数据挖掘课件数据挖掘03.pdf

Data Mining:
Concepts and Techniques
— Chapter 3 —
Jiawei Han
Department puter Science
University of Illinois at Urbana-Champaign
/~hanj
©2006 Jiawei Han and Micheline Kamber, All rights reserved
2011-1-19 School of Management, HUST 1
2011-1-19 School of Management, HUST 2
Chapter 3: Data Warehousing and
OLAP Technology: An Overview
 What is a data warehouse?
 A multi-dimensional data model
 Data warehouse architecture
 Data warehouse implementation
 From data warehousing to data mining
2011-1-19 School of Management, HUST 3
What is Data Warehouse?
 Defined in many different ways, but not rigorously.
 A decision support database that is maintained separately from
anization’s operational database
 Support information processing by providing a solid platform of
consolidated, historical data for analysis.
“A data warehouse is a subject-oriented, integrated, time-variant,
and nonvolatile collection of data in support of management’s
decision-making process.”—W. H. Inmon
 Data warehousing:
 The process of constructing and using data warehouses
2011-1-19 School of Management, HUST 4
Data Warehouse—Subject-Oriented
 Organized around major subjects, such as customer,
product, sales
 Focusing on the modeling and analysis of data for
decision makers, not on daily operations or transaction
processing
 Provide a simple and concise view around particular
subject issues by excluding data that are not useful in
the decision support process
2011-1-19 School of Management, HUST 5
Data Warehouse—Integrated
 Constructed by integrating multiple, heterogeneous data
sources
 relational databases, flat files, on-line transaction
records
 Data cleaning and data integration techniques are
applied.
 Ensure consistency in naming conventions, encoding
structures, attribute measures, etc. among different
data sources
 ., Hotel price: currency, tax, breakfast cov