TY - JOUR
T1 - Big data
T2 - From beginning to future
AU - Yaqoob, Ibrar
AU - Hashem, Ibrahim Abaker Targio
AU - Gani, Abdullah
AU - Mokhtar, Salimah
AU - Ahmed, Ejaz
AU - Anuar, Nor Badrul
AU - Vasilakos, Athanasios V.
N1 - Funding Information:
This work is fully funded by Bright Spark Unit, University of Malaya, Malaysia and partially funded by Malaysian Ministry of Higher Education under the University of Malaya High Impact Research Grant UM.C/625/1/HIR/MOE/FCSIT/03 and RP012C-13AFR.
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Big data is a potential research area receiving considerable attention from academia and IT communities. In the digital world, the amounts of data generated and stored have expanded within a short period of time. Consequently, this fast growing rate of data has created many challenges. In this paper, we use structuralism and functionalism paradigms to analyze the origins of big data applications and its current trends. This paper presents a comprehensive discussion on state-of-the-art big data technologies based on batch and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also discusses big data analytics techniques, processing methods, some reported case studies from different vendors, several open research challenges, and the opportunities brought about by big data. The similarities and differences of these techniques and technologies based on important parameters are also investigated. Emerging technologies are recommended as a solution for big data problems.
AB - Big data is a potential research area receiving considerable attention from academia and IT communities. In the digital world, the amounts of data generated and stored have expanded within a short period of time. Consequently, this fast growing rate of data has created many challenges. In this paper, we use structuralism and functionalism paradigms to analyze the origins of big data applications and its current trends. This paper presents a comprehensive discussion on state-of-the-art big data technologies based on batch and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also discusses big data analytics techniques, processing methods, some reported case studies from different vendors, several open research challenges, and the opportunities brought about by big data. The similarities and differences of these techniques and technologies based on important parameters are also investigated. Emerging technologies are recommended as a solution for big data problems.
KW - Analytics
KW - Big data
KW - Cloud computing
KW - Internet of things
KW - Parallel and distributed computing
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=84987937059&partnerID=8YFLogxK
U2 - 10.1016/j.ijinfomgt.2016.07.009
DO - 10.1016/j.ijinfomgt.2016.07.009
M3 - Review article
AN - SCOPUS:84987937059
SN - 0268-4012
VL - 36
SP - 1231
EP - 1247
JO - International Journal of Information Management
JF - International Journal of Information Management
IS - 6
ER -