Hasanen S. Abdullah; Saif Bashar Neama
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 ...
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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.
