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Web Log Data Analysis using Online Analytical Processing

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dc.contributor.author MOHAMED, MONA SULIEMAN MAHMOUD
dc.date.accessioned 2018-10-08T08:40:58Z
dc.date.available 2018-10-08T08:40:58Z
dc.date.issued 2018-05
dc.identifier.uri http://repo.uofg.edu.sd/handle/123456789/2237
dc.description A Dissertation Submitted to University of Gezira in Partial Fulfilment of the Requirements for the Award of the Degree of Master of Science in Computer Science Department of Computer Science Faculty of Mathematical and Computer Sciences April, 2018 en_US
dc.description.abstract Today the Web has turned to be the largest information source available on the planet. It is a huge, explosive, diverse, dynamic and mostly unstructured data repository, which supplies an incredible amount of information, and also raises the complexity of how to deal with the information from different perspectives of users view. Web log is a large amount of data, which requires new technologies and architectures so that it becomes possible to extract valuable and meaningful information. Due to such large size of data it becomes very difficult to perform effective analysis using the existing traditional techniques. Many businesses usually collect hundreds of megabytes of web log data every day that need to be analysed. Performing systematic analysis on such a huge amount of data is time-consuming. Online Analytical Process (OLAP) can be used for this purpose. The primary requirement in the construction of multidimensional data cube is the identification of dimensions and measures. In this Research, University of Gezira web log file is used to analyse the access patterns of the web server which contains a huge amount of information that if mined properly can help in taking the right decision to improve the services that are provided by the website. The log file normally contains a huge amount of information that needs to be organized and cleaned. The cleaning process was achieved by removing irrelevant data, the cleaning has reduce the data by 50% (percent) then the data was uploaded into a data warehouse in a form of dimension tables and fact table. The organization of the log file was achieved by grouping the data according to unique users, unique IP address, protocols, pages and agent. The web usage mining (WUM) is done by applying the Pattern Analysis techniques on web log data. The dimensions and measures in web usage data warehouse are nominated and then a technique on how to apply (OLAP) on web usage data warehouse is proposed. Cleaned and organized data were presented in the form of a cube, the basic structure that can be used by the (OLAP). The results achieved prove that the data warehouse can be implemented successfully to analyse the log files to make appropriate decisions and provide meaningful information. For future works and further improvement the study recommends to use other mining techniques such as patterns analysis. en_US
dc.description.sponsorship Awadallah Mohammed Ahmed ( Main Supervisor) Mohamed Albarra Hassan ( Co-supervisor) en_US
dc.language.iso en en_US
dc.publisher University of Gezira en_US
dc.subject World wide web en_US
dc.subject Sources of infrmation en_US
dc.subject Data warehouse en_US
dc.title Web Log Data Analysis using Online Analytical Processing en_US
dc.type Thesis en_US


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