Introduction to Structured Query Language - Database Processing: Fundamentals, Design, and Implementation - page 34

This approach to database querying has become important enough that
some companies produce dedicated applications to help users who are not
familiar with database structures create ad-hoc queries. One example is
OpenText's OpenText Business Intelligence product ( http://www.opentext.
com/2/global/products/products-content-reporting/products-opentext-
business-intelligence.htm ), which uses a user-friendly graphical user inter-
face (GUI) to simplify the creation of ad-hoc queries. Personal databases
such as Microsoft Access also have ad-hoc query tools available. Microsoft
Access uses a GUI style called query by example (QBE) to simplify ad-hoc
queries.
However, Structured Query Language (SQL) —the universal query lan-
guage of relational DBMS products—is always behind the user-friendly
GUIs. In this chapter, we will introduce SQL by learning how to write and run
SQL queries. We will then return to SQL in Chapter 7 to learn how to use it
for other purposes, such as how to create and add data to the databases
themselves.

Components of a Data Warehouse

BI systems typically store their associated data in data warehouses , which are database
systems that have data, programs, and personnel that specialize in the preparation of data
for BI processing. Data warehouses will be discussed in detail in Chapter 12, and for now we
will simply note that data warehouses vary in scale and scope. They can be as simple as a sole
employee processing a data extract on a part-time basis or as complex as a department with
dozens of employees maintaining libraries of data and programs.
Figure 2-1 shows the components of a typical company-wide data warehouse. Data are
read from operational databases (the databases that store the company's current day-to-day
transaction data), from other internal data, or from external data source by the Extract,
Transform, and Load (ETL) system . The ETL system then cleans and prepares the data
for BI processing. This can be a complex process, but the data is then stored in the data

Figure 2-1
Components of a Data
Warehouse

Data
Warehouse
Metadata

Data
Warehouse
Database

Operational
Databases

ETL System

Business
Intelligence
Tools

Data Extraction/
Cleaning/
Preparation
Programs

Other
Internal
Data

Data Warehouse
DBMS

External
Data

BI Users