Before diving into the process of building the data warehouse, it??™s important to
define the difference between a data warehouse and a data mart. The difference
between the two is one of scope: marts cover individual business areas, while
warehouses cover the entire business. Data marts focus on a particular business
function, such as finance, manufacturing, sales and marketing, and so forth. There
is a raging, often religious debate about the proper method of building a warehouse:
whether to build a number of marts and then roll them up into a warehouse, or build
a warehouse and then split out data marts as necessary. This debate is beyond the
scope of this book, and the good news is that the decision is unimportant for the
purposes of this book.
The process of building a data mart is identical to the process of building a data
warehouse; only the scope is different. Therefore, while most companies have one or
more marts and not a true warehouse, this book will use the term ???data warehouse???
as a generic term to cover both warehouses and marts. Because the process is the
same for building both marts and warehouses, this chapter will describe that process
and cover the aspects of the business intelligence process that build the foundation
for delivering value to the organization.
The process of building a warehouse involves a number of steps, each of which
contains an abundance of details. While entire books are written on the various
aspects, this chapter will seek to distill the most important parts of the warehouse
building process into an overview that will explain the importance of the decisions
made here and how they can affect the delivery of business intelligence information
through PerformancePoint Server and ProClarity.
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