Databases Reference
In-Depth Information
people are being exposed to these concepts for the first time. To ensure a
common understanding, it is worth taking the time to boil things down to the
essence of data warehousing.
What Is a Data Warehouse?
A
data warehouse (DW)
is the collection of processes and data whose overarching
purpose is to support the business with its analysis and decision-making. In
other words, it is not one thing per se, but a collection of many different
parts. Before looking more closely at the specific parts of a data warehouse
environment, it is helpful to compare the characteristics and purpose of a data
warehouse with an operational application system.
Differences Between Operational and DW Systems
Applications that run the business are called
online transaction processing systems
(OLTPs)
. OLTP systems are geared toward functions such as processing
incoming orders, getting products shipped out, and transferring funds as
requested. These applications must ensure that transactions are handled
accurately and efficiently. No one wants to wait minutes to get cash from
an automated teller machine, or to enter sales orders into a company's system.
In contrast, the purpose and characteristics of a data warehousing envi-
ronment are to provide data in a format easily understood by the business
community in order to support decision-making processes. The data ware-
house supports looking at the business data over time to identify significant
trends in buying behavior, customer retention, or changes in employee pro-
ductivity. Table 1-1 lays out the primary differences between these two types
of systems.
The inherent differences between the functions performed in OLTP and DW
systems result in methodology, architecture, tool, and technology differences.
Data warehousing emerged as an outgrowth of necessity, but has blossomed
into a full-fledged industry that serves a valuable function in the business
community.
Now that the differences between data warehouse and OLTP systems have
been reviewed, it is time to look deeper into the makeup of the data warehouse
itself.
The Data Warehousing Environment
There are many different parts of a data warehouse environment, which
encompasses everything from where the data lives today through where it is
ultimately used on reports and for analysis. Each of the main parts of the data
