Databases Reference
In-Depth Information
project by providing requirements. It also includes details for the project team.
The chapter is organized to provide the following:
An overview of the different kinds of requirements that are needed for
a successful data warehouse. This section contains information that is
useful for everyone involved with the data warehouse.
Details about what these business requirements look like, including
questions to help find them. This section is geared toward those who
are providing the requirements, but is still important for the rest of the
project team to understand.
Techniques for effectively gathering requirements. This section is geared
more specifically toward the project team members who are responsible
for driving this process.
A description of how to document the requirements. The project team can
use this to help them capture what is collected. This can also help those
providing requirements to understand what documentation to expect.
A review of how to ensure that the project will be able to deliver value to
the organization. This includes a process to help reset the priorities and
scope of the project based upon the requirements that have been collected.
This section is helpful for the project manager, business champion, data
warehouse manager, and other managers supporting this project.
What Requirements Are Needed?
Before getting too far on a data warehouse project, it is important to understand
the following:
Basics of the business itself
Challenges facing the organization
Strategic plans to move the organization forward
This provides the backdrop for designing an environment to support the
business now and into the future. With this basic understanding of the organi-
zation, it is easy to dive directly into defining report layouts.
Having a solid background is useful to help the project team to understand
what is shared during the requirements gathering process.
Peeling Back the Layers of Requirements Gathering
Multiple levels of requirements are needed to build a successful data ware-
house environment. These range from high-level strategic planning to detailed
