Spatial Data Warehouses - Data Warehouse Systems: Design and Implementation - page 457

If the MultiDim model is used to represent the traditional data warehouse
schema, the analysis of which elements can be spatially represented can be
conducted in a way similar to that in the analysis-driven approach above.
If spatial support is not provided by the underlying operational systems,
external sources may deliver the required spatial data. The corresponding
mapping should be included as part of the final schema.
We do not include an example to illustrate this approach since such an
example would proceed in the same way as for the creation of a schema using
the source-driven approach in the case of a traditional data warehouse and
for adding spatial support in the analysis-driven approach above.

Analysis/Source-Driven Approach

a

Document
requirements
specification

Analysis-driven
approach

Determine
analysis needs

Identify users

Document
requirements
specification

Identify source
systems

Apply derivation
process

Source-driven
approach

b

Late inclusion of
spatial support

Add
spatial
support

Define initial
conceptual
schema

Analysis-driven
approach

Define final
conceptual
schema and
mappings

Match the two
conceptual
schemas

Define initial
conceptual
schema

Source-driven
approach

Fig. 11.18 Steps of the analysis/source-driven approach for spatial data warehouses.
( a ) Requirements specification phase. ( b ) Conceptual design phase

This approach combines the two previously described approaches which
maybeusedinparallel,asmentionedinSect. 10.3.5 . Two chains of activities,
corresponding to the analysis-driven and source-driven approaches, can be
distinguished, as it can be seen in Fig. 11.18 . The figure shows the steps of
the analysis/source-driven approach for spatial data warehouses. Similarly
to the previous cases, we propose two different solutions, the choice of which
depends on whether the users are familiar with concepts related to spatial