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.