benefit from SOA offerings. ► SOA, cloud computing, Web 2.0/3.0 are all collectively transforming the IT ecosystem. ► Data, information and analytics are becoming primary beneficiaries of SOA. ► Business analytics can be categorized into descriptive, predictive and prescriptive analytics. |
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ISSN: | 0167-9236 1873-5797 |
DOI: | 10.1016/j.dss.2012.05.044 |