3. Map facts, dimensions, and measures identified during requirement analysis
onto entities in the source schema.
4. Generate a preliminary conceptual schema by navigating the functional dependencies
expressed by the source schema.
5. Edit the fact schemata to fully meet the user expectations.
Note that, though step 4 may be based on the same algorithm employed in step 2
of the data-driven approach, here navigation is not ???blind??? but rather it is actively
biased by the user requirements. Thus, the preliminary fact schemata generated here
may be considerably simpler and smaller than those obtained in the data-driven approach.
Besides, while in that approach the analyst is asked for identifying facts,
dimensions, and measures directly on the source schema, here such identification
is driven by the diagrams developed during requirement analysis.
Overall, the mixed framework is recommendable when source schemata are wellknown
but their size and complexity are substantial. In fact, the cost for a more
careful and formal analysis of requirement is balanced by the quickening of conceptual
design.
Open. Issues
A lot of work has been done in the field of conceptual modeling for DWs; nevertheless
some very important issues still remain open. We report some of them in
this section, as they emerged during joint discussion at the Perspective Seminar on
???Data Warehousing at the Crossroads??? that took place at Dagstuhl, Germany on
August 2004.
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