The advent of Big Data has revolutionized the way in which data are collected, analyzed, and processed, becoming a pre-requisite for each enterprise that competes in the global market. In this respect, the commodization of Big Data analytics is an essential goal to be faced in the near future. Recently, some preliminary approaches have been presented mostly focusing on distributing Big Data platforms as a service, while less has been done on cross-platform Big Data analytics. In this paper, we propose a model-based methodology for Big Data Analytics-as-a-Service that extends existing techniques by supporting cross-communication between batch and stream processing, deployment on multiple platforms, and end-to-end verification against users' requirements.

A Methodology for Cross-Platform, Event-Driven Big Data Analytics-as-a-Service / C.A. Ardagna, V. Bellandi, P. Ceravolo, E. Damiani, R. Finazzo - In: 2019 IEEE International Conference on Big Data (Big Data)[s.l] : IEEE, 2019. - ISBN 9781728108582. - pp. 3440-3448 (( convegno International Conference on Big Data, Big Data tenutosi a Los Angeles nel 2019 [10.1109/BigData47090.2019.9005503].

A Methodology for Cross-Platform, Event-Driven Big Data Analytics-as-a-Service

C.A. Ardagna;V. Bellandi;P. Ceravolo;E. Damiani;
2019

Abstract

The advent of Big Data has revolutionized the way in which data are collected, analyzed, and processed, becoming a pre-requisite for each enterprise that competes in the global market. In this respect, the commodization of Big Data analytics is an essential goal to be faced in the near future. Recently, some preliminary approaches have been presented mostly focusing on distributing Big Data platforms as a service, while less has been done on cross-platform Big Data analytics. In this paper, we propose a model-based methodology for Big Data Analytics-as-a-Service that extends existing techniques by supporting cross-communication between batch and stream processing, deployment on multiple platforms, and end-to-end verification against users' requirements.
Big Data Analytics; Model-Driven Development; Batch and Stream Processing
Settore INF/01 - Informatica
2019
Ankura
Baidu
IEEE
IEEE Computer Society
Very
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/727617
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