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Robert Wrembel and Christian Koncilia

"Data Warehouses and Olap: Concepts, Architectures and Solutions"

We review the state-of-the-art in the field, and show
that in spite of the tools and methodologies already proposed for the modeling and
design of decision support systems, DSS-METRIQ is the first one that supports the
whole process by means of an integral technique.
Introduction
It is a well-known fact that, among the phases of the software development process,
analysis and specification of functional and nonfunctional requirements is a
crucial one. The lack of good requirements specification is a major cause of failure
in software development (Thayer, 2002). The software engineering community has
developed many useful tools for requirements analysis in transactional systems.
These kinds of systems deal with the day-to-day operation of an organization. Decision
support systems (DSS) are of a completely different kind: they are focused
on integrating data and models in order to improve the decision-making process.
The data that feed a DSS generally reside in a data warehouse. The software development
cycle of DSS has particularities that require applying methodologies
different than the ones used for operational systems. The reason for this is twofold:
on the one hand, traditional methodologies have been thought and designed with
transactional systems in mind; on the other hand, specific methodologies applicable
to DSS arose as ad-hoc answers to practical needs, and most of them are just mere
enumerations of activities that must take place in order to implement the system,
focusing on populating the data repository while ignoring important issues like the
impact of changes in the operational data sources, or worse, if these data sources
satisfy the users??™ information requirements.


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