The Effect Between Web Usage Mining Data Techniques And Data Warehouse

Clickstream data is one of the most important sources of information in websites usage and customers' behaviour in Banks e-services. A number of web usage mining scenarios are possible depending on the available information. While simple traffic analysis based on clickstream data may easily be performed to improve the e- banks services. The banks need data mining techniques to substantially improve Banks e-services activities. The paper is descriptive study focus on the previous study in the field. The researcher study the relationships between data mining techniques and the Web usage mining: Web structure 12mining, has three types these types are web usage structure, mining data streams and web content. This paper provides a contribution to the literature about the integration between the Web usage mining and data mining techniques from processes at different stages, including the pattern discovery phases, and introduces banks cases, that have analytical mining technique. The researcher recommends that banks should have a methodology to introduced data mining Techniques, a lot of queries can be answered over data streams and support the data mining Techniques. The researcher recognizes that this study is no more than a first step toward a theoretical and practical study.