Databases Reference
In-Depth Information
SUCCESSFUL TIPS: DEPLOYING TOOLS SUCCESSFULLY
When implementing technology, many organizations purchase the best-of-
breed tool, but then cut corners when setting it up. Squeezing a sophisticated
piece of technology onto an existing computer server is not likely to allow that
tool to work effectively. It may even limit the functionality and will most
certainly degrade the performance. Don't try to save money by configuring the
minimum supported environment. Look for the recommended configuration
that will deliver the results you desire. If the technology does not work well, the
effort to build the data warehouse may have been in vain.
Roadblocks to Success
Many organizations have failed in their data warehousing efforts. Some have
struggled for years, while others have failed in a big and highly visible way.
Some data warehouses have not failed outright, but have never achieved their
full potential. While each case has unique characteristics, several common
themes regularly contribute to failure or the lack of total success.
Believing the Myth: ''If You Build It, They Will Come''
There are still many companies who invest in building a data warehouse
by pulling data from core operational systems into a common database,
expecting that the business will then begin to use it. This is a good exercise in
data movement and organization, but an approach that rarely leads to success.
The data is organized in ways that are not tied to actual business needs and
requirements. This is an approach that seems 'safe' from a systems perspective.
All design and development work is done without venturing into the business
community. The belief is that once the data is organized, the business can be
consulted to determine how to deliver it to them.
This approach does not take into consideration what the business community
is really doing and wants to do in the future. It is also limited to the way
that data is captured and stored in the underlying operational systems. The
reality of the business often differs from what is captured. Data is grouped
and reported in ways that may not be reflected in the underlying systems.
Such an approach also requires a large investment in infrastructure and
building this database before there is any link to business value. This was once
a very popular approach to data warehousing, but it is no longer a leading one.
Unfortunately, many organizations are already well on their way to building
this type of data warehousing environment.
