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Lookup NU author(s): Professor Raj Ranjan, Dr Ellis SolaimanORCiD, Professor Philip James
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2017.
For re-use rights please refer to the publisher's terms and conditions.
Data analytics has become not only an essential part of day-to-day decision making, but also reinforces long term strategic decisions. Whether it is real-time fraud detection, resource management, tracking and prevention of disease outbreak, natural disaster management or intelligent traffic management, the extraction and exploitation of insightful information from unparalleled quantities of data (BigData) is now a fundamental part of all decision making processes. Success in making smart decisions by analyzing BigData is possible due to the availability of improved analytical capabilities, increased access to different data sources, and cheaper and improved computing power in the form of cloud computing. However, BigData analysis is far more complicated than the perception created by the recent publicity. For example, one of the myths is that BigData analysis is driven purely by the innovation of new data mining and machine learning algorithms.
Author(s): Ranjan R, Garg S, Khoskbar A, Solaiman E, Philip J, Georgakopoulos D
Publication type: Article
Publication status: Published
Journal: IEEE Cloud Computing
Year: 2017
Volume: 4
Issue: 3
Online publication date: 29/06/2017
Acceptance date: 31/05/2017
Date deposited: 22/11/2017
ISSN (electronic): 2325-6095
Publisher: IEEE
URL: https://doi.org/10.1109/MCC.2017.55
DOI: 10.1109/MCC.2017.55
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