Big data platforms and techniques
Data is growing at unprecedented rateand has led to huge volume generated; the data sources include mobile, internet and sensors.This voluminous data is generated and updated at high velocity by batch and streaming platforms. This data is also varied along structured and unstructured types. This vol...
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| Main Authors: | , , |
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| Format: | Article |
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Institute of Advanced Engineering and Science
2016
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| Online Access: | http://eprints.utm.my/id/eprint/74360/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014351188&doi=10.11591%2fijeecs.v1.i1.pp191-200&partnerID=40&md5=ae3998c4861a9c30a3b96709f839733d |
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| Summary: | Data is growing at unprecedented rateand has led to huge volume generated; the data sources include mobile, internet and sensors.This voluminous data is generated and updated at high velocity by batch and streaming platforms. This data is also varied along structured and unstructured types. This volume, velocity and variety of data led to the term big data. Big data has been premised to contain untapped knowledge, its exploration and exploitation is termed big data analytics. This literature reviewed platforms such as batch processing, real time processing and interactive analytics used in big data environments. Techniques used for big data are machine learning, Data Mining, Neural Network and Deep Learning. Some big data architectures are offered from Microsoft, IBM and National Institute of Standards and Technology. Big data potentials can transform economies and reducerunning cost of institutions. Big data has challenges such as storage, computation, security and privacy. |
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