The Role of Data Warehousing in the Infrastructure of E-Commerce

Abstract

A data warehouse is a repository of data that can be analyzed to gain a better knowledge about the “goings on” in a company. The value of better knowledge can lead to superior decision making. Although this architecture has been around for a long time its use is not wide spread. Many researchers have noted the absence of its penetration in business. So, while on the one hand we find a rapid growth in the e-commerce industry and advances in hardware and software, on the other hand, very few companies seem to know how to use data warehousing technologies to succeed in e-commerce. There are companies that have successfully incorporated a data warehouse and have become pioneers and leaders in e-commerce. This article presents the success of Amazon. com in the business to consumer sector of e-commerce and the success of Wal-Mart as the leader in the business to business sector of e-commerce. Data warehousing and electronic-commerce are two of the most rapidly expanding  elds in recent information technologies. In this paper, we discuss the design of data warehouses for e- commerce environment. We discuss requirement analysis, logical design, and physical design issues in e-commerce environments. We have collected an extensive set of interesting OLAP queries for e-commerce environments, and classi ed them into categories. Based on these OLAP queries, we illustrate our design with data warehouse bus architecture, dimension table structures, a base star schema, and an aggregation star schema. We  nally present various physical design considerations for implementing the dimensional models. We believe that our collection of OLAP queries and dimensional models would be very useful in developing any real-world data warehouses in e-commerce environments. We have collected an extensive set of interesting OLAP queries for e-commerce environments, and classified them into categories. Based on these OLAP queries, we illustrate our design with data warehouse bus architecture, dimension table structures, a base star schema, and an aggregation star schema. We finally present various physical design considerations for implementing the dimensional models. We believe that our collection of OLAP queries and dimensional models would be very useful in developing any real-world data warehouses in e- commerce environments.