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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Ali Adel Flayyih
Amman Arab University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Enhancing Big Data Analysis by using Map-reduce Technique Alaa Hussein Al-Hamami; Ali Adel Flayyih
Bulletin of Electrical Engineering and Informatics Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (355.212 KB) | DOI: 10.11591/eei.v7i1.895

Abstract

Database is defined as a set of data that is organized and distributed in a manner that permits the user to access the data being stored in an easy and more convenient manner. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work enhances the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on Electroencephalogram (EEG) Big-data as a case study. The proposed approach showed clear enhancement on managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.
Enhancing Big Data Analysis by using Map-reduce Technique Alaa Hussein Al-Hamami; Ali Adel Flayyih
Bulletin of Electrical Engineering and Informatics Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (355.212 KB) | DOI: 10.11591/eei.v7i1.895

Abstract

Database is defined as a set of data that is organized and distributed in a manner that permits the user to access the data being stored in an easy and more convenient manner. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work enhances the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on Electroencephalogram (EEG) Big-data as a case study. The proposed approach showed clear enhancement on managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.
Enhancing Big Data Analysis by using Map-reduce Technique Alaa Hussein Al-Hamami; Ali Adel Flayyih
Bulletin of Electrical Engineering and Informatics Vol 7, No 1: March 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (355.212 KB) | DOI: 10.11591/eei.v7i1.895

Abstract

Database is defined as a set of data that is organized and distributed in a manner that permits the user to access the data being stored in an easy and more convenient manner. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work enhances the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on Electroencephalogram (EEG) Big-data as a case study. The proposed approach showed clear enhancement on managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.
Co-Authors Alaa Hussein Al-Hamami