FREE ESSAY ON DATA WAREHOUSE

DATA WAREHOUSE

The basic reasons organizations implement data warehouses are: 
To perform server/disk bound tasks associated with querying and reporting on
servers/disks not used by transaction processing systems most firms want to set up
transaction processing systems so there is a high probability that transactions will be
completed in what is judged to be an acceptable amount of time. Reports and queries,
which can require a much greater range of limited server/disk resources than transaction
processing, run on the servers/disks used by transaction processing systems can lower the
probability that transactions complete in an acceptable amount of time. Or, running
queries and reports, with their variable resource requirements, on the servers/disks used
by transaction processing systems can make it quite complex to manage servers/disks so
there is a high enough probability that acceptable response time can be achieved. Firms
therefore may find that the least expensive and/or most organizationally expeditious way
to obtain high probability of acceptable transaction processing response time is to
implement a data warehousing architecture that uses separate servers/disks for some
querying and reporting. 
To use data models and/or server technologies that speed up querying and reporting and
that are not appropriate for transaction processing
There are ways of modeling data that usually speed up querying and reporting (e.g., a
star schema) and may not be appropriate for transaction processing because the modeling
technique will slow down and complicate transaction processing. Also, there are server
technologies that that may speed up query and reporting processing but may slow down
transaction processing (e.g., bit-mapped indexing) and server technologies that may speed
up transaction processing but slow down query and report processing (e.g., technology for
transaction recovery.) - Do note that whether and by how much a modeling technique or
server technology is a help or hindrance to querying/reporting and transaction processing
varies across vendors' products and according to the situation in which the technique or
technology is used. 
To provide an environment where a relatively small amount of knowledge of the
technical aspects of database technology is required to write and maintain queries
and reports and/or to provide a means to speed up the writing and maintaining of
queries and reports by technical personnel
Often a data warehouse can be set up so that simpler queries and reports can be written
by less technically knowledgeable personnel. Nevertheless, less technically knowledgeable
personnel often hit a complexity wall and need IS help. IS, however, may also be able to
more quickly write and maintain queries and reports written against data warehouse data.
It should be noted, however, that much of the improved IS productivity probably comes
from the lack of bureaucracy usually associated with establishing reports and queries in
the data warehouse. 
To provide a repository of cleaned up transaction processing systems data that can be
reported against and that does not necessarily require fixing the transaction
processing systems the data warehouse provides an opportunity to clean up the data
without changing the transaction processing systems. Some data warehousing completions
provide a means to capture corrections made to the data warehouse data and feed the
corrections back into transaction processing systems. Sometimes it makes more sense to
handle corrections this way than to apply changes directly to the transaction processing
system. 
To make it easier, on a regular basis, to query and report data from multiple
transaction processing systems and/or from external data sources an/or from data that
must be stored for query/report purposes only
For a long time firms that need reports with data from multiple systems have been writing
data extracts and then running sort/merge logic to combine the extracted data and then
running reports against the sort/merged data. In many cases this is a perfectly adequate
strategy. However, if a company has large amounts of data that need to be sort/merged
frequently, if data purged from transaction processing systems needs to be reported upon,
and most importantly, if the data need to be cleaned, data warehousing may be
appropriate. 
To provide a repository of transaction processing system data that contains data from a
longer span of time than can efficiently be held in a transaction processing system
and/or to be able to generate reports as was as of a previous point in time
Older data are often purged from transaction processing systems so the expected response
time can be better controlled. For querying and reporting, this purged data and the
current data may be stored in the data warehouse where there presumably is less of a need
to control expected response time or the expected response time is at a much higher
level. - As for as was reporting, some times it is difficult, if not impossible, to
generate a report based on some characteristic at a previous point in time. For example,
if you want a report of the salaries of employees at grade Level 3 as of the beginning of
each month in 1997, you may not be able to do this because you only have a record of
current employee grade level. To be able to handle this type of reporting problem, firms
may implement data warehouses that handle what is called the slowly changing dimension
issue. 
To prevent persons who only need to query and report transaction processing system data
from having any access whatsoever to transaction processing system databases and logic
used to maintain those databases
The concern here is security. For example, data warehousing may be interesting to firms
that want to allow report and querying only over the Internet. 
Some firms implement data warehousing for all the reasons cited. Some firm implement data
warehousing for only one of the reasons cited.
I do believe that the achievement of a business objective for a data warehouse
necessarily comes about because of the achievement of one or many of the above
objectives. 
If you examine the list you may be struck that need for data warehousing is mainly caused
by the limitations of transaction processing systems. These limitations of transaction
processing systems are not, however, inherent. That is, the limitations will not be in
every implementation of a transaction processing system. Also, the limitations of
transaction processing systems will vary in how crippling they are. 
Finally, to repeat the point I made initially, a firm that expects to get business
intelligence, better decision making, closeness to its customers, and competitive
advantage simply by plopping down a data warehouse is in for a surprise. Obtaining these
next order benefits requires firms to figure out, usually by trial and error, how to
change business practices to best use the data warehouse and then to change their
business practices. And that can be harder than implementing a data warehouse.