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Article
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
إدارة البيانات الضخمة باستخدام تقنية المابريديوس على الحوسبة السحابية: دراسة حالة، بيانات صور المخططات التحليل العصبي

Author: Sahar Mahdie Klim سحر مهدي غليم
Journal: Al-Khwarizmi Engineering Journal مجلة الخوارزمي الهندسية ISSN: 18181171 23120789 Year: 2017 Volume: 13 Issue: 1 Pages: 129-137
Publisher: Baghdad University جامعة بغداد

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Abstract

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. 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 studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for 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.

قاعدة البيانات، تعرف بمجموعة من البيانات المرتبة والموزعة بطريقة تسمح للمستخدم بالوصول إليها بطريقة سهلة ومناسبة. لكن في عصر البيانات الضخمة، الطرق القديمة في إدارة البيانات لا تستطيع إدارة هذا الكم الهائل من البيانات. لكي يتم تطوير طريقة فعالة في إدارة هذه البيانات الضخمة. هذا البحث يدرس استخدام تقنية المابريديوس في معالجة البيانات الضخمة الموزعة على السحابة المحوسبة. هذه التقنية تم تقييمها باستخدام خادم الهادوب وتم تطبيقها على بيانات مأخوذة من صور التخطيط الدماغي، كدراسة حالة. الطريقة المقدمة في هذا العمل أظهرت تحسن واضح على إدارة ومعالجة البيانات الضخمة. بمعدل تحسين يساوي 50% مقارنة بالطرق الاعتيادية في معالجة وإدارة نفس البيانات. وهو ما يوفر طريقة سهلة وسريعة في التعامل مع البيانات الضخمة.


Article
Proposed Business Intelligence Systemthrough Big Data

Authors: Hasanen S. Abdullah --- Saif Bashar Neama
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2016 Volume: 34 Issue: 4 Part (B) Scientific Pages: 528-539
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Every company or institution in the world has huge amounts of raw data. Since, we are living now in the era of data and data explosion, data is generated in an alarming rates. AstheBig Data problem emerges, big data cannot be processed by traditional systems due to its huge size, complexity and rapid generation, and since data became the most important element in the business world to drive companies and institutions in the right direction. Business Intelligence Systems are built to serve that purpose. This paper introduces a system that will implement a Business Intelligence techniqueto handle Big Data problem through HadoopFramework benefiting from its functionalitiesto provide a parallel processing environmentby implementing a cluster of three nodes that will hold the data set and running queries on it in parallel using the functionality of MapReduce algorithm. The system consists of four primary stages: first is the stage of loading the data into the cluster, second is the stage of constructing the data warehouse to become the source layer for the data analysis stage to extract the business insights. Thethird stage analyzes the data and answers the business problems.Finallythe fourth stage isthe data visualization stage where the answers that gathered from the previous stage will take the form of visual charts and graphs that will be contained in a unified business intelligence dashboard that will provide the overall look for the business operations.


Article
Big Data Techniques: A Survey

Authors: Jamal N. Hasoon جمال ناصر حسون --- Assist. Prof. Dr. Rehab Hassan د. رحاب فليح حسن
Journal: Iraqi Journal of Information Technology المجلة العراقية لتكنولوجيا المعلومات ISSN: 19948638/26640600 Year: 2019 Volume: 9 Issue: 4 Pages: 135-146
Publisher: iraqi association of information الجمعية العراقية لتكنولوجيا المعلومات

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Abstract

Big data refer to the large volume of data, it can be analyzed for strategic Developing and better decisions. Big Data applications exaggerate in near few years because a traditional data techniques be limited specification. Various types of distributions and technologies used to suffer the Big Data challenges are developed. A survey of recent technologies are review for Big Data. The main technologies features are studied enable to extract knowledge from Big Data. Such distributions have some limitations and may differ in offerings and capacities. The used technologies face the increasing multi-streams and Big Data challenges. In this work review the big data technologies and challenge.

Keywords

Big Data --- Map --- Reduce --- Shuffle --- Hadoop --- HDFS --- YARN --- Internet of Things --- IoT

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