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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11231
Title: Big Data Processing and Visualization in the Context of Unstructured Data Set
???metadata.dc.contributor.*???: Dr. Million Meshesha
Temesgen, Desalegn
Keywords: Big Data;Hadoop;Map Reduce;Name Node;Data Node;JobTracker;Task Tracker;Hadoop Distributed File System;Visualization
Issue Date: 27-Jun-2016
Publisher: Addis Ababa University
Abstract: Today, it is not uncommon to face data deluge that has brought challenges to every sector across all industries. The rate of data growth is exceeding currently available storage capacity as a result of data creation by everything which is connected to internet; in addition to human activities over cyberspace, Internet of Things (IoT) are playing crucial role in business activities by generating highly valuable information and insights that cannot be tapped otherwise. On the other hand, social networks has brought a platform that facilitates human interaction among themselves which is creating a room to everyone to produce huge data sets using computers and smart phones as well. Moreover, data creation rate in variety of formats is yielding real challenges to traditional technologies. Big Data processing and visualization is current challenge due to data growth with high velocity in variety of data type. To tackle Big Data problems, the methodology applied is in detail investigation of current challenges, identification of technology frameworks and ecosystems, design solutions, implementation of the designed solution and test of implemented solution using Big Data set is taken place. Hadoop ecosystem which is starting point of technological shift from traditional technologies to more advanced and different has shown the change of data and technology landscape. The result of experimentation has revealed that Big Data processing and visualization requires comprehensive framework and collaborative ecosystem. In addition, change of model of data storage and processing is changed to send process where data resides rather than bring data to process. Huge and complex data sets visualization is not possible to realize using accustomed set of technologies.
URI: http://hdl.handle.net/123456789/11231
Appears in Collections:Thesis - Information Science

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