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Data Warehousing and Data Mining

notes extra analysis without slowing down the main system). In either case, however, it is not the
organization’s official repository, the way a data warehouse is.
2. Logical Data Marts: A logical data mart is a filtered view of the main data warehouse but
does not physically exist as a separate data copy. This approach to data marts delivers the
same benefits but has the additional advantages of not requiring additional (costly) disk
space and it is always as current with data as the main data warehouse. The downside is
that Logical Data Marts can have slower response times than physicalized ones.
3. Operational Data Store: An ODS is an integrated database of operational data. Its sources
include legacy systems, and it contains current or near-term data. An ODS may contain
30 to 60 days of information, while a data warehouse typically contains years of data.
ODSs are used in some data warehouse architectures to provide near-real-time reporting
capability in the event that the Data Warehouse’s loading time or architecture prevents it
from being able to provide near-real-time reporting capability.

1.5 Designing the Data Warehouse

Designing data warehouses is very different from designing traditional operational systems.
For one thing, data warehouse users typically don’t know nearly as much about their wants
and needs as operational users. Second, designing a data warehouse often involves thinking
in terms of much broader, and more difficult to define, business concepts than does designing
an operational system. In this respect, data warehousing is quite close to Business Process
Reengineering (BPR). Finally, the ideal design strategy for a data warehouse is often outside-in
as opposed to top-down.
But while data warehouse design is different from what we have been used to, it is no less
important. The fact that end-users have difficulty defining what they need as a bare minimum
is no less necessary. In practice, data warehouse designers find that they have to use every trick
in the book to help their users “visualize” their requirements. In this respect, robust working
prototypes are essential.

figure 1.2

The job of designing and implementing a data warehouse is very challenging and difficult one,
even though at the same time, there is a lot of focus and importance attached to it. The designer of
a data warehouse may be asked by the top management: “The all enterprise data and build a data
warehouse such that the management can get answers to all their questions”. This is a daunting
task with responsibility being visible and exciting. But how to get started? Where to start? Which
data should be put first? Where is that data available? Which queries should be answered? How

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