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Web usage mining (WUM) is a type of Web mining, which exploits data mining techniques to extract valuable information from navigation behavior of World Wide Web users. The data should be preprocessed to improve the efficiency and ease of the mining process. So it is important to define before applying data mining techniques to discover user access patterns from Web log. The main task of data preprocessing is to prune noisy and irrelevant data, and to reduce data volume for the pattern discovery phase. This paper mainly focus on data preprocessing stage of the first phase of Web usage mining with activities like field extraction and data cleaning algorithms. Field extraction algorithm performs the process of separating fields from the single line of the log file. Data cleaning algorithm eliminates inconsistent or unnecessary items in the analyzed data.