Databases Reference
In-Depth Information
Figure 14.10
Print screen from Microsoft Analysis Services, Storage Design Wizard.
highly dependent on the data. The views are picked for materialization using a greedy
algorithm, so the graph will indicate a trend toward diminishing returns. You can watch
the gain on the graph, and click the stop button anytime you think the gain is not
worth the disk space and the associated update costs. Also, if your specified gain is
reached, and the curve is not leveling out, you can reset the gain higher, and continue if
you wish.
TIPS AND INSIGHTS FOR DATABASE PROFESSIONALS
•
Tip 1. The dimensional design approach is appropriate for designing a data ware-
house.
The resulting star schemas are much more efficient than normalized tables in
the context of a data warehouse.
•
Tip 2. Use star schemas rather than snowflake schemas.
Star schemas require fewer
joins, and the schemas are more intuitive for users.
•
Tip 3. Conform dimensions across all business processes.
Discussions between dif-
ferent groups of users are more fruitful if terms carry the same meaning across the entire
enterprise.
•
Tip 4. Index dimension attributes with bitmap indexes when the attribute has a
small to medium cardinality of distinct values.
The bitmap indexes are efficient for
star joins.
