Database Reference
In-Depth Information
PRODUCT
CUSTOMER
Product Key
Product Name
Product Code
Brand Name
Product Category
Package Type
Customer Key
Customer Name
Customer Code
Marital Status
Address
State
Zip
Classification
SALES FACTS
Product Key
Time Key
Customer Key
SalesRep Key
Sales Quantity
Sales Dollars
Sales Price Margin
TIME
SALESREP
Time Key
Date
Month
Quarter
Year
Salesrep Key
Salesperson Name
Territory Name
Region Name
Figure 20-14
STAR schema for sales.
lent, you would expect to see data warehouse features being included in the soft-
ware products. That is exactly what the database vendors are doing. Data ware-
house-related add-ons are becoming parts of the database offerings. The database
software that started out for use in operational OLTP systems is being enhanced to
cater to decision support systems. DBMSs have also scaled up to support very large
databases.
Some RDBMS products now include support for the data acquisition area of the
data warehouse. Mass loading and retrieval of data from other database systems
have become easier. Some vendors have paid special attention to the data trans-
formation function. Replication features have been reinforced to assist in bulk
refreshes and incremental loading of the data warehouse.
Bitmapped indexes could be very effective in a data warehouse environment to
index on fields that have smaller number of distinct values. For example in a data-
base table containing geographic regions, the number of distinct region codes is low.
However, frequently queries involve selection by regions. In this case, retrieval by
a bitmapped index on the region code values can be very fast. Vendors have
strengthened this type of indexing.
Apart from these enhancements, the more important enhancements relate to
load balancing and query performance. These two features are critical in a data
warehouse. Your data warehouse is query-centric. Everything that can be done to
improve query performance is most desirable. The DBMS vendors are providing
parallel processing features to improve query performance. Let us briefly review
the parallel processing options within the DBMS that can take full advantage of
parallel server hardware.
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