Although DWARF and this framework
are close to the rationale of DSS-METRIQ, the main differences are (a) we give
64 Vaisman
Copyright ?© 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of
Idea Group Inc. is prohibited.
a more detailed and concrete set of tools for nonfunctional requirements elicitation;
(b) we provide a QFD-based method for data source ranking on a quantifiable
basis; and (c) we give a comprehensive detail of all the processes and documents
involved. Prakash and Gosain (2003) also emphasize the need for a requirements
engineering phase in data warehousing development. This phase precedes the logical,
conceptual, and physical design phases they propose as components of the data
warehouse development process. They propose the GDI (goal decision information)
model. However, the authors do not provide a level of detail that may allow
a more in-depth analysis.
In summary, although our proposal intersects many other similar ones, it integrates
the most popular techniques, resulting in a comprehensive and self-contained methodology
where each phase has clearly defined steps, as we will see in the following
sections. Most of all, DSS-METRIQ addresses the overlooked problem of data
source qualification and selection.
Quality. Concepts
When speaking about quality, people do not always refer to the same concept (Bobrowski,
Marr?© & Yankelevich, 1999).
Pages:
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148