A STUDY ON DESIGN AND ANALYSIS OF WEB MART MINING AND ITS RELEVANCE TODAY Ravikumar G K * *Dr. MGR University, Chennai, Tamilnadu, INDIA, Manjunath T. N + + Bharathiar University, Coimbatore, Tamil Nadu, INDIA, Ravindra S. Hegadi # #Karnatak University,Dharwad,Karnataka,INDIA, Archana R A ++ ++SJB Institute of Technology,Bangalore,Karnataka,INDIA, Abstract: Data warehousing is one of the latest trends in computing environment and information technology applications. A data warehouse is a system that extracts, cleans and delivers source data into dimensional data store and then supports and implements querying and analysis for the purpose of decision making. From a data warehouse, data flows to various departments for their customized decision support systems. These individual departmental components are called data marts. A data mart is a set of dimensional tables supporting a business process. Data marts contain all atomic detail needed to support drilling down to the lowest level. Every company or organization in the world has a website. Beneath each web site are web logs that record every object either posted to or served from the web server. Web logs are important because they reveal the user traffic on the web site. The activity of parsing web logs and storing the results in a data mart to analyze customer activity is known as click stream data warehousing. The web mart - database schema is designed to make the underlying data structure more comprehensible to users and to simplify the query process. The recommended approach for data warehouse data modeling is to follow a Dimensional Modeling approach - Star Schema. We explore the design and analysis of web mart and its relevance today at minute level. Keywords: Data warehousing, ETL, Web log, Data mart, Web mart. 1. Introduction - Star Schema of the Web Mart The web mart - database schema is designed to make the underlying data structure more comprehensible to users and to simplify the query process. The recommended approach for data warehouse data modeling is to follow a Dimensional Modeling approach-called Star Schema. The star schema has a central fact table with dimension tables at the points of the star. The single fact table’s composite primary key requires a foreign key field corresponding to the primary key field of each dimension table. The dimension tables are hierarchical and thus highly denormalised [4] .A fact table is a primary table in the web mart that contain the business facts, and dimension tables are companion tables to the fact table that represent the business critical dimensions and contain the attributes for the business critical dimensions. The central fact table provides users the ability to do analysis on business facts, and dimensional tables provide users the ability to do analysis on these business facts in various business critical dimensions[10]. The figure-1 presents the overall view of the click stream fact and the associated dimensions. Ravikumar G K et al. / International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 3 No. 4 Apr 2011 3141