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A Systematic Review of Big Data Analytics Using Model Driven Engineering

Authors:

Muhammad Nouman Zafar, Farooque Azam , Saad Rehmad , Muhammad Waseem Anwar

Publication Type:

Conference/Workshop Paper

Venue:

International Conference on Cloud and Big Data Computing

DOI:

https://doi.org/10.1145/3141128.3141138


Abstract

In this era of information technology, there is a huge and excessive amount of fully distributed, structured and unstructured data which is usually referred as 'Big Data'. This data cannot be easily and directly used for business purposes due to its excessiveness nature. Therefore, it is required to intelligently process this large amount of data to extract desired information and examine pattern to make decisions and predictions for certain business objectives. In this context, Model Driven Engineering (MDE) techniques are frequently applied for Big Data analytics. This paper investigates the latest models, approaches and tools for Big Data analytics using model driven approaches. Particularly, a Systematic Literature Review (SLR) is performed to select and analyze 24 researches published during 2010 to 2017. This leads to identify 18 models, 13 tools, and 10 approaches for big data analytics using model driven approaches. The findings of this SLR are highly valuable for the researchers, students and practitioners of the domain.

Bibtex

@inproceedings{Zafar6107,
author = {Muhammad Nouman Zafar and Farooque Azam and Saad Rehmad and Muhammad Waseem Anwar},
title = {A Systematic Review of Big Data Analytics Using Model Driven Engineering},
month = {September},
year = {2017},
booktitle = {International Conference on Cloud and Big Data Computing},
url = {http://www.es.mdh.se/publications/6107-}
}