An Ameliorated Methodology for Preprocessing Web Log Data using Data Warehousing and Data Mining Framework

A customer oriented business organization can survive and sustain by providing accurate and personalized services to their customers in real time. Hence, understanding individual users perception and their activities on the World Wide Web and then building a customized user model that provides the wealth of information for the customer is by recognizing the strategic use of historical data that have a competitive advantage in intelligence gathering and that aid in the decision making process so as to rationalize, automate, consolidate, transform and integrate ODS is important. The accuracy and accessibility of data is important in uncovering patterns from Web log data and it is needless to state that the quality of the information resulting from the data analysis is only as good as its underlying data. Hence the pre-processing is critical in any data querying, analysis, mining and reporting applications. This paper proposes an ameliorated methodology to pre-process terabytes or petabytes of raw server log file by building a DWH and Data mining framework so as to enhance the performance, throughput, scalability and multi-dimensional analysis economically