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Efficient Storage of System Logs using MongoDB for a Business Intelligence System


Sanket Dige , College Of Engineering Pune; Mohseen Mukaddam, College Of Engineering Pune; Aditya supugade, College Of Engineering Pune; Satyarth Jha, College Of Engineering Pune; Aakansha Jain, College Of Engineering Pune




Software failure has become common in the emerging IT sector on daily basis. Therefore to analyze and recover from these catastrophic failures, the analysis of system logs of that particular machine is paramount. But since this data is huge and unstructured, it becomes difficult for any support team analyzer, who is supposed to troubleshoot the failure problem, to analyze this raw data. The transformation of this raw data into useful information through processing and analysis is done by business intelligence systems. Business intelligence is such a tool which can help organizations refine and manage business information with aim of solving problems and making effective business decisions. But the key to making effective business decisions by such BI tools would be the efficient storage of the raw, unstructured data into a structured, sophisticated database environment. A NoSQL database like MongoDB provides efficient storage of such raw data using dynamic schematic design. It offers much better querying, data storage ability in BSON format as compared to traditional relational databases which means faster access, better consistency in data and can grow horizontally without performance degradation.

Other Details

Paper ID: IJSRDV3I31124
Published in: Volume : 3, Issue : 3
Publication Date: 01/06/2015
Page(s): 1915-1919

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