THE DATA WAREHOUSE - Fundamentals of Database Management Systems - page 335

CHAPTER 13

THE DATA WAREHOUSE

T raditionally, most data was created to support applications that involved
current corporate operations: accounting, inventory management, personnel
management, and so forth. As people began to understand to power of information
systems and their use became more pervasive, other options regarding data began to
develop. For example, companies began to perform sales trend analyses that required
historic sales data. The idea was to predict future sales and inventory requirements based
on past sales history. Applications such as this led to the realization that there is a great
deal of value in historic data, and that it would be worthwhile to organize it on a very
broad basis. This is the data warehouse.

OBJECTIVES

Compare the data needs of transaction processing systems with those of decision
support systems.

■

Describe the data warehouse concept and list its main features.

■

Compare the enterprise data warehouse with the data mart.

■

Design a data warehouse.

■

Build a data warehouse, including the steps of data extraction, data cleaning, data
transformation, and data loading.

■

Describe how to use a data warehouse with online analytic processing and data
mining.

■

List the types of expertise needed to administer a data warehouse.

■

List the challenges in data warehousing. ■

CHAPTER OUTLINE
Introduction
The Data Warehouse Concept
The Data is Subject Oriented
The Data is Integrated
The Data is Non-Volatile
The Data is Time Variant

The Data Must Be High Quality
The Data May Be Aggregated
The Data is Often Denormalized
The Data is Not Necessarily
Absolutely Current
Types of Data Warehouses