Oracle Tech Article – Taking Your OBIEE to the Next Level
with SmartView VBA 11.1.1.7.1
A data warehouse is the main repository of the organization's
historical data, its corporate memory. For example, an organization would use
the information that's stored in its data warehouse to find out what day of the
week they sold the most widgets in May 1992, or how employee sick leave the
week before the winter break differed between California
and New York
from 2001-2005. In other words, the data warehouse contains the raw material
for management's decision support system. The critical factor leading to the
use of a data warehouse is that a data analyst can perform complex queries and
analysis on the information without slowing down the operational systems.
While operational systems are optimized
for simplicity and speed of modification (online transaction processing, or
OLTP) through heavy use of database normalization and an entity-relationship
model, the data warehouse is optimized for reporting and analysis (on line
analytical processing, or OLAP). Frequently data in data warehouses is heavily
denormalised, summarised and/or stored in a dimension-based model but this is
not always required to achieve acceptable query response times.
More formally, Bill Inmon
(one of the earliest and most influential practitioners) defined a data
warehouse as follows:
Subject-oriented, meaning that the data in the
database is organized so that all the data elements relating to the same
real-world event or object are linked together;
Time-variant, meaning that the changes to the data in the database
are tracked and recorded so that reports can be produced showing changes over
time; obieefans.com
Non-volatile, meaning that data in the database is never
over-written or deleted, once committed, the data is static, read-only, but
retained for future reporting;
Integrated, meaning that the database contains data from most or
all of an organization's operational applications, and that this data is made
consistent History of data warehousing
Data Warehouses became a
distinct type of computer database during the late 1980s and early 1990s. They
were developed to meet a growing demand for management information and analysis
that could not be met by operational systems. Operational systems were unable
to meet this need for a range of reasons:
·
The processing load of reporting reduced the response time of
the operational systems,
·
The database designs of operational systems were not
optimized for information analysis and reporting,
·
Most organizations had more than one operational system, so
company-wide reporting could not be supported from a single system, and
·
Development of reports in operational systems often required
writing specific computer programs which was slow and expensive.
As a result, separate computer databases began
to be built that were specifically designed to support management information
and analysis purposes. These data warehouses were able to bring in dat
NIC CONTENT
ReplyDelete