@inproceedings{3b55b57e04dc43268e8e219616d1c9dc,
title = "A Model-Driven Methodology for Big Data Analytics-as-a-Service",
abstract = "The Big Data revolution has promised to build a data-driven ecosystem where better decisions are supported by enhanced analytics and data management. However, critical issues still need to be solved in the road that leads to commodization of Big Data Analytics, such as the management of Big Data complexity and the protection of data security and privacy. In this paper, we focus on the first issue and propose a methodology based on Model Driven Engineering (MDE) that aims to substantially lower the amount of competences needed in the management of a Big Data pipeline and to support automation of Big Data analytics. The proposal is experimentally evaluated in a real-world scenario: the implementation of novel functionality for Threat Detection Systems.",
keywords = "Big Data, Model-Driven Architecture, OWL-S",
author = "Ardagna, {Claudio A.} and Valerio Bellandi and Paolo Ceravolo and Ernesto Damiani and Michele Bezzi and Cedric Hebert",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 6th IEEE International Congress on Big Data, BigData Congress 2017 ; Conference date: 25-06-2017 Through 30-06-2017",
year = "2017",
month = sep,
day = "7",
doi = "10.1109/BigDataCongress.2017.23",
language = "British English",
series = "Proceedings - 2017 IEEE 6th International Congress on Big Data, BigData Congress 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "105--112",
editor = "George Karypis and Jia Zhang",
booktitle = "Proceedings - 2017 IEEE 6th International Congress on Big Data, BigData Congress 2017",
address = "United States",
}