Web Analytic

Web Analytic and Data Mining

Introduction

Web analytics is the measurement, collection, analysis, presentation and interpretation of information from visitors to Web sites for their improvement and optimization. The main objective of web analytics is the monitoring of attendance of websites based on data which is determined by the web audience, and study the behavior of web visitors to make decisions on the development and expansion of the functionality of a Web resource.

Modern researchers in various fields are confronted by an unprecedented wealth and complexity of data. However, the results available to these researchers through traditional data analysis techniques provide only limited solutions to complex situations. The approach to the huge demand for the analysis and interpretation of these complex data is managed under the name of data mining, or knowledge discovery. Data mining is defined as the process of extracting useful information from large data sets through the use of any relevant data analysis techniques developed to help people make better decisions. These data mining techniques themselves are defined and categorized according to their underlying statistical theories and computing algorithms. This entry discusses these various data mining methods and their applications (Chapelle, 2006, 45-53).

Data mining is the extraction of the related information with respect of the industry usage that can be predicted from the databases. It is one of the most powerful technology that has the potential to be used by the companies to assist them focusing on the information that is important for them to use, they can find the related information in their data warehouse. Data mining has several tools that help and assists the companies to predict the data for their future use, also allow them to find the future trends and behavior to follow for the betterment of the business's future. It allows the business to make use of the data in order to make down to business, and knowledge and technology-driven decisions. Data mining has the automated systems and sets of tools which allow businesses to make use of the potential future analysis that has been offered through the tools of data mining. It moved through the analysis of the past event and happenings that would be previously provided by the tools of decision support system (Zheng, 2001 44-55).

Data mining tools can respond to the businesses questions that previously took much time to resolve, it covers each and every problem and answer the queries in a timely manner so that the potential and proactive decision could be made for the betterment of the business. The data mining polishes the data in order to search the data and the past or future patterns that are hidden, and could find the analytical data that may perhaps be able to be overlooked by the experts, due to reason that it may perhaps fall apart of their expectations and thinking patterns (Agrawal and Srikant, 1994 54-61).

Most of the business and the large organisations have the databases maintain and they usually retain and get rid of impurities of the enormous ...