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they are used jointly a posteriori to verify the cor-
rectness of the conceptual model obtained.
Although, the formalisms used in the three ap-
proaches for the goal-oriented step are different,
their expressivity is very close, showing that a core
of common information to be captured has been
identified. In particular, the second and the third
ones are both based on
i*
(Yu, 1995; Yu, 1997). In
i*
(which stands for “distributed intentionality”),
early requirements are assumed to involve social
actors who depend on each other for goals to be
achieved, tasks to be performed, and resources
to be supplied. The
i*
framework includes the
strategic dependency model for describing the
network of relationships among actors, as well as
the strategic rationale model for describing and
supporting the reasoning that each actor has about
its relationships with other actors. These models
have been formalized using intentional concepts
such as goal, belief, ability, and commitment
(Cohen & Levesque, 1990). The framework has
been related to different application areas that,
beside DW, include requirements engineering
(Yu, 1993), business process reengineering (Yu
& Mylopoulos, 1996), and software processes
(Yu & Mylopoulos, 1994).
A further mixed method is the one proposed in
(Guo, 2006) that puts together all the three basic
approaches: a goal-oriented step determines the
subject area of interest, defines the main KPIs and
the target users. This information is exploited in
the data- driven step in order to select the source
systems and in the user-driven one to select the us-
ers to be interviewed. On the other hand, the results
of these two steps refine and detail the results of
the goal-oriented one and enable a more complete
multidimensional model to be delivered.
Till now we considered techniques oriented to
capturing
information
(functional) requirements
for DWs. On the other hand, the final product of
the DW design process is not just a data model
but a whole DW system, where users require the
information to have some characteristics when
it is provided (security, performance tuning,
user configurations, etc.). Here non-functional
requirements come into play. Only a few works
in the DW literature have specifically addressed
this issue. In particular, Paim & Castro (2003)
propose the Data Warehouse Requirements
Definition (DWARF) approach that adapts a
traditional requirements engineering process
for requirements definition and management of
DWs. DWARF requires particular attention to
non-functional requirements that are captured
through an ad-hoc extension of the NFR frame-
work. The NFR framework (Chung et al., 1999) is
a goal-oriented approach specifically devised for
non-functional requirements that are considered
as potentially conflicting or synergistic softgoals
to be achieved. A softgoal represent a goal that
has no clear-cut definition and/or criteria as to
whether it is satisfied or not. A softgoal is said
to be “satisfied” when there is sufficient positive
evidence and little negative evidence against it.
The same authors provide a detailed classification
of non-functional requirements (Paim & Castro,
2002) that must be addressed in the development
of DWs, and guidelines for their operationaliza-
tion. At the top level requirements are clustered
into four classes, namely: performance, security,
multidimensionality and user-friendliness.
Soler et al. (2008) investigate the security
aspects by integrating a non-functional require-
ment analysis step into an existing DW approach
for information requirements (Mazon & Trujillo,
2008).
CONCEPTUAL MODELS
Conceptual modeling is widely recognized to be
the necessary foundation for building a database
that is well-documented and fully satisfies the user
requirements. In particular, from the designer point
of view the availability of a conceptual model
provides a higher level of abstraction in describ-
ing the warehousing process and its architecture
in all its aspects.
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